Merge pull request #399 from jungmannlab/development

BUG FIXES 0.6.5

Author: rafalkowalewski1

.bumpversion.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.6.4
+current_version = 0.6.5
 commit = True
 tag = False
 parse = (?P<major>\d+)\.(?P<minor>\d+)\.(?P<patch>\d+)(\-(?P<release>[a-z]+)(?P<build>\d+))?

changelog.rst

@@ -1,16 +1,19 @@
 Changelog
 =========
 
-Last change: 26-SEP-2023 MTS
+Last change: 22-OCT-2023 MTS
 
-0.6.4
------
-- Fix RCC error for Render GUI (one click installer) (remove tqdm from GUI)
-
-0.6.3
------
+0.6.3 - 0.6.5
+-------------
 - Dependencies updated
-- Bug fixes due to Python 3.10 and PyQt5
+- Bug fixes due to Python 3.10 and PyQt5 (listed below)
+- Fix RCC error for Render GUI (one click installer) (remove tqdm from GUI)
+- Fix save pick properties bug in Picasso Render GUI (one click installer)
+- Fix render render properties bug in Picasso Render GUI (one click installer)
+- Fix animation building in Picasso Render GUI (one click installer)
+- Fix test clusterer HDBSCAN bug
+- Fix .nd2 localized files info loading (full loader changed to unsafe loader)
+- Fix rare bug with pick similar zero division error
 
 0.6.2
 -----
@@ -55,16 +58,16 @@ Last change: 26-SEP-2023 MTS
 - Updated 3D rendering and clustering documentation
 - Bug fixes
 
-0.5.5 - 0.5.6
--------------
+0.5.5-6
+-------
 - Cluster info is saved in ``_cluster_centers.hdf5`` files which are created when ``Save cluster centers`` box is ticked
 - Cluster centers contain info about group, mean frame (saved as ``frame``), standard deviation frame, area/volume and convex hull
 - ``gist_rainbow`` is used for rendering properties
 - NeNA can be calculated many times
 - Bug fixes
 
-0.5.1 - 0.5.4
--------------
+0.5.1-4
+-------
 - Sensitivity is a float number in Server: Watcher
 - One-click-installer available
 - Bug fixes

distribution/picasso.iss

@@ -2,10 +2,10 @@
 AppName=Picasso
 AppPublisher=Jungmann Lab, Max Planck Institute of Biochemistry
 
-AppVersion=0.6.4
+AppVersion=0.6.5
 DefaultDirName={commonpf}\Picasso
 DefaultGroupName=Picasso
-OutputBaseFilename="Picasso-Windows-64bit-0.6.4"
+OutputBaseFilename="Picasso-Windows-64bit-0.6.5"
 ArchitecturesAllowed=x64
 ArchitecturesInstallIn64BitMode=x64
 

docs/conf.py

@@ -26,7 +26,7 @@
 # The short X.Y version
 version = ""
 # The full version, including alpha/beta/rc tags
-release = "0.6.4"
+release = "0.6.5"
 
 # -- General configuration ---------------------------------------------------
 

picasso/__init__.py

@@ -8,7 +8,7 @@
 import os.path as _ospath
 import yaml as _yaml
 
-__version__ = "0.6.4"
+__version__ = "0.6.5"
 
 _this_file = _ospath.abspath(__file__)
 _this_dir = _ospath.dirname(_this_file)

picasso/__version__.py

@@ -1 +1 @@
-VERSION_NO = "0.6.4"
+VERSION_NO = "0.6.5"

picasso/clusterer.py

@@ -449,7 +449,7 @@ def _hdbscan(X, min_cluster_size, min_samples, cluster_eps=0):
 
 
 def hdbscan(
-    locs, min_cluster_size, min_samples, cluster_eps=0.0, pixelsize=None
+    locs, min_cluster_size, min_samples, pixelsize=None, cluster_eps=0.0
 ):
     """
     Performs HDBSCAN on localizations.
@@ -463,7 +463,7 @@ def hdbscan(
     min_samples : int
         Number of localizations within radius to consider a given point 
         a core sample
-    pixelsize : int
+    pixelsize : int (default=None)
         Camera pixel size in nm
     cluster_eps : float (default=0.)
         Distance threshold. Clusters below this value will be merged
@@ -478,7 +478,7 @@ def hdbscan(
     if hasattr(locs, "z"):
         if pixelsize is None:
             raise ValueError(
-                "Camera pixel size must be specified as an integer for 3D"
+                "Camera pixel size (nm) must be specified as an integer for 3D"
                 " clustering."
             )
         X = _np.vstack((locs.x, locs.y, locs.z / pixelsize)).T

