From 8a1b52c981cb7c4040351895bc7ee64cd3987d7a Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Mon, 26 Feb 2024 15:57:48 +0100
Subject: [PATCH 01/42] dissolve only relevant rows

---
 .../buffer_dissolve_explode.py                | 82 +++++++++++--------
 1 file changed, 47 insertions(+), 35 deletions(-)

diff --git a/src/sgis/geopandas_tools/buffer_dissolve_explode.py b/src/sgis/geopandas_tools/buffer_dissolve_explode.py
index 7ebe2859..b1530e27 100644
--- a/src/sgis/geopandas_tools/buffer_dissolve_explode.py
+++ b/src/sgis/geopandas_tools/buffer_dissolve_explode.py
@@ -14,17 +14,11 @@
 - The buff function returns a GeoDataFrame, the geopandas method returns a GeoSeries.
 """
 
-import joblib
 import numpy as np
+import pandas as pd
 from geopandas import GeoDataFrame, GeoSeries
-from shapely import Geometry, make_valid, unary_union
-
-from .general import (
-    _push_geom_col,
-    merge_geometries,
-    parallel_unary_union,
-    parallel_unary_union_geoseries,
-)
+
+from .general import merge_geometries, parallel_unary_union
 from .geometry_types import make_all_singlepart
 from .polygon_operations import get_cluster_mapper, get_grouped_centroids
 
@@ -172,17 +166,15 @@ def buffdiss(
 
 
 def _dissolve(gdf, aggfunc="first", grid_size=None, n_jobs=1, **dissolve_kwargs):
-    geom_col = gdf._geometry_column_name
-    # if grid_size is None:
-    #     dissolved = gdf.dissolve(aggfunc=aggfunc, **dissolve_kwargs)
-
-    #     dissolved[geom_col] = dissolved.make_valid()
-    #     return dissolved
+    if not len(gdf):
+        return gdf
 
     geom_col = gdf._geometry_column_name
 
     by = dissolve_kwargs.pop("by", None)
 
+    by_was_none = not bool(by)
+
     if by is None and dissolve_kwargs.get("level") is None:
         by = np.zeros(len(gdf), dtype="int64")
         other_cols = list(gdf.columns.difference({geom_col}))
@@ -191,32 +183,50 @@ def _dissolve(gdf, aggfunc="first", grid_size=None, n_jobs=1, **dissolve_kwargs)
             by = [by]
         other_cols = list(gdf.columns.difference({geom_col} | set(by or {})))
 
-    dissolved = gdf.groupby(by, **dissolve_kwargs)[other_cols].agg(aggfunc)
+    try:
+        is_one_hit = gdf.groupby(by, **dissolve_kwargs).transform("size") == 1
+    except IndexError:
+        # if no rows when dropna=True
+        original_by = [x for x in by]
+        query = gdf[by.pop(0)].notna()
+        for col in gdf[by]:
+            query &= gdf[col].notna()
+        gdf = gdf.loc[query]
+        assert not len(gdf), gdf
+        if not by_was_none and dissolve_kwargs.get("as_index", True):
+            try:
+                gdf = gdf.set_index(original_by)
+            except Exception as e:
+                print(gdf)
+                print(original_by)
+                raise e
+        return gdf
+
+    if not by_was_none and dissolve_kwargs.get("as_index", True):
+        one_hit = gdf[is_one_hit].set_index(by)
+    else:
+        one_hit = gdf[is_one_hit]
+    many_hits = gdf[~is_one_hit]
+
+    if not len(many_hits):
+        return GeoDataFrame(one_hit, geometry=geom_col, crs=gdf.crs)
+
+    dissolved = many_hits.groupby(by, **dissolve_kwargs)[other_cols].agg(aggfunc)
+
+    # dissolved = gdf.groupby(by, **dissolve_kwargs)[other_cols].agg(aggfunc)
 
     if n_jobs > 1:
-        dissolved[geom_col] = parallel_unary_union(
-            gdf, n_jobs=n_jobs, by=by, grid_size=grid_size, **dissolve_kwargs
-        )
         try:
+            agged = parallel_unary_union(
+                many_hits, n_jobs=n_jobs, by=by, grid_size=grid_size, **dissolve_kwargs
+            )
+            dissolved[geom_col] = agged
             return GeoDataFrame(dissolved, geometry=geom_col, crs=gdf.crs)
         except Exception as e:
-            print(e, dissolved[geom_col])
+            print(e, dissolved, agged, many_hits)
             raise e
-        # import dask_geopandas
-
-        # if not isinstance(by, str):
-        #     gdf["_by"] = 1
-        # ddf = dask_geopandas.from_geopandas(gdf, npartitions=n_jobs, by=by)
 
-        with joblib.Parallel(n_jobs=n_jobs, backend="threading") as parallel:
-            delayed_operations = []
-            for _, geoms in gdf.groupby(by, **dissolve_kwargs)[geom_col]:
-                delayed_operations.append(joblib.delayed(merge_geometries)(geoms))
-
-            dissolved[geom_col] = parallel(delayed_operations)
-            return GeoDataFrame(dissolved, geometry=geom_col, crs=gdf.crs)
-
-    geoms_agged = gdf.groupby(by, **dissolve_kwargs)[geom_col].agg(
+    geoms_agged = many_hits.groupby(by, **dissolve_kwargs)[geom_col].agg(
         lambda x: merge_geometries(x, grid_size=grid_size)
     )
 
@@ -228,7 +238,9 @@ def _dissolve(gdf, aggfunc="first", grid_size=None, n_jobs=1, **dissolve_kwargs)
 
     dissolved[geom_col] = geoms_agged
 
-    return GeoDataFrame(dissolved, geometry=geom_col, crs=gdf.crs)
+    return GeoDataFrame(
+        pd.concat([dissolved, one_hit]).sort_index(), geometry=geom_col, crs=gdf.crs
+    )
 
 
 def dissexp(

From a654b0c6be981ffe3aa30c569dca1e6d4adff413 Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Thu, 21 Mar 2024 08:43:39 +0100
Subject: [PATCH 02/42] add dissolve function

---
 .../buffer_dissolve_explode.py                | 114 ++++++++++++++++--
 1 file changed, 103 insertions(+), 11 deletions(-)

diff --git a/src/sgis/geopandas_tools/buffer_dissolve_explode.py b/src/sgis/geopandas_tools/buffer_dissolve_explode.py
index b1530e27..8aa1e80f 100644
--- a/src/sgis/geopandas_tools/buffer_dissolve_explode.py
+++ b/src/sgis/geopandas_tools/buffer_dissolve_explode.py
@@ -14,6 +14,8 @@
 - The buff function returns a GeoDataFrame, the geopandas method returns a GeoSeries.
 """
 
+from typing import Callable
+
 import numpy as np
 import pandas as pd
 from geopandas import GeoDataFrame, GeoSeries
@@ -166,6 +168,7 @@ def buffdiss(
 
 
 def _dissolve(gdf, aggfunc="first", grid_size=None, n_jobs=1, **dissolve_kwargs):
+
     if not len(gdf):
         return gdf
 
@@ -243,19 +246,18 @@ def _dissolve(gdf, aggfunc="first", grid_size=None, n_jobs=1, **dissolve_kwargs)
     )
 
 
-def dissexp(
+def diss(
     gdf: GeoDataFrame,
     by=None,
     aggfunc="first",
     as_index: bool = True,
-    index_parts: bool = False,
     grid_size: float | int | None = None,
     n_jobs: int = 1,
     **dissolve_kwargs,
 ):
-    """Dissolves overlapping geometries.
+    """Dissolves geometries.
 
-    It takes a GeoDataFrame and dissolves, fixes and explodes geometries.
+    It takes a GeoDataFrame and dissolves and fixes geometries.
 
     Args:
         gdf: the GeoDataFrame that will be dissolved and exploded.
@@ -263,12 +265,10 @@ def dissexp(
         aggfunc: How to aggregate the non-geometry colums not in "by".
         as_index: Whether the 'by' columns should be returned as index. Defaults to
             True to be consistent with geopandas.
-        index_parts: If False (default), the index after dissolve is respected. If
-            True, an integer index level is added during explode.
         **dissolve_kwargs: additional keyword arguments passed to geopandas' dissolve.
 
     Returns:
-        A GeoDataFrame where overlapping geometries are dissolved.
+        A GeoDataFrame with dissolved geometries.
     """
     if not len(gdf):
         if as_index:
@@ -279,6 +279,44 @@ def dissexp(
         else:
             return gdf
 
+    return _dissolve(
+        gdf,
+        by=by,
+        aggfunc=aggfunc,
+        grid_size=grid_size,
+        n_jobs=n_jobs,
+        as_index=as_index,
+        **dissolve_kwargs,
+    )
+
+
+def dissexp(
+    gdf: GeoDataFrame,
+    by=None,
+    aggfunc="first",
+    as_index: bool = True,
+    index_parts: bool = False,
+    grid_size: float | int | None = None,
+    n_jobs: int = 1,
+    **dissolve_kwargs,
+):
+    """Dissolves overlapping geometries.
+
+    It takes a GeoDataFrame and dissolves, fixes and explodes geometries.
+
+    Args:
+        gdf: the GeoDataFrame that will be dissolved and exploded.
+        by: Columns to dissolve by.
+        aggfunc: How to aggregate the non-geometry colums not in "by".
+        as_index: Whether the 'by' columns should be returned as index. Defaults to
+            True to be consistent with geopandas.
+        index_parts: If False (default), the index after dissolve is respected. If
+            True, an integer index level is added during explode.
+        **dissolve_kwargs: additional keyword arguments passed to geopandas' dissolve.
+
+    Returns:
+        A GeoDataFrame where overlapping geometries are dissolved.
+    """
     dissolve_kwargs = dissolve_kwargs | {
         "by": by,
         "as_index": as_index,
@@ -286,7 +324,7 @@ def dissexp(
 
     dissolve_kwargs, ignore_index = _decide_ignore_index(dissolve_kwargs)
 
-    dissolved = _dissolve(
+    dissolved = diss(
         gdf, aggfunc=aggfunc, grid_size=grid_size, n_jobs=n_jobs, **dissolve_kwargs
     )
 
@@ -308,6 +346,60 @@ def dissexp_by_cluster(
     This might be many times faster than a regular dissexp, if there are many
     non-overlapping geometries.
 
+    Args:
+        gdf: the GeoDataFrame that will be dissolved and exploded.
+        **dissolve_kwargs: Keyword arguments passed to geopandas' dissolve.
+
+    Returns:
+        A GeoDataFrame where overlapping geometries are dissolved.
+    """
+    return _run_func_by_cluster(
+        dissexp, gdf, predicate=predicate, n_jobs=n_jobs, **dissolve_kwargs
+    )
+
+
+def diss_by_cluster(
+    gdf: GeoDataFrame, predicate=None, n_jobs: int = 1, **dissolve_kwargs
+) -> GeoDataFrame:
+    """Dissolves overlapping geometries through clustering with sjoin and networkx.
+
+    Works exactly like dissexp, but, before dissolving, the geometries are divided
+    into clusters based on overlap (uses the function sgis.get_polygon_clusters).
+    The geometries are then dissolved based on this column (and optionally other
+    columns).
+
+    This might be many times faster than a regular dissexp, if there are many
+    non-overlapping geometries.
+
+    Args:
+        gdf: the GeoDataFrame that will be dissolved and exploded.
+        **dissolve_kwargs: Keyword arguments passed to geopandas' dissolve.
+
+    Returns:
+        A GeoDataFrame where overlapping geometries are dissolved.
+    """
+    return _run_func_by_cluster(
+        diss, gdf, predicate=predicate, n_jobs=n_jobs, **dissolve_kwargs
+    )
+
+
+def _run_func_by_cluster(
+    func: Callable,
+    gdf: GeoDataFrame,
+    predicate=None,
+    n_jobs: int = 1,
+    **dissolve_kwargs,
+) -> GeoDataFrame:
+    """Dissolves overlapping geometries through clustering with sjoin and networkx.
+
+    Works exactly like dissexp, but, before dissolving, the geometries are divided
+    into clusters based on overlap (uses the function sgis.get_polygon_clusters).
+    The geometries are then dissolved based on this column (and optionally other
+    columns).
+
+    This might be many times faster than a regular dissexp, if there are many
+    non-overlapping geometries.
+
     Args:
         gdf: the GeoDataFrame that will be dissolved and exploded.
         **dissolve_kwargs: Keyword arguments passed to geopandas' dissolve.
@@ -324,7 +416,7 @@ def dissexp_by_cluster(
         by = list(by)
 
     if not len(gdf):
-        return dissexp(gdf, by=by, **dissolve_kwargs)
+        return func(gdf, by=by, **dissolve_kwargs)
 
     def get_group_clusters(group: GeoDataFrame):
         """Adds cluster column. Applied to each group because much faster."""
@@ -340,11 +432,11 @@ def get_group_clusters(group: GeoDataFrame):
             make_all_singlepart(gdf)
             .groupby(by, group_keys=True, dropna=False, as_index=False)
             .apply(get_group_clusters)
-            .pipe(dissexp, by=["_cluster"] + by, n_jobs=n_jobs, **dissolve_kwargs)
+            .pipe(func, by=["_cluster"] + by, n_jobs=n_jobs, **dissolve_kwargs)
         )
     else:
         dissolved = get_group_clusters(make_all_singlepart(gdf)).pipe(
-            dissexp, by="_cluster", n_jobs=n_jobs, **dissolve_kwargs
+            func, by="_cluster", n_jobs=n_jobs, **dissolve_kwargs
         )
 
     if not by:

From 2a3734f620879b2b338b19d906b5916d085d7691 Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Fri, 22 Mar 2024 08:54:56 +0100
Subject: [PATCH 03/42] explore_locals now works

---
 src/sgis/maps/maps.py | 110 ++++++++++++++++++++++++++++++------------
 1 file changed, 78 insertions(+), 32 deletions(-)

diff --git a/src/sgis/maps/maps.py b/src/sgis/maps/maps.py
index 7212951f..4abd427e 100644
--- a/src/sgis/maps/maps.py
+++ b/src/sgis/maps/maps.py
@@ -13,6 +13,7 @@
 from typing import Any
 
 from geopandas import GeoDataFrame, GeoSeries
+from pandas.api.types import is_list_like
 from shapely import Geometry
 
 from ..geopandas_tools.conversion import to_gdf as to_gdf_func
@@ -73,6 +74,7 @@ def explore(
     *gdfs: GeoDataFrame | dict[str, GeoDataFrame],
     column: str | None = None,
     center: Any | None = None,
+    center_4326: Any | None = None,
     labels: tuple[str] | None = None,
     max_zoom: int = 40,
     browser: bool = False,
@@ -120,19 +122,23 @@ def explore(
 
     Examples
     --------
-    >>> from sgis import read_parquet_url, explore
-    >>> roads = read_parquet_url("https://media.githubusercontent.com/media/statisticsnorway/ssb-sgis/main/tests/testdata/roads_eidskog_2022.parquet")
-    >>> points = read_parquet_url("https://media.githubusercontent.com/media/statisticsnorway/ssb-sgis/main/tests/testdata/points_eidskog.parquet")
+    >>> import sgis as sg
+    >>> roads = sg.read_parquet_url("https://media.githubusercontent.com/media/statisticsnorway/ssb-sgis/main/tests/testdata/roads_oslo_2022.parquet")
+    >>> points = sg.read_parquet_url("https://media.githubusercontent.com/media/statisticsnorway/ssb-sgis/main/tests/testdata/points_oslo.parquet")
+
+    Explore the area 500 meter around a given point. Coordinates are in UTM 33 format (25833).
 
-    Simple explore of two GeoDataFrames.
+    >>> sg.explore(roads, points, center=(262274.6528, 6650143.176, 500))
 
-    >>> explore(roads, points)
+    Same as above, but with coordinates given as WGS84, same as the coordinates displayed in the corner of the map.
+
+    >>> sg.explore(roads, points, center_4326=(10.7463, 59.92, 500))
 
     With additional arguments.
 
     >>> roads["meters"] = roads.length
     >>> points["meters"] = points.length
-    >>> explore(roads, points, column="meters", cmap="plasma", max_zoom=60)
+    >>> sg.explore(roads, points, column="meters", cmap="plasma", max_zoom=60, center_4326=(10.7463, 59.92, 500))
     """
 
     gdfs, column, kwargs = Map._separate_args(gdfs, column, kwargs)
@@ -154,18 +160,37 @@ def explore(
             **kwargs,
         )
 
+    try:
+        to_crs = gdfs[0].crs
+    except IndexError:
+        try:
+            to_crs = [x for x in kwargs.values() if hasattr(x, "crs")][0].crs
+        except IndexError:
+            to_crs = None
+
+    if center_4326 is not None:
+        from_crs = 4326
+        center = center_4326
+    elif "crs" in kwargs:
+        from_crs = kwargs.pop("crs")
+    else:
+        from_crs = to_crs
+
     if center is not None:
         size = size or 1000
         if isinstance(center, str) and not is_wkt(center):
-            mask = address_to_gdf(center, crs=gdfs[0].crs).buffer(size)
-        elif isinstance(center, GeoDataFrame):
+            mask = address_to_gdf(center, crs=from_crs).buffer(size)
+        elif isinstance(center, (GeoDataFrame, GeoSeries)):
             mask = center
         else:
-            try:
-                mask = to_gdf_func(center, crs=gdfs[0].crs)
-            except IndexError:
-                df = [x for x in kwargs.values() if hasattr(x, "crs")][0]
-                mask = to_gdf_func(center, crs=df.crs)
+            if isinstance(center, (tuple, list)) and len(center) == 3:
+                *center, size = center
+            mask = to_gdf_func(center, crs=from_crs)
+
+        try:
+            mask = mask.to_crs(to_crs)
+        except ValueError:
+            pass
 
         if get_geom_type(mask) in ["point", "line"]:
             mask = mask.buffer(size)
@@ -421,36 +446,61 @@ def clipmap(
         qtm(m._gdf, column=m.column, cmap=m._cmap, k=m.k)
 
 
-def explore_locals(*gdfs, to_gdf: bool = True, **kwargs):
-    """Viser kart (explore) over alle lokale GeoDataFrames.
+def explore_locals(*gdfs, convert: bool = True, **kwargs):
+    """Displays all local variables with geometries (GeoDataFrame etc.).
 
-    Lokalt betyr enten inni funksjonen/metoden du er i, eller i notebooken
-    du jobber i.
+    Local means inside a function or file/notebook.
 
     Args:
-        *gdfs: Ekstra GeoDataFrames du vil legge til
-        **kwargs: keyword arguments som sendes til sg.explore.
+        *gdfs: Additional GeoDataFrames.
+        convert: If True (default), non-GeoDataFrames will be converted
+            to GeoDataFrames if possible.
+        **kwargs: keyword arguments passed to sg.explore.
     """
-    frame = inspect.currentframe()
 
+    def as_dict(obj):
+        if hasattr(obj, "__dict__"):
+            return obj.__dict__
+        elif isinstance(obj, dict):
+            return obj
+        raise TypeError
+
+    frame = inspect.currentframe().f_back
+
+    local_gdfs = {}
     while True:
-        local_gdfs = {}
         for name, value in frame.f_locals.items():
-            if isinstance(value, GeoDataFrame):
+            if isinstance(value, GeoDataFrame) and len(value):
                 local_gdfs[name] = value
                 continue
-            if not to_gdf:
+            if not convert:
                 continue
-            try:
-                if hasattr(value, "__len__") and not len(value):
-                    continue
-            except TypeError:
+
+            if isinstance(value, dict) or hasattr(value, "__dict__"):
+                # add dicts or classes with GeoDataFrames to kwargs
+                for key, value in as_dict(value).items():
+                    if isinstance(value, (GeoDataFrame, GeoSeries, Geometry)):
+                        gdf = clean_geoms(to_gdf_func(value))
+                        if len(gdf):
+                            local_gdfs[key] = gdf
+
+                    elif isinstance(value, dict) or hasattr(value, "__dict__"):
+                        try:
+                            for k, v in value.items():
+                                if isinstance(v, (GeoDataFrame, GeoSeries, Geometry)):
+                                    gdf = clean_geoms(to_gdf_func(v))
+                                    if len(gdf):
+                                        local_gdfs[k] = gdf
+                        except Exception:
+                            # no need to raise here
+                            pass
+
                 continue
-            #
             try:
                 gdf = clean_geoms(to_gdf_func(value))
                 if len(gdf):
                     local_gdfs[name] = gdf
+                continue
             except Exception:
                 pass
 
@@ -462,10 +512,6 @@ def explore_locals(*gdfs, to_gdf: bool = True, **kwargs):
         if not frame:
             break
 
-    mask = kwargs.pop("mask", None)
-    if mask is not None:
-        local_gdfs = {name: gdf.clip(mask) for name, gdf in local_gdfs.items()}
-
     explore(*gdfs, **local_gdfs, **kwargs)
 
 

From c575663991c91536f4b3f6ba54f63e29f8052796 Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Fri, 22 Mar 2024 08:56:57 +0100
Subject: [PATCH 04/42] parallel

---
 src/sgis/geopandas_tools/general.py | 35 +++++++++++++++++++++++++++++
 1 file changed, 35 insertions(+)

diff --git a/src/sgis/geopandas_tools/general.py b/src/sgis/geopandas_tools/general.py
index 650617b6..fc44899f 100644
--- a/src/sgis/geopandas_tools/general.py
+++ b/src/sgis/geopandas_tools/general.py
@@ -299,6 +299,16 @@ def sort_large_first(gdf: GeoDataFrame | GeoSeries) -> GeoDataFrame | GeoSeries:
     return gdf.iloc[list(sorted_areas)]
 
 
+def sort_df(
+    df: pd.DataFrame | GeoDataFrame, sort_col: pd.Series
+) -> pd.DataFrame | GeoDataFrame:
+    value_mapper: dict[int, Any] = dict(enumerate(sort_col.values))
+    sorted_indices = dict(
+        reversed(sorted(value_mapper.items(), key=lambda item: item[1]))
+    )
+    return df.iloc[list(sorted_indices)]
+
+
 def sort_long_first(gdf: GeoDataFrame | GeoSeries) -> GeoDataFrame | GeoSeries:
     """Sort GeoDataFrame by length in decending order.
 
@@ -736,6 +746,31 @@ def parallel_unary_union(
 def parallel_unary_union_geoseries(
     ser: GeoSeries, n_jobs: int = 1, grid_size=None, **kwargs
 ) -> list[Geometry]:
+
+    is_one_hit = ser.groupby(**kwargs).transform("size") == 1
+
+    one_hit = ser.loc[is_one_hit]
+    many_hits = ser.loc[~is_one_hit]
+
+    with joblib.Parallel(n_jobs=n_jobs, backend="threading") as parallel:
+        delayed_operations = []
+        for _, geoms in many_hits.groupby(**kwargs):
+            delayed_operations.append(
+                joblib.delayed(merge_geometries)(geoms, grid_size=grid_size)
+            )
+
+        dissolved = pd.Series(
+            parallel(delayed_operations),
+            index=is_one_hit[lambda x: x == False].index.unique(),
+        )
+
+    return pd.concat([dissolved, one_hit]).sort_index().values
+
+
+def parallel_unary_union_geoseries(
+    ser: GeoSeries, n_jobs: int = 1, grid_size=None, **kwargs
+) -> list[Geometry]:
+
     with joblib.Parallel(n_jobs=n_jobs, backend="threading") as parallel:
         delayed_operations = []
         for _, geoms in ser.groupby(**kwargs):

From 5bcc2ea1d27d0dc50eea73a3c85cbf23af560faf Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Fri, 22 Mar 2024 13:51:52 +0100
Subject: [PATCH 05/42] sjoin_within_distance

---
 src/sgis/geopandas_tools/neighbors.py | 32 ++++++++++++++++++++++++++-
 1 file changed, 31 insertions(+), 1 deletion(-)

diff --git a/src/sgis/geopandas_tools/neighbors.py b/src/sgis/geopandas_tools/neighbors.py
index f16960c4..8e174c5c 100644
--- a/src/sgis/geopandas_tools/neighbors.py
+++ b/src/sgis/geopandas_tools/neighbors.py
@@ -7,9 +7,12 @@
 The results of all functions will be identical with GeoDataFrame and GeoSeries as input
 types.
 """
+
 import numpy as np
+import shapely
 from geopandas import GeoDataFrame, GeoSeries
-from pandas import DataFrame, Series
+from pandas import DataFrame, Series, concat
+from shapely import STRtree
 from sklearn.neighbors import NearestNeighbors
 
 from .conversion import coordinate_array
@@ -237,6 +240,33 @@ def get_all_distances(
     )
 
 
+def sjoin_within_distance(
+    gdf: GeoDataFrame | GeoSeries,
+    neighbors: GeoDataFrame | GeoSeries,
+    distance: int | float,
+    distance_col: str = "distance",
+    **kwargs,
+) -> GeoDataFrame:
+    """Sjoin with a buffer on the right GeoDataFrame and adds a distance column."""
+
+    new_neighbor_cols = {"__left_range_idx": range(len(neighbors))}
+    if distance:
+        new_neighbor_cols[neighbors._geometry_column_name] = lambda x: x.buffer(
+            distance
+        )
+
+    # using assign to get a copy
+    neighbors = neighbors.assign(**new_neighbor_cols)
+
+    out = gdf.sjoin(neighbors, **kwargs)
+
+    out[distance_col] = shapely.distance(
+        out.geometry.values, neighbors.geometry.iloc[out["__left_range_idx"]].values
+    )
+
+    return out.drop(columns="__left_range_idx")
+
+
 def get_k_nearest_neighbors(
     gdf: GeoDataFrame | GeoSeries,
     neighbors: GeoDataFrame | GeoSeries,

From 490f5752bee30e64c0ddce526c4f74d71942ccd8 Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Fri, 22 Mar 2024 13:53:28 +0100
Subject: [PATCH 06/42] chunksize=1

---
 src/sgis/parallel/parallel.py | 58 ++++++++++++++++++++++++++++-------
 1 file changed, 47 insertions(+), 11 deletions(-)

diff --git a/src/sgis/parallel/parallel.py b/src/sgis/parallel/parallel.py
index 457713c0..b56e373f 100644
--- a/src/sgis/parallel/parallel.py
+++ b/src/sgis/parallel/parallel.py
@@ -2,6 +2,7 @@
 import inspect
 import itertools
 import multiprocessing
+import warnings
 from collections.abc import Callable, Collection, Iterable
 from pathlib import Path
 from typing import Any
@@ -102,6 +103,7 @@ def map(
         iterable: Collection,
         args: tuple | None = None,
         kwargs: dict | None = None,
+        chunksize: int = 1,
     ) -> list[Any]:
         """Run functions in parallel with items of an iterable as 0th arguemnt.
 
@@ -185,7 +187,11 @@ def map(
             with multiprocessing.get_context(self.context).Pool(
                 processes, maxtasksperchild=self.maxtasksperchild, **self.kwargs
             ) as pool:
-                return pool.map(func_with_kwargs, iterable)
+                try:
+                    return pool.map(func_with_kwargs, iterable, chunksize=chunksize)
+                except Exception as e:
+                    pool.terminate()
+                    raise e
 
         with joblib.Parallel(
             n_jobs=processes, backend=self.backend, **self.kwargs
@@ -198,6 +204,7 @@ def starmap(
         iterable: Collection[Iterable[Any]],
         args: tuple | None = None,
         kwargs: dict | None = None,
+        chunksize: int = 1,
     ) -> list[Any]:
         """Run functions in parallel where items of the iterable are unpacked.
 
@@ -282,7 +289,11 @@ def starmap(
             with multiprocessing.get_context(self.context).Pool(
                 processes, maxtasksperchild=self.maxtasksperchild, **self.kwargs
             ) as pool:
-                return pool.starmap(func_with_kwargs, iterable)
+                try:
+                    return pool.starmap(func_with_kwargs, iterable, chunksize=chunksize)
+                except Exception as e:
+                    pool.terminate()
+                    raise e
 
         with joblib.Parallel(
             n_jobs=processes, backend=self.backend, **self.kwargs
@@ -363,22 +374,30 @@ def write_municipality_data(
 
         Args:
             in_data: Dictionary with dataset names as keys and file paths or
-                (Geo)DataFrames as values.
+                (Geo)DataFrames as values. Note that the files will be read
+                in parallel if file paths are used.
             out_data: Either a single folder path or a dictionary with same keys as
-                'in_data' and folder paths as values. If a single folder is given,
+                'in_data' and folder paths as values. If a single folder is passed,
                 the 'in_data' keys will be used as subfolders.
-            year: Year of the municipality numbers.
+            municipalities: GeoDataFrame of municipalities (or similar) of which to
+                split the data by.
+            with_neighbors: If True, the resulting data will include
+                neighbor municipalities, as well as the munipality itself.
+                Defaults to False.
             funcdict: Dictionary with the keys of 'in_data' and functions as values.
                 The functions should take a GeoDataFrame as input and return a
                 GeoDataFrame. The function will be excecuted before the right after
                 the data is read.
             file_type: Defaults to parquet.
             muni_number_col: String column name with municipality
-                number/identifier. Defaults to KOMMUNENR.
+                number/identifier. Defaults to KOMMUNENR. If the column is not present
+                in the data to be split, the data will be intersected with the
+                municipalities.
             strict: If False (default), the dictionaries 'out_data' and 'funcdict' does
                 not have to have the same length as 'in_data'.
             write_empty: If False (default), municipalities with no data will be skipped.
                 If True, an empty parquet file will be written.
+            clip: If True (default), the data will be clipped.
         """
         shared_kwds = {
             "municipalities": municipalities,
@@ -389,6 +408,7 @@ def write_municipality_data(
             "clip": clip,
             "max_rows_per_chunk": max_rows_per_chunk,
             "processes_in_clip": processes_in_clip,
+            "strict": strict,
         }
 
         if isinstance(out_data, (str, Path)):
@@ -512,6 +532,7 @@ def write_municipality_data(
     clip: bool = True,
     max_rows_per_chunk: int = 150_000,
     processes_in_clip: int = 1,
+    strict: bool = True,
 ) -> None:
     write_func = (
         _write_neighbor_municipality_data
@@ -530,6 +551,7 @@ def write_municipality_data(
         clip=clip,
         max_rows_per_chunk=max_rows_per_chunk,
         processes_in_clip=processes_in_clip,
+        strict=strict,
     )
 
 
@@ -540,6 +562,7 @@ def _validate_data(data: str | list[str]) -> str:
         return data[0]
     elif not isinstance(data, GeoDataFrame):
         raise TypeError("'data' Must be a file path or a GeoDataFrame. Got", type(data))
+    return data
 
 
 def _get_out_path(out_folder, muni, file_type):
@@ -557,6 +580,7 @@ def _write_municipality_data(
     clip: bool = True,
     max_rows_per_chunk: int = 150_000,
     processes_in_clip: int = 1,
+    strict: bool = True,
 ) -> None:
     data = _validate_data(data)
 
@@ -583,6 +607,7 @@ def _write_municipality_data(
         clip,
         max_rows_per_chunk,
         processes_in_clip=processes_in_clip,
+        strict=strict,
     )
 
     for muni in municipalities[muni_number_col]:
@@ -612,6 +637,7 @@ def _write_neighbor_municipality_data(
     clip: bool = True,
     max_rows_per_chunk: int = 150_000,
     processes_in_clip: int = 1,
+    strict: bool = True,
 ) -> None:
     data = _validate_data(data)
 
@@ -628,6 +654,7 @@ def _write_neighbor_municipality_data(
         clip,
         max_rows_per_chunk,
         processes_in_clip,
+        strict=strict,
     )
 
     if municipalities.index.name != muni_number_col:
@@ -659,6 +686,7 @@ def _fix_missing_muni_numbers(
     clip,
     max_rows_per_chunk,
     processes_in_clip,
+    strict,
 ):
     if muni_number_col in gdf and gdf[muni_number_col].notna().all():
         if municipalities is None:
@@ -666,8 +694,13 @@ def _fix_missing_muni_numbers(
         if diffs := set(gdf[muni_number_col].values).difference(
             set(municipalities[muni_number_col].values)
         ):
-            raise ValueError(f"Different municipality numbers: {diffs}")
-
+            message = (
+                f"Different municipality numbers: {diffs}. Set 'strict=False' to ignore"
+            )
+            if strict:
+                raise ValueError(message)
+            else:
+                warnings.warn(message)
         return gdf
 
     if municipalities is None:
@@ -731,9 +764,12 @@ def intersect_by_municipalities(
     n_chunks = len(df) // max_rows_per_chunk
     chunks = np.array_split(np.arange(len(df)), n_chunks)
 
-    x_mapper = dict(enumerate(df.centroid))
-    sorted_xs = dict(reversed(sorted(x_mapper.items(), key=lambda item: item[1])))
-    df = df.iloc[list(sorted_xs)]
+    try:
+        x_mapper = dict(enumerate(df.centroid))
+        sorted_xs = dict(reversed(sorted(x_mapper.items(), key=lambda item: item[1])))
+        df = df.iloc[list(sorted_xs)]
+    except TypeError:
+        pass
 
     df_chunked: list[GeoDataFrame] = [df.iloc[chunk] for chunk in chunks]
 

From c1fab79ac1829f4e7ee6a889c9eb4126cd50e57c Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Fri, 22 Mar 2024 13:54:15 +0100
Subject: [PATCH 07/42] swap places

---
 src/sgis/raster/torchgeo.py | 24 ++++++++++++------------
 1 file changed, 12 insertions(+), 12 deletions(-)

diff --git a/src/sgis/raster/torchgeo.py b/src/sgis/raster/torchgeo.py
index 4ae0736a..1c7f81d8 100644
--- a/src/sgis/raster/torchgeo.py
+++ b/src/sgis/raster/torchgeo.py
@@ -36,18 +36,6 @@ def __init__(self, *args, **kwargs):
         if is_dapla():
             [file.close() for file in self.files]
 
-    def _get_gcs_paths(self, paths: str | Iterable[str], fs=None) -> set[str]:
-        if fs is None:
-            fs = dp.FileClient.get_gcs_file_system()
-
-        # Using set to remove any duplicates if directories are overlapping
-        out_paths: set[str] = set()
-        for path in paths:
-            pathname = os.path.join(path, "**", self.filename_glob)
-            if is_dapla():
-                out_paths |= {x for x in fs.glob(pathname, recursive=True) if "." in x}
-        return out_paths
-
     @property
     def files(self) -> set[str] | set[GCSFile]:
         """A list of all files in the dataset.
@@ -106,6 +94,18 @@ def _load_warp_file(self, filepath: str) -> DatasetReader:
             else:
                 return src
 
+    def _get_gcs_paths(self, paths: str | Iterable[str], fs=None) -> set[str]:
+        if fs is None:
+            fs = dp.FileClient.get_gcs_file_system()
+
+        # Using set to remove any duplicates if directories are overlapping
+        out_paths: set[str] = set()
+        for path in paths:
+            pathname = os.path.join(path, "**", self.filename_glob)
+            if is_dapla():
+                out_paths |= {x for x in fs.glob(pathname, recursive=True) if "." in x}
+        return out_paths
+
 
 class Sentinel2(DaplaRasterDataset):
     """Works like torchgeo's Sentinel2, with custom regexes."""

From c37993807bd4f44ec1f34bb1a8d72bceca33cd19 Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Fri, 22 Mar 2024 13:55:07 +0100
Subject: [PATCH 08/42] clearer error message

---
 src/sgis/geopandas_tools/polygons_as_rings.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/sgis/geopandas_tools/polygons_as_rings.py b/src/sgis/geopandas_tools/polygons_as_rings.py
index dd5cad2d..18ce5db4 100644
--- a/src/sgis/geopandas_tools/polygons_as_rings.py
+++ b/src/sgis/geopandas_tools/polygons_as_rings.py
@@ -169,7 +169,7 @@ def apply_numpy_func(
 
         if len(results) != len(self.rings):
             raise ValueError(
-                f"Different length of results. Got {len(results)} and n rings {len(self.rings)}"
+                f"Different length of results. Got {len(results)} and {len(self.rings)} original rings"
             )
 
         self.rings.loc[:] = results

From fe334d4554b6f9dcb968ba2318d64455b3b32464 Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Fri, 5 Apr 2024 12:06:03 +0200
Subject: [PATCH 09/42] allow copernicus coded wkt-string

---
 src/sgis/geopandas_tools/conversion.py | 49 ++++++++++++++++++++------
 src/sgis/io/dapla_functions.py         | 37 ++++++++-----------
 2 files changed, 53 insertions(+), 33 deletions(-)

diff --git a/src/sgis/geopandas_tools/conversion.py b/src/sgis/geopandas_tools/conversion.py
index 3b96c80a..124cb394 100644
--- a/src/sgis/geopandas_tools/conversion.py
+++ b/src/sgis/geopandas_tools/conversion.py
@@ -10,7 +10,9 @@
 import shapely
 from geopandas import GeoDataFrame, GeoSeries
 from pandas.api.types import is_array_like, is_dict_like, is_list_like
+from pyproj import CRS
 from shapely import Geometry, box, wkb, wkt
+from shapely.errors import GEOSException
 from shapely.geometry import Point
 from shapely.ops import unary_union
 
@@ -189,16 +191,18 @@ def coordinate_array(
 
 
 def to_gdf(
-    obj: Geometry
-    | str
-    | bytes
-    | list
-    | tuple
-    | dict
-    | GeoSeries
-    | pd.Series
-    | pd.DataFrame
-    | Iterator,
+    obj: (
+        Geometry
+        | str
+        | bytes
+        | list
+        | tuple
+        | dict
+        | GeoSeries
+        | pd.Series
+        | pd.DataFrame
+        | Iterator
+    ),
     crs: str | tuple[str] | None = None,
     geometry: str | tuple[str] | int | None = None,
     **kwargs,
@@ -316,6 +320,22 @@ def to_gdf(
         geom_col = geometry or "geometry"
         return _geoseries_to_gdf(obj, geom_col, crs, **kwargs)
 
+    if crs is None:
+        try:
+            crs = obj.crs
+        except AttributeError:
+            try:
+                matches = re.search(r"SRID=(\d+);", obj)
+            except TypeError:
+                try:
+                    matches = re.search(r"SRID=(\d+);", obj[0])
+                except Exception:
+                    pass
+            try:
+                crs = CRS(int("".join(x for x in matches.group(0) if x.isnumeric())))
+            except Exception:
+                pass
+
     if is_array_like(geometry) and len(geometry) == len(obj):
         geometry = GeoSeries(
             _make_one_shapely_geom(g) for g in geometry if g is not None
@@ -583,7 +603,14 @@ def _make_one_shapely_geom(obj):
     Works recursively if the object is a nested iterable.
     """
     if isinstance(obj, str):
-        return wkt.loads(obj)
+        try:
+            return wkt.loads(obj)
+        except GEOSException:
+            if obj.startswith("geography"):
+                matches = re.search(r"SRID=(\d+);", obj)
+                srid = matches.group(0)
+                _, _wkt = obj.split(srid)
+                return wkt.loads(_wkt)
 
     if isinstance(obj, bytes):
         return wkb.loads(obj)
diff --git a/src/sgis/io/dapla_functions.py b/src/sgis/io/dapla_functions.py
index 22c00cd7..cc3dbbf2 100644
--- a/src/sgis/io/dapla_functions.py
+++ b/src/sgis/io/dapla_functions.py
@@ -1,5 +1,6 @@
 """Functions for reading and writing GeoDataFrames in Statistics Norway's GCS Dapla.
 """
+
 from pathlib import Path
 from typing import Optional
 
@@ -15,7 +16,7 @@
 def read_geopandas(
     gcs_path: str | Path,
     pandas_fallback: bool = False,
-    file_system: Optional[dp.gcs.GCSFileSystem] = None,
+    fs: Optional[dp.gcs.GCSFileSystem] = None,
     **kwargs,
 ) -> GeoDataFrame | DataFrame:
     """Reads geoparquet or other geodata from a file on GCS.
@@ -44,11 +45,11 @@ def read_geopandas(
         except TypeError:
             raise TypeError(f"Unexpected type {type(gcs_path)}.")
 
-    if file_system is None:
-        file_system = dp.FileClient.get_gcs_file_system()
+    if fs is None:
+        fs = dp.FileClient.get_gcs_file_system()
 
     if "parquet" in gcs_path or "prqt" in gcs_path:
-        with file_system.open(gcs_path, mode="rb") as file:
+        with fs.open(gcs_path, mode="rb") as file:
             try:
                 return gpd.read_parquet(file, **kwargs)
             except ValueError as e:
@@ -59,19 +60,9 @@ def read_geopandas(
                 if pandas_fallback or not len(df):
                     return df
                 else:
-                    try:
-                        raise e.__class__(e, gcs_path)
-                    except Exception:
-                        print(gcs_path)
-                        raise e
-            except Exception as e:
-                try:
-                    raise e.__class__(e, gcs_path)
-                except Exception:
-                    print(gcs_path)
                     raise e
     else:
-        with file_system.open(gcs_path, mode="rb") as file:
+        with fs.open(gcs_path, mode="rb") as file:
             try:
                 return gpd.read_file(file, **kwargs)
             except ValueError as e:
@@ -90,7 +81,7 @@ def write_geopandas(
     gcs_path: str | Path,
     overwrite: bool = True,
     pandas_fallback: bool = False,
-    file_system: Optional[dp.gcs.GCSFileSystem] = None,
+    fs: Optional[dp.gcs.GCSFileSystem] = None,
     **kwargs,
 ) -> None:
     """Writes a GeoDataFrame to the speficied format.
@@ -115,8 +106,8 @@ def write_geopandas(
     if not overwrite and exists(gcs_path):
         raise ValueError("File already exists.")
 
