Merge develop into master - v2.0.1 (#109)

* create workaround for unknow zsh issue

* update documentation and GH Actions workflows

* removing geopandas installation from setup.py and moving import statement in AssetData class

* modifying ENGIE project pathname in exmaples so auto data extract works

* minor documentation updates

* Unfreezing sphinx dependencies

* undoing that change

* updating changelog with version 2.0.0 and unreleased

* replace geopandas with pyproj (#107)

* replace `GeoPandas` with `pyproj` and `Shapely`

* adding `pyproj` and `shapely` to `setup.py` and `requirements.txt`

* Update `python-ci.yml`to include Windows tests

* update software version to 2.0.1

Co-authored-by: Rob <robert.hammond@nrel.gov>

* Update AssetData docstring

Removed any lingering references to `GeoPandas`.

* Remove GDAL/Windows comments

* Update CHANGELOG.md

* Update readme.md

Co-authored-by: Rob <robert.hammond@nrel.gov>
Co-authored-by: Jordan Perr-Sauer <jordan.perr-sauer@nrel.gov>
Co-authored-by: ejsimley <eric.simley@nrel.gov>
Co-authored-by: ejsimley <40040961+ejsimley@users.noreply.github.com>

Author: 4 people

.github/workflows/python-ci.yml

@@ -9,10 +9,11 @@ on:
 jobs:
   build:
 
-    runs-on: ubuntu-latest
+    runs-on: ${{ matrix.os }}
     strategy:
       matrix:
-        python-version: [3.6, 3.7, 3.8]
+        os: [ubuntu-latest, windows-latest]
+        python-version: [3.6, 3.8]
 
     steps:
     - uses: actions/checkout@v2
@@ -24,11 +25,14 @@ jobs:
       run: |
         python -m pip install --upgrade pip
         pip install -r requirements.txt
+      shell: bash
     - name: Unzip example data
       run: |
-        yes | unzip examples/data/la_haute_borne.zip -d examples/data/la_haute_borne/
+        unzip examples/data/la_haute_borne.zip -d examples/data/la_haute_borne/
+      shell: bash
     - name: Test with pytest
       run: |
-        pytest -o python_files=test/*.py --cov=operational_analysis --cov-report=xml
+        pytest --cov=operational_analysis --cov-report=xml
+      shell: bash
     - name: Upload coverage to Codecov
       uses: codecov/codecov-action@v1

CHANGELOG.md

@@ -1,6 +1,11 @@
 # Changelog
 All notable changes to this project will be documented in this file. If you make a notable change to the project, please add a line describing the change to the "unreleased" section. The maintainers will make an effort to keep the [Github Releases](https://github.com/NREL/OpenOA/releases) page up to date with this changelog. The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/).
 
+## [2.0.1 - 2020-10-13]
+- Replaced `GeoPandas` functionality with `pyproj` and `Shapely` for coordinate
+reference system conversion and distance measurements.
+- Moved and renamed tests and updated the documentation accordingly.
+
 ## [2.0.0 - 2020-08-11]
 - Switch to [semantic versioning](https://semver.org) from this release forward.
 - Efficiency improvements in AEP calculation
@@ -31,4 +36,4 @@ All notable changes to this project will be documented in this file. If you make
 - Turbine / Scada level toolkits: Filtering, Imputing, Met, Pandas Plotting, Timeseries, Unit Conversion
 - Most toolkits and all methods are fully documented in Sphinx.
 - Two example notebooks: Operational AEP Analysis and Turbine Analysis
-- All toolkits except for Pandas Plotting have > 80% test coverage.
+- All toolkits except for Pandas Plotting have > 80% test coverage.

examples/00_toolkit_examples.ipynb

@@ -60,7 +60,7 @@
     }
    ],
    "source": [
-    "project = Project_Engie('./data/la_haute_borne/')\n",
+    "project = Project_Engie('./data/la_haute_borne')\n",
     "project.prepare()"
    ]
   },
@@ -493,4 +493,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 2
-}
+}

examples/02_plant_aep_analysis.ipynb

@@ -76,7 +76,7 @@
    "outputs": [],
    "source": [
     "# Load plant object\n",
-    "project = Project_Engie('./data/la_haute_borne/')"
+    "project = Project_Engie('./data/la_haute_borne')"
    ]
   },
   {
@@ -1001,4 +1001,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 2
-}
+}

examples/02b_augmented_plant_aep_analysis.ipynb

@@ -58,7 +58,7 @@
    "outputs": [],
    "source": [
     "# Load plant object\n",
-    "project = Project_Engie('./data/la_haute_borne/')"
+    "project = Project_Engie('./data/la_haute_borne')"
    ]
   },
   {
@@ -1240,7 +1240,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.7"
+   "version": "3.7.4"
   },
   "toc": {
    "base_numbering": 1,
@@ -1258,4 +1258,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 4
-}
+}

examples/03_turbine_ideal_energy.ipynb

@@ -62,7 +62,7 @@
    "outputs": [],
    "source": [
     "# Load plant object\n",
-    "project = Project_Engie('./data/la_haute_borne/')"
+    "project = Project_Engie('./data/la_haute_borne')"
    ]
   },
   {
@@ -628,7 +628,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.7"
+   "version": "3.7.4"
   },
   "toc": {
    "base_numbering": 1,
@@ -646,4 +646,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 4
-}
+}

examples/04_electrical_losses.ipynb

@@ -71,7 +71,7 @@
    "outputs": [],
    "source": [
     "# Load wind farm object\n",
-    "project = Project_Engie('./data/la_haute_borne/')"
+    "project = Project_Engie('./data/la_haute_borne')"
    ]
   },
   {
@@ -426,4 +426,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 2
-}
+}

