Upload the source files for version 0.9.6 of t4gpd

CITATION.cff

@@ -5,7 +5,7 @@ authors:
    given-names: "Thomas"
    orcid: "https://orcid.org/0000-0002-5728-9787"
 title: "t4gpd"
-version: 0.9.5
+version: 0.9.6
 doi: 10.5281/zenodo.5771916
-date-released: 2024-05-16
+date-released: 2024-12-19
 url: "https://pypi.org/project/t4gpd/"

HISTORY.md

@@ -1,5 +1,42 @@
 # Package t4gpd history
 
+## Version 0.9.6 - rev. 14829 - 19 Dec. 2024
+* Add new picoclim.PicopattReader class
+* Add new tests.commons.energy.PvlibProxyTest class
+* Add new commons.energy.PvlibProxy class
+* Add new morph.geoProcesses.EllipticityAxisIndices class
+* Add new morph.geoProcesses.LinearRegressionIndices class
+* Add new resilientgaia.STSatelliteLOSAnalysis class
+* Add new misc.PlotCorrelationMatrix
+* Add new commons.CorrelationLib class
+* Add new morph.geoProcesses.OrientedSVF class
+* Add new commons.EnergyLib class
+* Add new resilientgaia.STSatelliteLabelling class
+* Add new tests.commons.IntervalLibTest class
+* Add new commons.IntervalLib class
+* Add new resilientgaia.STSatelliteOnSiteProjection class
+* Add new tests.resilientgaia.STECEF2AERSatelliteReaderTest class
+* Add new tests.resilientgaia.SatelliteLibTest class
+* Add new resilientgaia.SatelliteLib class
+* Add new tests.commons.proj.AEProjectionLibTest class
+* Add new commons.proj.AEProjectionLib class
+* Add new resilientgaia.STECEF2AERSatelliteReader class
+* Add new tests.commons.overlap.OverlapLibTest class
+* Add new commons.overlap.OverlapLib class
+* Add new energy.STPvlibIrradiances class
+* Overwrite isovist.STIsovistField2D_new by isovist.STIsovistField2D
+* Add new tests.isovist.STExactIsovistField2DTest class
+* Add new isovist.STExactIsovistField2D class
+* Add new tests.commons.isovists.ExactIsovistLibTest class
+* Add new commons.isovists.ExactIsovistLib class
+* Remove useless tests.commons.RayCasting4LibTest class
+* Remove useless commons.RayCasting4Lib class
+* Refactor commons.raycasting.PanopticRaysLib class
+* Add new tests.morph.STMakeNeighborhoodTest class
+* Add new morph.STMakeNeighborhood class
+* Add new morph.STVoronoiPartition2 class
+* Refactor morph.STVoronoiPartition class
+
 ## Version 0.9.5 - rev. 14477 - 16 May 2024
 * Multiple debugging
 * Add new .github/workflows/python-package.yml config file

README.md

@@ -11,16 +11,16 @@ To be able to use the **t4gpd** plugin, perform geoprocessing and display your o
 
 > conda config --env --set channel_priority strict
 
-> conda install python=3.10 geopandas=0.12.2 contextily geocube imageio jupyterlab mapclassify matplotlib matplotlib-scalebar meshio networkx notebook openpyxl plotly pvlib Pyarrow pysolar pyvista pywavelets rasterio scikit-learn scipy seaborn windrose xlrd xlwt
+> conda install python=3.10 geopandas=0.12.2 contextily geocube imageio jupyterlab mapclassify matplotlib matplotlib-scalebar meshio networkx notebook openpyxl plotly pvlib Pyarrow pyogrio pysolar pyvista pywavelets rasterio scikit-learn scipy seaborn windrose xlrd xlwt
 
 > pip install dijkstar pythermalcomfort suntimes
 
 ## Installation instructions
 As **t4gpd** is now on [PyPI](https://pypi.org/project/t4gpd/), the easiest way to install the latest version is to use the pip command as follows:
 > pip install t4gpd
 
-Alternatively, you can download the **t4gpd** latest version from the [SourceSup website](https://sourcesup.renater.fr/projects/t4gs). Then, install the Python3 plugin you downloaded:
-> pip install t4gpd-0.9.5.tar.gz
+Alternatively, you can download the **t4gpd** latest version from the [PyPI](https://pypi.org/project/t4gpd/#files). Then, install the Python3 plugin you downloaded:
+> pip install t4gpd-0.9.6.tar.gz
 
 ## Read the documentation
 Go to [https://t4gpd-docs.readthedocs.io](https://t4gpd-docs.readthedocs.io) to consult the documentation.

t4gpd/_version.py

@@ -21,4 +21,4 @@
 along with t4gpd.  If not, see <https://www.gnu.org/licenses/>.
 '''
 # The following line *must* be the last in the module, exactly as formatted:
-__version__ = '0.9.5'
+__version__ = '0.9.6'

t4gpd/commons/AngleLib.py

@@ -3,7 +3,7 @@
 
 @author: tleduc
 
-Copyright 2020 Thomas Leduc
+Copyright 2020-2024 Thomas Leduc
 
 This file is part of t4gpd.
 