-    if file_system is None:
-        file_system = dp.FileClient.get_gcs_file_system()
+    if fs is None:
+        fs = dp.FileClient.get_gcs_file_system()
 
     pd.io.parquet.BaseImpl.validate_dataframe(df)
 
@@ -127,8 +118,10 @@ def write_geopandas(
         dp.write_pandas(df, gcs_path, **kwargs)
         return
 
+    fs = dp.FileClient.get_gcs_file_system()
+
     if ".parquet" in gcs_path or "prqt" in gcs_path:
-        with file_system.open(gcs_path, mode="wb") as buffer:
+        with fs.open(gcs_path, mode="wb") as buffer:
             table = _geopandas_to_arrow(df, index=df.index, schema_version=None)
             parquet.write_table(table, buffer, compression="snappy", **kwargs)
         return
@@ -146,7 +139,7 @@ def write_geopandas(
     else:
         driver = None
 
-    with file_system.open(gcs_path, "wb") as file:
+    with fs.open(gcs_path, "wb") as file:
         df.to_file(file, driver=driver, layer=layer)
 
 
@@ -160,8 +153,8 @@ def exists(path: str | Path) -> bool:
         True if the path exists, False if not.
     """
 
-    file_system = dp.FileClient.get_gcs_file_system()
-    return file_system.exists(path)
+    fs = dp.FileClient.get_gcs_file_system()
+    return fs.exists(path)
 
 
 def check_files(

From 17c19155001328c6a9a9a90d3ab522d126fa3acb Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Fri, 5 Apr 2024 12:12:57 +0200
Subject: [PATCH 10/42] parallel_overlay

---
 src/sgis/__init__.py          |  8 +++++-
 src/sgis/parallel/parallel.py | 54 ++++++++++++++++++-----------------
 2 files changed, 35 insertions(+), 27 deletions(-)

diff --git a/src/sgis/__init__.py b/src/sgis/__init__.py
index be9fc56c..76f9d798 100644
--- a/src/sgis/__init__.py
+++ b/src/sgis/__init__.py
@@ -22,13 +22,17 @@
     buffdiss,
     buffdissexp,
     buffdissexp_by_cluster,
+    diss,
+    diss_by_cluster,
     dissexp,
     dissexp_by_cluster,
 )
 from .geopandas_tools.centerlines import get_rough_centerlines
 from .geopandas_tools.cleaning import (
     coverage_clean,
+    remove_interior_slivers,
     remove_spikes,
+    simplify_and_update,
     snap_polygons,
     snap_to_mask,
     split_and_eliminate_by_longest,
@@ -76,6 +80,7 @@
     get_neighbor_dfs,
     get_neighbor_indices,
     k_nearest_neighbors,
+    sjoin_within_distance,
 )
 from .geopandas_tools.overlay import clean_overlay
 from .geopandas_tools.point_operations import snap_all, snap_within_distance
@@ -87,6 +92,7 @@
     eliminate_by_largest,
     eliminate_by_longest,
     eliminate_by_smallest,
+    get_cluster_mapper,
     get_gaps,
     get_holes,
     get_polygon_clusters,
@@ -130,7 +136,7 @@
     make_node_ids,
 )
 from .networkanalysis.traveling_salesman import traveling_salesman_problem
-from .parallel.parallel import Parallel
+from .parallel.parallel import Parallel, parallel_overlay
 from .raster.cube import DataCube
 
 
diff --git a/src/sgis/parallel/parallel.py b/src/sgis/parallel/parallel.py
index b56e373f..c891417f 100644
--- a/src/sgis/parallel/parallel.py
+++ b/src/sgis/parallel/parallel.py
@@ -727,12 +727,11 @@ def _fix_missing_muni_numbers(
         if not clip:
             notna_anymore = isna.sjoin(municipalities).drop(columns="index_right")
         else:
-            notna_anymore = intersect_by_municipalities(
+            notna_anymore = parallel_overlay(
                 isna,
-                municipalities,
-                muni_number_col,
-                max_rows_per_chunk,
-                processes_in_clip,
+                municipalities[[muni_number_col, municipalities._geometry_column_name]],
+                processes=processes_in_clip,
+                max_rows_per_chunk=max_rows_per_chunk,
             )
 
         return pd.concat([notna, notna_anymore], ignore_index=True)
@@ -740,43 +739,46 @@ def _fix_missing_muni_numbers(
     if not clip:
         return gdf.sjoin(municipalities).drop(columns="index_right")
     else:
-        return intersect_by_municipalities(
+        return parallel_overlay(
             gdf,
-            municipalities,
-            muni_number_col,
-            max_rows_per_chunk,
-            processes_in_clip,
+            municipalities[[muni_number_col, municipalities._geometry_column_name]],
+            processes=processes_in_clip,
+            max_rows_per_chunk=max_rows_per_chunk,
         )
 
 
-def intersect_by_municipalities(
-    df: GeoDataFrame,
-    municipalities: GeoDataFrame,
-    muni_number_col: str,
+def parallel_overlay(
+    df1: GeoDataFrame,
+    df2: GeoDataFrame,
+    # muni_number_col: str,
+    processes: int,
     max_rows_per_chunk: int,
-    processes_in_clip: int,
+    backend: str = "loky",
+    **kwargs,
 ) -> GeoDataFrame:
-    if len(df) < max_rows_per_chunk:
-        return clean_overlay(df, municipalities)
+    # df2 = df2[[muni_number_col, df2._geometry_column_name]]
 
-    municipalities = municipalities.dissolve(by=muni_number_col, as_index=False)
+    if len(df1) < max_rows_per_chunk:
+        return clean_overlay(df1, df2, **kwargs)
 
-    n_chunks = len(df) // max_rows_per_chunk
-    chunks = np.array_split(np.arange(len(df)), n_chunks)
+    # df2 = df2.dissolve(by=muni_number_col, as_index=False)
+
+    n_chunks = len(df1) // max_rows_per_chunk
+    chunks = np.array_split(np.arange(len(df1)), n_chunks)
 
     try:
-        x_mapper = dict(enumerate(df.centroid))
+        x_mapper = dict(enumerate(df1.centroid))
         sorted_xs = dict(reversed(sorted(x_mapper.items(), key=lambda item: item[1])))
-        df = df.iloc[list(sorted_xs)]
+        df1 = df1.iloc[list(sorted_xs)]
     except TypeError:
         pass
 
-    df_chunked: list[GeoDataFrame] = [df.iloc[chunk] for chunk in chunks]
+    df1_chunked: list[GeoDataFrame] = [df1.iloc[chunk] for chunk in chunks]
 
-    out = Parallel(processes_in_clip, backend="loky").map(
+    out = Parallel(processes, backend=backend).map(
         _clean_intersection,
-        df_chunked,
-        args=(municipalities,),
+        df1_chunked,
+        args=(df2,),
     )
     return pd.concat(out, ignore_index=True)
 

From 1bdf8d70409613f80e0c4695bbab55e941eba5d7 Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Fri, 5 Apr 2024 12:15:05 +0200
Subject: [PATCH 11/42] with 'if 1'

---
 src/sgis/geopandas_tools/overlay.py | 214 +++++++++++++++++++++-------
 1 file changed, 161 insertions(+), 53 deletions(-)

diff --git a/src/sgis/geopandas_tools/overlay.py b/src/sgis/geopandas_tools/overlay.py
index ebf64e88..bbfdaa1d 100644
--- a/src/sgis/geopandas_tools/overlay.py
+++ b/src/sgis/geopandas_tools/overlay.py
@@ -11,6 +11,7 @@
 import functools
 
 import dask
+import dask.array as da
 import geopandas as gpd
 import joblib
 import numpy as np
@@ -49,6 +50,7 @@ def clean_overlay(
     how: str = "intersection",
     keep_geom_type: bool | None = None,
     geom_type: str | None = None,
+    predicate: str | None = "intersects",
     grid_size: float | None = None,
     n_jobs: int = 1,
     lsuffix: str = DEFAULT_LSUFFIX,
@@ -158,6 +160,7 @@ def clean_overlay(
                 rsuffix=rsuffix,
                 geom_type=geom_type,
                 n_jobs=n_jobs,
+                predicate=predicate,
             ),
             geometry="geometry",
             crs=crs,
@@ -222,6 +225,7 @@ def _shapely_pd_overlay(
     df2: DataFrame,
     how: str,
     grid_size: float = DEFAULT_GRID_SIZE,
+    predicate: str = "intersects",
     lsuffix=DEFAULT_LSUFFIX,
     rsuffix=DEFAULT_RSUFFIX,
     geom_type=None,
@@ -231,7 +235,7 @@ def _shapely_pd_overlay(
         return _no_intersections_return(df1, df2, how, lsuffix, rsuffix)
 
     tree = STRtree(df2.geometry.values)
-    left, right = tree.query(df1.geometry.values, predicate="intersects")
+    left, right = tree.query(df1.geometry.values, predicate=predicate)
 
     pairs = _get_intersects_pairs(df1, df2, left, right, rsuffix)
     assert pairs.geometry.notna().all()
@@ -326,12 +330,25 @@ def _run_overlay_dask(arr1, arr2, func, n_jobs, grid_size):
             return func(arr1, arr2, grid_size=grid_size)
         except TypeError as e:
             raise TypeError(e, {type(x) for x in arr1}, {type(x) for x in arr2})
-    arr1 = dask.array.from_array(arr1, chunks=len(arr1) // n_jobs)
-    arr2 = dask.array.from_array(arr2, chunks=len(arr2) // n_jobs)
+    arr1 = da.from_array(arr1, chunks=len(arr1) // n_jobs)
+    arr2 = da.from_array(arr2, chunks=len(arr2) // n_jobs)
     res = arr1.map_blocks(func, arr2, grid_size=grid_size, dtype=float)
     return res.compute(scheduler="threads", optimize_graph=False, num_workers=n_jobs)
 
 
+def _run_overlay_dask(arr1, arr2, func, n_jobs, grid_size):
+    if len(arr1) // n_jobs <= 1:
+        try:
+            return func(arr1, arr2, grid_size=grid_size)
+        except TypeError as e:
+            raise TypeError(e, {type(x) for x in arr1}, {type(x) for x in arr2})
+    with joblib.Parallel(n_jobs=n_jobs, backend="threading") as parallel:
+        return parallel(
+            joblib.delayed(func)(g1, g2, grid_size=grid_size)
+            for g1, g2 in zip(arr1, arr2, strict=True)
+        )
+
+
 def _intersection(pairs, grid_size, geom_type, n_jobs=1) -> GeoDataFrame:
     if not len(pairs):
         return pairs.drop(columns="geom_right")
@@ -342,8 +359,8 @@ def _intersection(pairs, grid_size, geom_type, n_jobs=1) -> GeoDataFrame:
     arr2 = intersections["geom_right"].to_numpy()
 
     if n_jobs > 1 and len(arr1) / n_jobs > 10:
-        # dask_arr1 = dask.array.from_array(arr1, chunks=int(len(arr1) / n_jobs))
-        # dask_arr2 = dask.array.from_array(arr2, chunks=int(len(arr2) / n_jobs))
+        # dask_arr1 = da.from_array(arr1, chunks=int(len(arr1) / n_jobs))
+        # dask_arr2 = da.from_array(arr2, chunks=int(len(arr2) / n_jobs))
         try:
             res = _run_overlay_dask(
                 arr1,
@@ -359,12 +376,15 @@ def _intersection(pairs, grid_size, geom_type, n_jobs=1) -> GeoDataFrame:
             arr2 = make_valid_and_keep_geom_type(
                 arr2, geom_type=geom_type, n_jobs=n_jobs
             )
-            # dask_arr1 = dask.array.from_array(arr1, chunks=int(len(arr1) / n_jobs))
-            # dask_arr2 = dask.array.from_array(arr2, chunks=int(len(arr2) / n_jobs))
+            arr1 = arr1.loc[lambda x: x.index.isin(arr2.index)]
+            arr2 = arr2.loc[lambda x: x.index.isin(arr1.index)]
+
+            # dask_arr1 = da.from_array(arr1, chunks=int(len(arr1) / n_jobs))
+            # dask_arr2 = da.from_array(arr2, chunks=int(len(arr2) / n_jobs))
 
             res = _run_overlay_dask(
-                arr1,
-                arr2,
+                arr1.to_numpy(),
+                arr2.to_numpy(),
                 func=intersection,
                 n_jobs=n_jobs,
                 grid_size=grid_size,
@@ -379,18 +399,17 @@ def _intersection(pairs, grid_size, geom_type, n_jobs=1) -> GeoDataFrame:
             grid_size=grid_size,
         )
     except GEOSException:
+        left = make_valid_and_keep_geom_type(
+            intersections["geometry"].to_numpy(), geom_type, n_jobs=n_jobs
+        )
+        right = make_valid_and_keep_geom_type(
+            intersections["geom_right"].to_numpy(), geom_type, n_jobs=n_jobs
+        )
+        left = left.loc[lambda x: x.index.isin(right.index)]
+        right = right.loc[lambda x: x.index.isin(left.index)]
+
         intersections["geometry"] = intersection(
-            make_valid_and_keep_geom_type(
-                intersections["geometry"].to_numpy(),
-                geom_type=geom_type,
-                n_jobs=n_jobs,
-            ),
-            make_valid_and_keep_geom_type(
-                intersections["geom_right"].to_numpy(),
-                geom_type=geom_type,
-                n_jobs=n_jobs,
-            ),
-            grid_size=grid_size,
+            left.to_numpy(), right.to_numpy(), grid_size=grid_size
         )
 
     return intersections.drop(columns="geom_right")
@@ -531,17 +550,79 @@ def _shapely_diffclip_left(pairs, df1, grid_size, geom_type, n_jobs):
     """Aggregate areas in right by unique values of left, then use those to clip
     areas out of left"""
 
-    aggfuncs = {
-        c: "first"
-        for c in df1.columns
-        if c not in ["_overlay_index_right", "geom_right"]
-    }
+    keep_cols = list(df1.columns.difference({"_overlay_index_right"})) + ["geom_right"]
 
-    # if n_jobs == 1:
     agg_geoms_partial = functools.partial(agg_geoms, grid_size=grid_size)
-    aggfuncs |= {"geom_right": agg_geoms_partial}
 
-    clip_left = pairs.groupby(level=0).agg(aggfuncs)
+    try:
+        only_one = pairs.groupby(level=0).transform("size") == 1
+        one_hit = pairs.loc[only_one, list(keep_cols)]
+        many_hits = pairs.loc[~only_one, list(keep_cols) + ["_overlay_index_right"]]
+        # keep first in non-geom-cols, agg only geom col bacause of speed
+        many_hits_agged = many_hits.loc[
+            lambda x: ~x.index.duplicated(),
+            lambda x: x.columns.difference({"geom_right"}),
+        ]
+
+        if 1:
+
+            index_mapper = {
+                i: x
+                for i, x in many_hits.groupby(level=0)["_overlay_index_right"]
+                .unique()
+                .apply(lambda j: tuple(sorted(j)))
+                .items()
+            }
+
+            many_hits_agged["_right_indices"] = index_mapper
+
+            inverse_index_mapper = pd.Series(
+                {
+                    x[0]: x
+                    for x in many_hits_agged.reset_index()
+                    .groupby("_right_indices")["index"]
+                    .unique()
+                    .apply(tuple)
+                }
+            ).explode()
+            inverse_index_mapper = pd.Series(
+                inverse_index_mapper.index, index=inverse_index_mapper.values
+            )
+
+            agger = (
+                pd.Series(index_mapper.values(), index=index_mapper.keys())
+                .drop_duplicates()
+                .explode()
+                .to_frame("_overlay_index_right")
+            )
+            agger["geom_right"] = agger["_overlay_index_right"].map(
+                {
+                    i: g
+                    for i, g in zip(
+                        many_hits["_overlay_index_right"], many_hits["geom_right"]
+                    )
+                }
+            )
+
+            agged = pd.Series(
+                {
+                    i: agg_geoms_partial(geoms)
+                    for i, geoms in agger.groupby(level=0)["geom_right"]
+                }
+            )
+            many_hits_agged["geom_right"] = inverse_index_mapper.map(agged)
+            many_hits_agged = many_hits_agged.drop(columns=["_right_indices"])
+        else:
+            many_hits_agged["geom_right"] = {
+                i: agg_geoms_partial(geoms)
+                for i, geoms in many_hits.groupby(level=0)["geom_right"]
+            }  # .agg(
+            #     agg_geoms_partial
+            # )
+
+        clip_left = pd.concat([one_hit, many_hits_agged])
+    except IndexError:
+        clip_left = pairs.loc[:, list(keep_cols)]
 
     # if n_jobs > 1:
     #     clip_left["geom_right"] = parallel_unary_union(
@@ -565,23 +646,41 @@ def _shapely_diffclip_left(pairs, df1, grid_size, geom_type, n_jobs):
 def _shapely_diffclip_right(pairs, df1, df2, grid_size, rsuffix, geom_type, n_jobs):
     agg_geoms_partial = functools.partial(agg_geoms, grid_size=grid_size)
 
-    clip_right = (
-        pairs.rename(columns={"geometry": "geom_left", "geom_right": "geometry"})
-        .groupby(by="_overlay_index_right")
-        .agg(
-            {
-                "geom_left": agg_geoms_partial,
-                "geometry": "first",
-            }
+    pairs = pairs.rename(columns={"geometry": "geom_left", "geom_right": "geometry"})
+
+    try:
+        only_one = pairs.groupby("_overlay_index_right").transform("size") == 1
+        one_hit = pairs[only_one].set_index("_overlay_index_right")[
+            ["geom_left", "geometry"]
+        ]
+        many_hits = (
+            pairs[~only_one]
+            .groupby("_overlay_index_right")
+            .agg(
+                {
+                    "geom_left": agg_geoms_partial,
+                    "geometry": "first",
+                }
+            )
         )
-        .join(df2.drop(columns=["geometry"]))
-        .rename(
+        clip_right = (
+            pd.concat([one_hit, many_hits])
+            .join(df2.drop(columns=["geometry"]))
+            .rename(
+                columns={
+                    c: f"{c}{rsuffix}" if c in df1.columns and c != "geometry" else c
+                    for c in df2.columns
+                }
+            )
+        )
+    except IndexError:
+        # one_hit = pairs[lambda x: x.index == min(x.index) - 1]
+        clip_right = pairs.join(df2.drop(columns=["geometry"])).rename(
             columns={
                 c: f"{c}{rsuffix}" if c in df1.columns and c != "geometry" else c
                 for c in df2.columns
             }
         )
-    )
 
     assert clip_right["geometry"].notna().all()
     assert clip_right["geom_left"].notna().all()
@@ -599,8 +698,8 @@ def _shapely_diffclip_right(pairs, df1, df2, grid_size, rsuffix, geom_type, n_jo
 def _try_difference(left, right, grid_size, geom_type, n_jobs=1):
     """Try difference overlay, then make_valid and retry."""
     if n_jobs > 1 and len(left) / n_jobs > 10:
-        # dask_arr1 = dask.array.from_array(left, chunks=int(len(left) / n_jobs))
-        # dask_arr2 = dask.array.from_array(right, chunks=int(len(right) / n_jobs))
+        # dask_arr1 = da.from_array(left, chunks=int(len(left) / n_jobs))
+        # dask_arr2 = da.from_array(right, chunks=int(len(right) / n_jobs))
         # dask_arr1 = make_valid_and_keep_geom_type(dask_arr1, geom_type=geom_type)
         # dask_arr2 = make_valid_and_keep_geom_type(dask_arr2, geom_type=geom_type)
         try:
@@ -618,12 +717,14 @@ def _try_difference(left, right, grid_size, geom_type, n_jobs=1):
             right = make_valid_and_keep_geom_type(
                 right, geom_type=geom_type, n_jobs=n_jobs
             )
-            # dask_arr1 = dask.array.from_array(arr1, chunks=int(len(arr1) / n_jobs))
-            # dask_arr2 = dask.array.from_array(arr2, chunks=int(len(arr2) / n_jobs))
+            left = left.loc[lambda x: x.index.isin(right.index)]
+            right = right.loc[lambda x: x.index.isin(left.index)]
+            # dask_arr1 = da.from_array(arr1, chunks=int(len(arr1) / n_jobs))
+            # dask_arr2 = da.from_array(arr2, chunks=int(len(arr2) / n_jobs))
 
             return _run_overlay_dask(
-                left,
-                right,
+                left.to_numpy(),
+                right.to_numpy(),
                 func=difference,
                 n_jobs=n_jobs,
                 grid_size=grid_size,
@@ -636,10 +737,14 @@ def _try_difference(left, right, grid_size, geom_type, n_jobs=1):
             grid_size=grid_size,
         )
     except GEOSException:
+        left = make_valid_and_keep_geom_type(left, geom_type, n_jobs=n_jobs)
+        right = make_valid_and_keep_geom_type(right, geom_type, n_jobs=n_jobs)
+        left = left.loc[lambda x: x.index.isin(right.index)]
+        right = right.loc[lambda x: x.index.isin(left.index)]
         try:
             return difference(
-                make_valid_and_keep_geom_type(left, geom_type, n_jobs=n_jobs),
-                make_valid_and_keep_geom_type(right, geom_type, n_jobs=n_jobs),
+                left.to_numpy(),
+                right.to_numpy(),
                 grid_size=grid_size,
             )
         except GEOSException as e:
@@ -648,7 +753,7 @@ def _try_difference(left, right, grid_size, geom_type, n_jobs=1):
 
 def make_valid_and_keep_geom_type(
     geoms: np.ndarray, geom_type: str, n_jobs
-) -> np.ndarray:
+) -> GeoSeries:
     """Make GeometryCollections into (Multi)Polygons, (Multi)LineStrings or (Multi)Points.
 
     Because GeometryCollections might appear after dissolving (unary_union).
@@ -657,12 +762,15 @@ def make_valid_and_keep_geom_type(
     """
     geoms = GeoSeries(geoms)
     geoms.index = range(len(geoms))
-    geoms.loc[:] = make_valid(geoms.values)
+    geoms.loc[:] = make_valid(geoms.to_numpy())
     geoms = geoms.explode(index_parts=False).pipe(to_single_geom_type, geom_type)
-    return geoms.groupby(level=0).agg(unary_union).sort_index().values
+    only_one = geoms.groupby(level=0).transform("size") == 1
+    one_hit = geoms[only_one]
+    many_hits = geoms[~only_one].groupby(level=0).agg(unary_union)
+    return pd.concat([one_hit, many_hits]).sort_index()  # .to_numpy()
 
 
 def agg_geoms(g, grid_size=None):
-    return (
-        make_valid(unary_union(g, grid_size=grid_size)) if len(g) > 1 else make_valid(g)
-    )
+    return make_valid(
+        unary_union(g, grid_size=grid_size)
+    )  # if len(g) > 1 else make_valid(g)

From db1fc53b5b754f7acac6b66658adb87961c3b16c Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Fri, 5 Apr 2024 12:15:36 +0200
Subject: [PATCH 12/42] without 'if 1'

---
 src/sgis/geopandas_tools/overlay.py | 89 +++++++++++++----------------
 1 file changed, 40 insertions(+), 49 deletions(-)

diff --git a/src/sgis/geopandas_tools/overlay.py b/src/sgis/geopandas_tools/overlay.py
index bbfdaa1d..ba31eb73 100644
--- a/src/sgis/geopandas_tools/overlay.py
+++ b/src/sgis/geopandas_tools/overlay.py
@@ -564,61 +564,52 @@ def _shapely_diffclip_left(pairs, df1, grid_size, geom_type, n_jobs):
             lambda x: x.columns.difference({"geom_right"}),
         ]
 
-        if 1:
+        index_mapper = {
+            i: x
+            for i, x in many_hits.groupby(level=0)["_overlay_index_right"]
+            .unique()
+            .apply(lambda j: tuple(sorted(j)))
+            .items()
+        }
+
+        many_hits_agged["_right_indices"] = index_mapper
 
-            index_mapper = {
-                i: x
-                for i, x in many_hits.groupby(level=0)["_overlay_index_right"]
+        inverse_index_mapper = pd.Series(
+            {
+                x[0]: x
+                for x in many_hits_agged.reset_index()
+                .groupby("_right_indices")["index"]
                 .unique()
-                .apply(lambda j: tuple(sorted(j)))
-                .items()
+                .apply(tuple)
             }
+        ).explode()
+        inverse_index_mapper = pd.Series(
+            inverse_index_mapper.index, index=inverse_index_mapper.values
+        )
 
-            many_hits_agged["_right_indices"] = index_mapper
-
-            inverse_index_mapper = pd.Series(
-                {
-                    x[0]: x
-                    for x in many_hits_agged.reset_index()
-                    .groupby("_right_indices")["index"]
-                    .unique()
-                    .apply(tuple)
-                }
-            ).explode()
-            inverse_index_mapper = pd.Series(
-                inverse_index_mapper.index, index=inverse_index_mapper.values
-            )
-
-            agger = (
-                pd.Series(index_mapper.values(), index=index_mapper.keys())
-                .drop_duplicates()
-                .explode()
-                .to_frame("_overlay_index_right")
-            )
-            agger["geom_right"] = agger["_overlay_index_right"].map(
-                {
-                    i: g
-                    for i, g in zip(
-                        many_hits["_overlay_index_right"], many_hits["geom_right"]
-                    )
-                }
-            )
+        agger = (
+            pd.Series(index_mapper.values(), index=index_mapper.keys())
+            .drop_duplicates()
+            .explode()
+            .to_frame("_overlay_index_right")
+        )
+        agger["geom_right"] = agger["_overlay_index_right"].map(
+            {
+                i: g
+                for i, g in zip(
+                    many_hits["_overlay_index_right"], many_hits["geom_right"]
+                )
+            }
+        )
 
-            agged = pd.Series(
-                {
-                    i: agg_geoms_partial(geoms)
-                    for i, geoms in agger.groupby(level=0)["geom_right"]
-                }
-            )
-            many_hits_agged["geom_right"] = inverse_index_mapper.map(agged)
-            many_hits_agged = many_hits_agged.drop(columns=["_right_indices"])
-        else:
-            many_hits_agged["geom_right"] = {
+        agged = pd.Series(
+            {
                 i: agg_geoms_partial(geoms)
-                for i, geoms in many_hits.groupby(level=0)["geom_right"]
-            }  # .agg(
-            #     agg_geoms_partial
-            # )
+                for i, geoms in agger.groupby(level=0)["geom_right"]
+            }
+        )
+        many_hits_agged["geom_right"] = inverse_index_mapper.map(agged)
+        many_hits_agged = many_hits_agged.drop(columns=["_right_indices"])
 
         clip_left = pd.concat([one_hit, many_hits_agged])
     except IndexError:

From 2c25d1311f77fb2505c77c99bdace11d99cb519b Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Fri, 5 Apr 2024 12:17:12 +0200
Subject: [PATCH 13/42] with 'if 0'

---
 src/sgis/geopandas_tools/cleaning.py | 718 ++++++++++++++++++++-------
 1 file changed, 537 insertions(+), 181 deletions(-)

diff --git a/src/sgis/geopandas_tools/cleaning.py b/src/sgis/geopandas_tools/cleaning.py
index d0386978..ca24e207 100644
--- a/src/sgis/geopandas_tools/cleaning.py
+++ b/src/sgis/geopandas_tools/cleaning.py
@@ -2,6 +2,7 @@
 import warnings
 from typing import Callable
 
+import networkx as nx
 import numpy as np
 import pandas as pd
 import shapely
@@ -46,7 +47,7 @@
     to_lines,
 )
 from .geometry_types import get_geom_type, make_all_singlepart, to_single_geom_type
-from .neighbors import get_k_nearest_neighbors
+from .neighbors import get_k_nearest_neighbors, get_neighbor_indices
 from .overlay import clean_overlay
 from .polygon_operations import (
     close_all_holes,
@@ -64,6 +65,13 @@
 warnings.simplefilter(action="ignore", category=RuntimeWarning)
 
 
+from ..maps.maps import explore
+
+
+# def explore(*args, **kwargs):
+#     pass
+
+
 PRECISION = 1e-3
 BUFFER_RES = 50
 
@@ -151,7 +159,10 @@ def coverage_clean(
         lambda x: x.geom_type.isin(["Polygon", "MultiPolygon"])
     ]
 
-    gdf = safe_simplify(gdf, PRECISION)
+    try:
+        gdf = safe_simplify(gdf, PRECISION)
+    except GEOSException:
+        pass
 
     gdf = (
         clean_geoms(gdf)
@@ -188,9 +199,7 @@ def coverage_clean(
     gdf["_poly_idx"] = range(len(gdf))
 
     thin_gaps_and_double = pd.concat([gaps, double]).loc[
-        lambda x: (
-            shapely.simplify(x.geometry, PRECISION).buffer(-tolerance / 2).is_empty
-        )
+        lambda x: (x.buffer(-tolerance / 2).is_empty)
     ]
 
     all_are_thin = double["_double_idx"].isin(thin_gaps_and_double["_double_idx"]).all()
@@ -209,7 +218,7 @@ def coverage_clean(
         raise ValueError("Large double surfaces.")
 
     to_eliminate = pd.concat([thin_gaps_and_double, slivers], ignore_index=True)
-    to_eliminate = safe_simplify(to_eliminate, PRECISION)
+    # to_eliminate = safe_simplify(to_eliminate, PRECISION)
 
     to_eliminate = to_eliminate.loc[lambda x: ~x.buffer(-PRECISION / 10).is_empty]
 
@@ -309,7 +318,10 @@ def coverage_clean(
         one_hit = cleaned[only_one].drop(columns="_poly_idx")
         many_hits = cleaned[~only_one]
     except IndexError:
-        one_hit = cleaned[lambda x: x.index == min(x.index) - 1]
+        assert not cleaned["_poly_idx"].notna().any(), cleaned
+        one_hit = cleaned[lambda x: x.index == min(x.index) - 1].drop(
+            columns="_poly_idx", errors="ignore"
+        )
         many_hits = cleaned
 
     for i, grid_size in enumerate(grid_sizes):
@@ -336,10 +348,12 @@ def coverage_clean(
 
     cleaned = pd.concat([many_hits, one_hit], ignore_index=True)
 
+    gdf = gdf.drop(columns="_poly_idx")
+
     for i, grid_size in enumerate(grid_sizes):
         try:
             cleaned = clean_overlay(
-                gdf.drop(columns="_poly_idx"),
+                gdf,
                 cleaned,
                 how="update",
                 geom_type="polygon",
@@ -347,16 +361,6 @@ def coverage_clean(
             )
             break
         except GEOSException as e:
-            if 1 == 0:
-                try:
-                    cleaned = update_geometries(
-                        sort_small_first(cleaned),
-                        geom_type="polygon",
-                        grid_size=grid_size,
-                        n_jobs=n_jobs,
-                    )
-                except GEOSException:
-                    pass
             if i == len(grid_sizes) - 1:
                 explore_geosexception(
                     e,
@@ -369,7 +373,7 @@ def coverage_clean(
                 )
                 raise e
 
-    cleaned = sort_small_first(cleaned)
+    cleaned = sort_large_first(cleaned)
 
     # slivers on bottom
     cleaned = pd.concat(split_out_slivers(cleaned, tolerance))
@@ -399,10 +403,28 @@ def coverage_clean(
     cleaned = safe_simplify(cleaned, PRECISION)
     cleaned.geometry = shapely.make_valid(cleaned.geometry)
 
-    return cleaned
+    # TODO check why polygons dissappear in rare cases. For now, just add back the missing
+    dissapeared_polygons = sfilter_inverse(gdf, cleaned.buffer(-PRECISION))
+    cleaned = pd.concat([cleaned, dissapeared_polygons])
+
+    return to_single_geom_type(cleaned, "polygon")
 
 
-def safe_simplify(gdf, tolerance: float | int):
+def simplify_and_update(gdf, tolerance: float | int, **kwargs):
+    area_before = gdf.area
+    copied = gdf.copy()
+    copied.geometry = shapely.make_valid(
+        shapely.simplify(
+            copied.geometry.values,
+            tolerance,
+        )
+    )
+    diff_mapper = dict(enumerate((copied.area / area_before).values))
+    sorted_diffs = dict(reversed(sorted(diff_mapper.items(), key=lambda item: item[1])))
+    return update_geometries(copied.iloc[list(sorted_diffs)], **kwargs)
+
+
+def safe_simplify(gdf, tolerance: float | int, **kwargs):
     """Simplify only if the resulting area is no more than 1 percent larger.
 
     Because simplifying can result in holes being filled.
@@ -412,21 +434,28 @@ def safe_simplify(gdf, tolerance: float | int):
     copied.geometry = shapely.make_valid(
         shapely.simplify(copied.geometry.values, tolerance=tolerance)
     )
-    copied.loc[copied.area > length_then * 1.01, copied._geometry_column_name] = (
-        gdf.loc[copied.area > length_then * 1.01, copied._geometry_column_name]
-    )
+    filt = (copied.area > length_then * 1.01) | (copied.geometry.is_empty)
+    copied.loc[filt, copied._geometry_column_name] = gdf.loc[
+        filt, copied._geometry_column_name
+    ]
 
     return copied
 
 
-def simplify_and_put_small_on_top(gdf, tolerance: float | int, grid_size=None):
-    copied = sort_small_first(gdf)
-    copied.geometry = shapely.make_valid(
-        shapely.simplify(
-            shapely.segmentize(copied.geometry.values, tolerance), tolerance=tolerance
-        )
+def remove_interior_slivers(gdf, tolerance):
+    gdf, slivers = split_out_slivers(gdf, tolerance)
+    slivers["_idx"] = range(len(slivers))
+    without_thick = clean_overlay(
+        to_lines(slivers), buff(gdf, PRECISION), how="difference"
+    )
+    return pd.concat(
+        [
+            gdf,
+            slivers[lambda x: x["_idx"].isin(without_thick["_idx"])].drop(
+                columns="_idx"
+            ),
+        ]
     )
-    return update_geometries(copied, geom_type="polygon", grid_size=grid_size)
 
 
 def remove_spikes(
@@ -501,10 +530,8 @@ def try_for_grid_size(
     args: tuple | None = None,
     kwargs: dict | None = None,
 ):
-    if args is None:
-        args = ()
-    if kwargs is None:
-        kwargs = {}
+    args = args or ()
+    kwargs = kwargs or {}
     for i, grid_size in enumerate(grid_sizes):
         try:
             return func(*args, grid_size=grid_size, **kwargs)
@@ -589,7 +616,10 @@ def split_by_neighbors(df, split_by, tolerance, grid_size=None):
 
     intersecting_lines = (
         clean_overlay(
-            to_lines(split_by), buff(df, tolerance), how="identity", grid_size=grid_size
+            to_lines(split_by),
+            buff(df, tolerance),
+            how="intersection",
+            grid_size=grid_size,
         )
         .pipe(get_line_segments)
         .reset_index(drop=True)
@@ -703,7 +733,7 @@ def snap_polygons(
 
     geom_type = "polygon"
 
-    gdf = safe_simplify(gdf, PRECISION)
+    # gdf = safe_simplify(gdf, PRECISION)
 
     gdf = (
         clean_geoms(gdf)
@@ -734,6 +764,8 @@ def snap_polygons(
 
     gdf = to_single_geom_type(make_all_singlepart(clean_geoms(gdf)), geom_type)
 
+    return gdf  # .pipe(clean_clip, mask, geom_type="polygon")
+
     if snap_to_nodes:
         missing = clean_overlay(gdf_copy, gdf, how="difference")
 
@@ -753,7 +785,7 @@ def snap_polygons(
         sort_small_first(close_small_holes(gdf, PRECISION)), geom_type="polygon"
     )
 
-    return gdf
+    return gdf  # .pipe(clean_clip, mask, geom_type="polygon")
 
 
 def _snap_to_anchors(
@@ -761,6 +793,8 @@ def _snap_to_anchors(
     tolerance: int | float,
     anchors: GeoDataFrame | None = None,
     custom_func: Callable | None = None,
+    polygon_mapper: GeoSeries = None,
+    idx_start=0,
 ) -> GeoDataFrame:
     if not len(points):
         try:
@@ -827,24 +861,75 @@ def _snap_to_anchors(
             sfilter(points, anchors.buffer(tolerance)).index
         )
 
-    to_be_snapped = points.loc[should_be_snapped]
+    to_be_snapped = points.loc[should_be_snapped].rename(
+        columns={"_geom_idx": "_geom_idx_left"}, errors="raise"
+    )
 
     anchors["_right_geom"] = anchors.geometry
 
     snapped = (
         to_be_snapped.sjoin_nearest(anchors, max_distance=tolerance)
-        .sort_values("index_right")["_right_geom"]
+        .sort_values("index_right")  # ["_right_geom"]
         .loc[lambda x: ~x.index.duplicated()]
     )
 
-    # explore(
-    #     anchors,
-    #     to_be_snapped,
-    #     snapped=snapped,
-    #     left_on_top=points.loc[lambda x: (~x.index.isin(left_on_top.values))],
-    #     indices=points.loc[lambda x: (~x.index.isin(indices.values))],
-    #     points_i_snap_to=points.set_crs(25833),
-    # )
+    if 0:
+        # snapped_to_mask = snapped[lambda x: x["_geom_idx"] < idx_start]
+        # snapped_to_nodes = snapped  # [lambda x: x["_geom_idx"] >= idx_start]
+        snapped_to_other_polygon, snapped_to_self = (
+            snapped[
+                lambda x: (x["_geom_idx"] != x["_geom_idx_left"])
+                & (x["_geom_idx"] >= idx_start)
+            ],
+            snapped[
+                lambda x: (x["_geom_idx"] == x["_geom_idx_left"])
+                | (x["_geom_idx"] < idx_start)
+            ],
+        )
+
+        # anchors_as_polygons = anchors[
+        #     lambda x: x["_geom_idx"] >= idx_start, "_geom_idx"
+        # ].map(polygon_mapper)
+        # assert anchors_as_polygons.notna().all()
+
+        lines_to_snapped = shapely.shortest_line(
+            snapped_to_other_polygon.geometry.values,
+            snapped_to_other_polygon["_right_geom"].values,
+        )
+        assert polygon_mapper.index.name == "_geom_idx"
+        polygon_mapper = polygon_mapper.loc[
+            snapped_to_other_polygon["_geom_idx"].values
+        ]
+        was_snapped_too_far = shapely.intersects(
+            lines_to_snapped,
+            polygon_mapper.values,
+            # polygon_mapper,
+        )
+
+        snapped = pd.concat(
+            [
+                snapped_to_other_polygon["_right_geom"].iloc[
+                    was_snapped_too_far == False
+                ],
+                snapped_to_self["_right_geom"],
+            ]
+        )
+        # not_snapped_too_far = snapped_to_nodes.iloc[was_snapped_too_far == False]
+        # snapped = pd.concat(
+        #     [snapped_to_mask["_right_geom"], not_snapped_too_far["_right_geom"]]
+        # )
+
+        # lines_to_snapped = lines_to_snapped.intersects(polygon_mapper)
+
+        explore(
+            anchors,
+            snapped,
+            lines_to_snapped=to_gdf(lines_to_snapped, 25833),
+            too_far=snapped_to_other_polygon["_right_geom"].iloc[
+                was_snapped_too_far == False
+            ],
+            points_i_snap_to=points.set_crs(25833),
+        )
 
     points.loc[snapped.index, "geometry"] = snapped
 
@@ -878,22 +963,41 @@ def _snap_linearrings(
         {"geometry": geoms, "_geom_idx": np.arange(idx_start, len(geoms) + idx_start)}
     )
 
-    is_thin = GeoSeries(polygons(gdf.geometry)).buffer(-tolerance / 2).is_empty
+    as_polygons = GeoDataFrame(
+        {
+            "geometry": polygons(geoms),
+            "_geom_idx": np.arange(idx_start, len(geoms) + idx_start),
+        }
+    )
+
+    relevant_mask_nodes = sfilter(
+        mask_nodes, as_polygons.buffer(PRECISION + tolerance)
+    ).rename(columns={"_geom_idx": "_geom_idx_left"}, errors="raise")
+
+    relevant_mask_nodes["rgeom"] = relevant_mask_nodes.geometry
+
+    is_thin = as_polygons.buffer(-tolerance / 2).is_empty
+
+    as_polygons.geometry = as_polygons.geometry.buffer(-PRECISION)
+
+    polygon_mapper: GeoSeries = as_polygons.set_index("_geom_idx")["geometry"]
 
     gdf["_is_thin"] = is_thin
 
     thin = is_thin[lambda x: x == True]
+
     thin.loc[:] = None
     thin.index = thin.index.map(gdf["_geom_idx"])
 