examples/05_eya_gap_analysis.ipynb

@@ -67,7 +67,7 @@
    ],
    "source": [
     "# Load plant object and process plant data\n",
-    "project = Project_Engie('./data/la_haute_borne/')\n",
+    "project = Project_Engie('./data/la_haute_borne')\n",
     "project.prepare()"
    ]
   },
@@ -252,4 +252,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 2
-}
+}

operational_analysis/__init__.py

@@ -1,4 +1,4 @@
-__version__ = "2.0.0"
+__version__ = "2.0.1"
 
 import json
 import logging

operational_analysis/types/asset.py

@@ -1,17 +1,17 @@
 import importlib
 import itertools
 
-import geopandas as gp
 import numpy as np
 import pandas as pd
+from pyproj import Transformer
 from shapely.geometry import Point
 
 
 class AssetData(object):
     """
-    This class wraps around a GeoPandas dataframe that contains
+    This class wraps around a Pandas dataframe that contains
     metadata about the plant assets. It provides some useful functions
-    to work with this data (e.g., calculating nearest neighbors, etc.)
+    to work with this data (e.g., calculating nearest neighbors, etc.). 
     """
 
     def __init__(self, engine="pandas"):
@@ -89,12 +89,10 @@ def parse_geometry(self, srs='epsg:4326', zone=None, longitude=None):
                 longitude = self.df['longitude'].mean()
             zone = int(np.floor((180 + longitude) / 6.0)) + 1
 
-        self._asset = gp.GeoDataFrame(self._asset)
-        self._asset['geometry'] = self._asset.apply(lambda x: Point(x['longitude'], x['latitude']), 1)
-        self._asset.set_geometry('geometry')
-        self._asset.crs = {'init': srs}
-        self._asset = self._asset.to_crs(
-            "+proj=utm +zone=" + str(zone) + " +ellps=WGS84 +datum=WGS84 +units=m +no_defs")
+        to_crs = f"+proj=utm +zone={zone} +ellps=WGS84 +datum=WGS84 +units=m +no_defs"
+        transformer = Transformer.from_crs(srs.upper(), to_crs)
+        lats, lons = transformer.transform(self._asset["latitude"].values, self._asset["longitude"].values)
+        self._asset["geometry"] = [Point(lat, lon) for lat, lon in zip (lats, lons)]
 
     def calculate_nearest(self, active_turbine_ids, active_tower_ids):
         """Create or overwrite a column called 'nearest_turbine_id' or 'nearest_tower_id' which contains the asset id
@@ -124,11 +122,11 @@ def calculate_nearest(self, active_turbine_ids, active_tower_ids):
 
     def distance_matrix(self):
         ret = np.ones((self._asset.shape[0], self._asset.shape[0])) * -1
-        for i, j in itertools.permutations(self._asset.index, 2):
+        for i, j in itertools.combinations(self._asset.index, 2):
             point1 = self._asset.loc[i, 'geometry']
             point2 = self._asset.loc[j, 'geometry']
             distance = point1.distance(point2)
-            ret[i][j] = distance
+            ret[i, j] = ret[j, i] = distance
         return ret
 
     def asset_ids(self):

pytest.ini

@@ -0,0 +1,2 @@
+[pytest]
+python_files = test/*.py

readme.md

@@ -31,19 +31,6 @@ conda create --name openoa-env python=3
 conda activate openoa-env
 ```
 
-#### Special Note for users of Microsoft Windows:
-
-The Anaconda python distribution is *required* for users of Microsoft Windows. This is because the pip package of GDAL for Windows requires Visual Studio to compile some of the dependencies. While advanced users are welcome to explore this option, we find it is easier to install the following packages via Anaconda:
-
-```
-conda install shapely
-conda install geos
-conda install fiona
-```
-
-If errors about Visual Studio persist, you can try downloading the [Microsoft Visual Studio compiler for Python](https://www.microsoft.com/en-us/download/details.aspx?id=44266) and compiling GDAL yourself.
-
-
 ### Installation:
 
 Clone the repository and install the library and its dependencies using pip:
@@ -88,13 +75,13 @@ unzip examples/data/la_haute_borne.zip -d examples/data/la_haute_borne/
 Tests are written in the Python unittest framework and are runnable using pytest. To run all tests with code coverage reporting:
 
 ```
-pytest -o python_files=test/*.py --cov=operational_analysis
+pytest --cov=operational_analysis
 ```
 
 To run unit tests only:
 
 ```
-pytest -o python_files=test/test_*.py --cov=operational_analysis
+pytest --ignore=test/regression/ --cov=operational_analysis
 ```
 
 #### Documentation
@@ -117,6 +104,7 @@ Nathan Agarwal,
 Nicola Bodini,
 Anna Craig,
 Jason Fields,
+Rob Hammond,
 Travis Kemper,
 Joseph Lee,
 Monte Lunacek,

requirements.txt

@@ -1,6 +1,7 @@
 # Requirements for the OpenOA software package
 eia-python>=1.22
-geopandas>=0.4.0
+pyproj>=2.6.1
+shapely>=1.7.1
 numpy>=1.15.4
 pandas>=0.23.4
 pygam>=0.8.0

setup.py

@@ -49,12 +49,13 @@ def read_file(filename):
                         "scipy",
                         "pandas",
                         "pygam",
-                        "geopandas",
                         "tqdm",
                         "statsmodels",
                         "scikit_learn",
                         "EIA-python",
-                        "requests"],
+                        "requests",
+                        "pyproj",
+                        "shapely"],
       tests_require=['pytest', 'pytest-cov'],
       python_requires='>=3.6'
       )