@@ -20,7 +20,7 @@
 You should have received a copy of the GNU General Public License
 along with t4gpd.  If not, see <https://www.gnu.org/licenses/>.
 '''
-from numpy import arctan2, pi 
+from numpy import arctan2, degrees, pi, radians, r_
 
 
 class AngleLib(object):
@@ -29,29 +29,61 @@ class AngleLib(object):
     '''
 
     @staticmethod
-    def toDegrees(angle):
-        return (180.0 * angle) / pi
+    def angleBetween(direction1, direction2):
+        angle = AngleLib.normAzimuth(
+            direction2) - AngleLib.normAzimuth(direction1)
+        return angle % (2 * pi)
 
     @staticmethod
-    def toRadians(angle):
-        return (pi * angle) / 180.0
+    def angleBetweenNodes(node1, orig, node2):
+        return AngleLib.angleBetween([node1[0] - orig[0], node1[1] - orig[1]], [node2[0] - orig[0], node2[1] - orig[1]])
+
+    @staticmethod
+    def eastCCW2northCW(angle, degree=True):
+        return AngleLib.northCW2eastCCW(angle, degree)
+
+    @staticmethod
+    def fromEastCCWAzimuthToOppositeSliceIds(azim, nslices, offset=0, degree=True):
+        quadrant = nslices // 4
+        sliceId = AngleLib.fromEastCCWAzimuthToSliceId(azim, nslices, degree)
+        start = (sliceId + quadrant + offset) % nslices
+        stop = (sliceId + 3*quadrant - offset) % nslices
+        if (start < stop):
+            return slice(start, stop + 1)
+        return r_[slice(start, nslices), slice(0, stop + 1)]
+
+    @staticmethod
+    def fromEastCCWAzimuthToSliceId(azim, nslices, degree=True):
+        if not degree:
+            azim = degrees(azim)
+        azim = AngleLib.normalizeAngle(azim)
+        offset = 360 / nslices
+        return int((azim + offset/2) / offset) % nslices
+
+    @staticmethod
+    def normalizeAngle(angle, degree=True):
+        modulo = 360 if degree else 2 * pi
+        return angle % modulo
 
     @staticmethod
     def normAzimuth(direction):
-        result = arctan2(direction[1], direction[0])
-        if (result < 0.0):
-            return (2.0 * pi + result)
-        else:
-            return result
+        angle = arctan2(direction[1], direction[0])
+        return angle % (2 * pi)
 
     @staticmethod
-    def angleBetween(direction1, direction2):
-        result = AngleLib.normAzimuth(direction2) - AngleLib.normAzimuth(direction1)
-        if (result < 0.0):
-            return (2.0 * pi + result)
-        else:
-            return result
+    def northCW2eastCCW(angle, degree=True):
+        quarto = 90 if degree else pi / 2
+        return AngleLib.normalizeAngle(5 * quarto - angle, degree)
 
     @staticmethod
-    def angleBetweenNodes(node1, orig, node2):
-        return AngleLib.angleBetween([ node1[0] - orig[0] , node1[1] - orig[1] ], [ node2[0] - orig[0] , node2[1] - orig[1] ])
+    def southCCW2northCW(angle, degree=True):
+        half = 180 if degree else pi
+        return AngleLib.normalizeAngle(half - angle, degree)
+
+    @staticmethod
+    def toDegrees(angle):
+        return degrees(angle)
+
+    @staticmethod
+    def toRadians(angle):
+        return radians(angle)

t4gpd/commons/ArrayCoding.py

@@ -3,7 +3,7 @@
 
 @author: tleduc
 
-Copyright 2020 Thomas Leduc
+Copyright 2020-2024 Thomas Leduc
 
 This file is part of t4gpd.
 
@@ -20,6 +20,8 @@
 You should have received a copy of the GNU General Public License
 along with t4gpd.  If not, see <https://www.gnu.org/licenses/>.
 '''
+from numpy import nan
+from pandas import isna
 
 
 class ArrayCoding(object):
@@ -28,15 +30,19 @@ class ArrayCoding(object):
     '''
 
     @staticmethod
-    def encode(listOfValues, separator='#'):
+    def encode(listOfValues, separator="#"):
         try:
             iter(listOfValues)
             return separator.join([str(v) for v in listOfValues])
         except TypeError:
+            if isna(listOfValues) or (listOfValues is None):
+                return nan
             return str(listOfValues)
 
     @staticmethod
-    def decode(string, outputType=float, separator='#'):
-        if (0 == len(string)):
+    def decode(argument, outputType=float, separator="#"):
+        if isna(argument) or (argument is None):
+            return nan
+        if (0 == len(argument)):
             return []
-        return [outputType(v) for v in string.split(separator)]
+        return [outputType(v) for v in argument.split(separator)]

t4gpd/commons/CSVLib.py

@@ -3,7 +3,7 @@
 
 @author: tleduc
 
-Copyright 2020 Thomas Leduc
+Copyright 2020-2024 Thomas Leduc
 
 This file is part of t4gpd.
 