-    # points_from_thin = (
-    #     extract_unique_points(gdf.loc[is_thin, "geometry"])
-    #     .to_frame("geometry")
-    #     .explode(ignore_index=True)
-    #     .pipe(sfilter_inverse, gdf.buffer(PRECISION))
-    # )
+    points_from_thin = (
+        extract_unique_points(gdf.loc[is_thin, "geometry"])
+        .to_frame("geometry")
+        .explode(ignore_index=True)
+        .pipe(sfilter_inverse, gdf.buffer(PRECISION))
+    )
 
     gdf = gdf.loc[is_thin == False]
+    as_polygons = as_polygons.loc[is_thin == False]
 
     points: GeoDataFrame = gdf.assign(
         geometry=lambda x: extract_unique_points(x.geometry.values)
@@ -901,42 +1005,15 @@ def _snap_linearrings(
 
     # step 1: add vertices nearest to mask nodes
 
-    segments = points_to_line_segments(points.set_index("_geom_idx"))
-    segments["_geom_idx"] = segments.index
-    segments.index = points.index
-
-    mask_nodes["rgeom"] = mask_nodes.geometry
-    joined = segments.sjoin_nearest(mask_nodes, max_distance=tolerance)
-
-    midpoints = shapely.get_point(
-        shapely.shortest_line(joined.geometry.values, joined["rgeom"].values), 0
-    )
-
-    boundaries_groupby = joined.boundary.explode(index_parts=False).groupby(level=0)
-
-    with_new_midpoints = (
-        pd.concat(
-            [
-                # first point
-                GeoSeries(boundaries_groupby.nth(0)),
-                GeoSeries(midpoints, index=joined.index),
-                # last point
-                GeoSeries(boundaries_groupby.nth(-1)),
-            ]
-        )
-        .groupby(level=0)
-        .agg(lambda x: MultiPoint(x.values))
-    )
-
-    segments.loc[with_new_midpoints.index, "geometry"] = with_new_midpoints
-
-    segments.geometry = extract_unique_points(segments.geometry)
-    points = segments.explode(ignore_index=True)
+    points = _add_midpoints_to_segments(points, relevant_mask_nodes, tolerance)
 
     # step 2: snap to mask nodes
+    assert points.index.is_unique
 
     points_by_mask_nodes = sfilter(
-        points.loc[lambda x: x["_geom_idx"] >= idx_start], mask_nodes.buffer(tolerance)
+        # points.loc[lambda x: x["_geom_idx"] >= idx_start], mask_nodes.buffer(tolerance)
+        points.loc[lambda x: x["_geom_idx"] >= idx_start],
+        mask.buffer(tolerance),
     )
 
     relevant_mask_nodes = sfilter(
@@ -944,13 +1021,6 @@ def _snap_linearrings(
         points_by_mask_nodes.buffer(tolerance),
         predicate="within",
     )
-    # explore(
-    #     relevant_mask_nodes,
-    #     points_by_mask_nodes,
-    #     points=points.set_crs(25833),
-    #     mask=to_gdf([5.37166432, 59.00987036], 4326).to_crs(25833).buffer(100),
-    # )
-
     # explore(
     #     mask,
     #     gdf,
@@ -958,37 +1028,101 @@ def _snap_linearrings(
     #     points_by_mask_nodes,
     #     segments,
     #     points=points.set_crs(25833),
-    #     mask=to_gdf([5.37166432, 59.00987036], 4326).to_crs(25833).buffer(100),
+    #     mask=to_gdf([5.36878551, 59.00852282], 4326).to_crs(25833).buffer(100),
     # )
 
     if len(relevant_mask_nodes):
-        mask_nodes["_right_geom"] = mask_nodes.geometry
-        snapped = points_by_mask_nodes.sjoin_nearest(mask_nodes, max_distance=tolerance)
+        relevant_mask_nodes["_right_geom"] = relevant_mask_nodes.geometry
+        snapped = (
+            points_by_mask_nodes.sjoin_nearest(
+                relevant_mask_nodes.rename(
+                    columns={"_geom_idx": "_geom_idx_left"}, errors="raise"
+                ),
+                # max_distance=tolerance,
+                distance_col="_dist",
+            ).sort_values("_dist")
+            # .drop_duplicates("index_right")
+        )
+
+        # only_nearest_polys = snapped.drop_duplicates("index_right")
+        # snapped["_is_nearest"] = snapped["_geom_idx"] == only_nearest_polys["_geom_idx"]
+        # snapped = snapped.loc[lambda x: x["_is_nearest"]]
+        #
 
-        anchors = GeoDataFrame(
-            {"geometry": snapped.drop_duplicates("index_right")["_right_geom"].values}
+        lines_between_mask_and_node = shapely.shortest_line(
+            snapped.geometry.values, snapped["_right_geom"].values
         )
+        if 0:
+            snapped_too_far = (
+                GeoDataFrame(
+                    {
+                        "geometry": lines_between_mask_and_node,
+                        "_geom_idx_left": snapped["_geom_idx"].values,
+                    },
+                    index=range(len(snapped)),
+                )
+                .sjoin(as_polygons)
+                .loc[lambda x: x["_geom_idx_left"] != x["_geom_idx"]]
+                .loc[lambda x: ~x.index.duplicated()]
+            )
+            not_too_far = pd.Index(range(len(snapped))).difference(
+                snapped_too_far.index
+            )
+            lines_between_mask_and_node = lines_between_mask_and_node[not_too_far]
+            snapmapper = snapped["_right_geom"].iloc[not_too_far]
+        else:
+            snapmapper = snapped["_right_geom"]
 
-        snapmapper = snapped["_right_geom"].loc[lambda x: ~x.index.duplicated()]
+        try:
+            points.loc[snapmapper.index, "geometry"] = snapmapper
+        except Exception:
+            points.loc[snapmapper.index, "geometry"] = snapmapper.loc[
+                lambda x: ~x.index.duplicated()
+            ]
 
-        points.loc[snapmapper.index, "geometry"] = snapmapper
-    else:
-        anchors = None
+        explore(
+            points,
+            points_by_mask_nodes,
+            mask_nodes,
+            snapped,
+            snapmapper=to_gdf(snapmapper, 25833),
+        )
+        explore(
+            points,
+            mask_nodes,
+            points_by_mask_nodes=points_by_mask_nodes.loc[lambda x: x._geom_idx == 114],
+            snapped=snapped.loc[lambda x: x._geom_idx == 114],
+            snapmapper=to_gdf(snapmapper, 25833),
+        )
+        explore(
+            points,
+            mask_nodes,
+            points_by_mask_nodes=points_by_mask_nodes.loc[lambda x: x._geom_idx == 25],
+            snapped=snapped.loc[lambda x: x._geom_idx == 25],
+            snapmapper=to_gdf(snapmapper, 25833),
+        )
 
     if snap_to_nodes:
         snapped, anchors = _snap_to_anchors(
-            points, tolerance, anchors=mask_nodes
+            points,
+            tolerance,
+            anchors=mask_nodes,
+            idx_start=idx_start,
+            polygon_mapper=polygon_mapper,
+            # polygon_mapper=gdf.set_index("_geom_idx")["geometry"],
         )  # anchors)
     else:
         snapped = points
 
-    # remove duplicates
-    snapped = pd.concat(
-        snapped.loc[lambda x: x["_geom_idx"] == i].loc[lambda x: ~x.duplicated()]
-        for i in snapped.loc[
-            lambda x: (x["_geom_idx"] >= idx_start), "_geom_idx"
-        ].unique()
-    )
+    snapped = snapped.sort_index()
+
+    # # remove duplicates
+    # snapped = pd.concat(
+    #     snapped.loc[lambda x: x["_geom_idx"] == i].loc[lambda x: ~x.duplicated()]
+    #     for i in snapped.loc[
+    #         lambda x: (x["_geom_idx"] >= idx_start), "_geom_idx"
+    #     ].unique()
+    # )
 
     assert (snapped["_geom_idx"] >= idx_start).all()
 
@@ -1001,100 +1135,324 @@ def _snap_linearrings(
         .agg(LinearRing)
     )
 
-    as_polygons = GeoDataFrame(
+    as_snapped_polygons = GeoDataFrame(
         {"geometry": polygons(as_rings.values), "_geom_idx": as_rings.index}
     )
 
-    slivers = as_polygons.loc[lambda x: x.buffer(-tolerance / 2).is_empty]
-    snapped = snapped.loc[lambda x: ~x["_geom_idx"].isin(slivers["_geom_idx"])]
-
-    as_polygons = update_geometries(sort_small_first(as_polygons))
-
-    missing_mask_nodes = sfilter_inverse(
-        mask_nodes, as_polygons.buffer(PRECISION)
-    ).pipe(sfilter, as_polygons.buffer(PRECISION + tolerance))
-
     # explore(
     #     mask,
-    #     gdf,
-    #     anchors,
-    #     missing_mask_nodes,
-    #     snapped,
-    #     as_polygons,
-    #     points=points.set_crs(25833),
-    #     mask=to_gdf([5.37166432, 59.00987036], 4326).to_crs(25833).buffer(100),
+    #     gdf[lambda x: x["_geom_idx"] == 75],
+    #     # anchors,
+    #     snapped[lambda x: x["_geom_idx"] == 75],
+    #     as_snapped_polygons,
+    #     points=points.set_crs(25833)[lambda x: x["_geom_idx"] == 75],
+    #     mask=to_gdf([5.36878551, 59.00852282], 4326).to_crs(25833).buffer(100),
     # )
 
-    if snap_to_nodes or len(missing_mask_nodes):
-        thin_gaps = get_gaps(as_polygons, include_interiors=True).loc[
-            lambda x: x.buffer(-tolerance / 2).is_empty
-        ]
-        thin_gaps.geometry = thin_gaps.buffer(-PRECISION).buffer(PRECISION)
+    explore(
+        mask,
+        gdf,
+        # anchors,
+        snapped,
+        as_snapped_polygons,
+        upd=close_small_holes(
+            update_geometries(sort_large_first(as_snapped_polygons)), tolerance
+        ),
+        dup=get_intersections(as_snapped_polygons),
+        points=points.set_crs(25833),
+        # mask=to_gdf([5.36878551, 59.00852282], 4326).to_crs(25833).buffer(300),
+    )
 
-        assert snapped.index.is_unique
-        segments = points_to_line_segments(snapped.set_index("_geom_idx"))
-        segments["_geom_idx"] = segments.index
-        segments.index = snapped.index
+    as_snapped_polygons = close_small_holes(
+        update_geometries(sort_large_first(as_snapped_polygons)), tolerance
+    )
 
-        assert segments.index.is_unique
+    if not snap_to_nodes:
 
-        segs_by_gaps = sfilter(
-            segments,
-            pd.concat([thin_gaps, slivers]).buffer(PRECISION),
+        as_rings = (
+            GeoDataFrame(
+                {
+                    "geometry": extract_unique_points(
+                        as_snapped_polygons.geometry
+                    ).values,
+                },
+                index=as_snapped_polygons["_geom_idx"],
+            )
+            .explode(index_parts=False)
+            .loc[lambda x: x.groupby(level=0).size() > 2]
+            .groupby(level=0)["geometry"]
+            .agg(LinearRing)
         )
-        # gap_nodes = pd.concat(
-        #     [
-        #         missing_mask_nodes,
-        #         extract_unique_points(thin_gaps.geometry).to_frame("geometry"),
-        #     ]
-        # )
+
+        missing = gdf.set_index("_geom_idx")["geometry"].loc[
+            # lambda x: (~x.index.isin(as_rings.index))
+            lambda x: (~x.index.isin(as_rings.index.union(thin.index)))
+            & (x.index >= idx_start)
+        ]
+        missing.loc[:] = None
+
+        # return pd.concat([as_rings, missing]).sort_index()
+        return pd.concat([as_rings, thin, missing]).sort_index()
+
+    if 1:
+        missing_polygons = clean_overlay(
+            as_polygons, as_snapped_polygons, how="difference", geom_type="polygon"
+        )
+
+        as_snapped_polygons, slivers = split_out_slivers(as_snapped_polygons, tolerance)
+        # slivers = as_snapped_polygons.loc[
+        #     lambda x: x.buffer(-tolerance / 2).is_empty
+        # ]
+        # as_snapped_polygons = as_snapped_polygons.loc[
+        #     lambda x: ~x["_geom_idx"].isin(slivers["_geom_idx"])
+        # ]
 
         # explore(
-        #     # missing_mask_polygons,
-        #     missing_mask_nodes,
-        #     segs_by_gaps,
-        #     thin_gaps,
-        #     as_polygons=as_polygons,
-        #     anchors=anchors.set_crs(25833),
+        #     mask,
+        #     gdf,
+        #     slivers,
+        #     missing_polygons,
+        #     as_snapped_polygons=as_snapped_polygons.set_crs(25833),
         # )
 
-        # segs_by_gaps = _add_midpoints_to_segments2(
-        #     segs_by_gaps, points=gap_nodes, tolerance=tolerance
-        # )
+        as_snapped_polygons = eliminate_by_longest(
+            as_snapped_polygons, pd.concat([missing_polygons, slivers])
+        )
+        # as_snapped_polygons = pd.concat([as_snapped_polygons, missing_polygons])
+
+        # try:
+        #     only_one = as_snapped_polygons.groupby("_geom_idx").transform("size") == 1
+        #     one_hit = as_snapped_polygons[only_one]
+        #     many_hits = as_snapped_polygons[~only_one]
+        #     many_hits = (
+        #         dissexp(
+        #             many_hits,
+        #             by="_geom_idx",
+        #             aggfunc="first",
+        #             dropna=False,
+        #             # grid_size=grid_size,
+        #             # n_jobs=n_jobs,
+        #         )
+        #         .sort_index()
+        #         .reset_index(drop=False)
+        #     )
+        #     as_snapped_polygons = pd.concat([many_hits, one_hit])
+        # except IndexError:
+        #     pass
+
+        # as_snapped_polygons, slivers = split_out_slivers(as_snapped_polygons, tolerance)
+        # as_snapped_polygons = eliminate_by_longest(as_snapped_polygons, slivers)
 
-        segs_by_gaps.geometry = segmentize(segs_by_gaps.geometry, tolerance)
-        segs_by_gaps.geometry = extract_unique_points(segs_by_gaps.geometry)
-        assert segs_by_gaps.index.is_unique
+    missing_mask_nodes = sfilter_inverse(
+        mask_nodes, as_snapped_polygons.buffer(PRECISION)
+    ).pipe(sfilter, as_snapped_polygons.buffer(PRECISION + tolerance))
 
-        snapped = pd.concat(
+    print(len(missing_mask_nodes))
+
+    explore(
+        mask,
+        gdf,
+        # slivers,
+        # anchors,
+        missing_mask_nodes,
+        snapped,
+        as_snapped_polygons,
+        points=points.set_crs(25833),
+        MultiPolygon=to_gdf(
+            as_snapped_polygons[lambda x: x.geom_type == "MultiPolygon"], 25833
+        ),
+    )
+
+    as_snapped_polygons = as_snapped_polygons.explode(ignore_index=True)
+
+    snapped = (
+        GeoDataFrame(
+            {
+                "geometry": extract_unique_points(as_snapped_polygons.geometry.values),
+                "_geom_idx": as_snapped_polygons["_geom_idx"].values,
+            }
+        )
+        # .set_index("_geom_idx").geometry)
+        .explode(index_parts=False)
+    )
+
+    segments = points_to_line_segments(snapped)  # .set_index("_geom_idx"))
+    segments["_geom_idx"] = segments["_geom_idx"].values
+    segments["_new_geom_idx"] = segments.index
+    multipolygon_mapper = dict(segments["_new_geom_idx"].items())
+    assert len(snapped) == len(segments)
+    segments.index = range(len(segments))  # snapped.index
+    snapped.index = range(len(snapped))  # snapped.index
+
+    thin_gaps = get_gaps(as_snapped_polygons, include_interiors=True).loc[
+        lambda x: x.buffer(-tolerance / 2).is_empty
+    ]
+    thin_gaps.geometry = thin_gaps.buffer(-PRECISION).buffer(PRECISION)
+
+    segs_by_gaps = sfilter(
+        segments,
+        pd.concat([thin_gaps, slivers]).buffer(PRECISION),
+        # thin_gaps.buffer(PRECISION),
+    )
+    # gap_nodes = pd.concat(
+    #     [
+    #         missing_mask_nodes,
+    #         extract_unique_points(thin_gaps.geometry).to_frame("geometry"),
+    #     ]
+    # )
+
+    # segs_by_gaps = _add_midpoints_to_segments2(
+    #     segs_by_gaps, points=gap_nodes, tolerance=tolerance
+    # )
+
+    explore(
+        # missing_mask_polygons,
+        segs_by_gaps.pipe(buff, 0.08),
+        segments=segments.pipe(buff, 0.08),
+        snapped111=snapped.set_crs(25833).pipe(buff, 0.08),
+    )
+
+    segs_by_gaps.geometry = segmentize(segs_by_gaps.geometry, tolerance)
+    segs_by_gaps.geometry = extract_unique_points(segs_by_gaps.geometry)
+    assert segs_by_gaps.index.is_unique
+    assert snapped.index.is_unique
+
+    snapped = (
+        pd.concat(
             [snapped.loc[lambda x: ~x.index.isin(segs_by_gaps.index)], segs_by_gaps]
-        ).sort_index()
+        )
+        .sort_index()
+        .explode(ignore_index=True)
+    )
 
-        snapped = pd.concat(
-            snapped.loc[lambda x: x["_geom_idx"] == i].loc[lambda x: ~x.duplicated()]
-            for i in snapped["_geom_idx"].unique()
-        ).explode(ignore_index=True)
+    # snapped = pd.concat(
+    #     snapped.loc[lambda x: x["_geom_idx"] == i].loc[lambda x: ~x.duplicated()]
+    #     for i in snapped["_geom_idx"].unique()
+    # )
+
+    explore(
+        # missing_mask_polygons,
+        snapped,
+        missing_mask_nodes,
+        thin_gaps,
+        as_snapped_polygons2=as_snapped_polygons,
+        snapped2=snapped,
+        points2=points.set_crs(25833),
+    )
 
-        snapped, _ = _snap_to_anchors(snapped, tolerance, anchors=mask_nodes)
+    snapped, _ = _snap_to_anchors(
+        snapped,
+        tolerance,
+        anchors=mask_nodes,
+        idx_start=idx_start,
+        polygon_mapper=polygon_mapper,
+    )
+
+    print("snapped")
+    print(snapped)
 
     as_rings = (
-        snapped.loc[lambda x: (x["_geom_idx"] >= idx_start)]
-        .sort_index()
-        .set_index("_geom_idx")
+        snapped.sort_index()  # .loc[lambda x: (x["_geom_idx"] >= idx_start)]
+        .set_index("_new_geom_idx")
         # .pipe(_remove_legit_spikes)
         .loc[lambda x: x.groupby(level=0).size() > 2]
         .groupby(level=0)["geometry"]
         .agg(LinearRing)
     )
 
+    as_rings.index = as_rings.index.map(multipolygon_mapper)
+    print("as_rings")
+    print(as_rings)
+    as_rings = as_rings.groupby(level=0).agg(unary_union)
+
+    # as_rings = (
+    #     snapped.sort_index()  # .loc[lambda x: (x["_geom_idx"] >= idx_start)]
+    #     .set_index("_geom_idx")
+    #     # .pipe(_remove_legit_spikes)
+    #     .loc[lambda x: x.groupby(level=0).size() > 2]
+    #     .groupby(level=0)["geometry"]
+    #     .agg(LinearRing)
+    # )
+
+    slivers = slivers.set_index("_geom_idx")
+    slivers.geometry.loc[:] = None
+    thin = pd.concat([thin, slivers.geometry]).loc[
+        lambda x: (~x.index.duplicated()) & (~x.index.isin(as_rings.index))
+    ]
+
     missing = gdf.set_index("_geom_idx")["geometry"].loc[
-        lambda x: (~x.index.isin(as_rings.index)) & (x.index >= idx_start)
+        lambda x: (~x.index.isin(as_rings.index.union(thin.index)))
+        & (x.index >= idx_start)
     ]
     missing.loc[:] = None
 
     return pd.concat([as_rings, thin, missing]).sort_index()
 
 
+def _add_midpoints_to_segments(points, relevant_mask_nodes, tolerance):
+    while len(relevant_mask_nodes):
+        segments = points_to_line_segments(points.set_index("_geom_idx"))
+        segments["_geom_idx"] = segments.index
+        segments.index = points.index
+
+        joined = segments.sjoin_nearest(
+            relevant_mask_nodes,
+            max_distance=tolerance,
+        ).loc[lambda x: ~x.index.duplicated()]
+        boundaries_groupby = joined.boundary.explode(index_parts=False).groupby(level=0)
+
+        lines_between_mask_and_edge = shapely.shortest_line(
+            joined.geometry.values, joined["rgeom"].values
+        )
+
+        if 0:
+
+            snapped_too_far = (
+                GeoDataFrame(
+                    {
+                        "geometry": lines_between_mask_and_edge,
+                        "_geom_idx_left": joined["_geom_idx"].values,
+                    },
+                    index=range(len(joined)),
+                )
+                .sjoin(as_polygons)
+                .loc[lambda x: x["_geom_idx_left"] != x["_geom_idx"]]
+            )
+            not_too_far = pd.Index(range(len(joined))).difference(snapped_too_far.index)
+            joined = joined.iloc[not_too_far]
+
+            lines_between_mask_and_edge = lines_between_mask_and_edge[not_too_far]
+            midpoints = shapely.get_point(lines_between_mask_and_edge, 0)
+            # midpoints = shapely.get_point(lines_between_mask_and_edge, 1)
+
+        midpoints = shapely.get_point(lines_between_mask_and_edge, 0)
+
+        with_new_midpoints = pd.concat(
+            [
+                GeoSeries(boundaries_groupby.nth(0)),
+                GeoSeries(midpoints, index=joined.index),
+                GeoSeries(boundaries_groupby.nth(-1)),
+            ]
+        )
+
+        with_new_midpoints = (
+            with_new_midpoints.loc[lambda x: x.groupby(level=0).transform("size") == 3]
+            .groupby(level=0)
+            .agg(lambda x: LineString(x.values))
+        )
+
+        segments.loc[with_new_midpoints.index, "geometry"] = with_new_midpoints
+
+        segments.geometry = extract_unique_points(segments.geometry)
+        points = segments.explode(ignore_index=True)
+
+        relevant_mask_nodes = relevant_mask_nodes.loc[
+            lambda x: ~x.index.isin(joined["index_right"])
+        ]
+
+    return points
+
+
 def _remove_legit_spikes(df):
     """Remove points where the next and previous points are the same.
 
@@ -1264,17 +1622,15 @@ def _remove_spikes(df):
         ]
     )
 
-    # for _ in range(2):
-    if 1:
-        for i, grid_size in enumerate(grid_sizes):
-            try:
-                without_spikes = update_geometries(
-                    sort_small_first(without_spikes), geom_type="polygon"
-                )
-                break
-            except GEOSException as e:
-                if i == len(grid_sizes) - 1:
-                    raise e
+    for i, grid_size in enumerate(grid_sizes):
+        try:
+            without_spikes = update_geometries(
+                sort_small_first(without_spikes), geom_type="polygon"
+            )
+            break
+        except GEOSException as e:
+            if i == len(grid_sizes) - 1:
+                raise e
 
     for i, grid_size in enumerate(grid_sizes):
         try:

From 02e7211f01458aa81c8bbe97c9d068dca7bb5c79 Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Fri, 5 Apr 2024 12:17:45 +0200
Subject: [PATCH 14/42] without 'if 0'

---
 src/sgis/geopandas_tools/cleaning.py | 58 ----------------------------
 1 file changed, 58 deletions(-)

diff --git a/src/sgis/geopandas_tools/cleaning.py b/src/sgis/geopandas_tools/cleaning.py
index ca24e207..35c87702 100644
--- a/src/sgis/geopandas_tools/cleaning.py
+++ b/src/sgis/geopandas_tools/cleaning.py
@@ -873,64 +873,6 @@ def _snap_to_anchors(
         .loc[lambda x: ~x.index.duplicated()]
     )
 
-    if 0:
-        # snapped_to_mask = snapped[lambda x: x["_geom_idx"] < idx_start]
-        # snapped_to_nodes = snapped  # [lambda x: x["_geom_idx"] >= idx_start]
-        snapped_to_other_polygon, snapped_to_self = (
-            snapped[
-                lambda x: (x["_geom_idx"] != x["_geom_idx_left"])
-                & (x["_geom_idx"] >= idx_start)
-            ],
-            snapped[
-                lambda x: (x["_geom_idx"] == x["_geom_idx_left"])
-                | (x["_geom_idx"] < idx_start)
-            ],
-        )
-
-        # anchors_as_polygons = anchors[
-        #     lambda x: x["_geom_idx"] >= idx_start, "_geom_idx"
-        # ].map(polygon_mapper)
-        # assert anchors_as_polygons.notna().all()
-
-        lines_to_snapped = shapely.shortest_line(
-            snapped_to_other_polygon.geometry.values,
-            snapped_to_other_polygon["_right_geom"].values,
-        )
-        assert polygon_mapper.index.name == "_geom_idx"
-        polygon_mapper = polygon_mapper.loc[
-            snapped_to_other_polygon["_geom_idx"].values
-        ]
-        was_snapped_too_far = shapely.intersects(
-            lines_to_snapped,
-            polygon_mapper.values,
-            # polygon_mapper,
-        )
-
-        snapped = pd.concat(
-            [
-                snapped_to_other_polygon["_right_geom"].iloc[
-                    was_snapped_too_far == False
-                ],
-                snapped_to_self["_right_geom"],
-            ]
-        )
-        # not_snapped_too_far = snapped_to_nodes.iloc[was_snapped_too_far == False]
-        # snapped = pd.concat(
-        #     [snapped_to_mask["_right_geom"], not_snapped_too_far["_right_geom"]]
-        # )
-
-        # lines_to_snapped = lines_to_snapped.intersects(polygon_mapper)
-
-        explore(
-            anchors,
-            snapped,
-            lines_to_snapped=to_gdf(lines_to_snapped, 25833),
-            too_far=snapped_to_other_polygon["_right_geom"].iloc[
-                was_snapped_too_far == False
-            ],
-            points_i_snap_to=points.set_crs(25833),
-        )
-
     points.loc[snapped.index, "geometry"] = snapped
 
     return points, anchors[["geometry"]]

From 29eb84ae9acf5d2813d6d6639ce5c912fe6e6348 Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Fri, 5 Apr 2024 12:18:38 +0200
Subject: [PATCH 15/42] docstring

---
 src/sgis/geopandas_tools/bounds.py | 8 ++------
 1 file changed, 2 insertions(+), 6 deletions(-)

diff --git a/src/sgis/geopandas_tools/bounds.py b/src/sgis/geopandas_tools/bounds.py
index d4916e6c..cac53d93 100644
--- a/src/sgis/geopandas_tools/bounds.py
+++ b/src/sgis/geopandas_tools/bounds.py
@@ -59,19 +59,15 @@ class Gridlooper:
 
     Instantiate a gridlooper.
 
-    >>> looper = sg.Gridlooper(gridsize=200, mask=buffered, parallelizer=sg.Parallel(1, backend="multiprocessing"))
+    >>> looper = sg.Gridlooper(gridsize=200, mask=buffered, concat=True, parallelizer=sg.Parallel(1, backend="multiprocessing"))
 
     Run the function clean_overlay in a gridloop.
 
-    >>> resultslist = looper.run(
+    >>> results = looper.run(
     ...     sg.clean_overlay,
     ...     points,
     ...     buffered,
     ... )
-    >>> type(resultslist)
-    list
-
-    >>> results = pd.concat(resultslist, ignore_index=True)
     >>> results
         idx_1 idx_2                        geometry
     0      220   220  POINT (254575.200 6661631.500)

From 2951468a364b390724f80f8ce3f0333f24abda4a Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Fri, 5 Apr 2024 12:21:13 +0200
Subject: [PATCH 16/42] predicate etc

---
 src/sgis/geopandas_tools/duplicates.py | 122 ++++++++++++++++++++-----
 1 file changed, 99 insertions(+), 23 deletions(-)

diff --git a/src/sgis/geopandas_tools/duplicates.py b/src/sgis/geopandas_tools/duplicates.py
index 803e9827..0527aef2 100644
--- a/src/sgis/geopandas_tools/duplicates.py
+++ b/src/sgis/geopandas_tools/duplicates.py
@@ -6,10 +6,18 @@
 from shapely import STRtree, difference, make_valid, simplify, unary_union
 from shapely.errors import GEOSException
 
-from .buffer_dissolve_explode import parallel_unary_union_geoseries
-from .general import _determine_geom_type_args, _push_geom_col, clean_geoms
+from .general import (
+    _determine_geom_type_args,
+    _push_geom_col,
+    clean_geoms,
+    parallel_unary_union_geoseries,
+)
 from .geometry_types import get_geom_type, make_all_singlepart, to_single_geom_type
 from .overlay import _run_overlay_dask, clean_overlay, make_valid_and_keep_geom_type
+from .sfilter import sfilter_inverse, sfilter_split
+
+
+PRECISION = 1e-3
 
 
 def update_geometries(
@@ -18,6 +26,7 @@ def update_geometries(
     keep_geom_type: bool | None = None,
     grid_size: int | None = None,
     n_jobs: int = 1,
+    predicate: str | None = "intersects",
 ) -> GeoDataFrame:
     """Puts geometries on top of each other rowwise.
 
@@ -81,40 +90,43 @@ def update_geometries(
     if len(gdf) <= 1:
         return gdf
 
-    gdf = make_all_singlepart(clean_geoms(gdf))
+    copied = make_all_singlepart(clean_geoms(gdf))
 
-    gdf, geom_type, keep_geom_type = _determine_geom_type_args(
-        gdf, geom_type, keep_geom_type
+    copied, geom_type, keep_geom_type = _determine_geom_type_args(
+        copied, geom_type, keep_geom_type
     )
 
-    geom_col = gdf._geometry_column_name
-    index_mapper = {i: idx for i, idx in enumerate(gdf.index)}
-    gdf = gdf.reset_index(drop=True)
+    geom_col = copied._geometry_column_name
+    index_mapper = {i: idx for i, idx in enumerate(copied.index)}
+    copied = copied.reset_index(drop=True)
 
-    tree = STRtree(gdf.geometry.values)
-    left, right = tree.query(gdf.geometry.values, predicate="intersects")
+    tree = STRtree(copied.geometry.values)
+    left, right = tree.query(copied.geometry.values, predicate=predicate)
     indices = pd.Series(right, index=left).loc[lambda x: x.index > x.values]
 
     # select geometries from 'right', index from 'left', dissolve by 'left'
+    erasers = pd.Series(copied.geometry.loc[indices.values].values, index=indices.index)
     if n_jobs > 1:
         erasers = parallel_unary_union_geoseries(
-            pd.Series(gdf.geometry.loc[indices.values].values, index=indices.index),
+            erasers,
             level=0,
             n_jobs=n_jobs,
             grid_size=grid_size,
-            # index=indices.index.unique(),
         )
         erasers = pd.Series(erasers, index=indices.index.unique())
     else:
-        erasers = (
-            pd.Series(gdf.geometry.loc[indices.values].values, index=indices.index)
+        only_one = erasers.groupby(level=0).transform("size") == 1
+        one_hit = erasers[only_one]
+        many_hits = (
+            erasers[~only_one]
             .groupby(level=0)
             .agg(lambda x: make_valid(unary_union(x, grid_size=grid_size)))
         )
+        erasers = pd.concat([one_hit, many_hits]).sort_index()
 
     # match up the aggregated erasers by index
     if n_jobs > 1:
-        arr1 = gdf.geometry.loc[erasers.index].to_numpy()
+        arr1 = copied.geometry.loc[erasers.index].to_numpy()
         arr2 = erasers.to_numpy()
         try:
             erased = _run_overlay_dask(
@@ -134,28 +146,85 @@ def update_geometries(
     else:
         erased = make_valid(
             difference(
-                gdf.geometry.loc[erasers.index],
+                copied.geometry.loc[erasers.index],
                 erasers,
                 grid_size=grid_size,
             )
         )
 
-    gdf.loc[erased.index, geom_col] = erased
+    copied.loc[erased.index, geom_col] = erased
+
+    copied = copied.loc[~copied.is_empty]
+
+    copied.index = copied.index.map(index_mapper)
 
-    gdf = gdf.loc[~gdf.is_empty]
+    # TODO check why polygons dissappear in rare cases. For now, just add back the missing
+    dissapeared = sfilter_inverse(gdf, copied.buffer(-PRECISION))
+    copied = pd.concat([copied, dissapeared])
 
-    gdf.index = gdf.index.map(index_mapper)
+    # TODO fix dupliates again with dissolve?
+    # dups = get_intersections(copied, geom_type="polygon")
+    # dups["_cluster"] = get_cluster_mapper(dups.geometry.values)
+    # no_dups = dissexp(dups, by="_cluster").drop(columns="_cluster")
+    # copied = clean_overlay(copied, no_dups, how="update", geom_type="polygon")
 
     if keep_geom_type:
-        gdf = to_single_geom_type(gdf, geom_type)
+        copied = to_single_geom_type(copied, geom_type)
 
-    return gdf
+    return copied
+
+
+def _update(many_hits, right_index_name):
+    many_hits_agged = many_hits.loc[lambda x: ~x.index.duplicated()]
+
+    index_mapper = {
+        i: x
+        for i, x in many_hits.groupby(level=0)[right_index_name]
+        .unique()
+        .apply(lambda j: tuple(sorted(j)))
+        .items()
+    }
+
+    many_hits_agged["_right_indices"] = index_mapper
+
+    inverse_index_mapper = pd.Series(
+        {
+            x[0]: x
+            for x in many_hits_agged.reset_index()
+            .groupby("_right_indices")["index"]
+            .unique()
+            .apply(tuple)
+        }
+    ).explode()
+    inverse_index_mapper = pd.Series(
+        inverse_index_mapper.index, index=inverse_index_mapper.values
+    )
+
+    agger = (
+        pd.Series(index_mapper.values(), index=index_mapper.keys())
+        .drop_duplicates()
+        .explode()
+        .to_frame(right_index_name)
+    )
+    agger["geom_right"] = agger[right_index_name].map(
+        {i: g for i, g in zip(many_hits[right_index_name], many_hits["geom_right"])}
+    )
+
+    agged = pd.Series(
+        {
+            i: agg_geoms_partial(geoms)
+            for i, geoms in agger.groupby(level=0)["geom_right"]
+        }
+    )
+    many_hits_agged["geom_right"] = inverse_index_mapper.map(agged)
+    many_hits_agged = many_hits_agged.drop(columns=["_right_indices"])
 
 
 def get_intersections(
     gdf: GeoDataFrame,
     geom_type: str | None = None,
     keep_geom_type: bool | None = None,
+    predicate: str | None = "intersects",
     n_jobs: int = 1,
 ) -> GeoDataFrame:
     """Find geometries that intersect in a GeoDataFrame.
@@ -248,6 +317,7 @@ def get_intersections(
         geom_type,
         keep_geom_type,
         n_jobs=n_jobs,
+        predicate=predicate,
     ).pipe(clean_geoms)
 
     duplicated_geoms.index = duplicated_geoms["orig_idx"].values
@@ -260,7 +330,7 @@ def get_intersections(
 
 
 def _get_intersecting_geometries(
-    gdf: GeoDataFrame, geom_type, keep_geom_type, n_jobs
+    gdf: GeoDataFrame, geom_type, keep_geom_type, n_jobs, predicate
 ) -> GeoDataFrame:
     right = gdf[[gdf._geometry_column_name]]
     right["idx_right"] = right.index
@@ -280,6 +350,7 @@ def are_not_identical(df):
             left,
             right,
             how="intersection",
+            predicate=predicate,
             geom_type=geom_type,
             keep_geom_type=keep_geom_type,
             n_jobs=n_jobs,
@@ -296,7 +367,12 @@ def are_not_identical(df):
                 continue
             intersected += [
                 clean_overlay(
-                    left, right, how="intersection", geom_type=geom_type, n_jobs=n_jobs
+                    left,
+                    right,
+                    how="intersection",
+                    predicate=predicate,
+                    geom_type=geom_type,
+                    n_jobs=n_jobs,
                 )
             ]
         intersected = pd.concat(intersected, ignore_index=True).loc[are_not_identical]

From e8d194ee48bc05440794f57cca4df7a18a53c3d2 Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Fri, 5 Apr 2024 12:21:57 +0200
Subject: [PATCH 17/42] tests

---
 tests/test_buffdissexp.py |   7 ++
 tests/test_cleaning.py    | 144 +++++++++++++++++++++-----------------
 tests/test_cube.py        |   4 +-
 tests/test_neighbors.py   |  65 +++++++++++++++++
 tests/test_overlay.py     |  13 +++-
 5 files changed, 164 insertions(+), 69 deletions(-)

diff --git a/tests/test_buffdissexp.py b/tests/test_buffdissexp.py
index 8abf1b10..d0bf9c38 100644
--- a/tests/test_buffdissexp.py
+++ b/tests/test_buffdissexp.py
@@ -79,6 +79,13 @@ def test_dissexp_by_cluster():
 
         assert list(regular.columns) == ["x", "y", "geometry"], regular.columns
 
+        diss = sg.diss_by_cluster(gdf, by="x", n_jobs=n_jobs)
+        assert list(sorted(diss.columns)) == ["geometry", "y"], diss.columns
+        diss = sg.diss_by_cluster(gdf, by=["x", "y"], n_jobs=n_jobs)
+        assert list(diss.columns) == ["geometry"], diss.columns
+        diss = sg.diss_by_cluster(gdf, by=("y",), n_jobs=n_jobs)
+        assert list(sorted(diss.columns)) == ["geometry", "x"], diss.columns
+
         diss = sg.dissexp_by_cluster(gdf, by="x", n_jobs=n_jobs)
         assert list(sorted(diss.columns)) == ["geometry", "y"], diss.columns
         diss = sg.dissexp_by_cluster(gdf, by=["x", "y"], n_jobs=n_jobs)
diff --git a/tests/test_cleaning.py b/tests/test_cleaning.py
index 3ad4dbfd..60d14acc 100644
--- a/tests/test_cleaning.py
+++ b/tests/test_cleaning.py
@@ -103,6 +103,37 @@ def test_clean_1144():
             lambda x: ~x.buffer(-tolerance / 2).is_empty, "df_idx"
         ]
 
+        cleaned = sg.coverage_clean(df, tolerance)
+
+        # cleaned = sg.coverage_clean(
+        #     sg.sort_large_first(df), tolerance, mask=kommune_utenhav
+        # ).pipe(sg.snap_polygons, 0.1, mask=kommune_utenhav)
+
+        # allow edge cases
+        cleaned_clipped = sg.clean_clip(cleaned, bbox.buffer(-tolerance * 1.1))
+
+        gaps = sg.get_gaps(cleaned_clipped)
+        double = sg.get_intersections(cleaned_clipped)
+        missing = get_missing(
+            sg.clean_clip(df, bbox.buffer(-tolerance * 1.1)), cleaned_clipped
+        )
+
+        print(
+            "cleaned",
+            gaps.area.sum(),
+            double.area.sum(),
+            missing.area.sum(),
+        )
+
+        assert thick_df_indices.isin(cleaned_clipped["df_idx"]).all(), sg.explore(
+            df,
+            cleaned,
+            missing_polygons=df[
+                (df["df_idx"].isin(thick_df_indices))
+                & (~df["df_idx"].isin(cleaned_clipped["df_idx"]))
+            ],
+        )
+
         snapped_to_mask = sg.snap_to_mask(
             sg.sort_large_first(df), tolerance, mask=kommune_utenhav
         )
@@ -152,17 +183,17 @@ def test_clean_1144():
 
         gaps = sg.get_gaps(snapped)
         double = sg.get_intersections(snapped)
+
         missing = get_missing(sg.clean_clip(df, bbox.buffer(-tolerance * 1.1)), snapped)
 
-        if missing.area.sum() > 1:
-            sg.explore(
-                missing,
-                gaps,
-                double,
-                snapped,
-                df,
-                kommune_utenhav,
-            )
+        sg.explore(
+            missing,
+            gaps,
+            double,
+            snapped,
+            df,
+            kommune_utenhav,
+        )
 
         # assert thick_df_indices.isin(snapped["df_idx"]).all(), sg.explore(
         #     df,
@@ -182,40 +213,10 @@ def test_clean_1144():
             double.area.sum(),
             missing.area.sum(),
         )
+        sss
 
-        cleaned = df.pipe(sg.coverage_clean, tolerance)
-
-        # cleaned = sg.coverage_clean(
-        #     sg.sort_large_first(df), tolerance, mask=kommune_utenhav
-        # ).pipe(sg.snap_polygons, 0.1, mask=kommune_utenhav)
-
-        # allow edge cases
-        cleaned = sg.clean_clip(cleaned, bbox.buffer(-tolerance * 1.1))
-
-        gaps = sg.get_gaps(cleaned)
-        double = sg.get_intersections(cleaned)
-        missing = get_missing(sg.clean_clip(df, bbox.buffer(-tolerance * 1.1)), cleaned)
-
-        print(
-            "cleaned",
-            gaps.area.sum(),
-            double.area.sum(),
-            missing.area.sum(),
-        )
-
-        assert thick_df_indices.isin(cleaned["df_idx"]).all(), sg.explore(
-            df,
-            snapped_to_mask,
-            missing_polygons=df[
-                (df["df_idx"].isin(thick_df_indices))
-                & (~df["df_idx"].isin(cleaned["df_idx"]))
-            ],
-        )
-
-        cleaned_and_snapped = (
-            df.pipe(  # .pipe(sg.snap_to_mask, tolerance, mask=kommune_utenhav)
-                sg.coverage_clean, tolerance
-            ).pipe(sg.snap_to_mask, tolerance, mask=kommune_utenhav)
+        cleaned_and_snapped_to_mask = sg.snap_to_mask(
+            cleaned, tolerance, mask=kommune_utenhav
         )
 