picasso/gui/render.py

@@ -34,7 +34,6 @@
 from sklearn.metrics.pairwise import euclidean_distances
 from sklearn.cluster import KMeans
 from collections import Counter
-from tqdm import tqdm
 
 import colorsys
 
@@ -2307,7 +2306,7 @@ def cluster(self, locs, params):
                 params["min_cluster_size"],
                 params["min_samples"],
                 pixelsize,
-                params["intercluster_radius"]
+                params["intercluster_radius"],
             )
         elif clusterer_name == "SMLM":
             if params["frame_analysis"]:
@@ -2387,7 +2386,10 @@ def test_clusterer(self):
 
         # make sure one pick is present
         if len(self.window.view._picks) != 1:
-            raise ValueError("Choose only one pick region")
+            # display qt warning
+            message = "Choose only one pick region"
+            QtWidgets.QMessageBox.information(self, "No pick", message)
+            return
         # get clustering parameters
         params = self.get_cluster_params()
         # extract picked locs
@@ -5116,7 +5118,7 @@ def export_stack(self):
                     progress.show()
 
                     # save each channel one by one
-                    for i in tqdm(range(self.sl.maximum() + 1)):
+                    for i in range(self.sl.maximum() + 1):
                         self.sl.setValue(i)
                         out_path = (
                             base
@@ -5154,7 +5156,7 @@ def export_stack(self):
                 progress.set_value(0)
                 progress.show()
 
-                for i in tqdm(range(self.sl.maximum() + 1)):
+                for i in range(self.sl.maximum() + 1):
                     self.sl.setValue(i)
                     out_path = (
                         base
@@ -8284,7 +8286,9 @@ def analyze_cluster(self):
             progress = lib.ProgressDialog(
                 "Calculating pick properties", 0, n_groups, self
             )
-            pick_props = postprocess.groupprops(out_locs)
+            pick_props = postprocess.groupprops(
+                out_locs, callback=progress.set_value
+            )
             n_units = self.window.info_dialog.calculate_n_units(dark)
             pick_props = lib.append_to_rec(pick_props, n_units, "n_units")
             influx = self.window.info_dialog.influx_rate.value()
@@ -8452,6 +8456,7 @@ def pick_similar(self):
         NotImplementedError
             If pick shape is rectangle
         """
+
         if self._pick_shape == "Rectangle":
             raise NotImplementedError(
                 "Pick similar not implemented for rectangle picks"
@@ -8481,7 +8486,7 @@ def pick_similar(self):
             mean_rmsd = np.mean(rmsd)
             std_n_locs = np.std(n_locs)
             std_rmsd = np.std(rmsd)
-            min_n_locs = mean_n_locs - std_range * std_n_locs
+            min_n_locs = max(2, mean_n_locs - std_range * std_n_locs)
             max_n_locs = mean_n_locs + std_range * std_n_locs
             min_rmsd = mean_rmsd - std_range * std_rmsd
             max_rmsd = mean_rmsd + std_range * std_rmsd
@@ -9140,9 +9145,14 @@ def save_pick_properties(self, path, channel):
             progress.set_value(i + 1)
         out_locs = stack_arrays(out_locs, asrecarray=True, usemask=False)
         n_groups = len(picked_locs)
-        progress = lib.StatusDialog("Calculating pick properties", self)
+        progress = lib.ProgressDialog(
+            "Calculating pick properties", 0, n_groups, self
+        )
+        progress.show()
         # get mean and std of each dtype (x, y, photons, etc)
-        pick_props = postprocess.groupprops(out_locs)
+        pick_props = postprocess.groupprops(
+            out_locs, callback=progress.set_value
+        )
         progress.close()
         # QPAINT estimate of number of binding sites 
         n_units = self.window.info_dialog.calculate_n_units(dark)
@@ -9308,7 +9318,7 @@ def activate_render_property(self):
                 )
                 pb.set_value(0)
                 # assign locs by color
-                for i in tqdm(range(colors + 1)):
+                for i in range(colors + 1):
                     x_locs.append(self.locs[0][self.x_color == i])
                     pb.set_value(i + 1)
                 pb.close()
@@ -10746,7 +10756,9 @@ def initUI(self, plugins_loaded):
         )
         plotpick3d_iso_action.triggered.connect(self.view.show_pick_3d_iso)
 