@@ -48,27 +48,3 @@ def readLexeme(s, decimalSep='.'):
         except (TypeError, ValueError):
             pass
         return s
-
-    @staticmethod
-    def read(inputFile, fieldSep=',', decimalSep='.'):
-        rows, outputFields = [], []
-
-        with open(inputFile, 'r') as f:
-            for nline, line in enumerate(f, start=1):
-                # values = line.strip().split(self.fieldSep)
-                values = re.split(fieldSep, line.strip())
-                values = [value.strip() for value in values]
-
-                if (1 == nline):
-                    for fieldName in values:
-                        fieldName = fieldName.replace('"', '')
-                        if (0 == len(fieldName)):
-                            fieldName = 'gid'
-                        outputFields.append(fieldName)
-                else:
-                    row = dict()
-                    for i, value in enumerate(values):
-                        value = value.replace('"', '')
-                        row[outputFields[i]] = CSVLib.readLexeme(value, decimalSep)
-                    rows.append(row)
-        return rows

t4gpd/commons/ColorTemperature.py

@@ -29,7 +29,7 @@ class ColorTemperature(object):
     '''
 
     @staticmethod
-    def convert_K_to_RGB(colour_temperature):
+    def convert_K_to_RGB(colour_temperature, decimal=False):
         """
         Converts from K to RGB, algorithm courtesy of 
         http://www.tannerhelland.com/4435/convert-temperature-rgb-algorithm-code/
@@ -67,4 +67,6 @@ def setMinMax(value, minValue, maxValue): return min(
             blue = setMinMax(blue, 0, 255)
 
         # return red, green, blue
+        if decimal:
+            return red/255, green/255, blue/255
         return int(round(red)), int(round(green)), int(round(blue))

t4gpd/commons/CorrelationLib.py

@@ -0,0 +1,88 @@
+'''
+Created on 30 oct. 2024
+
+@author: tleduc
+
+Copyright 2020-2024 Thomas Leduc
+
+This file is part of t4gpd.
+
+t4gpd is free software: you can redistribute it and/or modify
+it under the terms of the GNU General Public License as published by
+the Free Software Foundation, either version 3 of the License, or
+(at your option) any later version.
+
+t4gpd is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+GNU General Public License for more details.
+
+You should have received a copy of the GNU General Public License
+along with t4gpd.  If not, see <https://www.gnu.org/licenses/>.
+'''
+from pandas import DataFrame
+from t4gpd.commons.IllegalArgumentTypeException import IllegalArgumentTypeException
+from scipy.stats import kendalltau, pearsonr, spearmanr
+
+
+class CorrelationLib(object):
+    '''
+    classdocs
+    '''
+
+    @staticmethod
+    def correlation_with_pvalues(df, method="pearson"):
+        def __get_pvalues_dataframe(df, corr, method):
+            from numpy import full, isnan, logical_or, nan, sum
+
+            # Return a new array of given shape, filled with nan values
+            pval = full(corr.shape, nan)
+            for i in range(corr.shape[0]):
+                for j in range(i, corr.shape[1]):
+                    x = df.iloc[:, i]
+                    y = df.iloc[:, j]
+                    mask = ~logical_or(isnan(x), isnan(y))
+                    if sum(mask) > 0:
+                        # Get Pearson correlation p-value
+                        pval[i, j] = pval[j, i] = method(x[mask], y[mask])[1]
+
+            pval = DataFrame(pval, columns=corr.columns, index=corr.index)
+            return pval
+
+        if not isinstance(df, DataFrame):
+            raise IllegalArgumentTypeException(df, "DataFrame")
+        if "pearson" == method:
+            _method = pearsonr
+        elif "kendall" == method:
+            _method = kendalltau
+        elif "spearman" == method:
+            _method = spearmanr
+        else:
+            raise IllegalArgumentTypeException(
+                method, "pearson, kendall or spearman")
+
+        _df = df.select_dtypes("number")
+        corr = _df.corr(method=method)
+        pval = __get_pvalues_dataframe(_df, corr, method=_method)
+
+        return corr, pval
+
+    @staticmethod
+    def test():
+        from numpy.random import default_rng
+
+        nrows, rng = 10, default_rng(123)
+        df = DataFrame(
+            data=rng.uniform(low=0, high=1, size=(nrows, 4)),
+            columns=["X1", "X2", "X3", "X4"])
+        df = df.assign(
+            Y1=lambda row: (10 * row.X1 + 0.5 * row.X2 + 0.4 * row.X3) / 10.9,
+            Y2=lambda row: (10 * row.X1 + 1.5 * row.X2 + 1.4 * row.X4) / 12.9,
+            Z=[f"z{i}" for i in range(len(df))]
+        )
+
+        corr, pval = CorrelationLib.correlation_with_pvalues(df)
+        return df, corr, pval
+
+
+# df, corr, pval = CorrelationLib.test()