         # cleaned = sg.coverage_clean(
@@ -223,18 +224,19 @@ def test_clean_1144():
         # ).pipe(sg.snap_polygons, 0.1, mask=kommune_utenhav)
 
         # allow edge cases
-        cleaned_and_snapped = sg.clean_clip(
-            cleaned_and_snapped, bbox.buffer(-tolerance * 1.1)
+        cleaned_and_snapped_to_mask = sg.clean_clip(
+            cleaned_and_snapped_to_mask, bbox.buffer(-tolerance * 1.1)
         )
 
-        gaps = sg.get_gaps(cleaned_and_snapped)
-        double = sg.get_intersections(cleaned_and_snapped)
+        gaps = sg.get_gaps(cleaned_and_snapped_to_mask)
+        double = sg.get_intersections(cleaned_and_snapped_to_mask)
         missing = get_missing(
-            sg.clean_clip(df, bbox.buffer(-tolerance * 1.1)), cleaned_and_snapped
+            sg.clean_clip(df, bbox.buffer(-tolerance * 1.1)),
+            cleaned_and_snapped_to_mask,
         )
 
         print(
-            "cleaned_and_snapped",
+            "cleaned_and_snapped_to_mask",
             gaps.area.sum(),
             double.area.sum(),
             missing.area.sum(),
@@ -254,14 +256,16 @@ def test_clean_1144():
         )
 
         assert list(sorted(cleaned.columns)) == cols, list(sorted(cleaned.columns))
-        # assert thick_df_indices.isin(cleaned_and_snapped["df_idx"]).all(), sg.explore(
-        #     df,
-        #     snapped_to_mask,
-        #     missing_polygons=df[
-        #         (df["df_idx"].isin(thick_df_indices))
-        #         & (~df["df_idx"].isin(cleaned_and_snapped["df_idx"]))
-        #     ],
-        # )
+        assert thick_df_indices.isin(
+            cleaned_and_snapped_to_mask["df_idx"]
+        ).all(), sg.explore(
+            df,
+            snapped_to_mask,
+            missing_polygons=df[
+                (df["df_idx"].isin(thick_df_indices))
+                & (~df["df_idx"].isin(cleaned_and_snapped_to_mask["df_idx"]))
+            ],
+        )
 
         assert double.area.sum() < 1e-4, double.area.sum()
         assert gaps.area.sum() < 1e-3, (
@@ -283,12 +287,12 @@ def test_clean_1144():
         assert sg.get_geom_type(cleaned) == "polygon", sg.get_geom_type(cleaned)
 
         print("cleaning cleaned")
-        cleaned2 = sg.coverage_clean(cleaned, tolerance=tolerance).pipe(
-            sg.snap_polygons, 0.1, mask=kommune_utenhav
+        cleaned_and_snapped_to_mask = sg.snap_polygons(
+            cleaned, tolerance, mask=kommune_utenhav
         )
 
-        gaps = sg.get_gaps(cleaned2)
-        double = sg.get_intersections(cleaned2)
+        gaps = sg.get_gaps(cleaned_and_snapped_to_mask)
+        double = sg.get_intersections(cleaned_and_snapped_to_mask)
         missing = get_missing(sg.clean_clip(df, bbox.buffer(-tolerance * 1.1)), cleaned)
 
         sg.explore(
@@ -306,7 +310,9 @@ def test_clean_1144():
             max_zoom=50,
         )
 
-        assert list(sorted(cleaned2.columns)) == cols, cleaned2.columns
+        assert (
+            list(sorted(cleaned_and_snapped_to_mask.columns)) == cols
+        ), cleaned_and_snapped_to_mask.columns
 
         assert double.area.sum() < 1e-3, double.area.sum()
         assert gaps.area.sum() < 1e-3, gaps.area.sum()
@@ -315,12 +321,14 @@ def test_clean_1144():
             missing.area.sort_values(),
         )
 
-        # assert int(cleaned2.area.sum()) == 154240, (
-        #     cleaned2.area.sum(),
+        # assert int(cleaned_and_snapped_to_mask.area.sum()) == 154240, (
+        #     cleaned_and_snapped_to_mask.area.sum(),
         #     f"tolerance: {tolerance}",
         # )
 
-        assert sg.get_geom_type(cleaned2) == "polygon", sg.get_geom_type(cleaned2)
+        assert (
+            sg.get_geom_type(cleaned_and_snapped_to_mask) == "polygon"
+        ), sg.get_geom_type(cleaned_and_snapped_to_mask)
 
         # cleaned = sg.coverage_clean(df, tolerance)
 
@@ -557,7 +565,8 @@ def not_test_spikes():
 
     tolerance = 0.09 * factor
 
-    # fixed_and_cleaned = sg.snap_polygons(df, tolerance)
+    snapped = sg.snap_polygons(df, tolerance)
+    spikes_removed = sg.remove_spikes(df, tolerance)
     spikes_fixed = sg.split_spiky_polygons(df, tolerance)
     fixed_and_cleaned = sg.coverage_clean(
         spikes_fixed, tolerance  # , pre_dissolve_func=_buff
@@ -566,6 +575,8 @@ def not_test_spikes():
     if __name__ == "__main__":
         sg.explore(
             fixed_and_cleaned=fixed_and_cleaned,
+            snapped=snapped,
+            spikes_removed=spikes_removed,
             # spikes_fixed=spikes_fixed,
             df=df,
         )
@@ -614,6 +625,7 @@ def is_close_enough(num1, num2):
     # assert (area := sorted([round(x, 3) for x in cleaned.area])) == sorted(
 
     #     [
+
     #         7.225,
     #         1.89,
     #         0.503,
@@ -630,12 +642,14 @@ def is_close_enough(num1, num2):
 
     #         4.02,
     #     ]
+
     # ), length
 
 
 def main():
     test_clean_1144()
     test_clean_dissappearing_polygon()
+
     test_clean()
     not_test_spikes()
 
diff --git a/tests/test_cube.py b/tests/test_cube.py
index cd41682f..98f313e3 100644
--- a/tests/test_cube.py
+++ b/tests/test_cube.py
@@ -586,6 +586,7 @@ def regular_torch(cube):
         for batch in dataloader:
             image = batch["image"]
             mask = batch["mask"]
+            print(image)
             # train a model, or make predictions using a pre-trained model
 
     cube = cube_with_torch()
@@ -598,6 +599,8 @@ def regular_torch(cube):
     # write_sentinel()
 
     def test_cube():
+        not_test_torch()
+        sss
         test_sentinel()
         not_test_gradient()
         test_explode()
@@ -615,7 +618,6 @@ def test_cube():
         not_test_zonal()
         not_test_to_crs()
         not_test_merge_from_array()
-        not_test_torch()
         # not_test_df()
 
     # cProfile.run("test_merge_performance()", sort="cumtime")
diff --git a/tests/test_neighbors.py b/tests/test_neighbors.py
index 3f7d64d5..0be48cd5 100644
--- a/tests/test_neighbors.py
+++ b/tests/test_neighbors.py
@@ -14,6 +14,70 @@
 import sgis as sg
 
 
+def test_within_distance(points_oslo):
+    p = points_oslo.copy()
+
+    p["idx"] = p.index
+    p["idx2"] = np.random.randint(10_000, 20_000, size=len(p))
+    p.index = np.random.choice(range(len(p) // 10), len(p))
+
+    df = sg.sjoin_within_distance(
+        gdf=p,
+        neighbors=p,
+        distance=0,
+        lsuffix="left",
+        rsuffix="right",
+    ).sort_index()
+    print(df)
+    assert len(df) == len(p)
+    assert (x := df["distance"] == 0).all(), x
+
+    df2 = p.sjoin(
+        p,
+        lsuffix="left",
+        rsuffix="right",
+    ).sort_index()
+    assert (df2 := df2.loc[:, lambda x: list(sorted(x.columns))]).equals(
+        df1 := df.loc[:, lambda x: list(sorted(x.columns))].drop(columns="distance")
+    ), (df1, df2)
+
+    # with buffer
+    distance = 100
+    p = p.sample(100)
+
+    df = (
+        sg.sjoin_within_distance(
+            gdf=p,
+            neighbors=p,
+            distance=distance,
+            lsuffix="left",
+            rsuffix="right",
+        )
+        .sort_index()
+        .loc[:, lambda x: list(sorted(x.columns))]
+    )
+    df = df.sort_values(list(df.columns.difference({"geometry", "distance"})))
+
+    assert (x := df["distance"] <= distance).all(), x
+
+    df2 = (
+        p.sjoin(
+            p.assign(geometry=p.buffer(distance)),
+            lsuffix="left",
+            rsuffix="right",
+        )
+        .sort_index()
+        .loc[:, lambda x: list(sorted(x.columns))]
+    )
+    df2 = df2.sort_values(list(df2.columns.difference({"geometry"})))
+
+    for col in df2.columns.difference({"geometry"}):
+        assert df2[col].equals(df[col]), (col, df2[col], df[col])
+    assert df2.index.equals(df.index), (df2.sort_index().index, df.sort_index().index)
+
+    # assert df2.equals(df.drop(columns="distance")), (df2, df.drop(columns="distance"))
+
+
 def test_k_neighbors(points_oslo):
     p = points_oslo
 
@@ -197,6 +261,7 @@ def main():
 
     points_oslo = points_oslo()
 
+    test_within_distance(points_oslo)
     test_get_neighbor_indices()
     test_k_neighbors(points_oslo)
 
diff --git a/tests/test_overlay.py b/tests/test_overlay.py
index c6c51e43..291a3660 100644
--- a/tests/test_overlay.py
+++ b/tests/test_overlay.py
@@ -1,4 +1,5 @@
 # %%
+import random
 import sys
 import warnings
 from pathlib import Path
@@ -29,7 +30,10 @@ def test_overlay(points_oslo):
     for n_jobs in [1, 3]:
         overlayed = sg.clean_overlay(p500, p1000, how="update", n_jobs=n_jobs)
         cols_should_be = ["idx", "idx1", "idx2", "geometry"]
-        assert list(overlayed.columns) == cols_should_be, list(overlayed.columns)
+        assert list(overlayed.columns) == cols_should_be, (
+            list(overlayed.columns),
+            cols_should_be,
+        )
 
         hows = [
             "difference",
@@ -55,10 +59,10 @@ def test_overlay(points_oslo):
                 .explode(ignore_index=True)
                 .explode(ignore_index=True)
             )
-            assert list(overlayed.columns) == cols, list(overlayed.columns)
+            assert list(overlayed.columns) == cols, (list(overlayed.columns), cols)
 
             overlayed2 = sg.clean_overlay(p500, p1000, how=how)
-            assert list(overlayed2.columns) == cols, list(overlayed2.columns)
+            assert list(overlayed2.columns) == cols, (list(overlayed2.columns), cols)
 
             if int(overlayed.area.sum()) != int(overlayed2.area.sum()):
                 raise ValueError(
@@ -103,6 +107,9 @@ def test_overlay_random(n=25):
             gdf1 = sg.random_points(n, loc=loc_num).pipe(sg.buff, buff_num)
             gdf2 = sg.random_points(n, loc=loc_num).pipe(sg.buff, buff_num * 0.5)
 
+            gdf1.index = [np.random.randint(low=0, high=10) for _ in range(len(gdf1))]
+            gdf2.index = [np.random.randint(low=0, high=10) for _ in range(len(gdf2))]
+
             overlayed = (
                 gdf1.overlay(gdf2, how=how)
                 .explode(ignore_index=True)

From 66dd53837775e49bace84f450eb6af53605c7383 Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Fri, 12 Apr 2024 12:47:32 +0200
Subject: [PATCH 18/42] geocoder=False because api seems to be down

---
 src/sgis/maps/explore.py | 11 +++++++++--
 1 file changed, 9 insertions(+), 2 deletions(-)

diff --git a/src/sgis/maps/explore.py b/src/sgis/maps/explore.py
index 87cf40c7..3292fcb7 100644
--- a/src/sgis/maps/explore.py
+++ b/src/sgis/maps/explore.py
@@ -3,6 +3,7 @@
 This module holds the Explore class, which is the basis for the explore, samplemap and
 clipmap functions from the 'maps' module.
 """
+
 import os
 import warnings
 from collections.abc import Iterable
@@ -138,7 +139,13 @@ def to_tile(tile: str | xyzservices.TileProvider, max_zoom: int) -> folium.TileL
 
 class Explore(Map):
     # class attribute that can be overridden locally
-    tiles = ("OpenStreetMap", "dark", "norge_i_bilder", "grunnkart")
+    tiles = (
+        "OpenStreetMap",
+        "dark",
+        "norge_i_bilder",
+        "grunnkart",
+        "OpenStreetMap",
+    )
 
     def __init__(
         self,
@@ -151,7 +158,7 @@ def __init__(
         browser: bool = False,
         prefer_canvas: bool = True,
         measure_control: bool = True,
-        geocoder: bool = True,
+        geocoder: bool = False,
         save=None,
         show: bool | Iterable[bool] | None = None,
         text: str | None = None,

From 2d64211d91d6f50f6a7582669da8aa7bf7e5fa24 Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Fri, 12 Apr 2024 12:48:29 +0200
Subject: [PATCH 19/42] change param name from fs to file_system

---
 src/sgis/io/dapla_functions.py | 34 +++++++++++++++++-----------------
 1 file changed, 17 insertions(+), 17 deletions(-)

diff --git a/src/sgis/io/dapla_functions.py b/src/sgis/io/dapla_functions.py
index cc3dbbf2..abcb1ace 100644
--- a/src/sgis/io/dapla_functions.py
+++ b/src/sgis/io/dapla_functions.py
@@ -16,7 +16,7 @@
 def read_geopandas(
     gcs_path: str | Path,
     pandas_fallback: bool = False,
-    fs: Optional[dp.gcs.GCSFileSystem] = None,
+    file_system: Optional[dp.gcs.GCSFileSystem] = None,
     **kwargs,
 ) -> GeoDataFrame | DataFrame:
     """Reads geoparquet or other geodata from a file on GCS.
@@ -45,11 +45,11 @@ def read_geopandas(
         except TypeError:
             raise TypeError(f"Unexpected type {type(gcs_path)}.")
 
-    if fs is None:
-        fs = dp.FileClient.get_gcs_file_system()
+    if file_system is None:
+        file_system = dp.FileClient.get_gcs_file_system()
 
     if "parquet" in gcs_path or "prqt" in gcs_path:
-        with fs.open(gcs_path, mode="rb") as file:
+        with file_system.open(gcs_path, mode="rb") as file:
             try:
                 return gpd.read_parquet(file, **kwargs)
             except ValueError as e:
@@ -62,7 +62,7 @@ def read_geopandas(
                 else:
                     raise e
     else:
-        with fs.open(gcs_path, mode="rb") as file:
+        with file_system.open(gcs_path, mode="rb") as file:
             try:
                 return gpd.read_file(file, **kwargs)
             except ValueError as e:
@@ -81,7 +81,7 @@ def write_geopandas(
     gcs_path: str | Path,
     overwrite: bool = True,
     pandas_fallback: bool = False,
-    fs: Optional[dp.gcs.GCSFileSystem] = None,
+    file_system: Optional[dp.gcs.GCSFileSystem] = None,
     **kwargs,
 ) -> None:
     """Writes a GeoDataFrame to the speficied format.
@@ -106,8 +106,8 @@ def write_geopandas(
     if not overwrite and exists(gcs_path):
         raise ValueError("File already exists.")
 
-    if fs is None:
-        fs = dp.FileClient.get_gcs_file_system()
+    if file_system is None:
+        file_system = dp.FileClient.get_gcs_file_system()
 
     pd.io.parquet.BaseImpl.validate_dataframe(df)
 
@@ -118,10 +118,10 @@ def write_geopandas(
         dp.write_pandas(df, gcs_path, **kwargs)
         return
 
-    fs = dp.FileClient.get_gcs_file_system()
+    file_system = dp.FileClient.get_gcs_file_system()
 
     if ".parquet" in gcs_path or "prqt" in gcs_path:
-        with fs.open(gcs_path, mode="wb") as buffer:
+        with file_system.open(gcs_path, mode="wb") as buffer:
             table = _geopandas_to_arrow(df, index=df.index, schema_version=None)
             parquet.write_table(table, buffer, compression="snappy", **kwargs)
         return
@@ -139,7 +139,7 @@ def write_geopandas(
     else:
         driver = None
 
-    with fs.open(gcs_path, "wb") as file:
+    with file_system.open(gcs_path, "wb") as file:
         df.to_file(file, driver=driver, layer=layer)
 
 
@@ -153,8 +153,8 @@ def exists(path: str | Path) -> bool:
         True if the path exists, False if not.
     """
 
-    fs = dp.FileClient.get_gcs_file_system()
-    return fs.exists(path)
+    file_system = dp.FileClient.get_gcs_file_system()
+    return file_system.exists(path)
 
 
 def check_files(
@@ -170,10 +170,10 @@ def check_files(
         within_minutes: Optionally include only files that were updated in the
             last n minutes.
     """
-    fs = dp.FileClient.get_gcs_file_system()
+    file_system = dp.FileClient.get_gcs_file_system()
 
     # (recursive doesn't work, so doing recursive search below)
-    info = fs.ls(folder, detail=True, recursive=True)
+    info = file_system.ls(folder, detail=True, recursive=True)
 
     if not info:
         return pd.DataFrame(columns=["kb", "mb", "name", "child", "path"])
@@ -225,7 +225,7 @@ def check_files(
 
 
 def get_files_in_subfolders(folderinfo: list[dict]) -> list[dict]:
-    fs = dp.FileClient.get_gcs_file_system()
+    file_system = dp.FileClient.get_gcs_file_system()
 
     if isinstance(folderinfo, (str, Path)):
         folderinfo = [folderinfo]
@@ -235,7 +235,7 @@ def get_files_in_subfolders(folderinfo: list[dict]) -> list[dict]:
     while folderinfo:
         new_folderinfo = []
         for m in folderinfo:
-            more_info = fs.ls(m, detail=True, recursive=True)
+            more_info = file_system.ls(m, detail=True, recursive=True)
             if not more_info:
                 continue
 

From 9c287333ef69b50ecdd13e365b9637f51ac90b8f Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Fri, 12 Apr 2024 12:51:28 +0200
Subject: [PATCH 20/42] swap order of bg maps because default seems to be the
 last one added now

---
 src/sgis/maps/explore.py | 5 ++---
 1 file changed, 2 insertions(+), 3 deletions(-)

diff --git a/src/sgis/maps/explore.py b/src/sgis/maps/explore.py
index 3292fcb7..0089601b 100644
--- a/src/sgis/maps/explore.py
+++ b/src/sgis/maps/explore.py
@@ -140,10 +140,9 @@ def to_tile(tile: str | xyzservices.TileProvider, max_zoom: int) -> folium.TileL
 class Explore(Map):
     # class attribute that can be overridden locally
     tiles = (
-        "OpenStreetMap",
-        "dark",
-        "norge_i_bilder",
         "grunnkart",
+        "norge_i_bilder",
+        "dark",
         "OpenStreetMap",
     )
 

From f77e080870e86bccaf817cb7efe00140dc4870da Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Fri, 12 Apr 2024 13:02:21 +0200
Subject: [PATCH 21/42] updates

---
 poetry.lock | 1622 +++++++++++++++++++++++++--------------------------
 1 file changed, 801 insertions(+), 821 deletions(-)

diff --git a/poetry.lock b/poetry.lock
index 22c7e899..5eacfe47 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -138,13 +138,13 @@ files = [
 
 [[package]]
 name = "anyio"
-version = "4.2.0"
+version = "4.3.0"
 description = "High level compatibility layer for multiple asynchronous event loop implementations"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "anyio-4.2.0-py3-none-any.whl", hash = "sha256:745843b39e829e108e518c489b31dc757de7d2131d53fac32bd8df268227bfee"},
-    {file = "anyio-4.2.0.tar.gz", hash = "sha256:e1875bb4b4e2de1669f4bc7869b6d3f54231cdced71605e6e64c9be77e3be50f"},
+    {file = "anyio-4.3.0-py3-none-any.whl", hash = "sha256:048e05d0f6caeed70d731f3db756d35dcc1f35747c8c403364a8332c630441b8"},
+    {file = "anyio-4.3.0.tar.gz", hash = "sha256:f75253795a87df48568485fd18cdd2a3fa5c4f7c5be8e5e36637733fce06fed6"},
 ]
 
 [package.dependencies]
@@ -323,13 +323,13 @@ dev = ["freezegun (>=1.0,<2.0)", "pytest (>=6.0)", "pytest-cov"]
 
 [[package]]
 name = "bandit"
-version = "1.7.7"
+version = "1.7.8"
 description = "Security oriented static analyser for python code."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "bandit-1.7.7-py3-none-any.whl", hash = "sha256:17e60786a7ea3c9ec84569fd5aee09936d116cb0cb43151023258340dbffb7ed"},
-    {file = "bandit-1.7.7.tar.gz", hash = "sha256:527906bec6088cb499aae31bc962864b4e77569e9d529ee51df3a93b4b8ab28a"},
+    {file = "bandit-1.7.8-py3-none-any.whl", hash = "sha256:509f7af645bc0cd8fd4587abc1a038fc795636671ee8204d502b933aee44f381"},
+    {file = "bandit-1.7.8.tar.gz", hash = "sha256:36de50f720856ab24a24dbaa5fee2c66050ed97c1477e0a1159deab1775eab6b"},
 ]
 
 [package.dependencies]
@@ -340,6 +340,7 @@ stevedore = ">=1.20.0"
 
 [package.extras]
 baseline = ["GitPython (>=3.1.30)"]
+sarif = ["jschema-to-python (>=1.2.3)", "sarif-om (>=1.0.4)"]
 test = ["beautifulsoup4 (>=4.8.0)", "coverage (>=4.5.4)", "fixtures (>=3.0.0)", "flake8 (>=4.0.0)", "pylint (==1.9.4)", "stestr (>=2.5.0)", "testscenarios (>=0.5.0)", "testtools (>=2.3.0)"]
 toml = ["tomli (>=1.1.0)"]
 yaml = ["PyYAML"]
@@ -367,33 +368,33 @@ lxml = ["lxml"]
 
 [[package]]
 name = "black"
-version = "24.1.1"
+version = "24.3.0"
 description = "The uncompromising code formatter."
 optional = false
 python-versions = ">=3.8"
 files = [
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-    {file = "black-24.1.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:1a95915c98d6e32ca43809d46d932e2abc5f1f7d582ffbe65a5b4d1588af7445"},
-    {file = "black-24.1.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2fa6a0e965779c8f2afb286f9ef798df770ba2b6cee063c650b96adec22c056a"},
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+    {file = "black-24.3.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d7de8d330763c66663661a1ffd432274a2f92f07feeddd89ffd085b5744f85e7"},
+    {file = "black-24.3.0-cp39-cp39-win_amd64.whl", hash = "sha256:7bb041dca0d784697af4646d3b62ba4a6b028276ae878e53f6b4f74ddd6db99f"},
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+    {file = "black-24.3.0.tar.gz", hash = "sha256:a0c9c4a0771afc6919578cec71ce82a3e31e054904e7197deacbc9382671c41f"},
 ]
 
 [package.dependencies]
@@ -535,17 +536,6 @@ files = [
     {file = "cfgv-3.4.0.tar.gz", hash = "sha256:e52591d4c5f5dead8e0f673fb16db7949d2cfb3f7da4582893288f0ded8fe560"},
 ]
 
-[[package]]
-name = "chardet"
-version = "5.2.0"
-description = "Universal encoding detector for Python 3"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "chardet-5.2.0-py3-none-any.whl", hash = "sha256:e1cf59446890a00105fe7b7912492ea04b6e6f06d4b742b2c788469e34c82970"},
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-]
-
 [[package]]
 name = "charset-normalizer"
 version = "3.3.2"
@@ -717,13 +707,13 @@ files = [
 
 [[package]]
 name = "comm"
-version = "0.2.1"
+version = "0.2.2"
 description = "Jupyter Python Comm implementation, for usage in ipykernel, xeus-python etc."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "comm-0.2.1-py3-none-any.whl", hash = "sha256:87928485c0dfc0e7976fd89fc1e187023cf587e7c353e4a9b417555b44adf021"},
-    {file = "comm-0.2.1.tar.gz", hash = "sha256:0bc91edae1344d39d3661dcbc36937181fdaddb304790458f8b044dbc064b89a"},
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+    {file = "comm-0.2.2.tar.gz", hash = "sha256:3fd7a84065306e07bea1773df6eb8282de51ba82f77c72f9c85716ab11fe980e"},
 ]
 
 [package.dependencies]
@@ -734,126 +724,126 @@ test = ["pytest"]
 
 [[package]]
 name = "contourpy"
-version = "1.2.0"
+version = "1.2.1"
 description = "Python library for calculating contours of 2D quadrilateral grids"
 optional = false
 python-versions = ">=3.9"
 files = [
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 [package.dependencies]
@@ -890,20 +880,20 @@ files = [
 
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 name = "dask"
-version = "2024.1.1"
+version = "2024.4.1"
 description = "Parallel PyData with Task Scheduling"
 optional = false
 python-versions = ">=3.9"
 files = [
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 [package.dependencies]
 click = ">=8.1"
 cloudpickle = ">=1.5.0"
 fsspec = ">=2021.09.0"
-importlib-metadata = ">=4.13.0"
+importlib-metadata = {version = ">=4.13.0", markers = "python_version < \"3.12\""}
 packaging = ">=20.0"
 partd = ">=1.2.0"
 pyyaml = ">=5.3.1"
@@ -912,36 +902,40 @@ toolz = ">=0.10.0"
 [package.extras]
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 complete = ["dask[array,dataframe,diagnostics,distributed]", "lz4 (>=4.3.2)", "pyarrow (>=7.0)", "pyarrow-hotfix"]
-dataframe = ["dask[array]", "pandas (>=1.3)"]
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 diagnostics = ["bokeh (>=2.4.2)", "jinja2 (>=2.10.3)"]
-distributed = ["distributed (==2024.1.1)"]
+distributed = ["distributed (==2024.4.1)"]
 test = ["pandas[test]", "pre-commit", "pytest", "pytest-cov", "pytest-rerunfailures", "pytest-timeout", "pytest-xdist"]
 
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 name = "debugpy"
-version = "1.8.0"
+version = "1.8.1"
 description = "An implementation of the Debug Adapter Protocol for Python"
 optional = false
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 ]
 
 [package.dependencies]
@@ -1103,14 +1103,13 @@ certifi = "*"
 click = ">=8.0,<9.0"
 click-plugins = ">=1.0"
 cligj = ">=0.5"
-setuptools = "*"
 six = "*"
 
 [package.extras]
-all = ["Fiona[calc,s3,test]"]
+all = ["fiona[calc,s3,test]"]
 calc = ["shapely"]
 s3 = ["boto3 (>=1.3.1)"]
-test = ["Fiona[s3]", "pytest (>=7)", "pytest-cov", "pytz"]
+test = ["fiona[s3]", "pytest (>=7)", "pytest-cov", "pytz"]
 
 [[package]]
 name = "flake8"
@@ -1197,13 +1196,13 @@ develop = ["build", "twine"]
 
 [[package]]
 name = "folium"
-version = "0.15.1"
+version = "0.16.0"
 description = "Make beautiful maps with Leaflet.js & Python"
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.dependencies]
@@ -1218,53 +1217,53 @@ testing = ["pytest"]
 
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 name = "fonttools"
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+version = "4.50.0"
 description = "Tools to manipulate font files"
 optional = false
 python-versions = ">=3.8"
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+    {file = "fonttools-4.50.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:a4062cc7e8de26f1603323ef3ae2171c9d29c8a9f5e067d555a2813cd5c7a7e0"},
+    {file = "fonttools-4.50.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:34692850dfd64ba06af61e5791a441f664cb7d21e7b544e8f385718430e8f8e4"},
+    {file = "fonttools-4.50.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:678dd95f26a67e02c50dcb5bf250f95231d455642afbc65a3b0bcdacd4e4dd38"},
+    {file = "fonttools-4.50.0-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:4f2ce7b0b295fe64ac0a85aef46a0f2614995774bd7bc643b85679c0283287f9"},
+    {file = "fonttools-4.50.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:d346f4dc2221bfb7ab652d1e37d327578434ce559baf7113b0f55768437fe6a0"},
+    {file = "fonttools-4.50.0-cp39-cp39-win32.whl", hash = "sha256:a51eeaf52ba3afd70bf489be20e52fdfafe6c03d652b02477c6ce23c995222f4"},
+    {file = "fonttools-4.50.0-cp39-cp39-win_amd64.whl", hash = "sha256:8639be40d583e5d9da67795aa3eeeda0488fb577a1d42ae11a5036f18fb16d93"},
+    {file = "fonttools-4.50.0-py3-none-any.whl", hash = "sha256:48fa36da06247aa8282766cfd63efff1bb24e55f020f29a335939ed3844d20d3"},
+    {file = "fonttools-4.50.0.tar.gz", hash = "sha256:fa5cf61058c7dbb104c2ac4e782bf1b2016a8cf2f69de6e4dd6a865d2c969bb5"},
 ]
 
 [package.extras]
@@ -1380,13 +1379,13 @@ files = [
 
 [[package]]
 name = "fsspec"
-version = "2024.2.0"
+version = "2024.3.1"
 description = "File-system specification"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "fsspec-2024.2.0-py3-none-any.whl", hash = "sha256:817f969556fa5916bc682e02ca2045f96ff7f586d45110fcb76022063ad2c7d8"},
-    {file = "fsspec-2024.2.0.tar.gz", hash = "sha256:b6ad1a679f760dda52b1168c859d01b7b80648ea6f7f7c7f5a8a91dc3f3ecb84"},
+    {file = "fsspec-2024.3.1-py3-none-any.whl", hash = "sha256:918d18d41bf73f0e2b261824baeb1b124bcf771767e3a26425cd7dec3332f512"},
+    {file = "fsspec-2024.3.1.tar.gz", hash = "sha256:f39780e282d7d117ffb42bb96992f8a90795e4d0fb0f661a70ca39fe9c43ded9"},
 ]
 
 [package.extras]
@@ -1432,12 +1431,13 @@ sphinx-basic-ng = "*"
 
 [[package]]
 name = "future"
-version = "0.18.3"
+version = "1.0.0"
 description = "Clean single-source support for Python 3 and 2"
 optional = false
 python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*"
 files = [
-    {file = "future-0.18.3.tar.gz", hash = "sha256:34a17436ed1e96697a86f9de3d15a3b0be01d8bc8de9c1dffd59fb8234ed5307"},
+    {file = "future-1.0.0-py3-none-any.whl", hash = "sha256:929292d34f5872e70396626ef385ec22355a1fae8ad29e1a734c3e43f9fbc216"},
+    {file = "future-1.0.0.tar.gz", hash = "sha256:bd2968309307861edae1458a4f8a4f3598c03be43b97521076aebf5d94c07b05"},
 ]
 
 [[package]]
@@ -1489,13 +1489,13 @@ files = [
 
 [[package]]
 name = "httpcore"
-version = "1.0.2"
+version = "1.0.5"
 description = "A minimal low-level HTTP client."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "httpcore-1.0.2-py3-none-any.whl", hash = "sha256:096cc05bca73b8e459a1fc3dcf585148f63e534eae4339559c9b8a8d6399acc7"},
-    {file = "httpcore-1.0.2.tar.gz", hash = "sha256:9fc092e4799b26174648e54b74ed5f683132a464e95643b226e00c2ed2fa6535"},
+    {file = "httpcore-1.0.5-py3-none-any.whl", hash = "sha256:421f18bac248b25d310f3cacd198d55b8e6125c107797b609ff9b7a6ba7991b5"},
+    {file = "httpcore-1.0.5.tar.gz", hash = "sha256:34a38e2f9291467ee3b44e89dd52615370e152954ba21721378a87b2960f7a61"},
 ]
 
 [package.dependencies]
@@ -1506,17 +1506,17 @@ h11 = ">=0.13,<0.15"
 asyncio = ["anyio (>=4.0,<5.0)"]
 http2 = ["h2 (>=3,<5)"]
 socks = ["socksio (==1.*)"]
-trio = ["trio (>=0.22.0,<0.23.0)"]
+trio = ["trio (>=0.22.0,<0.26.0)"]
 
 [[package]]
 name = "httpx"
-version = "0.26.0"
+version = "0.27.0"
 description = "The next generation HTTP client."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "httpx-0.26.0-py3-none-any.whl", hash = "sha256:8915f5a3627c4d47b73e8202457cb28f1266982d1159bd5779d86a80c0eab1cd"},
-    {file = "httpx-0.26.0.tar.gz", hash = "sha256:451b55c30d5185ea6b23c2c793abf9bb237d2a7dfb901ced6ff69ad37ec1dfaf"},
+    {file = "httpx-0.27.0-py3-none-any.whl", hash = "sha256:71d5465162c13681bff01ad59b2cc68dd838ea1f10e51574bac27103f00c91a5"},
+    {file = "httpx-0.27.0.tar.gz", hash = "sha256:a0cb88a46f32dc874e04ee956e4c2764aba2aa228f650b06788ba6bda2962ab5"},
 ]
 
 [package.dependencies]
@@ -1534,13 +1534,13 @@ socks = ["socksio (==1.*)"]
 
 [[package]]
 name = "identify"
-version = "2.5.33"
+version = "2.5.35"
 description = "File identification library for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "identify-2.5.33-py2.py3-none-any.whl", hash = "sha256:d40ce5fcd762817627670da8a7d8d8e65f24342d14539c59488dc603bf662e34"},
-    {file = "identify-2.5.33.tar.gz", hash = "sha256:161558f9fe4559e1557e1bff323e8631f6a0e4837f7497767c1782832f16b62d"},
+    {file = "identify-2.5.35-py2.py3-none-any.whl", hash = "sha256:c4de0081837b211594f8e877a6b4fad7ca32bbfc1a9307fdd61c28bfe923f13e"},
+    {file = "identify-2.5.35.tar.gz", hash = "sha256:10a7ca245cfcd756a554a7288159f72ff105ad233c7c4b9c6f0f4d108f5f6791"},
 ]
 
 [package.extras]
@@ -1627,22 +1627,22 @@ files = [
 
 [[package]]
 name = "importlib-metadata"
-version = "7.0.1"
+version = "7.1.0"
 description = "Read metadata from Python packages"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "importlib_metadata-7.0.1-py3-none-any.whl", hash = "sha256:4805911c3a4ec7c3966410053e9ec6a1fecd629117df5adee56dfc9432a1081e"},
-    {file = "importlib_metadata-7.0.1.tar.gz", hash = "sha256:f238736bb06590ae52ac1fab06a3a9ef1d8dce2b7a35b5ab329371d6c8f5d2cc"},
+    {file = "importlib_metadata-7.1.0-py3-none-any.whl", hash = "sha256:30962b96c0c223483ed6cc7280e7f0199feb01a0e40cfae4d4450fc6fab1f570"},
+    {file = "importlib_metadata-7.1.0.tar.gz", hash = "sha256:b78938b926ee8d5f020fc4772d487045805a55ddbad2ecf21c6d60938dc7fcd2"},
 ]
 
 [package.dependencies]
 zipp = ">=0.5"
 
 [package.extras]
-docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (<7.2.5)", "sphinx (>=3.5)", "sphinx-lint"]
+docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
 perf = ["ipython"]
-testing = ["flufl.flake8", "importlib-resources (>=1.3)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy (>=0.9.1)", "pytest-perf (>=0.9.2)", "pytest-ruff"]
+testing = ["flufl.flake8", "importlib-resources (>=1.3)", "jaraco.test (>=5.4)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy", "pytest-perf (>=0.9.2)", "pytest-ruff (>=0.2.1)"]
 
 [[package]]
 name = "iniconfig"
@@ -1657,13 +1657,13 @@ files = [
 
 [[package]]
 name = "ipykernel"
-version = "6.29.2"
+version = "6.29.4"
 description = "IPython Kernel for Jupyter"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "ipykernel-6.29.2-py3-none-any.whl", hash = "sha256:50384f5c577a260a1d53f1f59a828c7266d321c9b7d00d345693783f66616055"},
-    {file = "ipykernel-6.29.2.tar.gz", hash = "sha256:3bade28004e3ff624ed57974948116670604ac5f676d12339693f3142176d3f0"},
+    {file = "ipykernel-6.29.4-py3-none-any.whl", hash = "sha256:1181e653d95c6808039c509ef8e67c4126b3b3af7781496c7cbfb5ed938a27da"},
+    {file = "ipykernel-6.29.4.tar.gz", hash = "sha256:3d44070060f9475ac2092b760123fadf105d2e2493c24848b6691a7c4f42af5c"},
 ]
 
 [package.dependencies]
@@ -1686,17 +1686,17 @@ cov = ["coverage[toml]", "curio", "matplotlib", "pytest-cov", "trio"]
 docs = ["myst-parser", "pydata-sphinx-theme", "sphinx", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling", "trio"]
 pyqt5 = ["pyqt5"]
 pyside6 = ["pyside6"]
-test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0)", "pytest-asyncio (==0.23.4)", "pytest-cov", "pytest-timeout"]
+test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0)", "pytest-asyncio (>=0.23.5)", "pytest-cov", "pytest-timeout"]
 
 [[package]]
 name = "ipython"
-version = "8.21.0"
+version = "8.23.0"
 description = "IPython: Productive Interactive Computing"
 optional = false
 python-versions = ">=3.10"
 files = [
-    {file = "ipython-8.21.0-py3-none-any.whl", hash = "sha256:1050a3ab8473488d7eee163796b02e511d0735cf43a04ba2a8348bd0f2eaf8a5"},
-    {file = "ipython-8.21.0.tar.gz", hash = "sha256:48fbc236fbe0e138b88773fa0437751f14c3645fb483f1d4c5dee58b37e5ce73"},
+    {file = "ipython-8.23.0-py3-none-any.whl", hash = "sha256:07232af52a5ba146dc3372c7bf52a0f890a23edf38d77caef8d53f9cdc2584c1"},
+    {file = "ipython-8.23.0.tar.gz", hash = "sha256:7468edaf4f6de3e1b912e57f66c241e6fd3c7099f2ec2136e239e142e800274d"},
 ]
 
 [package.dependencies]
@@ -1705,24 +1705,26 @@ decorator = "*"
 exceptiongroup = {version = "*", markers = "python_version < \"3.11\""}
 jedi = ">=0.16"
 matplotlib-inline = "*"
-pexpect = {version = ">4.3", markers = "sys_platform != \"win32\""}
+pexpect = {version = ">4.3", markers = "sys_platform != \"win32\" and sys_platform != \"emscripten\""}
 prompt-toolkit = ">=3.0.41,<3.1.0"
 pygments = ">=2.4.0"
 stack-data = "*"
-traitlets = ">=5"
+traitlets = ">=5.13.0"
+typing-extensions = {version = "*", markers = "python_version < \"3.12\""}
 
 [package.extras]
-all = ["black", "curio", "docrepr", "exceptiongroup", "ipykernel", "ipyparallel", "ipywidgets", "matplotlib", "matplotlib (!=3.2.0)", "nbconvert", "nbformat", "notebook", "numpy (>=1.23)", "pandas", "pickleshare", "pytest (<8)", "pytest-asyncio (<0.22)", "qtconsole", "setuptools (>=18.5)", "sphinx (>=1.3)", "sphinx-rtd-theme", "stack-data", "testpath", "trio", "typing-extensions"]
+all = ["ipython[black,doc,kernel,matplotlib,nbconvert,nbformat,notebook,parallel,qtconsole]", "ipython[test,test-extra]"]
 black = ["black"]
-doc = ["docrepr", "exceptiongroup", "ipykernel", "matplotlib", "pickleshare", "pytest (<8)", "pytest-asyncio (<0.22)", "setuptools (>=18.5)", "sphinx (>=1.3)", "sphinx-rtd-theme", "stack-data", "testpath", "typing-extensions"]
+doc = ["docrepr", "exceptiongroup", "ipykernel", "ipython[test]", "matplotlib", "setuptools (>=18.5)", "sphinx (>=1.3)", "sphinx-rtd-theme", "sphinxcontrib-jquery", "stack-data", "typing-extensions"]
 kernel = ["ipykernel"]
+matplotlib = ["matplotlib"]
 nbconvert = ["nbconvert"]
 nbformat = ["nbformat"]
 notebook = ["ipywidgets", "notebook"]
 parallel = ["ipyparallel"]
 qtconsole = ["qtconsole"]
 test = ["pickleshare", "pytest (<8)", "pytest-asyncio (<0.22)", "testpath"]
-test-extra = ["curio", "matplotlib (!=3.2.0)", "nbformat", "numpy (>=1.23)", "pandas", "pickleshare", "pytest (<8)", "pytest-asyncio (<0.22)", "testpath", "trio"]
+test-extra = ["curio", "ipython[test]", "matplotlib (!=3.2.0)", "nbformat", "numpy (>=1.23)", "pandas", "trio"]
 