-        filter_picks_action = tools_menu.addAction("Filter picks by locs")
+        filter_picks_action = tools_menu.addAction(
+            "Filter picks by number of locs"
+        )
         filter_picks_action.triggered.connect(self.view.filter_picks)
 
         pickadd_action = tools_menu.addAction("Subtract pick regions")
@@ -11881,7 +11893,7 @@ def save_pick_properties(self):
                     "_pickprops",
                 )
                 if ok:
-                    for channel in tqdm(range(len(self.view.locs_paths))):
+                    for channel in range(len(self.view.locs_paths)):
                         base, ext = os.path.splitext(
                             self.view.locs_paths[channel]
                         )

picasso/gui/rotation.py

@@ -713,7 +713,7 @@ def build_animation(self):
             ] # paths to each frame
             image_files.sort(key=natural_keys) # sort frames
             video = ImageSequenceClip(image_files, fps=self.fps.value())
-            video.write_videofile(name)
+            video.write_videofile(name, logger=None)
 
             # delete animation frames
             for file in os.listdir(path):

picasso/io.py

@@ -198,7 +198,7 @@ def load_info(path, qt_parent=None):
     filename = path_base + ".yaml"
     try:
         with open(filename, "r") as info_file:
-            info = list(_yaml.load_all(info_file, Loader=_yaml.FullLoader))
+            info = list(_yaml.load_all(info_file, Loader=_yaml.UnsafeLoader))
     except FileNotFoundError as e:
         print("\nAn error occured. Could not find metadata file:\n{}".format(filename))
         if qt_parent is not None:

picasso/postprocess.py

@@ -165,8 +165,11 @@ def pick_similar(
                         picked_locs_xy = _locs_at(
                             x_test, y_test, block_locs_xy, r
                         )
-                        x_test = _np.mean(picked_locs_xy[0])
-                        y_test = _np.mean(picked_locs_xy[1])
+                        if picked_locs_xy.shape[1] > 1:
+                            x_test = _np.mean(picked_locs_xy[0])
+                            y_test = _np.mean(picked_locs_xy[1])
+                        else:
+                            break
                     if _np.all(
                         (x_similar - x_test) ** 2
                         + (y_similar - y_test) ** 2
@@ -1167,9 +1170,12 @@ def groupprops(locs, callback=None):
     groups = _np.recarray(n, formats=formats, names=names)
     if callback is not None:
         callback(0)
-    for i, group_id in enumerate(
-        _tqdm(group_ids, desc="Calculating group statistics", unit="Groups")
-    ):
+        it = enumerate(group_ids)
+    else:
+        it = enumerate(_tqdm(
+            group_ids, desc="Calculating group statistics", unit="Groups"
+        ))
+    for i, group_id in it:
         group_locs = locs[locs.group == group_id]
         groups["group"][i] = group_id
         groups["n_events"][i] = len(group_locs)

release/one_click_windows_gui/create_installer_windows.bat

@@ -11,7 +11,7 @@ call conda activate picasso_installer
 call python setup.py sdist bdist_wheel
 
 call cd release/one_click_windows_gui
-call pip install "../../dist/picassosr-0.6.4-py3-none-any.whl"
+call pip install "../../dist/picassosr-0.6.5-py3-none-any.whl"
 
 call pip install pyinstaller==5.7
 call pyinstaller ../pyinstaller/picasso.spec -y --clean

release/one_click_windows_gui/picasso_innoinstaller.iss

@@ -1,10 +1,10 @@
 [Setup]
 AppName=Picasso
 AppPublisher=Jungmann Lab, Max Planck Institute of Biochemistry
-AppVersion=0.6.4
+AppVersion=0.6.5
 DefaultDirName={commonpf}\Picasso
 DefaultGroupName=Picasso
-OutputBaseFilename="Picasso-Windows-64bit-0.6.4"
+OutputBaseFilename="Picasso-Windows-64bit-0.6.5"
 ArchitecturesAllowed=x64
 ArchitecturesInstallIn64BitMode=x64
 

setup.py

@@ -8,7 +8,7 @@
 
 setup(
     name="picassosr",
-    version="0.6.4",
+    version="0.6.5",
     author="Joerg Schnitzbauer, Maximilian T. Strauss, Rafal Kowalewski",
     author_email=("joschnitzbauer@gmail.com, straussmaximilian@gmail.com, rafalkowalewski998@gmail.com"),
     url="https://github.com/jungmannlab/picasso",