 [[package]]
 name = "isoduration"
@@ -1840,18 +1842,15 @@ files = [
 
 [[package]]
 name = "json5"
-version = "0.9.14"
+version = "0.9.24"
 description = "A Python implementation of the JSON5 data format."
 optional = false
-python-versions = "*"
+python-versions = ">=3.8"
 files = [
-    {file = "json5-0.9.14-py2.py3-none-any.whl", hash = "sha256:740c7f1b9e584a468dbb2939d8d458db3427f2c93ae2139d05f47e453eae964f"},
-    {file = "json5-0.9.14.tar.gz", hash = "sha256:9ed66c3a6ca3510a976a9ef9b8c0787de24802724ab1860bc0153c7fdd589b02"},
+    {file = "json5-0.9.24-py3-none-any.whl", hash = "sha256:4ca101fd5c7cb47960c055ef8f4d0e31e15a7c6c48c3b6f1473fc83b6c462a13"},
+    {file = "json5-0.9.24.tar.gz", hash = "sha256:0c638399421da959a20952782800e5c1a78c14e08e1dc9738fa10d8ec14d58c8"},
 ]
 
-[package.extras]
-dev = ["hypothesis"]
-
 [[package]]
 name = "jsonpointer"
 version = "2.4"
@@ -1908,13 +1907,13 @@ referencing = ">=0.31.0"
 
 [[package]]
 name = "jupyter-client"
-version = "8.6.0"
+version = "8.6.1"
 description = "Jupyter protocol implementation and client libraries"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "jupyter_client-8.6.0-py3-none-any.whl", hash = "sha256:909c474dbe62582ae62b758bca86d6518c85234bdee2d908c778db6d72f39d99"},
-    {file = "jupyter_client-8.6.0.tar.gz", hash = "sha256:0642244bb83b4764ae60d07e010e15f0e2d275ec4e918a8f7b80fbbef3ca60c7"},
+    {file = "jupyter_client-8.6.1-py3-none-any.whl", hash = "sha256:3b7bd22f058434e3b9a7ea4b1500ed47de2713872288c0d511d19926f99b459f"},
+    {file = "jupyter_client-8.6.1.tar.gz", hash = "sha256:e842515e2bab8e19186d89fdfea7abd15e39dd581f94e399f00e2af5a1652d3f"},
 ]
 
 [package.dependencies]
@@ -1930,13 +1929,13 @@ test = ["coverage", "ipykernel (>=6.14)", "mypy", "paramiko", "pre-commit", "pyt
 
 [[package]]
 name = "jupyter-core"
-version = "5.7.1"
+version = "5.7.2"
 description = "Jupyter core package. A base package on which Jupyter projects rely."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "jupyter_core-5.7.1-py3-none-any.whl", hash = "sha256:c65c82126453a723a2804aa52409930434598fd9d35091d63dfb919d2b765bb7"},
-    {file = "jupyter_core-5.7.1.tar.gz", hash = "sha256:de61a9d7fc71240f688b2fb5ab659fbb56979458dc66a71decd098e03c79e218"},
+    {file = "jupyter_core-5.7.2-py3-none-any.whl", hash = "sha256:4f7315d2f6b4bcf2e3e7cb6e46772eba760ae459cd1f59d29eb57b0a01bd7409"},
+    {file = "jupyter_core-5.7.2.tar.gz", hash = "sha256:aa5f8d32bbf6b431ac830496da7392035d6f61b4f54872f15c4bd2a9c3f536d9"},
 ]
 
 [package.dependencies]
@@ -1946,17 +1945,17 @@ traitlets = ">=5.3"
 
 [package.extras]
 docs = ["myst-parser", "pydata-sphinx-theme", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling", "traitlets"]
-test = ["ipykernel", "pre-commit", "pytest", "pytest-cov", "pytest-timeout"]
+test = ["ipykernel", "pre-commit", "pytest (<8)", "pytest-cov", "pytest-timeout"]
 
 [[package]]
 name = "jupyter-events"
-version = "0.9.0"
+version = "0.10.0"
 description = "Jupyter Event System library"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "jupyter_events-0.9.0-py3-none-any.whl", hash = "sha256:d853b3c10273ff9bc8bb8b30076d65e2c9685579db736873de6c2232dde148bf"},
-    {file = "jupyter_events-0.9.0.tar.gz", hash = "sha256:81ad2e4bc710881ec274d31c6c50669d71bbaa5dd9d01e600b56faa85700d399"},
+    {file = "jupyter_events-0.10.0-py3-none-any.whl", hash = "sha256:4b72130875e59d57716d327ea70d3ebc3af1944d3717e5a498b8a06c6c159960"},
+    {file = "jupyter_events-0.10.0.tar.gz", hash = "sha256:670b8229d3cc882ec782144ed22e0d29e1c2d639263f92ca8383e66682845e22"},
 ]
 
 [package.dependencies]
@@ -1975,13 +1974,13 @@ test = ["click", "pre-commit", "pytest (>=7.0)", "pytest-asyncio (>=0.19.0)", "p
 
 [[package]]
 name = "jupyter-lsp"
-version = "2.2.2"
+version = "2.2.4"
 description = "Multi-Language Server WebSocket proxy for Jupyter Notebook/Lab server"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "jupyter-lsp-2.2.2.tar.gz", hash = "sha256:256d24620542ae4bba04a50fc1f6ffe208093a07d8e697fea0a8d1b8ca1b7e5b"},
-    {file = "jupyter_lsp-2.2.2-py3-none-any.whl", hash = "sha256:3b95229e4168355a8c91928057c1621ac3510ba98b2a925e82ebd77f078b1aa5"},
+    {file = "jupyter-lsp-2.2.4.tar.gz", hash = "sha256:5e50033149344065348e688608f3c6d654ef06d9856b67655bd7b6bac9ee2d59"},
+    {file = "jupyter_lsp-2.2.4-py3-none-any.whl", hash = "sha256:da61cb63a16b6dff5eac55c2699cc36eac975645adee02c41bdfc03bf4802e77"},
 ]
 
 [package.dependencies]
@@ -1989,13 +1988,13 @@ jupyter-server = ">=1.1.2"
 
 [[package]]
 name = "jupyter-server"
-version = "2.12.5"
+version = "2.13.0"
 description = "The backend—i.e. core services, APIs, and REST endpoints—to Jupyter web applications."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "jupyter_server-2.12.5-py3-none-any.whl", hash = "sha256:184a0f82809a8522777cfb6b760ab6f4b1bb398664c5860a27cec696cb884923"},
-    {file = "jupyter_server-2.12.5.tar.gz", hash = "sha256:0edb626c94baa22809be1323f9770cf1c00a952b17097592e40d03e6a3951689"},
+    {file = "jupyter_server-2.13.0-py3-none-any.whl", hash = "sha256:77b2b49c3831fbbfbdb5048cef4350d12946191f833a24e5f83e5f8f4803e97b"},
+    {file = "jupyter_server-2.13.0.tar.gz", hash = "sha256:c80bfb049ea20053c3d9641c2add4848b38073bf79f1729cea1faed32fc1c78e"},
 ]
 
 [package.dependencies]
@@ -2021,17 +2020,17 @@ websocket-client = "*"
 
 [package.extras]
 docs = ["ipykernel", "jinja2", "jupyter-client", "jupyter-server", "myst-parser", "nbformat", "prometheus-client", "pydata-sphinx-theme", "send2trash", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-openapi (>=0.8.0)", "sphinxcontrib-spelling", "sphinxemoji", "tornado", "typing-extensions"]
-test = ["flaky", "ipykernel", "pre-commit", "pytest (>=7.0)", "pytest-console-scripts", "pytest-jupyter[server] (>=0.4)", "pytest-timeout", "requests"]
+test = ["flaky", "ipykernel", "pre-commit", "pytest (>=7.0)", "pytest-console-scripts", "pytest-jupyter[server] (>=0.7)", "pytest-timeout", "requests"]
 
 [[package]]
 name = "jupyter-server-terminals"
-version = "0.5.2"
+version = "0.5.3"
 description = "A Jupyter Server Extension Providing Terminals."
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -2044,13 +2043,13 @@ test = ["jupyter-server (>=2.0.0)", "pytest (>=7.0)", "pytest-jupyter[server] (>
 
 [[package]]
 name = "jupyterlab"
-version = "4.1.0"
+version = "4.1.5"
 description = "JupyterLab computational environment"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -2069,7 +2068,7 @@ tornado = ">=6.2.0"
 traitlets = "*"
 
 [package.extras]
-dev = ["build", "bump2version", "coverage", "hatch", "pre-commit", "pytest-cov", "ruff (==0.1.15)"]
+dev = ["build", "bump2version", "coverage", "hatch", "pre-commit", "pytest-cov", "ruff (==0.2.0)"]
 docs = ["jsx-lexer", "myst-parser", "pydata-sphinx-theme (>=0.13.0)", "pytest", "pytest-check-links", "pytest-jupyter", "sphinx (>=1.8,<7.3.0)", "sphinx-copybutton"]
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@@ -2087,13 +2086,13 @@ files = [
 
 [[package]]
 name = "jupyterlab-server"
-version = "2.25.2"
+version = "2.25.4"
 description = "A set of server components for JupyterLab and JupyterLab like applications."
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -2108,7 +2107,7 @@ requests = ">=2.31"
 [package.extras]
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+test = ["hatch", "ipykernel", "openapi-core (>=0.18.0,<0.19.0)", "openapi-spec-validator (>=0.6.0,<0.8.0)", "pytest (>=7.0,<8)", "pytest-console-scripts", "pytest-cov", "pytest-jupyter[server] (>=0.6.2)", "pytest-timeout", "requests-mock", "ruamel-yaml", "sphinxcontrib-spelling", "strict-rfc3339", "werkzeug"]
 
 [[package]]
 name = "jupytext"
@@ -2431,39 +2430,39 @@ files = [
 
 [[package]]
 name = "matplotlib"
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+version = "3.8.4"
 description = "Python plotting package"
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 python-versions = ">=3.9"
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 [package.dependencies]
@@ -2471,7 +2470,7 @@ contourpy = ">=1.0.1"
 cycler = ">=0.10"
 fonttools = ">=4.22.0"
 kiwisolver = ">=1.3.1"
-numpy = ">=1.21,<2"
+numpy = ">=1.21"
 packaging = ">=20.0"
 pillow = ">=8"
 pyparsing = ">=2.3.1"
@@ -2644,38 +2643,38 @@ files = [
 
 [[package]]
 name = "mypy"
-version = "1.8.0"
+version = "1.9.0"
 description = "Optional static typing for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -2728,13 +2727,13 @@ testing-docutils = ["pygments", "pytest (>=7,<8)", "pytest-param-files (>=0.3.4,
 
 [[package]]
 name = "nbclient"
-version = "0.9.0"
+version = "0.10.0"
 description = "A client library for executing notebooks. Formerly nbconvert's ExecutePreprocessor."
 optional = false
 python-versions = ">=3.8.0"
 files = [
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 ]
 
 [package.dependencies]
@@ -2746,17 +2745,17 @@ traitlets = ">=5.4"
 [package.extras]
 dev = ["pre-commit"]
 docs = ["autodoc-traits", "mock", "moto", "myst-parser", "nbclient[test]", "sphinx (>=1.7)", "sphinx-book-theme", "sphinxcontrib-spelling"]
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+test = ["flaky", "ipykernel (>=6.19.3)", "ipython", "ipywidgets", "nbconvert (>=7.0.0)", "pytest (>=7.0,<8)", "pytest-asyncio", "pytest-cov (>=4.0)", "testpath", "xmltodict"]
 
 [[package]]
 name = "nbconvert"
-version = "7.16.0"
-description = "Converting Jupyter Notebooks"
+version = "7.16.3"
+description = "Converting Jupyter Notebooks (.ipynb files) to other formats.  Output formats include asciidoc, html, latex, markdown, pdf, py, rst, script.  nbconvert can be used both as a Python library (`import nbconvert`) or as a command line tool (invoked as `jupyter nbconvert ...`)."
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -2782,24 +2781,24 @@ docs = ["ipykernel", "ipython", "myst-parser", "nbsphinx (>=0.2.12)", "pydata-sp
 qtpdf = ["nbconvert[qtpng]"]
 qtpng = ["pyqtwebengine (>=5.15)"]
 serve = ["tornado (>=6.1)"]
-test = ["flaky", "ipykernel", "ipywidgets (>=7.5)", "pytest"]
+test = ["flaky", "ipykernel", "ipywidgets (>=7.5)", "pytest (>=7)"]
 webpdf = ["playwright"]
 
 [[package]]
 name = "nbformat"
-version = "5.9.2"
+version = "5.10.4"
 description = "The Jupyter Notebook format"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
-fastjsonschema = "*"
+fastjsonschema = ">=2.15"
 jsonschema = ">=2.6"
-jupyter-core = "*"
+jupyter-core = ">=4.12,<5.0.dev0 || >=5.1.dev0"
 traitlets = ">=5.1"
 
 [package.extras]
@@ -2851,13 +2850,13 @@ setuptools = "*"
 
 [[package]]
 name = "notebook-shim"
-version = "0.2.3"
+version = "0.2.4"
 description = "A shim layer for notebook traits and config"
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.dependencies]
@@ -2953,13 +2952,13 @@ files = [
 
 [[package]]
 name = "packaging"
-version = "23.2"
+version = "24.0"
 description = "Core utilities for Python packages"
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
 [[package]]
@@ -3041,18 +3040,18 @@ files = [
 
 [[package]]
 name = "parso"
-version = "0.8.3"
+version = "0.8.4"
 description = "A Python Parser"
 optional = false
 python-versions = ">=3.6"
 files = [
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 ]
 
 [package.extras]
-qa = ["flake8 (==3.8.3)", "mypy (==0.782)"]
-testing = ["docopt", "pytest (<6.0.0)"]
+qa = ["flake8 (==5.0.4)", "mypy (==0.971)", "types-setuptools (==67.2.0.1)"]
+testing = ["docopt", "pytest"]
 
 [[package]]
 name = "partd"
@@ -3124,79 +3123,80 @@ ptyprocess = ">=0.5"
 
 [[package]]
 name = "pillow"
-version = "10.2.0"
+version = "10.3.0"
 description = "Python Imaging Library (Fork)"
 optional = false
 python-versions = ">=3.8"
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 ]
 
 [package.dependencies]
@@ -3423,13 +3423,13 @@ files = [
 
 [[package]]
 name = "pycparser"
-version = "2.21"
+version = "2.22"
 description = "C parser in Python"
 optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+python-versions = ">=3.8"
 files = [
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-    {file = "pycparser-2.21.tar.gz", hash = "sha256:e644fdec12f7872f86c58ff790da456218b10f863970249516d60a5eaca77206"},
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+    {file = "pycparser-2.22.tar.gz", hash = "sha256:491c8be9c040f5390f5bf44a5b07752bd07f56edf992381b05c701439eec10f6"},
 ]
 
 [[package]]
@@ -3522,13 +3522,13 @@ test = ["pytest", "pytest-cov"]
 
 [[package]]
 name = "pyparsing"
-version = "3.1.1"
+version = "3.1.2"
 description = "pyparsing module - Classes and methods to define and execute parsing grammars"
 optional = false
 python-versions = ">=3.6.8"
 files = [
-    {file = "pyparsing-3.1.1-py3-none-any.whl", hash = "sha256:32c7c0b711493c72ff18a981d24f28aaf9c1fb7ed5e9667c9e84e3db623bdbfb"},
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+    {file = "pyparsing-3.1.2-py3-none-any.whl", hash = "sha256:f9db75911801ed778fe61bb643079ff86601aca99fcae6345aa67292038fb742"},
+    {file = "pyparsing-3.1.2.tar.gz", hash = "sha256:a1bac0ce561155ecc3ed78ca94d3c9378656ad4c94c1270de543f621420f94ad"},
 ]
 
 [package.extras]
@@ -3575,13 +3575,13 @@ certifi = "*"
 
 [[package]]
 name = "pytest"
-version = "8.0.0"
+version = "8.1.1"
 description = "pytest: simple powerful testing with Python"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "pytest-8.0.0-py3-none-any.whl", hash = "sha256:50fb9cbe836c3f20f0dfa99c565201fb75dc54c8d76373cd1bde06b06657bdb6"},
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 ]
 
 [package.dependencies]
@@ -3589,21 +3589,21 @@ colorama = {version = "*", markers = "sys_platform == \"win32\""}
 exceptiongroup = {version = ">=1.0.0rc8", markers = "python_version < \"3.11\""}
 iniconfig = "*"
 packaging = "*"
-pluggy = ">=1.3.0,<2.0"
-tomli = {version = ">=1.0.0", markers = "python_version < \"3.11\""}
+pluggy = ">=1.4,<2.0"
+tomli = {version = ">=1", markers = "python_version < \"3.11\""}
 
 [package.extras]
-testing = ["argcomplete", "attrs (>=19.2.0)", "hypothesis (>=3.56)", "mock", "nose", "pygments (>=2.7.2)", "requests", "setuptools", "xmlschema"]
+testing = ["argcomplete", "attrs (>=19.2)", "hypothesis (>=3.56)", "mock", "pygments (>=2.7.2)", "requests", "setuptools", "xmlschema"]
 
 [[package]]
 name = "pytest-cov"
-version = "4.1.0"
+version = "5.0.0"
 description = "Pytest plugin for measuring coverage."
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
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+    {file = "pytest-cov-5.0.0.tar.gz", hash = "sha256:5837b58e9f6ebd335b0f8060eecce69b662415b16dc503883a02f45dfeb14857"},
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 ]
 
 [package.dependencies]
@@ -3611,34 +3611,34 @@ coverage = {version = ">=5.2.1", extras = ["toml"]}
 pytest = ">=4.6"
 
 [package.extras]
-testing = ["fields", "hunter", "process-tests", "pytest-xdist", "six", "virtualenv"]
+testing = ["fields", "hunter", "process-tests", "pytest-xdist", "virtualenv"]
 
 [[package]]
 name = "pytest-mock"
-version = "3.12.0"
+version = "3.14.0"
 description = "Thin-wrapper around the mock package for easier use with pytest"
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "pytest-mock-3.14.0.tar.gz", hash = "sha256:2719255a1efeceadbc056d6bf3df3d1c5015530fb40cf347c0f9afac88410bd0"},
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 ]
 
 [package.dependencies]
-pytest = ">=5.0"
+pytest = ">=6.2.5"
 
 [package.extras]
 dev = ["pre-commit", "pytest-asyncio", "tox"]
 
 [[package]]
 name = "python-dateutil"
-version = "2.8.2"
+version = "2.9.0.post0"
 description = "Extensions to the standard Python datetime module"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7"
 files = [
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 ]
 
 [package.dependencies]
@@ -3668,13 +3668,13 @@ files = [
 
 [[package]]
 name = "pyupgrade"
-version = "3.15.0"
+version = "3.15.2"
 description = "A tool to automatically upgrade syntax for newer versions."
 optional = false
 python-versions = ">=3.8.1"
 files = [
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+    {file = "pyupgrade-3.15.2-py2.py3-none-any.whl", hash = "sha256:ce309e0ff8ecb73f56a45f12570be84bbbde9540d13697cacb261a7f595fb1f5"},
+    {file = "pyupgrade-3.15.2.tar.gz", hash = "sha256:c488d6896c546d25845712ef6402657123008d56c1063174e27aabe15bd6b4e5"},
 ]
 
 [package.dependencies]
@@ -3705,17 +3705,17 @@ files = [
 
 [[package]]
 name = "pywinpty"
-version = "2.0.12"
+version = "2.0.13"
 description = "Pseudo terminal support for Windows from Python."
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [[package]]
@@ -3937,13 +3937,13 @@ decorator = "*"
 
 [[package]]
 name = "referencing"
-version = "0.33.0"
+version = "0.34.0"
 description = "JSON Referencing + Python"
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "referencing-0.34.0.tar.gz", hash = "sha256:5773bd84ef41799a5a8ca72dc34590c041eb01bf9aa02632b4a973fb0181a844"},
 ]
 
 [package.dependencies]
@@ -4011,13 +4011,13 @@ files = [
 
 [[package]]
 name = "rich"
-version = "13.7.0"
+version = "13.7.1"
 description = "Render rich text, tables, progress bars, syntax highlighting, markdown and more to the terminal"
 optional = false
 python-versions = ">=3.7.0"
 files = [
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-    {file = "rich-13.7.0.tar.gz", hash = "sha256:5cb5123b5cf9ee70584244246816e9114227e0b98ad9176eede6ad54bf5403fa"},
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 ]
 
 [package.dependencies]
@@ -4054,110 +4054,110 @@ test = ["dask", "netcdf4", "pytest (>=3.6)", "pytest-cov", "pytest-timeout"]
 
 [[package]]
 name = "rpds-py"
-version = "0.17.1"
+version = "0.18.0"
 description = "Python bindings to Rust's persistent data structures (rpds)"
 optional = false
 python-versions = ">=3.8"
 files = [
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 threadpoolctl = ">=2.0.0"
 
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 [package.dependencies]
-numpy = ">=1.14"
+numpy = ">=1.14,<2"
 
 [package.extras]
 docs = ["matplotlib", "numpydoc (==1.1.*)", "sphinx", "sphinx-book-theme", "sphinx-remove-toctrees"]
@@ -4448,13 +4428,13 @@ files = [
 
 [[package]]
 name = "sniffio"
-version = "1.3.0"
+version = "1.3.1"
 description = "Sniff out which async library your code is running under"
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
 [[package]]
@@ -4552,13 +4532,13 @@ test = ["pytest (>=6.0)", "pytest-cov"]
 
 [[package]]
 name = "sphinx-autodoc-typehints"
-version = "1.25.3"
+version = "2.0.0"
 description = "Type hints (PEP 484) support for the Sphinx autodoc extension"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -4701,13 +4681,13 @@ tests = ["cython", "littleutils", "pygments", "pytest", "typeguard"]
 
 [[package]]
 name = "stevedore"
-version = "5.1.0"
+version = "5.2.0"
 description = "Manage dynamic plugins for Python applications"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -4715,13 +4695,13 @@ pbr = ">=2.0.0,<2.1.0 || >2.1.0"
 
 [[package]]
 name = "terminado"
-version = "0.18.0"
+version = "0.18.1"
 description = "Tornado websocket backend for the Xterm.js Javascript terminal emulator library."
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 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -4747,13 +4727,13 @@ files = [
 
 [[package]]
 name = "threadpoolctl"
-version = "3.2.0"
+version = "3.4.0"
 description = "threadpoolctl"
 optional = false
 python-versions = ">=3.8"
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 ]
 
 [[package]]
@@ -4840,50 +4820,50 @@ files = [
 
 [[package]]
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-version = "5.14.1"
+version = "5.14.2"
 description = "Traitlets Python configuration system"
 optional = false
 python-versions = ">=3.8"
 files = [
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 [package.extras]
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+test = ["argcomplete (>=3.0.3)", "mypy (>=1.7.0)", "pre-commit", "pytest (>=7.0,<8.1)", "pytest-mock", "pytest-mypy-testing"]
 
 [[package]]
 name = "types-python-dateutil"
-version = "2.8.19.20240106"
+version = "2.9.0.20240316"
 description = "Typing stubs for python-dateutil"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [[package]]
 name = "typing-extensions"
-version = "4.9.0"
+version = "4.10.0"
 description = "Backported and Experimental Type Hints for Python 3.8+"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [[package]]
 name = "tzdata"
-version = "2023.4"
+version = "2024.1"
 description = "Provider of IANA time zone data"
 optional = false
 python-versions = ">=2"
 files = [
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 ]
 
 [[package]]
@@ -4902,13 +4882,13 @@ dev = ["flake8", "flake8-annotations", "flake8-bandit", "flake8-bugbear", "flake
 
 [[package]]
 name = "urllib3"
-version = "2.2.0"
+version = "2.2.1"
 description = "HTTP library with thread-safe connection pooling, file post, and more."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "urllib3-2.2.0-py3-none-any.whl", hash = "sha256:ce3711610ddce217e6d113a2732fafad960a03fd0318c91faa79481e35c11224"},
-    {file = "urllib3-2.2.0.tar.gz", hash = "sha256:051d961ad0c62a94e50ecf1af379c3aba230c66c710493493560c0c223c49f20"},
+    {file = "urllib3-2.2.1-py3-none-any.whl", hash = "sha256:450b20ec296a467077128bff42b73080516e71b56ff59a60a02bef2232c4fa9d"},
+    {file = "urllib3-2.2.1.tar.gz", hash = "sha256:d0570876c61ab9e520d776c38acbbb5b05a776d3f9ff98a5c8fd5162a444cf19"},
 ]
 
 [package.extras]
@@ -4919,13 +4899,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "virtualenv"
-version = "20.25.0"
+version = "20.25.1"
 description = "Virtual Python Environment builder"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "virtualenv-20.25.0-py3-none-any.whl", hash = "sha256:4238949c5ffe6876362d9c0180fc6c3a824a7b12b80604eeb8085f2ed7460de3"},
-    {file = "virtualenv-20.25.0.tar.gz", hash = "sha256:bf51c0d9c7dd63ea8e44086fa1e4fb1093a31e963b86959257378aef020e1f1b"},
+    {file = "virtualenv-20.25.1-py3-none-any.whl", hash = "sha256:961c026ac520bac5f69acb8ea063e8a4f071bcc9457b9c1f28f6b085c511583a"},
+    {file = "virtualenv-20.25.1.tar.gz", hash = "sha256:e08e13ecdca7a0bd53798f356d5831434afa5b07b93f0abdf0797b7a06ffe197"},
 ]
 
 [package.dependencies]
@@ -5043,13 +5023,13 @@ tests-strict = ["pytest (==4.6.0)", "pytest (==4.6.0)", "pytest (==6.2.5)", "pyt
 
 [[package]]
 name = "xyzservices"
-version = "2023.10.1"
+version = "2024.4.0"
 description = "Source of XYZ tiles providers"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "xyzservices-2023.10.1-py3-none-any.whl", hash = "sha256:6a4c38d3a9f89d3e77153eff9414b36a8ee0850c9e8b85796fd1b2a85b8dfd68"},
-    {file = "xyzservices-2023.10.1.tar.gz", hash = "sha256:091229269043bc8258042edbedad4fcb44684b0473ede027b5672ad40dc9fa02"},
+    {file = "xyzservices-2024.4.0-py3-none-any.whl", hash = "sha256:b83e48c5b776c9969fffcfff57b03d02b1b1cd6607a9d9c4e7f568b01ef47f4c"},
+    {file = "xyzservices-2024.4.0.tar.gz", hash = "sha256:6a04f11487a6fb77d92a98984cd107fbd9157fd5e65f929add9c3d6e604ee88c"},
 ]
 
 [[package]]
@@ -5157,18 +5137,18 @@ multidict = ">=4.0"
 
 [[package]]
 name = "zipp"
-version = "3.17.0"
+version = "3.18.1"
 description = "Backport of pathlib-compatible object wrapper for zip files"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "zipp-3.17.0-py3-none-any.whl", hash = "sha256:0e923e726174922dce09c53c59ad483ff7bbb8e572e00c7f7c46b88556409f31"},
-    {file = "zipp-3.17.0.tar.gz", hash = "sha256:84e64a1c28cf7e91ed2078bb8cc8c259cb19b76942096c8d7b84947690cabaf0"},
+    {file = "zipp-3.18.1-py3-none-any.whl", hash = "sha256:206f5a15f2af3dbaee80769fb7dc6f249695e940acca08dfb2a4769fe61e538b"},
+    {file = "zipp-3.18.1.tar.gz", hash = "sha256:2884ed22e7d8961de1c9a05142eb69a247f120291bc0206a00a7642f09b5b715"},
 ]
 
 [package.extras]
-docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (<7.2.5)", "sphinx (>=3.5)", "sphinx-lint"]
-testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy (>=0.9.1)", "pytest-ruff"]
+docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy", "pytest-ruff (>=0.2.1)"]
 
 [metadata]
 lock-version = "2.0"

From 5ddb63cc69c5f2862a0eea98887f04fe7c967289 Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Fri, 12 Apr 2024 13:04:51 +0200
Subject: [PATCH 22/42] version 1, status production

---
 pyproject.toml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index ea422771..596a6b40 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "ssb-sgis"
-version = "0.3.13"
+version = "1.0.0"
 description = "GIS functions used at Statistics Norway."
 authors = ["Statistics Norway <ort@ssb.no>"]
 license = "MIT"
@@ -9,7 +9,7 @@ packages = [{include = "sgis", from = "src"}]
 homepage = "https://github.com/statisticsnorway/ssb-sgis"
 repository = "https://github.com/statisticsnorway/ssb-sgis"
 classifiers = [
-    "Development Status :: 3 - Alpha",
+    "Development Status :: 5 - Production/Stable",
     "Topic :: Scientific/Engineering :: GIS",
 ]
 

From e937829b2d50a409bc0cef3c5fd80a5ad64eb598 Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Fri, 12 Apr 2024 14:54:13 +0200
Subject: [PATCH 23/42] cleaning fixed, snapping back to drawing board

---
 src/sgis/geopandas_tools/cleaning.py |  6 +++---
 tests/test_cleaning.py               | 30 +++++++++++++++++++++++++---
 2 files changed, 30 insertions(+), 6 deletions(-)

diff --git a/src/sgis/geopandas_tools/cleaning.py b/src/sgis/geopandas_tools/cleaning.py
index 35c87702..ba2b046b 100644
--- a/src/sgis/geopandas_tools/cleaning.py
+++ b/src/sgis/geopandas_tools/cleaning.py
@@ -65,7 +65,7 @@
 warnings.simplefilter(action="ignore", category=RuntimeWarning)
 
 
-from ..maps.maps import explore
+from ..maps.maps import explore, explore_locals
 
 
 # def explore(*args, **kwargs):
@@ -400,8 +400,8 @@ def coverage_clean(
                 )
                 raise e
 
-    cleaned = safe_simplify(cleaned, PRECISION)
-    cleaned.geometry = shapely.make_valid(cleaned.geometry)
+    # cleaned = safe_simplify(cleaned, PRECISION)
+    # cleaned.geometry = shapely.make_valid(cleaned.geometry)
 
     # TODO check why polygons dissappear in rare cases. For now, just add back the missing
     dissapeared_polygons = sfilter_inverse(gdf, cleaned.buffer(-PRECISION))
diff --git a/tests/test_cleaning.py b/tests/test_cleaning.py
index 60d14acc..8812c927 100644
--- a/tests/test_cleaning.py
+++ b/tests/test_cleaning.py
@@ -134,6 +134,8 @@ def test_clean_1144():
             ],
         )
 
+        continue
+
         snapped_to_mask = sg.snap_to_mask(
             sg.sort_large_first(df), tolerance, mask=kommune_utenhav
         )
@@ -213,7 +215,6 @@ def test_clean_1144():
             double.area.sum(),
             missing.area.sum(),
         )
-        sss
 
         cleaned_and_snapped_to_mask = sg.snap_to_mask(
             cleaned, tolerance, mask=kommune_utenhav
@@ -383,12 +384,35 @@ def test_clean():
     mask = sg.close_all_holes(sg.dissexp_by_cluster(df)).dissolve()
 
     for tolerance in [5, 10]:
-        print(tolerance)
+        print("tolerance:", tolerance)
 
         # from shapely import segmentize
 
         # df.geometry = segmentize(df.geometry, tolerance)
 
+        snapped = sg.coverage_clean(df, tolerance).pipe(sg.coverage_clean, tolerance)
+        assert sg.get_geom_type(snapped) == "polygon", sg.get_geom_type(snapped)
+
+        double = sg.get_intersections(snapped).loc[lambda x: ~x.buffer(-1e-9).is_empty]
+        gaps = sg.get_gaps(snapped).loc[lambda x: ~x.buffer(-1e-9).is_empty]
+        missing = get_missing(df, snapped)
+
+        print(double.area.sum(), missing.area.sum(), gaps.area.sum())
+
+        sg.explore(
+            df,
+            snapped,
+            double,
+            missing,
+            gaps,
+        )
+
+        assert (a := max(list(double.area) + [0])) < 1e-4, a
+        assert (a := max(list(missing.area) + [0])) < 1e-4, a
+        assert (a := max(list(gaps.area) + [0])) < 1e-4, a
+
+        continue
+
         snapped = sg.snap_polygons(
             df, tolerance, mask=mask.buffer(0.1, resolution=1, join_style=2)
         )
@@ -647,10 +671,10 @@ def is_close_enough(num1, num2):
 
 
 def main():
+    test_clean()
     test_clean_1144()
     test_clean_dissappearing_polygon()
 
-    test_clean()
     not_test_spikes()
 
 

From a23857c16f2cb151fe14749f1140178362e1f350 Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Fri, 12 Apr 2024 15:00:34 +0200
Subject: [PATCH 24/42] remove unused

---
 src/sgis/geopandas_tools/cleaning.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/src/sgis/geopandas_tools/cleaning.py b/src/sgis/geopandas_tools/cleaning.py
index ba2b046b..eabf2c65 100644
--- a/src/sgis/geopandas_tools/cleaning.py
+++ b/src/sgis/geopandas_tools/cleaning.py
@@ -218,7 +218,6 @@ def coverage_clean(
         raise ValueError("Large double surfaces.")
 
     to_eliminate = pd.concat([thin_gaps_and_double, slivers], ignore_index=True)
-    # to_eliminate = safe_simplify(to_eliminate, PRECISION)
 
     to_eliminate = to_eliminate.loc[lambda x: ~x.buffer(-PRECISION / 10).is_empty]
 

From f7f90a8d8a6b105af0e1e0a2d83a1a3ee95646e7 Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Fri, 12 Apr 2024 15:13:19 +0200
Subject: [PATCH 25/42] fix path to constraints

---
 .github/workflows/docs.yml    | 6 +++---
 .github/workflows/release.yml | 4 ++--
 .github/workflows/tests.yml   | 8 ++++----
 3 files changed, 9 insertions(+), 9 deletions(-)

diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml
index 225e453f..114dc26d 100644
--- a/.github/workflows/docs.yml
+++ b/.github/workflows/docs.yml
@@ -34,13 +34,13 @@ jobs:
       - name: Checkout
         uses: actions/checkout@v3
       - name: Setup Pages
-        uses: actions/configure-pages@v3
+        uses: actions/configure-pages@v5
       - name: Install Poetry
         run: |
-          pipx install --pip-args=--constraint=.github/workflows/constraints.txt poetry
+          pipx install --pip-args=--constraint=${{ github.workspace }}/.github/workflows/constraints.txt poetry
           poetry --version
       - name: Set up Python
-        uses: actions/setup-python@v4
+        uses: actions/setup-python@v5.1.0
         with:
           python-version: "3.10"
           cache: "poetry"
diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml
index 1ba14669..4e7a78e4 100644
--- a/.github/workflows/release.yml
+++ b/.github/workflows/release.yml
@@ -23,12 +23,12 @@ jobs:
 
       - name: Upgrade pip
         run: |
-          pip install --constraint=.github/workflows/constraints.txt pip
+          pip install --constraint=${{ github.workspace }}/.github/workflows/constraints.txt pip
           pip --version
 
       - name: Install Poetry
         run: |
-          pip install --constraint=.github/workflows/constraints.txt poetry
+          pip install --constraint=${{ github.workspace }}/.github/workflows/constraints.txt poetry
           poetry --version
 
       - name: Check if there is a parent commit
diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml
index 9b82770f..141fe3c9 100644
--- a/.github/workflows/tests.yml
+++ b/.github/workflows/tests.yml
@@ -22,22 +22,22 @@ jobs:
       - name: Upgrade pip
         if: matrix.os != 'macos-latest'
         run: |
-          pip install --constraint=.github/workflows/constraints.txt pip
+          pip install --constraint=${{ github.workspace }}/.github/workflows/constraints.txt pip
           pip --version
 
       - name: Upgrade pip on MacOS
         if: matrix.os == 'macos-latest'
         run: |
-          pip3 install --constraint=.github/workflows/constraints.txt pip
+          pip3 install --constraint=${{ github.workspace }}/.github/workflows/constraints.txt pip
           pip3 --version
 
       - name: Install Poetry
         run: |
-          pipx install --pip-args=--constraint=.github/workflows/constraints.txt poetry
+          pipx install --pip-args=--constraint=${{ github.workspace }}/.github/workflows/constraints.txt poetry
           poetry --version
 
       - name: Set up Python
-        uses: actions/setup-python@v4
+        uses: actions/setup-python@v5.1.0
         with:
           python-version: ${{ matrix.python-version }}
           cache: "poetry"

From 47cebacebe4b5bc3f30a2b88aebf6602d72db3fd Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Sat, 13 Apr 2024 10:10:24 +0200
Subject: [PATCH 26/42] remove unused

---
 src/sgis/geopandas_tools/duplicates.py | 46 --------------------------
 src/sgis/geopandas_tools/overlay.py    | 33 ++++--------------
 2 files changed, 7 insertions(+), 72 deletions(-)

diff --git a/src/sgis/geopandas_tools/duplicates.py b/src/sgis/geopandas_tools/duplicates.py
index 0527aef2..98f338d7 100644
--- a/src/sgis/geopandas_tools/duplicates.py
+++ b/src/sgis/geopandas_tools/duplicates.py
@@ -174,52 +174,6 @@ def update_geometries(
     return copied
 
 
-def _update(many_hits, right_index_name):
-    many_hits_agged = many_hits.loc[lambda x: ~x.index.duplicated()]
-
-    index_mapper = {
-        i: x
-        for i, x in many_hits.groupby(level=0)[right_index_name]
-        .unique()
-        .apply(lambda j: tuple(sorted(j)))
-        .items()
-    }
-
-    many_hits_agged["_right_indices"] = index_mapper
-
-    inverse_index_mapper = pd.Series(
-        {
-            x[0]: x
-            for x in many_hits_agged.reset_index()
-            .groupby("_right_indices")["index"]
-            .unique()
-            .apply(tuple)
-        }
-    ).explode()
-    inverse_index_mapper = pd.Series(
-        inverse_index_mapper.index, index=inverse_index_mapper.values
-    )
-
-    agger = (
-        pd.Series(index_mapper.values(), index=index_mapper.keys())
-        .drop_duplicates()
-        .explode()
-        .to_frame(right_index_name)
-    )
-    agger["geom_right"] = agger[right_index_name].map(
-        {i: g for i, g in zip(many_hits[right_index_name], many_hits["geom_right"])}
-    )
-
-    agged = pd.Series(
-        {
-            i: agg_geoms_partial(geoms)
-            for i, geoms in agger.groupby(level=0)["geom_right"]
-        }
-    )
-    many_hits_agged["geom_right"] = inverse_index_mapper.map(agged)
-    many_hits_agged = many_hits_agged.drop(columns=["_right_indices"])
-
-
 def get_intersections(
     gdf: GeoDataFrame,
     geom_type: str | None = None,
diff --git a/src/sgis/geopandas_tools/overlay.py b/src/sgis/geopandas_tools/overlay.py
index ba31eb73..17f30e64 100644
--- a/src/sgis/geopandas_tools/overlay.py
+++ b/src/sgis/geopandas_tools/overlay.py
@@ -336,7 +336,7 @@ def _run_overlay_dask(arr1, arr2, func, n_jobs, grid_size):
     return res.compute(scheduler="threads", optimize_graph=False, num_workers=n_jobs)
 
 
-def _run_overlay_dask(arr1, arr2, func, n_jobs, grid_size):
+def _run_overlay_joblib_threading(arr1, arr2, func, n_jobs, grid_size):
     if len(arr1) // n_jobs <= 1:
         try:
             return func(arr1, arr2, grid_size=grid_size)
@@ -359,10 +359,8 @@ def _intersection(pairs, grid_size, geom_type, n_jobs=1) -> GeoDataFrame:
     arr2 = intersections["geom_right"].to_numpy()
 
     if n_jobs > 1 and len(arr1) / n_jobs > 10:
-        # dask_arr1 = da.from_array(arr1, chunks=int(len(arr1) / n_jobs))
-        # dask_arr2 = da.from_array(arr2, chunks=int(len(arr2) / n_jobs))
         try:
-            res = _run_overlay_dask(
+            res = _run_overlay_joblib_threading(
                 arr1,
                 arr2,
                 func=intersection,
@@ -379,10 +377,7 @@ def _intersection(pairs, grid_size, geom_type, n_jobs=1) -> GeoDataFrame:
             arr1 = arr1.loc[lambda x: x.index.isin(arr2.index)]
             arr2 = arr2.loc[lambda x: x.index.isin(arr1.index)]
 
-            # dask_arr1 = da.from_array(arr1, chunks=int(len(arr1) / n_jobs))
-            # dask_arr2 = da.from_array(arr2, chunks=int(len(arr2) / n_jobs))
-
-            res = _run_overlay_dask(
+            res = _run_overlay_joblib_threading(
                 arr1.to_numpy(),
                 arr2.to_numpy(),
                 func=intersection,
@@ -615,11 +610,6 @@ def _shapely_diffclip_left(pairs, df1, grid_size, geom_type, n_jobs):
     except IndexError:
         clip_left = pairs.loc[:, list(keep_cols)]
 
-    # if n_jobs > 1:
-    #     clip_left["geom_right"] = parallel_unary_union(
-    #         pairs, level=0, n_jobs=n_jobs, grid_size=grid_size
-    #     )
-
     assert clip_left["geometry"].notna().all()
     assert clip_left["geom_right"].notna().all()
 
@@ -665,7 +655,6 @@ def _shapely_diffclip_right(pairs, df1, df2, grid_size, rsuffix, geom_type, n_jo
             )
         )
     except IndexError:
-        # one_hit = pairs[lambda x: x.index == min(x.index) - 1]
         clip_right = pairs.join(df2.drop(columns=["geometry"])).rename(
             columns={
                 c: f"{c}{rsuffix}" if c in df1.columns and c != "geometry" else c
@@ -689,12 +678,8 @@ def _shapely_diffclip_right(pairs, df1, df2, grid_size, rsuffix, geom_type, n_jo
 def _try_difference(left, right, grid_size, geom_type, n_jobs=1):
     """Try difference overlay, then make_valid and retry."""
     if n_jobs > 1 and len(left) / n_jobs > 10:
-        # dask_arr1 = da.from_array(left, chunks=int(len(left) / n_jobs))
-        # dask_arr2 = da.from_array(right, chunks=int(len(right) / n_jobs))
-        # dask_arr1 = make_valid_and_keep_geom_type(dask_arr1, geom_type=geom_type)
-        # dask_arr2 = make_valid_and_keep_geom_type(dask_arr2, geom_type=geom_type)
         try:
-            return _run_overlay_dask(
+            return _run_overlay_joblib_threading(
                 left,
                 right,
                 func=difference,
@@ -710,10 +695,8 @@ def _try_difference(left, right, grid_size, geom_type, n_jobs=1):
             )
             left = left.loc[lambda x: x.index.isin(right.index)]
             right = right.loc[lambda x: x.index.isin(left.index)]
-            # dask_arr1 = da.from_array(arr1, chunks=int(len(arr1) / n_jobs))
-            # dask_arr2 = da.from_array(arr2, chunks=int(len(arr2) / n_jobs))
 
-            return _run_overlay_dask(
+            return _run_overlay_joblib_threading(
                 left.to_numpy(),
                 right.to_numpy(),
                 func=difference,
@@ -758,10 +741,8 @@ def make_valid_and_keep_geom_type(
     only_one = geoms.groupby(level=0).transform("size") == 1
     one_hit = geoms[only_one]
     many_hits = geoms[~only_one].groupby(level=0).agg(unary_union)
-    return pd.concat([one_hit, many_hits]).sort_index()  # .to_numpy()
+    return pd.concat([one_hit, many_hits]).sort_index()
 
 
 def agg_geoms(g, grid_size=None):
-    return make_valid(
-        unary_union(g, grid_size=grid_size)
-    )  # if len(g) > 1 else make_valid(g)
+    return make_valid(unary_union(g, grid_size=grid_size))

From cdf6b983fa581164a1ada58ae5c22eaf82a5ebc0 Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Sun, 14 Apr 2024 21:06:14 +0200
Subject: [PATCH 27/42] add torchgeo dataset

---
 src/sgis/geopandas_tools/conversion.py | 55 +++++++++++++++++++++++++-
 1 file changed, 54 insertions(+), 1 deletion(-)

diff --git a/src/sgis/geopandas_tools/conversion.py b/src/sgis/geopandas_tools/conversion.py
index 124cb394..475bdcaf 100644
--- a/src/sgis/geopandas_tools/conversion.py
+++ b/src/sgis/geopandas_tools/conversion.py
@@ -7,16 +7,27 @@
 import numpy as np
 import pandas as pd
 import pyproj
+import rasterio
 import shapely
+from affine import Affine
 from geopandas import GeoDataFrame, GeoSeries
 from pandas.api.types import is_array_like, is_dict_like, is_list_like
 from pyproj import CRS
+from rasterio import features
 from shapely import Geometry, box, wkb, wkt
 from shapely.errors import GEOSException
-from shapely.geometry import Point
+from shapely.geometry import Point, shape
 from shapely.ops import unary_union
 
 
+try:
+    from torchgeo.datasets.geo import RasterDataset
+except ImportError:
+
+    class RasterDataset:
+        """Placeholder"""
+
+
 @staticmethod
 def crs_to_string(crs):
     if crs is None:
@@ -336,6 +347,21 @@ def to_gdf(
             except Exception:
                 pass
 
+    if isinstance(obj, RasterDataset):
+        # read the entire dataset
+        obj = obj[obj.bounds]
+        crs = obj["crs"]
+        array = np.array(obj["image"])
+        transform = get_transform_from_bounds(obj["bbox"], shape=array.shape)
+        return gpd.GeoDataFrame(
+            pd.DataFrame(
+                _array_to_geojson(array, transform),
+                columns=["value", "geometry"],
+            ),
+            geometry="geometry",
+            crs=crs,
+        )
+
     if is_array_like(geometry) and len(geometry) == len(obj):
         geometry = GeoSeries(
             _make_one_shapely_geom(g) for g in geometry if g is not None
@@ -445,6 +471,33 @@ def to_gdf(
     return GeoDataFrame(geometry=geoseries, crs=crs, **kwargs)
 
 
+def _array_to_geojson(array: np.ndarray, transform: Affine):
+    try:
+        return [
+            (value, shape(geom))
+            for geom, value in features.shapes(array, transform=transform)
+        ]
+    except ValueError:
+        array = array.astype(np.float32)
+        return [
+            (value, shape(geom))
+            for geom, value in features.shapes(array, transform=transform)
+        ]
+
+
+def get_transform_from_bounds(
+    obj: GeoDataFrame | GeoSeries | Geometry | tuple, shape: tuple[float, ...]
+) -> Affine:
+    minx, miny, maxx, maxy = to_bbox(obj)
+    if len(shape) == 2:
+        width, height = shape
+    elif len(shape) == 3:
+        _, width, height = shape
+    else:
+        raise ValueError
+    return rasterio.transform.from_bounds(minx, miny, maxx, maxy, width, height)
+
+
 def make_shapely_geoms(obj):
     if _is_one_geometry(obj):
         return _make_one_shapely_geom(obj)

From ae4ac1fa772216a2ad629f2146649d3563622559 Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Sun, 14 Apr 2024 21:08:34 +0200
Subject: [PATCH 28/42] test torchgeo

---
 tests/test_torchgeo.py | 57 ++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 57 insertions(+)
 create mode 100644 tests/test_torchgeo.py

diff --git a/tests/test_torchgeo.py b/tests/test_torchgeo.py
new file mode 100644
index 00000000..11e6f6fa
--- /dev/null
+++ b/tests/test_torchgeo.py
@@ -0,0 +1,57 @@
+# %%
+import multiprocessing
+import os
+import sys
+from pathlib import Path
+from time import perf_counter
+
+import numpy as np
+import pandas as pd
+import shapely
+import xarray as xr
+from IPython.display import display
+from pyproj import CRS
+from shapely import box
+
+
+src = str(Path(__file__).parent.parent) + "/src"
+testdata = str(Path(__file__).parent.parent) + "/tests/testdata/raster"
+
+sys.path.insert(0, src)
+
+import sgis as sg
+
+
+path_sentinel = testdata + "/sentinel2"
+
+
+def test_torch():
+
+    from torch.utils.data import DataLoader
+    from torchgeo.datasets import stack_samples
+    from torchgeo.samplers import RandomGeoSampler
+
+    torch_dataset = sg.torchgeo.Sentinel2(path_sentinel, res=10)
+
+    sg.explore(torch_dataset, "value")
+    gdf = sg.to_gdf(torch_dataset)
+    assert len(gdf)
+
+    assert len(torch_dataset) == 10, len(torch_dataset)
+
+    sampler = RandomGeoSampler(torch_dataset, size=16, length=10)
+    dataloader = DataLoader(
+        torch_dataset, batch_size=2, sampler=sampler, collate_fn=stack_samples
+    )
+
+    for batch in dataloader:
+        image = batch["image"]
+        mask = batch["mask"]
+        print(image)
+
+
+if __name__ == "__main__":
+    test_torch()
+
+
+# %%

From fa25b843f5eddcfdc4c87810eb8233df7b4130fd Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Sun, 14 Apr 2024 21:24:24 +0200
Subject: [PATCH 29/42] add plot, from method to function

---
 src/sgis/raster/torchgeo.py | 46 ++++++++++++++++++++++---------------
 1 file changed, 28 insertions(+), 18 deletions(-)

diff --git a/src/sgis/raster/torchgeo.py b/src/sgis/raster/torchgeo.py
index 1c7f81d8..7ffbe228 100644
--- a/src/sgis/raster/torchgeo.py
+++ b/src/sgis/raster/torchgeo.py
@@ -8,6 +8,7 @@
 from rasterio.io import DatasetReader
 from rasterio.vrt import WarpedVRT
 from torchgeo.datasets.geo import RasterDataset
+from torchgeo.datasets.sentinel import Sentinel2 as TorchgeoSentinel2
 
 
 try:
@@ -28,8 +29,8 @@ class GCSFile:
 from .bands import SENTINEL2_FILENAME_REGEX
 
 
-class DaplaRasterDataset(RasterDataset):
-    """Custom version of torchgeo's class that works in and outside of Dapla (stat norway)."""
+class GCSRasterDataset(RasterDataset):
+    """Wrapper around torchgeo's RasterDataset that works in and outside of Dapla (stat norway)."""
 
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
@@ -37,7 +38,7 @@ def __init__(self, *args, **kwargs):
             [file.close() for file in self.files]
 
     @property
-    def files(self) -> set[str] | set[GCSFile]:
+    def files(self) -> set[GCSFile] | set[str]:
         """A list of all files in the dataset.
 
         Returns:
@@ -52,7 +53,12 @@ def files(self) -> set[str] | set[GCSFile]:
 
         if is_dapla():
             fs = dp.FileClient.get_gcs_file_system()
-            files = {fs.open(x) for x in self._get_gcs_paths(paths, fs)}
+            files: set[GCSFile] = {
+                fs.open(x)
+                for x in _get_gcs_paths(
+                    paths, filename_glob=self.filename_glob, file_system=fs
+                )
+            }
             return files
 
         # Using set to remove any duplicates if directories are overlapping
@@ -94,20 +100,25 @@ def _load_warp_file(self, filepath: str) -> DatasetReader:
             else:
                 return src
 
-    def _get_gcs_paths(self, paths: str | Iterable[str], fs=None) -> set[str]:
-        if fs is None:
-            fs = dp.FileClient.get_gcs_file_system()
 
-        # Using set to remove any duplicates if directories are overlapping
-        out_paths: set[str] = set()
-        for path in paths:
-            pathname = os.path.join(path, "**", self.filename_glob)
-            if is_dapla():
-                out_paths |= {x for x in fs.glob(pathname, recursive=True) if "." in x}
-        return out_paths
+def _get_gcs_paths(
+    paths: str | Iterable[str], filename_glob: str, file_system=None
+) -> set[str]:
+    if file_system is None:
+        file_system = dp.FileClient.get_gcs_file_system()
+
+    # Using set to remove any duplicates if directories are overlapping
+    out_paths: set[str] = set()
+    for path in paths:
+        pathname = os.path.join(path, "**", filename_glob)
+        if is_dapla():
+            out_paths |= {
+                x for x in file_system.glob(pathname, recursive=True) if "." in x
+            }
+    return out_paths
 
 
-class Sentinel2(DaplaRasterDataset):
+class Sentinel2(GCSRasterDataset):
     """Works like torchgeo's Sentinel2, with custom regexes."""
 
     date_format: str = "%Y%m%d"
@@ -115,9 +126,6 @@ class Sentinel2(DaplaRasterDataset):
 
     filename_regex = SENTINEL2_FILENAME_REGEX
 
-    _indexes = 1
-    _nodata = 0
-
     all_bands = [
         # "B1",
         "B2",
@@ -138,3 +146,5 @@ class Sentinel2(DaplaRasterDataset):
     separate_files = True
 
     cmap: dict[int, tuple[int, int, int, int]] = {}
+
+    plot = TorchgeoSentinel2.plot

From a4b0f982bb001e9f5f259d5b278fe3bef285a172 Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Sun, 14 Apr 2024 21:25:07 +0200
Subject: [PATCH 30/42] torch

---
 pyproject.toml | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/pyproject.toml b/pyproject.toml
index 596a6b40..31f0d083 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -70,6 +70,8 @@ pyupgrade = ">=3.3.1"
 sphinx = ">=6.1.3"
 sphinx-autobuild = ">=2021.3.14"
 sphinx-autodoc-typehints = ">=1.22"
+torch = ">=2.2.2"
+torchgeo = ">=0.5.2"
 xdoctest = {extras = ["colors"], version = ">=1.1.1"}
 
 

From eeb7c07325bba11fd202c5017077b8454fe7d7ea Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Sun, 14 Apr 2024 21:25:40 +0200
Subject: [PATCH 31/42] torch

---
 poetry.lock | 1749 +++++++++++++++++++++++++++++++++++++++++++--------
 1 file changed, 1477 insertions(+), 272 deletions(-)

diff --git a/poetry.lock b/poetry.lock
index 5eacfe47..ebd13ca8 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,5 +1,17 @@
 # This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand.
 
+[[package]]
+name = "aenum"
+version = "3.1.15"
+description = "Advanced Enumerations (compatible with Python's stdlib Enum), NamedTuples, and NamedConstants"
+optional = false
+python-versions = "*"
+files = [
+    {file = "aenum-3.1.15-py2-none-any.whl", hash = "sha256:27b1710b9d084de6e2e695dab78fe9f269de924b51ae2850170ee7e1ca6288a5"},
+    {file = "aenum-3.1.15-py3-none-any.whl", hash = "sha256:e0dfaeea4c2bd362144b87377e2c61d91958c5ed0b4daf89cb6f45ae23af6288"},
+    {file = "aenum-3.1.15.tar.gz", hash = "sha256:8cbd76cd18c4f870ff39b24284d3ea028fbe8731a58df3aa581e434c575b9559"},
+]
+
 [[package]]
 name = "affine"
 version = "2.4.0"
@@ -17,87 +29,87 @@ test = ["pytest (>=4.6)", "pytest-cov"]
 
 [[package]]
 name = "aiohttp"
-version = "3.9.3"
+version = "3.9.4"
 description = "Async http client/server framework (asyncio)"
 optional = false
 python-versions = ">=3.8"
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+    {file = "aiohttp-3.9.4.tar.gz", hash = "sha256:6ff71ede6d9a5a58cfb7b6fffc83ab5d4a63138276c771ac91ceaaddf5459644"},
 ]
 
 [package.dependencies]
@@ -136,6 +148,16 @@ files = [
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 ]
 
+[[package]]
+name = "antlr4-python3-runtime"
+version = "4.9.3"
+description = "ANTLR 4.9.3 runtime for Python 3.7"
+optional = false
+python-versions = "*"
+files = [
+    {file = "antlr4-python3-runtime-4.9.3.tar.gz", hash = "sha256:f224469b4168294902bb1efa80a8bf7855f24c99aef99cbefc1bcd3cce77881b"},
+]
+
 [[package]]
 name = "anyio"
 version = "4.3.0"
@@ -366,35 +388,46 @@ charset-normalizer = ["charset-normalizer"]
 html5lib = ["html5lib"]
 lxml = ["lxml"]
 
+[[package]]
+name = "bitsandbytes"
+version = "0.41.0"
+description = "k-bit optimizers and matrix multiplication routines."
+optional = false
+python-versions = "*"
+files = [
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+]
+
 [[package]]
 name = "black"
-version = "24.3.0"
+version = "24.4.0"
 description = "The uncompromising code formatter."
 optional = false
 python-versions = ">=3.8"
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 ]
 
 [package.dependencies]
@@ -962,21 +995,21 @@ files = [
 
 [[package]]
 name = "deptry"
-version = "0.16.0"
+version = "0.16.1"
 description = "A command line utility to check for unused, missing and transitive dependencies in a Python project."
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "deptry-0.16.1.tar.gz", hash = "sha256:39fb62da4a8f4d17ed282310f7bcaadec55a95a8c471b01e0fcdf5351a7ac323"},
 ]
 
 [package.dependencies]
@@ -995,6 +1028,17 @@ files = [
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 ]
 
+[[package]]
+name = "docstring-parser"
+version = "0.16"
+description = "Parse Python docstrings in reST, Google and Numpydoc format"
+optional = false
+python-versions = ">=3.6,<4.0"
+files = [
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+    {file = "docstring_parser-0.16.tar.gz", hash = "sha256:538beabd0af1e2db0146b6bd3caa526c35a34d61af9fd2887f3a8a27a739aa6e"},
+]
+
 [[package]]
 name = "docutils"
 version = "0.20.1"
@@ -1006,6 +1050,30 @@ files = [
     {file = "docutils-0.20.1.tar.gz", hash = "sha256:f08a4e276c3a1583a86dce3e34aba3fe04d02bba2dd51ed16106244e8a923e3b"},
 ]
 
+[[package]]
+name = "efficientnet-pytorch"
+version = "0.7.1"
+description = "EfficientNet implemented in PyTorch."
+optional = false
+python-versions = ">=3.5.0"
+files = [
+    {file = "efficientnet_pytorch-0.7.1.tar.gz", hash = "sha256:00b9b261effce59d2d47aae2ad238c29a2a65175470f41ada7ecac439b7c1ee1"},
+]
+
+[package.dependencies]
+torch = "*"
+
+[[package]]
+name = "einops"
+version = "0.7.0"
+description = "A new flavour of deep learning operations"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "einops-0.7.0-py3-none-any.whl", hash = "sha256:0f3096f26b914f465f6ff3c66f5478f9a5e380bb367ffc6493a68143fbbf1fd1"},
+    {file = "einops-0.7.0.tar.gz", hash = "sha256:b2b04ad6081a3b227080c9bf5e3ace7160357ff03043cd66cc5b2319eb7031d1"},
+]
+
 [[package]]
 name = "exceptiongroup"
 version = "1.2.0"
@@ -1050,13 +1118,13 @@ devel = ["colorama", "json-spec", "jsonschema", "pylint", "pytest", "pytest-benc
 
 [[package]]
 name = "filelock"
-version = "3.13.3"
+version = "3.13.4"
 description = "A platform independent file lock."
 optional = false
 python-versions = ">=3.8"
 files = [
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 [package.extras]
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+
 [package.extras]
 abfs = ["adlfs"]
 adl = ["adlfs"]
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 http2 = ["h2 (>=3,<5)"]
 socks = ["socksio (==1.*)"]
 
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+
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+all = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "gradio", "jedi", "minijinja (>=1.0)", "mypy (==1.5.1)", "numpy", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "ruff (>=0.3.0)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
+cli = ["InquirerPy (==0.3.4)"]
+dev = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "gradio", "jedi", "minijinja (>=1.0)", "mypy (==1.5.1)", "numpy", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "ruff (>=0.3.0)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
+fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
+hf-transfer = ["hf-transfer (>=0.1.4)"]
+inference = ["aiohttp", "minijinja (>=1.0)"]
+quality = ["mypy (==1.5.1)", "ruff (>=0.3.0)"]
+tensorflow = ["graphviz", "pydot", "tensorflow"]
+tensorflow-testing = ["keras (<3.0)", "tensorflow"]
+testing = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "gradio", "jedi", "minijinja (>=1.0)", "numpy", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "soundfile", "urllib3 (<2.0)"]
+torch = ["safetensors", "torch"]
+typing = ["types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)"]
+
+[[package]]
+name = "hydra-core"
+version = "1.3.2"
+description = "A framework for elegantly configuring complex applications"
+optional = false
+python-versions = "*"
+files = [
+    {file = "hydra-core-1.3.2.tar.gz", hash = "sha256:8a878ed67216997c3e9d88a8e72e7b4767e81af37afb4ea3334b269a4390a824"},
+    {file = "hydra_core-1.3.2-py3-none-any.whl", hash = "sha256:fa0238a9e31df3373b35b0bfb672c34cc92718d21f81311d8996a16de1141d8b"},
+]
+
+[package.dependencies]
+antlr4-python3-runtime = "==4.9.*"
+omegaconf = ">=2.2,<2.4"
+packaging = "*"
+
 [[package]]
 name = "identify"
 version = "2.5.35"
@@ -1548,13 +1669,13 @@ license = ["ukkonen"]
 
 [[package]]
 name = "idna"
-version = "3.6"
+version = "3.7"
 description = "Internationalized Domain Names in Applications (IDNA)"
 optional = false
 python-versions = ">=3.5"
 files = [
-    {file = "idna-3.6-py3-none-any.whl", hash = "sha256:c05567e9c24a6b9faaa835c4821bad0590fbb9d5779e7caa6e1cc4978e7eb24f"},
-    {file = "idna-3.6.tar.gz", hash = "sha256:9ecdbbd083b06798ae1e86adcbfe8ab1479cf864e4ee30fe4e46a003d12491ca"},
+    {file = "idna-3.7-py3-none-any.whl", hash = "sha256:82fee1fc78add43492d3a1898bfa6d8a904cc97d8427f683ed8e798d07761aa0"},
+    {file = "idna-3.7.tar.gz", hash = "sha256:028ff3aadf0609c1fd278d8ea3089299412a7a8b9bd005dd08b9f8285bcb5cfc"},
 ]
 
 [[package]]
@@ -1644,6 +1765,21 @@ docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.link
 perf = ["ipython"]
 testing = ["flufl.flake8", "importlib-resources (>=1.3)", "jaraco.test (>=5.4)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy", "pytest-perf (>=0.9.2)", "pytest-ruff (>=0.2.1)"]
 
+[[package]]
+name = "importlib-resources"
+version = "6.4.0"
+description = "Read resources from Python packages"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "importlib_resources-6.4.0-py3-none-any.whl", hash = "sha256:50d10f043df931902d4194ea07ec57960f66a80449ff867bfe782b4c486ba78c"},
+    {file = "importlib_resources-6.4.0.tar.gz", hash = "sha256:cdb2b453b8046ca4e3798eb1d84f3cce1446a0e8e7b5ef4efb600f19fc398145"},
+]
+
+[package.extras]
+docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (<7.2.5)", "sphinx (>=3.5)", "sphinx-lint"]
+testing = ["jaraco.test (>=5.4)", "pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy", "pytest-ruff (>=0.2.1)", "zipp (>=3.17)"]
+
 [[package]]
 name = "iniconfig"
 version = "2.0.0"
@@ -1831,26 +1967,61 @@ i18n = ["Babel (>=2.7)"]
 
 [[package]]
 name = "joblib"
-version = "1.3.2"
+version = "1.4.0"
 description = "Lightweight pipelining with Python functions"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "joblib-1.3.2-py3-none-any.whl", hash = "sha256:ef4331c65f239985f3f2220ecc87db222f08fd22097a3dd5698f693875f8cbb9"},
-    {file = "joblib-1.3.2.tar.gz", hash = "sha256:92f865e621e17784e7955080b6d042489e3b8e294949cc44c6eac304f59772b1"},
+    {file = "joblib-1.4.0-py3-none-any.whl", hash = "sha256:42942470d4062537be4d54c83511186da1fc14ba354961a2114da91efa9a4ed7"},
+    {file = "joblib-1.4.0.tar.gz", hash = "sha256:1eb0dc091919cd384490de890cb5dfd538410a6d4b3b54eef09fb8c50b409b1c"},
 ]
 
 [[package]]
 name = "json5"
-version = "0.9.24"
+version = "0.9.25"
 description = "A Python implementation of the JSON5 data format."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "json5-0.9.24-py3-none-any.whl", hash = "sha256:4ca101fd5c7cb47960c055ef8f4d0e31e15a7c6c48c3b6f1473fc83b6c462a13"},
-    {file = "json5-0.9.24.tar.gz", hash = "sha256:0c638399421da959a20952782800e5c1a78c14e08e1dc9738fa10d8ec14d58c8"},
+    {file = "json5-0.9.25-py3-none-any.whl", hash = "sha256:34ed7d834b1341a86987ed52f3f76cd8ee184394906b6e22a1e0deb9ab294e8f"},
+    {file = "json5-0.9.25.tar.gz", hash = "sha256:548e41b9be043f9426776f05df8635a00fe06104ea51ed24b67f908856e151ae"},
+]
+
+[[package]]
+name = "jsonargparse"
+version = "4.27.7"
+description = "Implement minimal boilerplate CLIs derived from type hints and parse from command line, config files and environment variables."
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "jsonargparse-4.27.7-py3-none-any.whl", hash = "sha256:9042339d1fc9f39b2ef61c0f9c4accd144db14a3aab9359e9b2e883d3af3740a"},
+    {file = "jsonargparse-4.27.7.tar.gz", hash = "sha256:480fa4b2f4c75f267cbaa13fbf4dc86553f27252041d1d9066f2d0e25bf6389b"},
 ]
 
+[package.dependencies]
+docstring-parser = {version = ">=0.15", optional = true, markers = "extra == \"signatures\""}
+PyYAML = ">=3.13"
+typeshed-client = {version = ">=2.1.0", optional = true, markers = "extra == \"signatures\""}
+
+[package.extras]
+all = ["jsonargparse[argcomplete]", "jsonargparse[fsspec]", "jsonargparse[jsonnet]", "jsonargparse[jsonschema]", "jsonargparse[omegaconf]", "jsonargparse[reconplogger]", "jsonargparse[ruyaml]", "jsonargparse[signatures]", "jsonargparse[typing-extensions]", "jsonargparse[urls]"]
+argcomplete = ["argcomplete (>=2.0.0)"]
+coverage = ["jsonargparse[test-no-urls]", "pytest-cov (>=4.0.0)"]
+dev = ["build (>=0.10.0)", "jsonargparse[coverage]", "jsonargparse[doc]", "jsonargparse[mypy]", "jsonargparse[test]", "pre-commit (>=2.19.0)", "tox (>=3.25.0)"]
+doc = ["Sphinx (>=1.7.9)", "autodocsumm (>=0.1.10)", "sphinx-autodoc-typehints (>=1.19.5)", "sphinx-rtd-theme (>=1.2.2)"]
+fsspec = ["fsspec (>=0.8.4)"]
+jsonnet = ["jsonnet (>=0.13.0)", "jsonnet-binary (>=0.17.0)"]
+jsonschema = ["jsonschema (>=3.2.0)"]
+maintainer = ["bump2version (>=0.5.11)", "twine (>=4.0.2)"]
+omegaconf = ["omegaconf (>=2.1.1)"]
+reconplogger = ["reconplogger (>=4.4.0)"]
+ruyaml = ["ruyaml (>=0.20.0)"]
+signatures = ["docstring-parser (>=0.15)", "jsonargparse[typing-extensions]", "typeshed-client (>=2.1.0)"]
+test = ["attrs (>=22.2.0)", "jsonargparse[test-no-urls]", "pydantic (>=2.3.0)", "responses (>=0.12.0)", "types-PyYAML (>=6.0.11)", "types-requests (>=2.28.9)"]
+test-no-urls = ["pytest (>=6.2.5)", "pytest-subtests (>=0.8.0)"]
+typing-extensions = ["typing-extensions (>=3.10.0.0)"]
+urls = ["requests (>=2.18.4)"]
+
 [[package]]
 name = "jsonpointer"
 version = "2.4"
@@ -1974,13 +2145,13 @@ test = ["click", "pre-commit", "pytest (>=7.0)", "pytest-asyncio (>=0.19.0)", "p
 
 [[package]]
 name = "jupyter-lsp"
-version = "2.2.4"
+version = "2.2.5"
 description = "Multi-Language Server WebSocket proxy for Jupyter Notebook/Lab server"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "jupyter-lsp-2.2.4.tar.gz", hash = "sha256:5e50033149344065348e688608f3c6d654ef06d9856b67655bd7b6bac9ee2d59"},
-    {file = "jupyter_lsp-2.2.4-py3-none-any.whl", hash = "sha256:da61cb63a16b6dff5eac55c2699cc36eac975645adee02c41bdfc03bf4802e77"},
+    {file = "jupyter-lsp-2.2.5.tar.gz", hash = "sha256:793147a05ad446f809fd53ef1cd19a9f5256fd0a2d6b7ce943a982cb4f545001"},
+    {file = "jupyter_lsp-2.2.5-py3-none-any.whl", hash = "sha256:45fbddbd505f3fbfb0b6cb2f1bc5e15e83ab7c79cd6e89416b248cb3c00c11da"},
 ]
 
 [package.dependencies]
@@ -1988,39 +2159,39 @@ jupyter-server = ">=1.1.2"
 
 [[package]]
 name = "jupyter-server"
-version = "2.13.0"
+version = "2.14.0"
 description = "The backend—i.e. core services, APIs, and REST endpoints—to Jupyter web applications."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "jupyter_server-2.13.0-py3-none-any.whl", hash = "sha256:77b2b49c3831fbbfbdb5048cef4350d12946191f833a24e5f83e5f8f4803e97b"},
-    {file = "jupyter_server-2.13.0.tar.gz", hash = "sha256:c80bfb049ea20053c3d9641c2add4848b38073bf79f1729cea1faed32fc1c78e"},
+    {file = "jupyter_server-2.14.0-py3-none-any.whl", hash = "sha256:fb6be52c713e80e004fac34b35a0990d6d36ba06fd0a2b2ed82b899143a64210"},
+    {file = "jupyter_server-2.14.0.tar.gz", hash = "sha256:659154cea512083434fd7c93b7fe0897af7a2fd0b9dd4749282b42eaac4ae677"},
 ]
 
 [package.dependencies]
 anyio = ">=3.1.0"
-argon2-cffi = "*"
-jinja2 = "*"
+argon2-cffi = ">=21.1"
+jinja2 = ">=3.0.3"
 jupyter-client = ">=7.4.4"
 jupyter-core = ">=4.12,<5.0.dev0 || >=5.1.dev0"
 jupyter-events = ">=0.9.0"
-jupyter-server-terminals = "*"
+jupyter-server-terminals = ">=0.4.4"
 nbconvert = ">=6.4.4"
 nbformat = ">=5.3.0"
-overrides = "*"
-packaging = "*"
-prometheus-client = "*"
-pywinpty = {version = "*", markers = "os_name == \"nt\""}
+overrides = ">=5.0"
+packaging = ">=22.0"
+prometheus-client = ">=0.9"
+pywinpty = {version = ">=2.0.1", markers = "os_name == \"nt\""}
 pyzmq = ">=24"
 send2trash = ">=1.8.2"
 terminado = ">=0.8.3"
 tornado = ">=6.2.0"
 traitlets = ">=5.6.0"
-websocket-client = "*"
+websocket-client = ">=1.7"
 
 [package.extras]
 docs = ["ipykernel", "jinja2", "jupyter-client", "jupyter-server", "myst-parser", "nbformat", "prometheus-client", "pydata-sphinx-theme", "send2trash", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-openapi (>=0.8.0)", "sphinxcontrib-spelling", "sphinxemoji", "tornado", "typing-extensions"]
-test = ["flaky", "ipykernel", "pre-commit", "pytest (>=7.0)", "pytest-console-scripts", "pytest-jupyter[server] (>=0.7)", "pytest-timeout", "requests"]
+test = ["flaky", "ipykernel", "pre-commit", "pytest (>=7.0,<9)", "pytest-console-scripts", "pytest-jupyter[server] (>=0.7)", "pytest-timeout", "requests"]
 
 [[package]]
 name = "jupyter-server-terminals"
@@ -2043,19 +2214,19 @@ test = ["jupyter-server (>=2.0.0)", "pytest (>=7.0)", "pytest-jupyter[server] (>
 
 [[package]]
 name = "jupyterlab"
-version = "4.1.5"
+version = "4.1.6"
 description = "JupyterLab computational environment"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "jupyterlab-4.1.5-py3-none-any.whl", hash = "sha256:3bc843382a25e1ab7bc31d9e39295a9f0463626692b7995597709c0ab236ab2c"},
-    {file = "jupyterlab-4.1.5.tar.gz", hash = "sha256:c9ad75290cb10bfaff3624bf3fbb852319b4cce4c456613f8ebbaa98d03524db"},
+    {file = "jupyterlab-4.1.6-py3-none-any.whl", hash = "sha256:cf3e862bc10dbf4331e4eb37438634f813c238cfc62c71c640b3b3b2caa089a8"},
+    {file = "jupyterlab-4.1.6.tar.gz", hash = "sha256:7935f36ba26eb615183a4f5c2bbca5791b5108ce2a00b5505f8cfd100d53648e"},
 ]
 
 [package.dependencies]
 async-lru = ">=1.0.0"
 httpx = ">=0.25.0"
-ipykernel = "*"
+ipykernel = ">=6.5.0"
 jinja2 = ">=3.0.3"
 jupyter-core = "*"
 jupyter-lsp = ">=2.0.0"
@@ -2063,7 +2234,7 @@ jupyter-server = ">=2.4.0,<3"
 jupyterlab-server = ">=2.19.0,<3"
 notebook-shim = ">=0.2"
 packaging = "*"
-tomli = {version = "*", markers = "python_version < \"3.11\""}
+tomli = {version = ">=1.2.2", markers = "python_version < \"3.11\""}
 tornado = ">=6.2.0"
 traitlets = "*"
 
@@ -2072,6 +2243,7 @@ dev = ["build", "bump2version", "coverage", "hatch", "pre-commit", "pytest-cov",
 docs = ["jsx-lexer", "myst-parser", "pydata-sphinx-theme (>=0.13.0)", "pytest", "pytest-check-links", "pytest-jupyter", "sphinx (>=1.8,<7.3.0)", "sphinx-copybutton"]
 docs-screenshots = ["altair (==5.2.0)", "ipython (==8.16.1)", "ipywidgets (==8.1.1)", "jupyterlab-geojson (==3.4.0)", "jupyterlab-language-pack-zh-cn (==4.0.post6)", "matplotlib (==3.8.2)", "nbconvert (>=7.0.0)", "pandas (==2.2.0)", "scipy (==1.12.0)", "vega-datasets (==0.9.0)"]
 test = ["coverage", "pytest (>=7.0)", "pytest-check-links (>=0.7)", "pytest-console-scripts", "pytest-cov", "pytest-jupyter (>=0.5.3)", "pytest-timeout", "pytest-tornasync", "requests", "requests-cache", "virtualenv"]
+upgrade-extension = ["copier (>=8.0,<9.0)", "jinja2-time (<0.3)", "pydantic (<2.0)", "pyyaml-include (<2.0)", "tomli-w (<2.0)"]
 
 [[package]]
 name = "jupyterlab-pygments"
@@ -2086,13 +2258,13 @@ files = [
 
 [[package]]
 name = "jupyterlab-server"
-version = "2.25.4"
+version = "2.26.0"
 description = "A set of server components for JupyterLab and JupyterLab like applications."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "jupyterlab_server-2.25.4-py3-none-any.whl", hash = "sha256:eb645ecc8f9b24bac5decc7803b6d5363250e16ec5af814e516bc2c54dd88081"},
-    {file = "jupyterlab_server-2.25.4.tar.gz", hash = "sha256:2098198e1e82e0db982440f9b5136175d73bea2cd42a6480aa6fd502cb23c4f9"},
+    {file = "jupyterlab_server-2.26.0-py3-none-any.whl", hash = "sha256:54622cbd330526a385ee0c1fdccdff3a1e7219bf3e864a335284a1270a1973df"},
+    {file = "jupyterlab_server-2.26.0.tar.gz", hash = "sha256:9b3ba91cf2837f7f124fca36d63f3ca80ace2bed4898a63dd47e6598c1ab006f"},
 ]
 
 [package.dependencies]
@@ -2252,19 +2424,197 @@ files = [
 ]
 
 [[package]]
-name = "livereload"
-version = "2.6.3"
-description = "Python LiveReload is an awesome tool for web developers"
+name = "kornia"
+version = "0.7.2"
+description = "Open Source Differentiable Computer Vision Library for PyTorch"
 optional = false
-python-versions = "*"
+python-versions = ">=3.8"
 files = [
-    {file = "livereload-2.6.3-py2.py3-none-any.whl", hash = "sha256:ad4ac6f53b2d62bb6ce1a5e6e96f1f00976a32348afedcb4b6d68df2a1d346e4"},
-    {file = "livereload-2.6.3.tar.gz", hash = "sha256:776f2f865e59fde56490a56bcc6773b6917366bce0c267c60ee8aaf1a0959869"},
+    {file = "kornia-0.7.2-py2.py3-none-any.whl", hash = "sha256:411e09ccdc4efde351f90a81f35a6eb9fad3bcf58ac037cbec4d41a8364dd039"},
+    {file = "kornia-0.7.2.tar.gz", hash = "sha256:f834ccd51188d071ed286a6727471c94344ea2a718903cc6f0e56a92f9c66ac5"},
 ]
 
 [package.dependencies]
-six = "*"
-tornado = {version = "*", markers = "python_version > \"2.7\""}
+kornia-rs = ">=0.1.0"
+packaging = "*"
+torch = ">=1.9.1"
+
+[package.extras]
+dev = ["coverage", "mypy", "numpy", "onnx", "pre-commit (>=2)", "pydocstyle", "pytest (==8.1.1)", "pytest-timeout", "requests"]
+docs = ["PyYAML (>=5.1)", "furo", "kornia-moons", "matplotlib", "opencv-python", "sphinx", "sphinx-autodoc-defaultargs", "sphinx-autodoc-typehints", "sphinx-copybutton (>=0.3)", "sphinx-design", "sphinx-notfound-page", "sphinxcontrib-bibtex", "sphinxcontrib-gtagjs", "sphinxcontrib-youtube"]
+x = ["accelerate", "onnxruntime-gpu (>=1.16)"]
+
+[[package]]
+name = "kornia-rs"
+version = "0.1.3"
+description = "Low level implementations for computer vision in Rust"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "kornia_rs-0.1.3-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:e57fa6c44dcaf896e2b3d9afad0e67b0c6615f5274c3c48d12fe37f4ae6f2a9b"},
+    {file = "kornia_rs-0.1.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:530771c49b74fe70fa794ef2d5b9976c993e4dcb976b08608471949e4ef56e87"},
+    {file = "kornia_rs-0.1.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0b8ef31b823c07b8ff30587c163ca280145ae867192a86ac4505bc73ae4be9a4"},
+    {file = "kornia_rs-0.1.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ce91aa5fa6d8068c33ba53bdf3cf943cb53ad8b14b06b2812dd10f104b61a161"},
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@@ -2542,6 +2892,23 @@ files = [
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@@ -2818,20 +3200,20 @@ files = [
 
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+
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+optional = false
+python-versions = ">=3"
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+optional = false
+python-versions = ">=3.6"
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+PyYAML = ">=5.1.0"
+
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 name = "overrides"
 version = "7.7.0"
@@ -3268,19 +3806,35 @@ virtualenv = ">=20.10.0"
 
 [[package]]
 name = "pre-commit-hooks"
-version = "4.5.0"
+version = "4.6.0"
 description = "Some out-of-the-box hooks for pre-commit."
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 tomli = {version = ">=1.1.0", markers = "python_version < \"3.11\""}
 
+[[package]]
+name = "pretrainedmodels"
+version = "0.7.4"
+description = "Pretrained models for Pytorch"
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+python-versions = "*"
+files = [
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+[package.dependencies]
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+tqdm = "*"
+
 [[package]]
 name = "prometheus-client"
 version = "0.20.0"
@@ -3309,6 +3863,26 @@ files = [
 [package.dependencies]
 wcwidth = "*"
 
+[[package]]
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+description = ""
+optional = false
+python-versions = ">=3.8"
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+
+[package.extras]
+dotenv = ["python-dotenv (>=0.10.4)"]
+email = ["email-validator (>=1.0.3)"]
+
 [[package]]
 name = "pydocstyle"
 version = "6.3.0"
@@ -3655,6 +4281,37 @@ files = [
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 ]
 
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+name = "pytorch-lightning"
+version = "2.2.2"
+description = "PyTorch Lightning is the lightweight PyTorch wrapper for ML researchers. Scale your models. Write less boilerplate."
+optional = false
+python-versions = ">=3.8"
+files = [
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+numpy = ">=1.17.2"
+packaging = ">=20.0"
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+torch = ">=1.13.0"
+torchmetrics = ">=0.7.0"
+tqdm = ">=4.57.0"
+typing-extensions = ">=4.4.0"
+
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+strategies = ["deepspeed (>=0.8.2,<=0.9.3)"]
+test = ["cloudpickle (>=1.3)", "coverage (==7.3.1)", "fastapi", "onnx (>=0.14.0)", "onnxruntime (>=0.15.0)", "pandas (>1.0)", "psutil (<5.9.6)", "pytest (==7.4.0)", "pytest-cov (==4.1.0)", "pytest-random-order (==1.1.0)", "pytest-rerunfailures (==12.0)", "pytest-timeout (==2.1.0)", "scikit-learn (>0.22.1)", "tensorboard (>=2.9.1)", "uvicorn"]
+
 [[package]]
 name = "pytz"
 version = "2024.1"
@@ -3874,32 +4531,32 @@ cffi = {version = "*", markers = "implementation_name == \"pypy\""}
 
 [[package]]
 name = "rasterio"
-version = "1.3.9"
+version = "1.3.10"
 description = "Fast and direct raster I/O for use with Numpy and SciPy"
 optional = false
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-numpy = ">=1.19.5,<2.0"
+numpy = ">=1.19.5"
 scipy = ">=1.6.0"
 threadpoolctl = ">=2.0.0"
 
@@ -4326,15 +5115,37 @@ dev = ["cython-lint (>=0.12.2)", "doit (>=0.36.0)", "mypy", "pycodestyle", "pyde
 doc = ["jupyterlite-pyodide-kernel", "jupyterlite-sphinx (>=0.12.0)", "jupytext", "matplotlib (>=3.5)", "myst-nb", "numpydoc", "pooch", "pydata-sphinx-theme (>=0.15.2)", "sphinx (>=5.0.0)", "sphinx-design (>=0.4.0)"]
 test = ["array-api-strict", "asv", "gmpy2", "hypothesis (>=6.30)", "mpmath", "pooch", "pytest", "pytest-cov", "pytest-timeout", "pytest-xdist", "scikit-umfpack", "threadpoolctl"]
 
+[[package]]
+name = "segmentation-models-pytorch"
+version = "0.3.3"
+description = "Image segmentation models with pre-trained backbones. PyTorch."
+optional = false
+python-versions = ">=3.7.0"
+files = [
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+[package.dependencies]
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+pretrainedmodels = "0.7.4"
+timm = "0.9.2"
+torchvision = ">=0.5.0"
+tqdm = "*"
+
+[package.extras]
+test = ["black (==22.3.0)", "flake8 (==4.0.1)", "flake8-docstrings (==1.6.0)", "mock", "pre-commit", "pytest"]
+
 [[package]]
 name = "send2trash"
-version = "1.8.2"
+version = "1.8.3"
 description = "Send file to trash natively under Mac OS X, Windows and Linux"
 optional = false
-python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,>=2.7"
+python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7"
 files = [
-    {file = "Send2Trash-1.8.2-py3-none-any.whl", hash = "sha256:a384719d99c07ce1eefd6905d2decb6f8b7ed054025bb0e618919f945de4f679"},
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+    {file = "Send2Trash-1.8.3.tar.gz", hash = "sha256:b18e7a3966d99871aefeb00cfbcfdced55ce4871194810fc71f4aa484b953abf"},
 ]
 
 [package.extras]
@@ -4513,41 +5324,43 @@ test = ["cython (>=3.0)", "filelock", "html5lib", "pytest (>=4.6)", "setuptools
 
 [[package]]
 name = "sphinx-autobuild"
-version = "2024.2.4"
-description = "Rebuild Sphinx documentation on changes, with live-reload in the browser."
+version = "2024.4.13"
+description = "Rebuild Sphinx documentation on changes, with hot reloading in the browser."
 optional = false
 python-versions = ">=3.9"
 files = [
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 ]
 
 [package.dependencies]
 colorama = "*"
-livereload = "*"
 sphinx = "*"
+starlette = ">=0.35"
+uvicorn = ">=0.25"
+websockets = ">=11.0"
 
 [package.extras]
 test = ["pytest (>=6.0)", "pytest-cov"]
 
 [[package]]
 name = "sphinx-autodoc-typehints"
-version = "2.0.0"
+version = "2.0.1"
 description = "Type hints (PEP 484) support for the Sphinx autodoc extension"
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 files = [
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 ]
 
 [package.dependencies]
 sphinx = ">=7.1.2"
 
 [package.extras]
-docs = ["furo (>=2023.9.10)"]
+docs = ["furo (>=2024.1.29)"]
 numpy = ["nptyping (>=2.5)"]
-testing = ["covdefaults (>=2.3)", "coverage (>=7.3.2)", "diff-cover (>=8.0.1)", "pytest (>=7.4.3)", "pytest-cov (>=4.1)", "sphobjinv (>=2.3.1)", "typing-extensions (>=4.8)"]
+testing = ["covdefaults (>=2.3)", "coverage (>=7.4.2)", "diff-cover (>=8.0.3)", "pytest (>=8.0.1)", "pytest-cov (>=4.1)", "sphobjinv (>=2.3.1)", "typing-extensions (>=4.9)"]
 
 [[package]]
 name = "sphinx-basic-ng"
@@ -4679,6 +5492,23 @@ pure-eval = "*"
 [package.extras]
 tests = ["cython", "littleutils", "pygments", "pytest", "typeguard"]
 
+[[package]]
+name = "starlette"
+version = "0.37.2"
+description = "The little ASGI library that shines."
+optional = false
+python-versions = ">=3.8"
+files = [
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+[package.dependencies]
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+
+[package.extras]
+full = ["httpx (>=0.22.0)", "itsdangerous", "jinja2", "python-multipart (>=0.0.7)", "pyyaml"]
+
 [[package]]
 name = "stevedore"
 version = "5.2.0"
@@ -4693,6 +5523,36 @@ files = [
 [package.dependencies]
 pbr = ">=2.0.0,<2.1.0 || >2.1.0"
 
+[[package]]
+name = "sympy"
+version = "1.12"
+description = "Computer algebra system (CAS) in Python"
+optional = false
+python-versions = ">=3.8"
+files = [
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+
+[package.dependencies]
+mpmath = ">=0.19"
+
+[[package]]
+name = "tensorboardx"
+version = "2.6.2.2"
+description = "TensorBoardX lets you watch Tensors Flow without Tensorflow"
+optional = false
+python-versions = "*"
+files = [
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+
+[package.dependencies]
+numpy = "*"
+packaging = "*"
+protobuf = ">=3.20"
+
 [[package]]
 name = "terminado"
 version = "0.18.1"
@@ -4736,6 +5596,24 @@ files = [
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 ]
 
+[[package]]
+name = "timm"
+version = "0.9.2"
+description = "PyTorch Image Models"
+optional = false
+python-versions = ">=3.7"
+files = [
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+]
+
+[package.dependencies]
+huggingface-hub = "*"
+pyyaml = "*"
+safetensors = "*"
+torch = ">=1.7"
+torchvision = "*"
+
 [[package]]
 name = "tinycss2"
 version = "1.2.1"
@@ -4798,6 +5676,175 @@ files = [
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 ]
 
+[[package]]
+name = "torch"
+version = "2.2.2"
+description = "Tensors and Dynamic neural networks in Python with strong GPU acceleration"
+optional = false
+python-versions = ">=3.8.0"
+files = [
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+
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+
 [[package]]
 name = "tornado"
 version = "6.4"
@@ -4818,6 +5865,26 @@ files = [
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+slack = ["slack-sdk"]
+telegram = ["requests"]
+
 [[package]]
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 version = "5.14.2"
@@ -4833,6 +5900,29 @@ files = [
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 test = ["argcomplete (>=3.0.3)", "mypy (>=1.7.0)", "pre-commit", "pytest (>=7.0,<8.1)", "pytest-mock", "pytest-mypy-testing"]
 
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+description = "A language and compiler for custom Deep Learning operations"
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+python-versions = "*"
+files = [
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+tutorials = ["matplotlib", "pandas", "tabulate", "torch"]
+
 [[package]]
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@@ -4844,15 +5934,30 @@ files = [
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+python-versions = ">=3.8"
+files = [
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+
 [[package]]
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 python-versions = ">=3.8"
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 [[package]]
@@ -4897,6 +6002,25 @@ h2 = ["h2 (>=4,<5)"]
 socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"]
 zstd = ["zstandard (>=0.18.0)"]
 
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+python-versions = ">=3.8"
+files = [
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+
 [[package]]
 name = "virtualenv"
 version = "20.25.1"
@@ -4970,6 +6094,87 @@ docs = ["Sphinx (>=6.0)", "sphinx-rtd-theme (>=1.1.0)"]
 optional = ["python-socks", "wsaccel"]
 test = ["websockets"]
 
+[[package]]
+name = "websockets"
+version = "12.0"
+description = "An implementation of the WebSocket Protocol (RFC 6455 & 7692)"
+optional = false
+python-versions = ">=3.8"
+files = [
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+    {file = "websockets-12.0-py3-none-any.whl", hash = "sha256:dc284bbc8d7c78a6c69e0c7325ab46ee5e40bb4d50e494d8131a07ef47500e9e"},
+    {file = "websockets-12.0.tar.gz", hash = "sha256:81df9cbcbb6c260de1e007e58c011bfebe2dafc8435107b0537f393dd38c8b1b"},
+]
+
 [[package]]
 name = "xarray"
 version = "2023.8.0"
@@ -5153,4 +6358,4 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.10,<4"
-content-hash = "3d7e0b678e178e90377160d240734543faa9cce8d6974ad07c61a44ddc72ef4e"
+content-hash = "cc1490350473569db2b7c118ade179b03d6a94645913a15227b1c8e40b0425c8"

From 67599c85afdfed5549aa7c65745d275ad1c048f6 Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Sun, 14 Apr 2024 21:26:22 +0200
Subject: [PATCH 32/42] torch

---
 src/sgis/maps/explore.py | 22 +++++++++++++++++++++-
 src/sgis/maps/map.py     | 20 ++++++++++++++++----
 src/sgis/maps/maps.py    | 40 ++++++++++++++++++++--------------------
 3 files changed, 57 insertions(+), 25 deletions(-)

diff --git a/src/sgis/maps/explore.py b/src/sgis/maps/explore.py
index 0089601b..23e665b9 100644
--- a/src/sgis/maps/explore.py
+++ b/src/sgis/maps/explore.py
@@ -32,6 +32,14 @@
 from .tilesources import kartverket, xyz
 
 
+try:
+    from torchgeo.datasets.geo import RasterDataset
+except ImportError:
+
+    class RasterDataset:
+        """Placeholder"""
+
+
 # the geopandas._explore raises a deprication warning. Ignoring for now.
 warnings.filterwarnings(
     action="ignore", category=matplotlib.MatplotlibDeprecationWarning
@@ -187,6 +195,13 @@ def __init__(
         else:
             show_was_none = False
 
+        self.raster_datasets = tuple(
+            raster_dataset_to_background_map(x)
+            for x in gdfs
+            if isinstance(x, RasterDataset)
+        )
+        self.tiles  # += self.raster_datasets
+
         super().__init__(*gdfs, column=column, show=show, **kwargs)
 
         if self.gdfs is None:
@@ -253,7 +268,7 @@ def __repr__(self):
     def explore(
         self, column: str | None = None, center=None, size=None, **kwargs
     ) -> None:
-        if not any(len(gdf) for gdf in self._gdfs):
+        if not any(len(gdf) for gdf in self._gdfs) and not len(self.raster_datasets):
             warnings.warn("None of the GeoDataFrames have rows.")
             return
         if column:
@@ -827,6 +842,11 @@ def _tooltip_popup(type, fields, gdf, **kwds):
         return folium.GeoJsonPopup(fields, **kwds)
 
 
+def raster_dataset_to_background_map(dataset: RasterDataset):
+    crs = dataset.crs
+    bbox = dataset.bounds
+
+
 def _categorical_legend(m, title, categories, colors):
     """
     Add categorical legend to a map
diff --git a/src/sgis/maps/map.py b/src/sgis/maps/map.py
index b2e888d5..a771f5a8 100644
--- a/src/sgis/maps/map.py
+++ b/src/sgis/maps/map.py
@@ -2,6 +2,7 @@
 
 This module holds the Map class, which is the basis for the Explore class.
 """
+
 import warnings
 
 import matplotlib
@@ -23,6 +24,14 @@
 from ..helpers import get_object_name
 
 
+try:
+    from torchgeo.datasets.geo import RasterDataset
+except ImportError:
+
+    class RasterDataset:
+        """Placeholder"""
+
+
 # the geopandas._explore raises a deprication warning. Ignoring for now.
 warnings.filterwarnings(
     action="ignore", category=matplotlib.MatplotlibDeprecationWarning
@@ -83,6 +92,7 @@ def __init__(
         scheme: str = DEFAULT_SCHEME,
         **kwargs,
     ):
+
         gdfs, column, kwargs = self._separate_args(gdfs, column, kwargs)
 
         self._column = column
@@ -326,7 +336,9 @@ def as_dict(obj):
                 return obj
             raise TypeError
 
-        gdfs: tuple[GeoDataFrame] = ()
+        allowed_types = (GeoDataFrame, GeoSeries, Geometry, RasterDataset)
+
+        gdfs: tuple[GeoDataFrame | GeoSeries | Geometry | RasterDataset] = ()
         for arg in args:
             if isinstance(arg, str):
                 if column is None:
@@ -335,13 +347,13 @@ def as_dict(obj):
                     raise ValueError(
                         "Can specify at most one string as a positional argument."
                     )
-            elif isinstance(arg, (GeoDataFrame, GeoSeries, Geometry)):
+            elif isinstance(arg, allowed_types):
                 gdfs = gdfs + (arg,)
             elif isinstance(arg, dict) or hasattr(arg, "__dict__"):
                 # add dicts or classes with GeoDataFrames to kwargs
                 more_gdfs = {}
                 for key, value in as_dict(arg).items():
-                    if isinstance(value, (GeoDataFrame, GeoSeries, Geometry)):
+                    if isinstance(value, allowed_types):
                         more_gdfs[key] = value
                     elif isinstance(value, dict) or hasattr(value, "__dict__"):
                         try:
@@ -349,7 +361,7 @@ def as_dict(obj):
                             more_gdfs |= {
                                 k: v
                                 for k, v in value.items()
-                                if isinstance(v, (GeoDataFrame, GeoSeries, Geometry))
+                                if isinstance(v, allowed_types)
                             }
                         except Exception:
                             # no need to raise here
diff --git a/src/sgis/maps/maps.py b/src/sgis/maps/maps.py
index 4abd427e..eaae04f5 100644
--- a/src/sgis/maps/maps.py
+++ b/src/sgis/maps/maps.py
@@ -8,12 +8,11 @@
 """
 
 import inspect
-import warnings
 from numbers import Number
 from typing import Any
 
 from geopandas import GeoDataFrame, GeoSeries
-from pandas.api.types import is_list_like
+from pyproj import CRS
 from shapely import Geometry
 
 from ..geopandas_tools.conversion import to_gdf as to_gdf_func
@@ -25,24 +24,23 @@
 from .thematicmap import ThematicMap
 
 
+try:
+    from torchgeo.datasets.geo import RasterDataset
+except ImportError:
+
+    class RasterDataset:
+        """Placeholder"""
+
+
 def _get_location_mask(kwargs: dict, gdfs) -> tuple[GeoDataFrame | None, dict]:
     try:
         crs = get_common_crs(gdfs)
     except IndexError:
-        try:
-            crs = [x for x in kwargs.values() if hasattr(x, "crs")][0].crs
-        except IndexError:
-            crs = None
-        except Exception:
-            crs = set()
-            for x in kwargs.values():
-                try:
-                    crs.add(x.crs)
-                except Exception:
-                    pass
+        for x in kwargs.values():
             try:
-                crs = list(crs)[0]
-            except IndexError:
+                crs = CRS(x.crs) if hasattr(x, "crs") else CRS(x["crs"])
+                break
+            except Exception:
                 crs = None
 
     masks = {
@@ -215,7 +213,7 @@ def explore(
         **kwargs,
     )
 
-    if m.gdfs is None:
+    if m.gdfs is None and not len(m.raster_datasets):
         return
 
     if not kwargs.pop("explore", True):
@@ -311,7 +309,7 @@ def samplemap(
             smooth_factor=smooth_factor,
             **kwargs,
         )
-        if m.gdfs is None:
+        if m.gdfs is None and not len(m.raster_datasets):
             return
         if mask is not None:
             m._gdfs = [gdf.clip(mask) for gdf in m._gdfs]
@@ -420,7 +418,7 @@ def clipmap(
             smooth_factor=smooth_factor,
             **kwargs,
         )
-        if m.gdfs is None:
+        if m.gdfs is None and not len(m.raster_datasets):
             return
 
         m._gdfs = [gdf.clip(mask) for gdf in m._gdfs]
@@ -467,6 +465,8 @@ def as_dict(obj):
 
     frame = inspect.currentframe().f_back
 
+    allowed_types = (GeoDataFrame, GeoSeries, Geometry, RasterDataset)
+
     local_gdfs = {}
     while True:
         for name, value in frame.f_locals.items():
@@ -479,7 +479,7 @@ def as_dict(obj):
             if isinstance(value, dict) or hasattr(value, "__dict__"):
                 # add dicts or classes with GeoDataFrames to kwargs
                 for key, value in as_dict(value).items():
-                    if isinstance(value, (GeoDataFrame, GeoSeries, Geometry)):
+                    if isinstance(value, allowed_types):
                         gdf = clean_geoms(to_gdf_func(value))
                         if len(gdf):
                             local_gdfs[key] = gdf
@@ -487,7 +487,7 @@ def as_dict(obj):
                     elif isinstance(value, dict) or hasattr(value, "__dict__"):
                         try:
                             for k, v in value.items():
-                                if isinstance(v, (GeoDataFrame, GeoSeries, Geometry)):
+                                if isinstance(v, allowed_types):
                                     gdf = clean_geoms(to_gdf_func(v))
                                     if len(gdf):
                                         local_gdfs[k] = gdf

From 405128d8262b5769f9536ec9d082f9db245bf423 Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Mon, 15 Apr 2024 10:04:16 +0200
Subject: [PATCH 33/42] remove unreachable

---
 src/sgis/geopandas_tools/cleaning.py | 21 ---------------------
 1 file changed, 21 deletions(-)

diff --git a/src/sgis/geopandas_tools/cleaning.py b/src/sgis/geopandas_tools/cleaning.py
index eabf2c65..75c8a45e 100644
--- a/src/sgis/geopandas_tools/cleaning.py
+++ b/src/sgis/geopandas_tools/cleaning.py
@@ -765,27 +765,6 @@ def snap_polygons(
 
     return gdf  # .pipe(clean_clip, mask, geom_type="polygon")
 
-    if snap_to_nodes:
-        missing = clean_overlay(gdf_copy, gdf, how="difference")
-
-        missing, isolated = sfilter_split(missing, gdf)
-        isolated.geometry = isolated.buffer(PRECISION * 10)
-        gdf = eliminate_by_longest(
-            gdf, pd.concat([missing, isolated]), remove_isolated=False
-        )
-
-    missing = clean_overlay(mask, gdf, how="difference")
-
-    gdf = eliminate_by_longest(
-        gdf, missing.buffer(PRECISION * 10).to_frame("geometry"), remove_isolated=False
-    ).pipe(clean_clip, mask, geom_type="polygon")
-
-    gdf = update_geometries(
-        sort_small_first(close_small_holes(gdf, PRECISION)), geom_type="polygon"
-    )
-
-    return gdf  # .pipe(clean_clip, mask, geom_type="polygon")
-
 
 def _snap_to_anchors(
     points: GeoDataFrame,

From 5c7ee6234e29b4d52662d2f09ce8c24461183149 Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Mon, 15 Apr 2024 10:16:10 +0200
Subject: [PATCH 34/42] add parallel

---
 tests/test_overlay.py | 23 +++++++++++++++++++++++
 1 file changed, 23 insertions(+)

diff --git a/tests/test_overlay.py b/tests/test_overlay.py
index 291a3660..413f07a7 100644
--- a/tests/test_overlay.py
+++ b/tests/test_overlay.py
@@ -89,6 +89,29 @@ def test_overlay(points_oslo):
                     geom_type="polygon",
                 )
 
+            overlayed3 = sg.parallel_overlay(
+                p500, p1000, processes=4, max_rows_per_chunk=100, how=how
+            )
+            assert list(overlayed3.columns) == cols, (list(overlayed3.columns), cols)
+
+            if int(overlayed.area.sum()) != int(overlayed3.area.sum()):
+                raise ValueError(
+                    int(overlayed.area.sum()) != int(overlayed3.area.sum())
+                )
+
+            if len(overlayed) != len(overlayed3):
+                raise ValueError(how, len(overlayed), len(overlayed3))
+
+            # area is slightly different, but same area with 3 digits is good enough
+            for i in [1, 2, 3]:
+                if round(sum(overlayed.area), i) != round(sum(overlayed3.area), i):
+                    raise ValueError(
+                        how,
+                        i,
+                        round(sum(overlayed.area), i),
+                        round(sum(overlayed3.area), i),
+                    )
+
 
 def test_overlay_random(n=25):
     for _ in range(n):

From 252fd1bb699b9f87de46adefc99ed6af74920503 Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Mon, 15 Apr 2024 10:28:36 +0200
Subject: [PATCH 35/42] test snap, no asserts

---
 tests/test_cleaning.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/tests/test_cleaning.py b/tests/test_cleaning.py
index 8812c927..d95831d9 100644
--- a/tests/test_cleaning.py
+++ b/tests/test_cleaning.py
@@ -134,12 +134,12 @@ def test_clean_1144():
             ],
         )
 
-        continue
-
         snapped_to_mask = sg.snap_to_mask(
             sg.sort_large_first(df), tolerance, mask=kommune_utenhav
         )
 
+        continue
+
         gaps = sg.get_gaps(snapped_to_mask)
         double = sg.get_intersections(snapped_to_mask)
         missing = sg.clean_overlay(
@@ -411,13 +411,13 @@ def test_clean():
         assert (a := max(list(missing.area) + [0])) < 1e-4, a
         assert (a := max(list(gaps.area) + [0])) < 1e-4, a
 
-        continue
-
         snapped = sg.snap_polygons(
             df, tolerance, mask=mask.buffer(0.1, resolution=1, join_style=2)
         )
         assert sg.get_geom_type(snapped) == "polygon", sg.get_geom_type(snapped)
 
+        continue
+
         double = sg.get_intersections(snapped).loc[lambda x: ~x.buffer(-1e-9).is_empty]
         gaps = sg.get_gaps(snapped).loc[lambda x: ~x.buffer(-1e-9).is_empty]
         missing = get_missing(df, snapped)

From 643337ae8eedfbaa4fc97a5150bd3bb583cd53f6 Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Mon, 15 Apr 2024 14:10:21 +0200
Subject: [PATCH 36/42] test

---
 tests/test_cube.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/tests/test_cube.py b/tests/test_cube.py
index 98f313e3..28b4cabb 100644
--- a/tests/test_cube.py
+++ b/tests/test_cube.py
@@ -546,7 +546,7 @@ def _save_raster(file, src_path_sentinel):
         _save_raster(file, src_path_sentinel + "/MASKS")
 
 
-def not_test_torch():
+def test_torch():
 
     # from lightning.pytorch import Trainer
     from torch.utils.data import DataLoader
@@ -599,7 +599,7 @@ def regular_torch(cube):
     # write_sentinel()
 
     def test_cube():
-        not_test_torch()
+        test_torch()
         sss
         test_sentinel()
         not_test_gradient()

From 00b1c715355a5beccc0ecc70c1028049713e1b1c Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Mon, 15 Apr 2024 14:29:50 +0200
Subject: [PATCH 37/42] remove snap

---
 src/sgis/__init__.py                 |   4 -
 src/sgis/geopandas_tools/cleaning.py | 844 +--------------------------
 tests/test_cleaning.py               | 481 ---------------
 3 files changed, 20 insertions(+), 1309 deletions(-)

diff --git a/src/sgis/__init__.py b/src/sgis/__init__.py
index 76f9d798..7dbfedaf 100644
--- a/src/sgis/__init__.py
+++ b/src/sgis/__init__.py
@@ -32,12 +32,8 @@
     coverage_clean,
     remove_interior_slivers,
     remove_spikes,
-    simplify_and_update,
-    snap_polygons,
-    snap_to_mask,
     split_and_eliminate_by_longest,
     split_by_neighbors,
-    split_spiky_polygons,
 )
 from .geopandas_tools.conversion import (
     coordinate_array,
diff --git a/src/sgis/geopandas_tools/cleaning.py b/src/sgis/geopandas_tools/cleaning.py
index 75c8a45e..85337629 100644
--- a/src/sgis/geopandas_tools/cleaning.py
+++ b/src/sgis/geopandas_tools/cleaning.py
@@ -65,13 +65,6 @@
 warnings.simplefilter(action="ignore", category=RuntimeWarning)
 
 
-from ..maps.maps import explore, explore_locals
-
-
-# def explore(*args, **kwargs):
-#     pass
-
-
 PRECISION = 1e-3
 BUFFER_RES = 50
 
@@ -134,7 +127,7 @@ def coverage_clean(
     it might be a good idea to buffer the gaps, slivers and double surfaces
     before elimination to make sure the polygons are properly dissolved.
 
-    >>> def _small<_buffer(df):
+    >>> def _small_buffer(df):
     ...     df.geometry = df.buffer(0.001)
     ...     return df
     ...
@@ -409,20 +402,6 @@ def coverage_clean(
     return to_single_geom_type(cleaned, "polygon")
 
 
-def simplify_and_update(gdf, tolerance: float | int, **kwargs):
-    area_before = gdf.area
-    copied = gdf.copy()
-    copied.geometry = shapely.make_valid(
-        shapely.simplify(
-            copied.geometry.values,
-            tolerance,
-        )
-    )
-    diff_mapper = dict(enumerate((copied.area / area_before).values))
-    sorted_diffs = dict(reversed(sorted(diff_mapper.items(), key=lambda item: item[1])))
-    return update_geometries(copied.iloc[list(sorted_diffs)], **kwargs)
-
-
 def safe_simplify(gdf, tolerance: float | int, **kwargs):
     """Simplify only if the resulting area is no more than 1 percent larger.
 
@@ -685,717 +664,6 @@ def make_lines_between_points(
     return linestrings(coords.values, indices=coords.index)
 
 
-def explore_geosexception(e: GEOSException, *gdfs, logger=None):
-    from ..maps.maps import Explore, explore
-    from .conversion import to_gdf
-
-    pattern = r"(\d+\.\d+)\s+(\d+\.\d+)"
-
-    matches = re.findall(pattern, str(e))
-    coords_in_error_message = [(float(match[0]), float(match[1])) for match in matches]
-    exception_point = to_gdf(coords_in_error_message, crs=gdfs[0].crs)
-    if len(exception_point):
-        exception_point["wkt"] = exception_point.to_wkt()
-        if logger:
-            logger.error(
-                e, Explore(exception_point, *gdfs, mask=exception_point.buffer(100))
-            )
-        else:
-            explore(exception_point, *gdfs, mask=exception_point.buffer(100))
-    else:
-        if logger:
-            logger.error(e, Explore(*gdfs))
-        else:
-            explore(*gdfs)
-
-
-def snap_to_mask(
-    gdf: GeoDataFrame, tolerance: int | float, mask: GeoDataFrame | GeoSeries | Geometry
-):
-    return snap_polygons(
-        gdf,
-        mask=mask,
-        tolerance=tolerance,
-        snap_to_nodes=False,
-    )
-
-
-def snap_polygons(
-    gdf: GeoDataFrame,
-    tolerance: int | float,
-    mask: GeoDataFrame | GeoSeries | Geometry | None = None,
-    snap_to_nodes: bool = True,
-    **kwargs,
-):
-    if not len(gdf):
-        return gdf
-
-    geom_type = "polygon"
-
-    # gdf = safe_simplify(gdf, PRECISION)
-
-    gdf = (
-        clean_geoms(gdf)
-        .pipe(make_all_singlepart, ignore_index=True)
-        .pipe(to_single_geom_type, geom_type)
-    )
-
-    gdf = close_thin_holes(gdf, tolerance)
-
-    if mask is None:
-        mask: GeoDataFrame = close_all_holes(dissexp_by_cluster(gdf)).dissolve()
-    else:
-        try:
-            mask: GeoDataFrame = mask[["geometry"]]
-        except Exception:
-            mask: GeoDataFrame = to_geoseries(mask).to_frame("geometry")
-
-    gdf_copy = gdf.copy()
-
-    gdf.geometry = (
-        PolygonsAsRings(gdf.geometry.values)
-        .apply_numpy_func(
-            _snap_linearrings,
-            kwargs=dict(tolerance=tolerance, mask=mask, snap_to_nodes=snap_to_nodes),
-        )
-        .to_numpy()
-    )
-
-    gdf = to_single_geom_type(make_all_singlepart(clean_geoms(gdf)), geom_type)
-
-    return gdf  # .pipe(clean_clip, mask, geom_type="polygon")
-
-
-def _snap_to_anchors(
-    points: GeoDataFrame,
-    tolerance: int | float,
-    anchors: GeoDataFrame | None = None,
-    custom_func: Callable | None = None,
-    polygon_mapper: GeoSeries = None,
-    idx_start=0,
-) -> GeoDataFrame:
-    if not len(points):
-        try:
-            return points, anchors[["geometry"]]
-        except TypeError:
-            return points, points[["geometry"]]
-
-    assert points.index.is_unique
-
-    tree = STRtree(points.geometry.values)
-    left, right = tree.query(
-        points.geometry.values,
-        predicate="dwithin",
-        distance=tolerance,
-    )
-    indices = pd.Series(right, index=left, name="_right_idx")
-
-    geom_idx_left = indices.index.map(dict(enumerate(points["_geom_idx"])))
-    geom_idx_right = indices.map(dict(enumerate(points["_geom_idx"])))
-
-    left_on_top = indices.loc[geom_idx_left < geom_idx_right].sort_index()
-
-    # keep only indices from left if they have not already appeared in right
-    # these shouldn't be anchors, but instead be snapped
-    new_indices = []
-    values = []
-    right_indices = set()
-    for left, right in left_on_top.items():
-        if left not in right_indices:
-            new_indices.append(left)
-            values.append(right)
-            right_indices.add(right)
-
-    snap_indices = pd.Series(values, index=new_indices)
-
-    if custom_func:
-        snap_indices = custom_func(snap_indices)
-
-    new_anchors = points.loc[
-        points.index.isin(snap_indices.index), ["geometry", "_geom_idx"]
-    ]
-    new_anchors["_cluster"] = get_cluster_mapper(new_anchors.buffer(0.1))
-
-    assert new_anchors["_geom_idx"].notna().all()
-
-    no_longer_anchors: pd.Index = new_anchors.loc[
-        lambda x: (x["_cluster"].duplicated())  # & (x["_geom_idx"] >= idx_start)
-    ].index
-    new_anchors = new_anchors.loc[lambda x: ~x.index.isin(no_longer_anchors)]
-
-    if anchors is not None:
-        anchors = pd.concat([anchors, new_anchors]).loc[
-            lambda x: ~x.geometry.duplicated()
-        ]
-    else:
-        anchors = new_anchors
-        anchors["_was_anchor"] = 0
-
-    should_be_snapped = (points.index.isin(snap_indices.values)) | (
-        points.index.isin(no_longer_anchors)
-    )
-    if anchors is not None:
-        should_be_snapped |= points.index.isin(
-            sfilter(points, anchors.buffer(tolerance)).index
-        )
-
-    to_be_snapped = points.loc[should_be_snapped].rename(
-        columns={"_geom_idx": "_geom_idx_left"}, errors="raise"
-    )
-
-    anchors["_right_geom"] = anchors.geometry
-
-    snapped = (
-        to_be_snapped.sjoin_nearest(anchors, max_distance=tolerance)
-        .sort_values("index_right")  # ["_right_geom"]
-        .loc[lambda x: ~x.index.duplicated()]
-    )
-
-    points.loc[snapped.index, "geometry"] = snapped
-
-    return points, anchors[["geometry"]]
-
-
-def _snap_linearrings(
-    geoms: NDArray[LinearRing],
-    tolerance: int | float,
-    mask: GeoDataFrame | None = None,
-    snap_to_nodes: bool = True,
-    gaps=None,
-):
-    if not len(geoms):
-        return geoms
-
-    if mask is None:
-        idx_start = 0
-    else:
-        mask: GeoSeries = make_all_singlepart(mask).geometry
-        mask_nodes = GeoDataFrame(
-            {
-                "geometry": extract_unique_points(mask.geometry),
-                "_geom_idx": range(len(mask)),
-            }
-        ).explode(ignore_index=True)
-
-        idx_start = len(mask)
-
-    gdf = GeoDataFrame(
-        {"geometry": geoms, "_geom_idx": np.arange(idx_start, len(geoms) + idx_start)}
-    )
-
-    as_polygons = GeoDataFrame(
-        {
-            "geometry": polygons(geoms),
-            "_geom_idx": np.arange(idx_start, len(geoms) + idx_start),
-        }
-    )
-
-    relevant_mask_nodes = sfilter(
-        mask_nodes, as_polygons.buffer(PRECISION + tolerance)
-    ).rename(columns={"_geom_idx": "_geom_idx_left"}, errors="raise")
-
-    relevant_mask_nodes["rgeom"] = relevant_mask_nodes.geometry
-
-    is_thin = as_polygons.buffer(-tolerance / 2).is_empty
-
-    as_polygons.geometry = as_polygons.geometry.buffer(-PRECISION)
-
-    polygon_mapper: GeoSeries = as_polygons.set_index("_geom_idx")["geometry"]
-
-    gdf["_is_thin"] = is_thin
-
-    thin = is_thin[lambda x: x == True]
-
-    thin.loc[:] = None
-    thin.index = thin.index.map(gdf["_geom_idx"])
-
-    points_from_thin = (
-        extract_unique_points(gdf.loc[is_thin, "geometry"])
-        .to_frame("geometry")
-        .explode(ignore_index=True)
-        .pipe(sfilter_inverse, gdf.buffer(PRECISION))
-    )
-
-    gdf = gdf.loc[is_thin == False]
-    as_polygons = as_polygons.loc[is_thin == False]
-
-    points: GeoDataFrame = gdf.assign(
-        geometry=lambda x: extract_unique_points(x.geometry.values)
-    ).explode(ignore_index=True)
-
-    # step 1: add vertices nearest to mask nodes
-
-    points = _add_midpoints_to_segments(points, relevant_mask_nodes, tolerance)
-
-    # step 2: snap to mask nodes
-    assert points.index.is_unique
-
-    points_by_mask_nodes = sfilter(
-        # points.loc[lambda x: x["_geom_idx"] >= idx_start], mask_nodes.buffer(tolerance)
-        points.loc[lambda x: x["_geom_idx"] >= idx_start],
-        mask.buffer(tolerance),
-    )
-
-    relevant_mask_nodes = sfilter(
-        mask_nodes,
-        points_by_mask_nodes.buffer(tolerance),
-        predicate="within",
-    )
-    # explore(
-    #     mask,
-    #     gdf,
-    #     relevant_mask_nodes,
-    #     points_by_mask_nodes,
-    #     segments,
-    #     points=points.set_crs(25833),
-    #     mask=to_gdf([5.36878551, 59.00852282], 4326).to_crs(25833).buffer(100),
-    # )
-
-    if len(relevant_mask_nodes):
-        relevant_mask_nodes["_right_geom"] = relevant_mask_nodes.geometry
-        snapped = (
-            points_by_mask_nodes.sjoin_nearest(
-                relevant_mask_nodes.rename(
-                    columns={"_geom_idx": "_geom_idx_left"}, errors="raise"
-                ),
-                # max_distance=tolerance,
-                distance_col="_dist",
-            ).sort_values("_dist")
-            # .drop_duplicates("index_right")
-        )
-
-        # only_nearest_polys = snapped.drop_duplicates("index_right")
-        # snapped["_is_nearest"] = snapped["_geom_idx"] == only_nearest_polys["_geom_idx"]
-        # snapped = snapped.loc[lambda x: x["_is_nearest"]]
-        #
-
-        lines_between_mask_and_node = shapely.shortest_line(
-            snapped.geometry.values, snapped["_right_geom"].values
-        )
-        if 0:
-            snapped_too_far = (
-                GeoDataFrame(
-                    {
-                        "geometry": lines_between_mask_and_node,
-                        "_geom_idx_left": snapped["_geom_idx"].values,
-                    },
-                    index=range(len(snapped)),
-                )
-                .sjoin(as_polygons)
-                .loc[lambda x: x["_geom_idx_left"] != x["_geom_idx"]]
-                .loc[lambda x: ~x.index.duplicated()]
-            )
-            not_too_far = pd.Index(range(len(snapped))).difference(
-                snapped_too_far.index
-            )
-            lines_between_mask_and_node = lines_between_mask_and_node[not_too_far]
-            snapmapper = snapped["_right_geom"].iloc[not_too_far]
-        else:
-            snapmapper = snapped["_right_geom"]
-
-        try:
-            points.loc[snapmapper.index, "geometry"] = snapmapper
-        except Exception:
-            points.loc[snapmapper.index, "geometry"] = snapmapper.loc[
-                lambda x: ~x.index.duplicated()
-            ]
-
-        explore(
-            points,
-            points_by_mask_nodes,
-            mask_nodes,
-            snapped,
-            snapmapper=to_gdf(snapmapper, 25833),
-        )
-        explore(
-            points,
-            mask_nodes,
-            points_by_mask_nodes=points_by_mask_nodes.loc[lambda x: x._geom_idx == 114],
-            snapped=snapped.loc[lambda x: x._geom_idx == 114],
-            snapmapper=to_gdf(snapmapper, 25833),
-        )
-        explore(
-            points,
-            mask_nodes,
-            points_by_mask_nodes=points_by_mask_nodes.loc[lambda x: x._geom_idx == 25],
-            snapped=snapped.loc[lambda x: x._geom_idx == 25],
-            snapmapper=to_gdf(snapmapper, 25833),
-        )
-
-    if snap_to_nodes:
-        snapped, anchors = _snap_to_anchors(
-            points,
-            tolerance,
-            anchors=mask_nodes,
-            idx_start=idx_start,
-            polygon_mapper=polygon_mapper,
-            # polygon_mapper=gdf.set_index("_geom_idx")["geometry"],
-        )  # anchors)
-    else:
-        snapped = points
-
-    snapped = snapped.sort_index()
-
-    # # remove duplicates
-    # snapped = pd.concat(
-    #     snapped.loc[lambda x: x["_geom_idx"] == i].loc[lambda x: ~x.duplicated()]
-    #     for i in snapped.loc[
-    #         lambda x: (x["_geom_idx"] >= idx_start), "_geom_idx"
-    #     ].unique()
-    # )
-
-    assert (snapped["_geom_idx"] >= idx_start).all()
-
-    as_rings = (
-        snapped.sort_index()
-        .set_index("_geom_idx")
-        # .pipe(_remove_legit_spikes)
-        .loc[lambda x: x.groupby(level=0).size() > 2]
-        .groupby(level=0)["geometry"]
-        .agg(LinearRing)
-    )
-
-    as_snapped_polygons = GeoDataFrame(
-        {"geometry": polygons(as_rings.values), "_geom_idx": as_rings.index}
-    )
-
-    # explore(
-    #     mask,
-    #     gdf[lambda x: x["_geom_idx"] == 75],
-    #     # anchors,
-    #     snapped[lambda x: x["_geom_idx"] == 75],
-    #     as_snapped_polygons,
-    #     points=points.set_crs(25833)[lambda x: x["_geom_idx"] == 75],
-    #     mask=to_gdf([5.36878551, 59.00852282], 4326).to_crs(25833).buffer(100),
-    # )
-
-    explore(
-        mask,
-        gdf,
-        # anchors,
-        snapped,
-        as_snapped_polygons,
-        upd=close_small_holes(
-            update_geometries(sort_large_first(as_snapped_polygons)), tolerance
-        ),
-        dup=get_intersections(as_snapped_polygons),
-        points=points.set_crs(25833),
-        # mask=to_gdf([5.36878551, 59.00852282], 4326).to_crs(25833).buffer(300),
-    )
-
-    as_snapped_polygons = close_small_holes(
-        update_geometries(sort_large_first(as_snapped_polygons)), tolerance
-    )
-
-    if not snap_to_nodes:
-
-        as_rings = (
-            GeoDataFrame(
-                {
-                    "geometry": extract_unique_points(
-                        as_snapped_polygons.geometry
-                    ).values,
-                },
-                index=as_snapped_polygons["_geom_idx"],
-            )
-            .explode(index_parts=False)
-            .loc[lambda x: x.groupby(level=0).size() > 2]
-            .groupby(level=0)["geometry"]
-            .agg(LinearRing)
-        )
-
-        missing = gdf.set_index("_geom_idx")["geometry"].loc[
-            # lambda x: (~x.index.isin(as_rings.index))
-            lambda x: (~x.index.isin(as_rings.index.union(thin.index)))
-            & (x.index >= idx_start)
-        ]
-        missing.loc[:] = None
-
-        # return pd.concat([as_rings, missing]).sort_index()
-        return pd.concat([as_rings, thin, missing]).sort_index()
-
-    if 1:
-        missing_polygons = clean_overlay(
-            as_polygons, as_snapped_polygons, how="difference", geom_type="polygon"
-        )
-
-        as_snapped_polygons, slivers = split_out_slivers(as_snapped_polygons, tolerance)
-        # slivers = as_snapped_polygons.loc[
-        #     lambda x: x.buffer(-tolerance / 2).is_empty
-        # ]
-        # as_snapped_polygons = as_snapped_polygons.loc[
-        #     lambda x: ~x["_geom_idx"].isin(slivers["_geom_idx"])
-        # ]
-
-        # explore(
-        #     mask,
-        #     gdf,
-        #     slivers,
-        #     missing_polygons,
-        #     as_snapped_polygons=as_snapped_polygons.set_crs(25833),
-        # )
-
-        as_snapped_polygons = eliminate_by_longest(
-            as_snapped_polygons, pd.concat([missing_polygons, slivers])
-        )
-        # as_snapped_polygons = pd.concat([as_snapped_polygons, missing_polygons])
-
-        # try:
-        #     only_one = as_snapped_polygons.groupby("_geom_idx").transform("size") == 1
-        #     one_hit = as_snapped_polygons[only_one]
-        #     many_hits = as_snapped_polygons[~only_one]
-        #     many_hits = (
-        #         dissexp(
-        #             many_hits,
-        #             by="_geom_idx",
-        #             aggfunc="first",
-        #             dropna=False,
-        #             # grid_size=grid_size,
-        #             # n_jobs=n_jobs,
-        #         )
-        #         .sort_index()
-        #         .reset_index(drop=False)
-        #     )
-        #     as_snapped_polygons = pd.concat([many_hits, one_hit])
-        # except IndexError:
-        #     pass
-
-        # as_snapped_polygons, slivers = split_out_slivers(as_snapped_polygons, tolerance)
-        # as_snapped_polygons = eliminate_by_longest(as_snapped_polygons, slivers)
-
-    missing_mask_nodes = sfilter_inverse(
-        mask_nodes, as_snapped_polygons.buffer(PRECISION)
-    ).pipe(sfilter, as_snapped_polygons.buffer(PRECISION + tolerance))
-
-    print(len(missing_mask_nodes))
-
-    explore(
-        mask,
-        gdf,
-        # slivers,
-        # anchors,
-        missing_mask_nodes,
-        snapped,
-        as_snapped_polygons,
-        points=points.set_crs(25833),
-        MultiPolygon=to_gdf(
-            as_snapped_polygons[lambda x: x.geom_type == "MultiPolygon"], 25833
-        ),
-    )
-
-    as_snapped_polygons = as_snapped_polygons.explode(ignore_index=True)
-
-    snapped = (
-        GeoDataFrame(
-            {
-                "geometry": extract_unique_points(as_snapped_polygons.geometry.values),
-                "_geom_idx": as_snapped_polygons["_geom_idx"].values,
-            }
-        )
-        # .set_index("_geom_idx").geometry)
-        .explode(index_parts=False)
-    )
-
-    segments = points_to_line_segments(snapped)  # .set_index("_geom_idx"))
-    segments["_geom_idx"] = segments["_geom_idx"].values
-    segments["_new_geom_idx"] = segments.index
-    multipolygon_mapper = dict(segments["_new_geom_idx"].items())
-    assert len(snapped) == len(segments)
-    segments.index = range(len(segments))  # snapped.index
-    snapped.index = range(len(snapped))  # snapped.index
-
-    thin_gaps = get_gaps(as_snapped_polygons, include_interiors=True).loc[
-        lambda x: x.buffer(-tolerance / 2).is_empty
-    ]
-    thin_gaps.geometry = thin_gaps.buffer(-PRECISION).buffer(PRECISION)
-
-    segs_by_gaps = sfilter(
-        segments,
-        pd.concat([thin_gaps, slivers]).buffer(PRECISION),
-        # thin_gaps.buffer(PRECISION),
-    )
-    # gap_nodes = pd.concat(
-    #     [
-    #         missing_mask_nodes,
-    #         extract_unique_points(thin_gaps.geometry).to_frame("geometry"),
-    #     ]
-    # )
-
-    # segs_by_gaps = _add_midpoints_to_segments2(
-    #     segs_by_gaps, points=gap_nodes, tolerance=tolerance
-    # )
-
-    explore(
-        # missing_mask_polygons,
-        segs_by_gaps.pipe(buff, 0.08),
-        segments=segments.pipe(buff, 0.08),
-        snapped111=snapped.set_crs(25833).pipe(buff, 0.08),
-    )
-
-    segs_by_gaps.geometry = segmentize(segs_by_gaps.geometry, tolerance)
-    segs_by_gaps.geometry = extract_unique_points(segs_by_gaps.geometry)
-    assert segs_by_gaps.index.is_unique
-    assert snapped.index.is_unique
-
-    snapped = (
-        pd.concat(
-            [snapped.loc[lambda x: ~x.index.isin(segs_by_gaps.index)], segs_by_gaps]
-        )
-        .sort_index()
-        .explode(ignore_index=True)
-    )
-
-    # snapped = pd.concat(
-    #     snapped.loc[lambda x: x["_geom_idx"] == i].loc[lambda x: ~x.duplicated()]
-    #     for i in snapped["_geom_idx"].unique()
-    # )
-
-    explore(
-        # missing_mask_polygons,
-        snapped,
-        missing_mask_nodes,
-        thin_gaps,
-        as_snapped_polygons2=as_snapped_polygons,
-        snapped2=snapped,
-        points2=points.set_crs(25833),
-    )
-
-    snapped, _ = _snap_to_anchors(
-        snapped,
-        tolerance,
-        anchors=mask_nodes,
-        idx_start=idx_start,
-        polygon_mapper=polygon_mapper,
-    )
-
-    print("snapped")
-    print(snapped)
-
-    as_rings = (
-        snapped.sort_index()  # .loc[lambda x: (x["_geom_idx"] >= idx_start)]
-        .set_index("_new_geom_idx")
-        # .pipe(_remove_legit_spikes)
-        .loc[lambda x: x.groupby(level=0).size() > 2]
-        .groupby(level=0)["geometry"]
-        .agg(LinearRing)
-    )
-
-    as_rings.index = as_rings.index.map(multipolygon_mapper)
-    print("as_rings")
-    print(as_rings)
-    as_rings = as_rings.groupby(level=0).agg(unary_union)
-
-    # as_rings = (
-    #     snapped.sort_index()  # .loc[lambda x: (x["_geom_idx"] >= idx_start)]
-    #     .set_index("_geom_idx")
-    #     # .pipe(_remove_legit_spikes)
-    #     .loc[lambda x: x.groupby(level=0).size() > 2]
-    #     .groupby(level=0)["geometry"]
-    #     .agg(LinearRing)
-    # )
-
-    slivers = slivers.set_index("_geom_idx")
-    slivers.geometry.loc[:] = None
-    thin = pd.concat([thin, slivers.geometry]).loc[
-        lambda x: (~x.index.duplicated()) & (~x.index.isin(as_rings.index))
-    ]
-
-    missing = gdf.set_index("_geom_idx")["geometry"].loc[
-        lambda x: (~x.index.isin(as_rings.index.union(thin.index)))
-        & (x.index >= idx_start)
-    ]
-    missing.loc[:] = None
-
-    return pd.concat([as_rings, thin, missing]).sort_index()
-
-
-def _add_midpoints_to_segments(points, relevant_mask_nodes, tolerance):
-    while len(relevant_mask_nodes):
-        segments = points_to_line_segments(points.set_index("_geom_idx"))
-        segments["_geom_idx"] = segments.index
-        segments.index = points.index
-
-        joined = segments.sjoin_nearest(
-            relevant_mask_nodes,
-            max_distance=tolerance,
-        ).loc[lambda x: ~x.index.duplicated()]
-        boundaries_groupby = joined.boundary.explode(index_parts=False).groupby(level=0)
-
-        lines_between_mask_and_edge = shapely.shortest_line(
-            joined.geometry.values, joined["rgeom"].values
-        )
-
-        if 0:
-
-            snapped_too_far = (
-                GeoDataFrame(
-                    {
-                        "geometry": lines_between_mask_and_edge,
-                        "_geom_idx_left": joined["_geom_idx"].values,
-                    },
-                    index=range(len(joined)),
-                )
-                .sjoin(as_polygons)
-                .loc[lambda x: x["_geom_idx_left"] != x["_geom_idx"]]
-            )
-            not_too_far = pd.Index(range(len(joined))).difference(snapped_too_far.index)
-            joined = joined.iloc[not_too_far]
-
-            lines_between_mask_and_edge = lines_between_mask_and_edge[not_too_far]
-            midpoints = shapely.get_point(lines_between_mask_and_edge, 0)
-            # midpoints = shapely.get_point(lines_between_mask_and_edge, 1)
-
-        midpoints = shapely.get_point(lines_between_mask_and_edge, 0)
-
-        with_new_midpoints = pd.concat(
-            [
-                GeoSeries(boundaries_groupby.nth(0)),
-                GeoSeries(midpoints, index=joined.index),
-                GeoSeries(boundaries_groupby.nth(-1)),
-            ]
-        )
-
-        with_new_midpoints = (
-            with_new_midpoints.loc[lambda x: x.groupby(level=0).transform("size") == 3]
-            .groupby(level=0)
-            .agg(lambda x: LineString(x.values))
-        )
-
-        segments.loc[with_new_midpoints.index, "geometry"] = with_new_midpoints
-
-        segments.geometry = extract_unique_points(segments.geometry)
-        points = segments.explode(ignore_index=True)
-
-        relevant_mask_nodes = relevant_mask_nodes.loc[
-            lambda x: ~x.index.isin(joined["index_right"])
-        ]
-
-    return points
-
-
-def _remove_legit_spikes(df):
-    """Remove points where the next and previous points are the same.
-
-    The lines these points make are as spiky as they come,
-    hence the term "legit spikes".
-    """
-    df["next"] = df.groupby(level=0)["geometry"].shift(-1)
-    df["prev"] = df.groupby(level=0)["geometry"].shift(1)
-
-    first_points = df.loc[lambda x: ~x.index.duplicated(keep="first"), "geometry"]
-    is_last_point = df["next"].isna()
-    df.loc[is_last_point, "next"] = first_points
-
-    last_points = df.loc[lambda x: ~x.index.duplicated(keep="last"), "geometry"]
-    is_first_point = df["prev"].isna()
-    df.loc[is_first_point, "prev"] = last_points
-
-    assert df["next"].notna().all()
-    assert df["prev"].notna().all()
-
-    return df.loc[lambda x: x["next"] != x["prev"]]
-
-
 def get_line_segments(lines) -> GeoDataFrame:
     assert lines.index.is_unique
     if isinstance(lines, GeoDataFrame):
@@ -1466,97 +734,25 @@ def points_to_line_segments(points: GeoDataFrame) -> GeoDataFrame:
     )
 
 
-def split_spiky_polygons(
-    gdf: GeoDataFrame, tolerance: int | float, grid_sizes: tuple[None | int] = (None,)
-) -> GeoDataFrame:
-    if not len(gdf):
-        return gdf
-
-    gdf = to_single_geom_type(make_all_singlepart(gdf), "polygon")
-
-    if not gdf.index.is_unique:
-        gdf = gdf.reset_index(drop=True)
-
-    # remove both inwards and outwards spikes
-    polygons_without_spikes = (
-        gdf.buffer(-tolerance / 2, join_style=2)
-        .buffer(tolerance, join_style=2)
-        .buffer(-tolerance / 2, join_style=2)
-    )
-
-    donuts_around_polygons = to_lines(
-        polygons_without_spikes.to_frame("geometry")
-    ).pipe(buff, 1e-3, copy=False)
-
-    # donuts_around_polygons["_poly_idx"] = donuts_around_polygons.index
-
-    def _remove_spikes(df):
-        df = df.to_frame("geometry")
-        # df = df.reset_index(drop=True)
-        df["_poly_idx"] = df.index
-        df["_ring_idx"] = range(len(df))
-
-        points = df.copy()
-        points.geometry = extract_unique_points(points.geometry)
-        points = points.explode(index_parts=False).explode(index_parts=False)
-        points["_idx"] = range(len(points))
-
-        # keep only matches from same polygon
-        not_spikes = points.sjoin(donuts_around_polygons).loc[
-            lambda x: x["_poly_idx"] == x["index_right"]
-        ]
-        can_be_polygons = not_spikes.iloc[
-            (not_spikes.groupby("_ring_idx").transform("size") >= 3).values
-        ]
-
-        without_spikes = (
-            can_be_polygons.sort_values("_idx")
-            .groupby("_ring_idx")["geometry"]
-            .agg(LinearRing)
-        )
-
-        missing = df.loc[
-            ~df["_ring_idx"].isin(without_spikes.index), df._geometry_column_name
-        ]
-        return pd.concat(
-            [without_spikes, missing]
-        ).sort_index()  # .to_frame("geometry")
-
-    without_spikes = GeoDataFrame(
-        {
-            "geometry": PolygonsAsRings(gdf.geometry)
-            .apply_geoseries_func(_remove_spikes)
-            .to_numpy()
-        },
-        crs=gdf.crs,
-    ).pipe(to_single_geom_type, "polygon")
-    without_spikes.index = gdf.index
-
-    is_thin = without_spikes.buffer(-tolerance / 2).is_empty
-    without_spikes = pd.concat(
-        [
-            split_by_neighbors(
-                without_spikes[is_thin], without_spikes, tolerance=tolerance
-            ),
-            without_spikes[~is_thin],
-        ]
-    )
+def explore_geosexception(e: GEOSException, *gdfs, logger=None):
+    from ..maps.maps import Explore, explore
+    from .conversion import to_gdf
 
-    for i, grid_size in enumerate(grid_sizes):
-        try:
-            without_spikes = update_geometries(
-                sort_small_first(without_spikes), geom_type="polygon"
-            )
-            break
-        except GEOSException as e:
-            if i == len(grid_sizes) - 1:
-                raise e
+    pattern = r"(\d+\.\d+)\s+(\d+\.\d+)"
 
-    for i, grid_size in enumerate(grid_sizes):
-        try:
-            return clean_overlay(
-                gdf, without_spikes, how="identity", grid_size=grid_size
+    matches = re.findall(pattern, str(e))
+    coords_in_error_message = [(float(match[0]), float(match[1])) for match in matches]
+    exception_point = to_gdf(coords_in_error_message, crs=gdfs[0].crs)
+    if len(exception_point):
+        exception_point["wkt"] = exception_point.to_wkt()
+        if logger:
+            logger.error(
+                e, Explore(exception_point, *gdfs, mask=exception_point.buffer(100))
             )
-        except GEOSException as e:
-            if i == len(grid_sizes) - 1:
-                raise e
+        else:
+            explore(exception_point, *gdfs, mask=exception_point.buffer(100))
+    else:
+        if logger:
+            logger.error(e, Explore(*gdfs))
+        else:
+            explore(*gdfs)
diff --git a/tests/test_cleaning.py b/tests/test_cleaning.py
index d95831d9..8687ae5d 100644
--- a/tests/test_cleaning.py
+++ b/tests/test_cleaning.py
@@ -134,223 +134,6 @@ def test_clean_1144():
             ],
         )
 
-        snapped_to_mask = sg.snap_to_mask(
-            sg.sort_large_first(df), tolerance, mask=kommune_utenhav
-        )
-
-        continue
-
-        gaps = sg.get_gaps(snapped_to_mask)
-        double = sg.get_intersections(snapped_to_mask)
-        missing = sg.clean_overlay(
-            sg.clean_clip(df, bbox.buffer(-tolerance * 1.1)),
-            snapped_to_mask,
-            how="difference",
-            geom_type="polygon",
-        )
-
-        if missing.area.sum() > 1:
-            sg.explore(
-                missing,
-                gaps,
-                double,
-                snapped_to_mask,
-                df,
-                kommune_utenhav,
-            )
-
-        assert double.area.sum() < 1e-4, double.area.sum()
-        assert missing.area.sum() < 1e-4, missing.area.sum()
-        assert gaps.area.sum() < 1e-4, gaps.area.sum()
-
-        # assert thick_df_indices.isin(snapped_to_mask["df_idx"]).all(), sg.explore(
-        #     df,
-        #     snapped_to_mask,
-        #     missing_polygons=df[
-        #         (df["df_idx"].isin(thick_df_indices))
-        #         & (~df["df_idx"].isin(snapped_to_mask["df_idx"]))
-        #     ],
-        # )
-
-        print(
-            "snapped_to_mask",
-            gaps.area.sum(),
-            double.area.sum(),
-            missing.area.sum(),
-        )
-
-        snapped = sg.snap_polygons(
-            sg.sort_large_first(df), tolerance, mask=kommune_utenhav
-        )
-
-        gaps = sg.get_gaps(snapped)
-        double = sg.get_intersections(snapped)
-
-        missing = get_missing(sg.clean_clip(df, bbox.buffer(-tolerance * 1.1)), snapped)
-
-        sg.explore(
-            missing,
-            gaps,
-            double,
-            snapped,
-            df,
-            kommune_utenhav,
-        )
-
-        # assert thick_df_indices.isin(snapped["df_idx"]).all(), sg.explore(
-        #     df,
-        #     snapped_to_mask,
-        #     missing_polygons=df[
-        #         (df["df_idx"].isin(thick_df_indices))
-        #         & (~df["df_idx"].isin(snapped["df_idx"]))
-        #     ],
-        # )
-        assert double.area.sum() < 1e-4, double.area.sum()
-        assert missing.area.sum() < 1e-4, missing.area.sum()
-        assert gaps.area.sum() < 1e-4, gaps.area.sum()
-
-        print(
-            "snapped",
-            gaps.area.sum(),
-            double.area.sum(),
-            missing.area.sum(),
-        )
-
-        cleaned_and_snapped_to_mask = sg.snap_to_mask(
-            cleaned, tolerance, mask=kommune_utenhav
-        )
-
-        # cleaned = sg.coverage_clean(
-        #     sg.sort_large_first(df), tolerance, mask=kommune_utenhav
-        # ).pipe(sg.snap_polygons, 0.1, mask=kommune_utenhav)
-
-        # allow edge cases
-        cleaned_and_snapped_to_mask = sg.clean_clip(
-            cleaned_and_snapped_to_mask, bbox.buffer(-tolerance * 1.1)
-        )
-
-        gaps = sg.get_gaps(cleaned_and_snapped_to_mask)
-        double = sg.get_intersections(cleaned_and_snapped_to_mask)
-        missing = get_missing(
-            sg.clean_clip(df, bbox.buffer(-tolerance * 1.1)),
-            cleaned_and_snapped_to_mask,
-        )
-
-        print(
-            "cleaned_and_snapped_to_mask",
-            gaps.area.sum(),
-            double.area.sum(),
-            missing.area.sum(),
-        )
-
-        sg.explore(
-            df,  # =cleaned.assign(wkt=lambda x: x.geometry.to_wkt()),
-            snapped_to_mask,  # =cleaned.assign(wkt=lambda x: x.geometry.to_wkt()),
-            cleaned,  # =cleaned.assign(wkt=lambda x: x.geometry.to_wkt()),
-            double,  # =double.assign(wkt=lambda x: x.to_wkt()),
-            gaps,  # =gaps.assign(wkt=lambda x: x.to_wkt()),
-            missing,
-            kommune_utenhav,
-            thick_missing=missing[~missing.buffer(-0.01).is_empty].assign(
-                area=lambda x: x.area
-            ),
-        )
-
-        assert list(sorted(cleaned.columns)) == cols, list(sorted(cleaned.columns))
-        assert thick_df_indices.isin(
-            cleaned_and_snapped_to_mask["df_idx"]
-        ).all(), sg.explore(
-            df,
-            snapped_to_mask,
-            missing_polygons=df[
-                (df["df_idx"].isin(thick_df_indices))
-                & (~df["df_idx"].isin(cleaned_and_snapped_to_mask["df_idx"]))
-            ],
-        )
-
-        assert double.area.sum() < 1e-4, double.area.sum()
-        assert gaps.area.sum() < 1e-3, (
-            gaps.area.sum(),
-            gaps.area.max(),
-            gaps.area,
-            gaps,
-        )
-        assert missing.area.sum() < 1e-3 or (missing.area.sum() + 1e-10) < 1e-3, (
-            missing.area.sum(),
-            missing.area.sort_values(),
-        )
-
-        # assert int(cleaned.area.sum()) == 154240, (
-        #     cleaned.area.sum(),
-        #     f"tolerance: {tolerance}",
-        # )
-
-        assert sg.get_geom_type(cleaned) == "polygon", sg.get_geom_type(cleaned)
-
-        print("cleaning cleaned")
-        cleaned_and_snapped_to_mask = sg.snap_polygons(
-            cleaned, tolerance, mask=kommune_utenhav
-        )
-
-        gaps = sg.get_gaps(cleaned_and_snapped_to_mask)
-        double = sg.get_intersections(cleaned_and_snapped_to_mask)
-        missing = get_missing(sg.clean_clip(df, bbox.buffer(-tolerance * 1.1)), cleaned)
-
-        sg.explore(
-            df,  # =cleaned.assign(wkt=lambda x: x.geometry.to_wkt()),
-            cleaned,  # =cleaned.assign(wkt=lambda x: x.geometry.to_wkt()),
-            double,  # =double.assign(wkt=lambda x: x.to_wkt()),
-            gaps,  # =gaps.assign(wkt=lambda x: x.to_wkt()),
-            missing,
-            kommune_utenhav,
-            thick_missing=missing[~missing.buffer(-0.01).is_empty].assign(
-                area=lambda x: x.area
-            ),
-            # mask=sg.to_gdf([5.36750884, 59.00830496], 4326).to_crs(25833).buffer(10),
-            # browser=True,
-            max_zoom=50,
-        )
-
-        assert (
-            list(sorted(cleaned_and_snapped_to_mask.columns)) == cols
-        ), cleaned_and_snapped_to_mask.columns
-
-        assert double.area.sum() < 1e-3, double.area.sum()
-        assert gaps.area.sum() < 1e-3, gaps.area.sum()
-        assert missing.area.sum() < 1e-3 or (missing.area.sum() + 1e-10), (
-            missing.area.sum(),
-            missing.area.sort_values(),
-        )
-
-        # assert int(cleaned_and_snapped_to_mask.area.sum()) == 154240, (
-        #     cleaned_and_snapped_to_mask.area.sum(),
-        #     f"tolerance: {tolerance}",
-        # )
-
-        assert (
-            sg.get_geom_type(cleaned_and_snapped_to_mask) == "polygon"
-        ), sg.get_geom_type(cleaned_and_snapped_to_mask)
-
-        # cleaned = sg.coverage_clean(df, tolerance)
-
-        # gaps = sg.get_gaps(cleaned)
-        # double = sg.get_intersections(cleaned)
-        # missing = sg.clean_overlay(df, cleaned, how="difference", geom_type="polygon")
-
-        # assert list(sorted(cleaned.columns)) == cols, list(sorted(cleaned.columns))
-
-        # assert double.area.sum() < 1e-4, double.area.sum()
-        # assert gaps.area.sum() < 1e-3, (
-        #     gaps.area.sum(),
-        #     gaps.area.max(),
-        #     gaps.area,
-        #     gaps,
-        # )
-        # assert missing.area.sum() < 1e-3, (
-        #     missing.area.sum(),
-        #     missing.area.sort_values(),
-        # )
-
 
 def get_missing(df, other):
     return (
@@ -386,10 +169,6 @@ def test_clean():
     for tolerance in [5, 10]:
         print("tolerance:", tolerance)
 
-        # from shapely import segmentize
-
-        # df.geometry = segmentize(df.geometry, tolerance)
-
         snapped = sg.coverage_clean(df, tolerance).pipe(sg.coverage_clean, tolerance)
         assert sg.get_geom_type(snapped) == "polygon", sg.get_geom_type(snapped)
 
@@ -411,272 +190,12 @@ def test_clean():
         assert (a := max(list(missing.area) + [0])) < 1e-4, a
         assert (a := max(list(gaps.area) + [0])) < 1e-4, a
 
-        snapped = sg.snap_polygons(
-            df, tolerance, mask=mask.buffer(0.1, resolution=1, join_style=2)
-        )
-        assert sg.get_geom_type(snapped) == "polygon", sg.get_geom_type(snapped)
-
-        continue
-
-        double = sg.get_intersections(snapped).loc[lambda x: ~x.buffer(-1e-9).is_empty]
-        gaps = sg.get_gaps(snapped).loc[lambda x: ~x.buffer(-1e-9).is_empty]
-        missing = get_missing(df, snapped)
-
-        print(double.area.sum(), missing.area.sum(), gaps.area.sum())
-
-        sg.explore(
-            df,
-            snapped,
-            double,
-            missing,
-            gaps,
-        )
-
-        assert (a := max(list(gaps.area) + [0])) < 1e-4, a
-        assert (a := max(list(double.area) + [0])) < 1e-4, a
-        assert (a := max(list(missing.area) + [0])) < 1e-4, a
-
-        # snapped = sg.snap_to_mask(
-        #     df, tolerance, mask=mask.buffer(0.1, resolution=1, join_style=2)
-        # )
-
-        # double = sg.get_intersections(snapped)
-        # missing = sg.clean_overlay(df, snapped, how="difference", geom_type="polygon")
-        # gaps = sg.get_gaps(snapped)
-
-        # print(double.area.sum(), missing.area.sum(), gaps.area.sum())
-
-        # sg.explore(
-        #     df,
-
-        #     snapped,
-        #     double,
-
-        #     missing,
-        # )
-
-        snapped_twice = sg.snap_polygons(snapped, tolerance)
-        assert sg.get_geom_type(snapped_twice) == "polygon", sg.get_geom_type(
-            snapped_twice
-        )
-
-        double = sg.get_intersections(snapped_twice)
-        missing = get_missing(df, snapped_twice)
-
-        sg.explore(
-            df,
-            snapped,
-            snapped_twice,
-            double,
-            missing,
-        )
-
-        # assert (a := max(list(double.area) + [0])) < 1e-4, a
-        # assert (a := max(list(missing.area) + [0])) < 1e-4, a
-
-        snapped = sg.snap_polygons(
-            df, tolerance, mask=mask.buffer(0.1, resolution=1, join_style=2)
-        )
-
-        sg.explore(snapped.assign(idx=lambda x: [str(i) for i in range(len(x))]), "idx")
-
-        gaps = sg.get_gaps(snapped)
-        double = sg.get_intersections(snapped)
-        missing = get_missing(df, snapped)
-
-        sg.explore(
-            df,
-            snapped,
-            gaps,
-            double,
-            missing,
-        )
-
-        sg.explore(snapped.assign(idx=lambda x: [str(i) for i in range(len(x))]), "idx")
-
-        assert sg.get_geom_type(snapped) == "polygon", sg.get_geom_type(snapped)
-        assert (a := max(list(gaps.area) + [0])) < 1e-4, a
-        assert (a := max(list(double.area) + [0])) < 1e-4, a
-        assert (a := max(list(missing.area) + [0])) < 1e-4, a
-
-        snapped_to_snapped = sg.snap_to_mask(snapped, tolerance, mask=snapped)
-
-        sg.explore(
-            df,
-            snapped,
-            snapped_to_snapped,
-        )
-        sg.explore(
-            snapped.assign(idx=lambda x: [str(i) for i in range(len(x))]),
-            "idx",
-        )
-
-        assert sg.get_geom_type(snapped_to_snapped) == "polygon", sg.get_geom_type(
-            snapped_to_snapped
-        )
-
-        # assert (nums1 := [round(num, 3) for num in sorted(snapped.area)]) == (
-        #     nums2 := [round(num, 3) for num in sorted(snapped_to_snapped.area)]
-        # ), (nums1, nums2)
-
-
-def not_test_spikes():
-    from shapely.geometry import Point, Polygon
-
-    factor = 10000
-
-    sliver = sg.to_gdf(
-        Polygon(
-            [
-                (0, 0),
-                (0.1 * factor, 1 * factor),
-                (0, 2 * factor),
-                (-0.1 * factor, 1 * factor),
-            ]
-        )
-    ).assign(what="sliver", num=1)
-    poly_with_spike = sg.to_gdf(
-        Polygon(
-            [
-                (0 * factor, 0 * factor),
-                (-0.1 * factor, 1 * factor),
-                (0 * factor, 2 * factor),
-                (-0.99 * factor, 2 * factor),
-                (-0.99 * factor, 1.5 * factor),
-                (-1.01 * factor, 1.5 * factor),
-                (-1.01 * factor, 2 * factor),
-                (-1.51 * factor, 2 * factor),
-                (-1.51 * factor, 1.7 * factor),
-                (-1.52 * factor, 2 * factor),
-                (-2 * factor, 2 * factor),
-                (-1 * factor, 1 * factor),
-            ],
-            holes=[
-                (
-                    [
-                        (-0.5 * factor, 1.25 * factor),
-                        (-0.5 * factor, 1.65 * factor),
-                        (-0.49 * factor, 1.65 * factor),
-                        (-0.49 * factor, 1.25 * factor),
-                    ]
-                ),
-            ],
-        )
-    ).assign(what="small", num=2)
-    poly_filling_the_spike = sg.to_gdf(
-        Polygon(
-            [
-                (0, 2 * factor),
-                (-0.99 * factor, 2 * factor),
-                (-0.99 * factor, 1.5 * factor),
-                (-1.01 * factor, 1.5 * factor),
-                (-1.01 * factor, 2 * factor),
-                (-2 * factor, 2 * factor),
-                (-2 * factor, 6 * factor),
-                (0, 6 * factor),
-                (0, 2 * factor),
-            ],
-        )
-    ).assign(what="small", num=2)
-
-    df = pd.concat([sliver, poly_with_spike, poly_filling_the_spike])
-    holes = sg.buff(
-        sg.to_gdf([(-0.84 * factor, 3 * factor), (-0.84 * factor, 4.4 * factor)]),
-        [0.4 * factor, 0.3 * factor],
-    )
-    df = sg.clean_overlay(df, holes, how="update")
-    df.crs = 25833
-
-    tolerance = 0.09 * factor
-
-    snapped = sg.snap_polygons(df, tolerance)
-    spikes_removed = sg.remove_spikes(df, tolerance)
-    spikes_fixed = sg.split_spiky_polygons(df, tolerance)
-    fixed_and_cleaned = sg.coverage_clean(
-        spikes_fixed, tolerance  # , pre_dissolve_func=_buff
-    )  # .pipe(sg.remove_spikes, tolerance / 100)
-
-    if __name__ == "__main__":
-        sg.explore(
-            fixed_and_cleaned=fixed_and_cleaned,
-            snapped=snapped,
-            spikes_removed=spikes_removed,
-            # spikes_fixed=spikes_fixed,
-            df=df,
-        )
-
-    def is_close_enough(num1, num2):
-        if num1 >= num2 - 1e-3 and num1 <= num2 + 1e-3:
-            return True
-        return False
-
-    area_should_be = [
-        725264293.6535025,
-        20000000.0,
-        190000000.0,
-        48285369.993336275,
-        26450336.353161283,
-    ]
-    print(list(fixed_and_cleaned.area))
-    for area1, area2 in zip(
-        sorted(fixed_and_cleaned.area),
-        sorted(area_should_be),
-    ):
-        assert is_close_enough(area1, area2), (area1, area2)
-
-    length_should_be = [
-        163423.91054766334,
-        40199.502484483564,
-        68384.02248970368,
-        24882.8908851665,
-        18541.01966249684,
-    ]
-
-    print(list(fixed_and_cleaned.length))
-    for length1, length2 in zip(
-        sorted(fixed_and_cleaned.length),
-        sorted(length_should_be),
-    ):
-        assert is_close_enough(length1, length2), (length1, length2)
-
-    # cleaned = sg.coverage_clean(df, tolerance)
-    # if __name__ == "__main__":
-    #     sg.explore(
-    #         cleaned=cleaned,
-    #         df=df,
-    #     )
-
-    # assert (area := sorted([round(x, 3) for x in cleaned.area])) == sorted(
-
-    #     [
-
-    #         7.225,
-    #         1.89,
-    #         0.503,
-    #         0.283,
-    #         0.2,
-    #     ]
-    # ), area
-    # assert (length := sorted([round(x, 3) for x in cleaned.length])) == sorted(
-    #     [
-    #         17.398,
-    #         7.838,
-    #         2.513,
-    #         1.885,
-
-    #         4.02,
-    #     ]
-
-    # ), length
-
 
 def main():
     test_clean()
     test_clean_1144()
     test_clean_dissappearing_polygon()
 
-    not_test_spikes()
-
 
 if __name__ == "__main__":
     import cProfile

From 391cfa021ec48221be7f490d267b4fefc03b5d34 Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Mon, 15 Apr 2024 15:12:19 +0200
Subject: [PATCH 38/42] up coverage

---
 tests/test_explore.py  | 11 +++++++++++
 tests/test_parallel.py | 18 ++++++++++++++++++
 2 files changed, 29 insertions(+)

diff --git a/tests/test_explore.py b/tests/test_explore.py
index c3f09ced..e4a2ccdc 100644
--- a/tests/test_explore.py
+++ b/tests/test_explore.py
@@ -8,6 +8,7 @@
 
 
 src = str(Path(__file__).parent).strip("tests") + "src"
+testdata = str(Path(__file__).parent.parent) + "/tests/testdata/raster"
 
 import sys
 
@@ -17,6 +18,16 @@
 import sgis as sg
 
 
+path_sentinel = testdata + "/sentinel2"
+
+
+def test_torch():
+
+    torch_dataset = sg.torchgeo.Sentinel2(path_sentinel, res=10)
+
+    sg.explore(torch_dataset, "value")
+
+
 def not_test_center(r300, r200, r100, p):
     for center in [
         (263206.184457095, 6651199.528012605),
diff --git a/tests/test_parallel.py b/tests/test_parallel.py
index 4ee83fba..d9fe0a0a 100644
--- a/tests/test_parallel.py
+++ b/tests/test_parallel.py
@@ -57,6 +57,23 @@ def not_test_map():
         assert results == [1, 3, 5, 7, 9, 11], results
 
 
+def test_args_to_kwargs():
+    def func(x, y, z):
+        pass
+
+    x = 1
+    y = ["xx"]
+    z = {1: "a", 2: "b"}
+    args = (x, y, z)
+    kwargs = sg.parallel.parallel.turn_args_into_kwargs(func, args, 0)
+    assert list(kwargs) == ["x", "y", "z"], kwargs
+    assert list(kwargs.values()) == [x, y, z], kwargs
+
+    kwargs = sg.parallel.parallel.turn_args_into_kwargs(func, (y, z), 1)
+    assert list(kwargs) == ["y", "z"], kwargs
+    assert list(kwargs.values()) == [y, z], kwargs
+
+
 def not_test_starmap():
     iterable = [(1, 2), (2, 3), (3, 4)]
 
@@ -75,5 +92,6 @@ def add2(x, y, z):
 
 
 if __name__ == "__main__":
+    test_args_to_kwargs()
     not_test_map()
     not_test_starmap()

From efe2bdd93dbad06b169ec1865a95fee7359dcc9f Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Tue, 16 Apr 2024 09:35:22 +0200
Subject: [PATCH 39/42] satisfy sonar

---
 src/sgis/maps/maps.py | 2 +-
 tests/test_explore.py | 4 ++++
 tests/test_overlay.py | 6 ++++++
 3 files changed, 11 insertions(+), 1 deletion(-)

diff --git a/src/sgis/maps/maps.py b/src/sgis/maps/maps.py
index eaae04f5..1d9b2827 100644
--- a/src/sgis/maps/maps.py
+++ b/src/sgis/maps/maps.py
@@ -177,7 +177,7 @@ def explore(
     if center is not None:
         size = size or 1000
         if isinstance(center, str) and not is_wkt(center):
-            mask = address_to_gdf(center, crs=from_crs).buffer(size)
+            mask = address_to_gdf(center, crs=from_crs)
         elif isinstance(center, (GeoDataFrame, GeoSeries)):
             mask = center
         else:
diff --git a/tests/test_explore.py b/tests/test_explore.py
index e4a2ccdc..b0d6152c 100644
--- a/tests/test_explore.py
+++ b/tests/test_explore.py
@@ -71,6 +71,10 @@ def test_explore(points_oslo, roads_oslo):
     r100 = roads.clip(p.buffer(100))
 
     sg.explore(r300, "meters", r100, bygdoy=7000)
+
+    sg.explore(r300, r100, center_4326=(10.75966535, 59.92945927, 1000))
+    sg.explore(r300, r100, center=(10.75966535, 59.92945927, 1000), crs=4326)
+
     sg.clipmap(r300, r200, "meters", show_in_browser=False)
     sg.explore(r300, r200, bygdoy=1, size=10_000, show_in_browser=False)
     not_test_center(r300, r200, r100, p)
diff --git a/tests/test_overlay.py b/tests/test_overlay.py
index 413f07a7..a4d9010b 100644
--- a/tests/test_overlay.py
+++ b/tests/test_overlay.py
@@ -52,6 +52,12 @@ def test_overlay(points_oslo):
         for cols, how in zip(cols_should_be, hows):
             print(how)
             print(p500.columns)
+            no_rows = p500.loc[lambda x: x.index.isin([])].pipe(
+                sg.clean_overlay, p1000.loc[lambda x: x.index.isin([])], how=how
+            )
+            assert not len(no_rows)
+            assert list(no_rows.columns) == cols, (list(no_rows.columns), cols)
+
             overlayed = (
                 sg.clean_geoms(p500)
                 .explode(ignore_index=True)

From fa24f143b716ee182525d68b96347956a65a3118 Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Tue, 16 Apr 2024 13:04:36 +0200
Subject: [PATCH 40/42] satisfy sonar

---
 tests/test_parallel.py | 17 ++++++++++++-----
 1 file changed, 12 insertions(+), 5 deletions(-)

diff --git a/tests/test_parallel.py b/tests/test_parallel.py
index d9fe0a0a..60a71585 100644
--- a/tests/test_parallel.py
+++ b/tests/test_parallel.py
@@ -74,18 +74,25 @@ def func(x, y, z):
     assert list(kwargs.values()) == [y, z], kwargs
 
 
-def not_test_starmap():
+def test_starmap():
     iterable = [(1, 2), (2, 3), (3, 4)]
 
     def add(x, y):
         return x + y
 
-    p = sg.Parallel(3, backend="loky")
+    def add2(x, y, z):
+        return x + y + z
+
+    p = sg.Parallel(1, backend="loky")
     results = p.starmap(add, iterable)
     assert results == [3, 5, 7]
 
-    def add2(x, y, z):
-        return x + y + z
+    results = p.starmap(add2, iterable, kwargs=dict(z=1))
+    assert results == [4, 6, 8]
+
+    p = sg.Parallel(3, backend="loky")
+    results = p.starmap(add, iterable)
+    assert results == [3, 5, 7]
 
     results = p.starmap(add2, iterable, kwargs=dict(z=1))
     assert results == [4, 6, 8]
@@ -93,5 +100,5 @@ def add2(x, y, z):
 
 if __name__ == "__main__":
     test_args_to_kwargs()
+    test_starmap()
     not_test_map()
-    not_test_starmap()

From 863167a109fb10e48aa753234084d2439291429e Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Tue, 16 Apr 2024 14:00:26 +0200
Subject: [PATCH 41/42] sonar

---
 tests/test_torchgeo.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/tests/test_torchgeo.py b/tests/test_torchgeo.py
index 11e6f6fa..b07d7b63 100644
--- a/tests/test_torchgeo.py
+++ b/tests/test_torchgeo.py
@@ -32,6 +32,8 @@ def test_torch():
     from torchgeo.samplers import RandomGeoSampler
 
     torch_dataset = sg.torchgeo.Sentinel2(path_sentinel, res=10)
+    data_loaded = torch_dataset[torch_dataset.bounds]
+    torch_dataset.plot(data_loaded)
 
     sg.explore(torch_dataset, "value")
     gdf = sg.to_gdf(torch_dataset)

From 9a2819a1c4f953c4e501966c2febfe19060ff908 Mon Sep 17 00:00:00 2001
From: Morten Letnes <ort@ssb.no>
Date: Tue, 16 Apr 2024 14:28:21 +0200
Subject: [PATCH 42/42] satisfy sonar

---
 tests/test_parallel.py | 27 +++++++++++++++++++--------
 1 file changed, 19 insertions(+), 8 deletions(-)

diff --git a/tests/test_parallel.py b/tests/test_parallel.py
index 60a71585..cff9178e 100644
--- a/tests/test_parallel.py
+++ b/tests/test_parallel.py
@@ -39,7 +39,15 @@ def x2_with_arg_kwarg(x, plus, minus):
     return x * 2 + plus - minus
 
 
-def not_test_map():
+def add(x, y):
+    return x + y
+
+
+def add2(x, y, z):
+    return x + y + z
+
+
+def test_map():
     for backend in ["loky", "multiprocessing", "threading"]:
         print(backend)
         iterable = [1, 2, 3, 4, 5, 6]
@@ -77,20 +85,23 @@ def func(x, y, z):
 def test_starmap():
     iterable = [(1, 2), (2, 3), (3, 4)]
 
-    def add(x, y):
-        return x + y
+    p = sg.Parallel(1, backend="loky")
+    results = p.starmap(add, iterable)
+    assert results == [3, 5, 7]
 
-    def add2(x, y, z):
-        return x + y + z
+    results = p.starmap(add2, iterable, kwargs=dict(z=1))
+    assert results == [4, 6, 8]
 
-    p = sg.Parallel(1, backend="loky")
+    p = sg.Parallel(2, backend="loky")
+    results = p.starmap(add, [])
+    assert results == []
     results = p.starmap(add, iterable)
     assert results == [3, 5, 7]
 
     results = p.starmap(add2, iterable, kwargs=dict(z=1))
     assert results == [4, 6, 8]
 
-    p = sg.Parallel(3, backend="loky")
+    p = sg.Parallel(2, backend="multiprocessing")
     results = p.starmap(add, iterable)
     assert results == [3, 5, 7]
 
@@ -101,4 +112,4 @@ def add2(x, y, z):
 if __name__ == "__main__":
     test_args_to_kwargs()
     test_starmap()
-    not_test_map()
+    test_map()