BugFixes: Wrong deletion behaviour fixed, by centralizing it (also index comparison was wrong)

Features: Added histograms
Generates plots now, only for different RMSE/MAE/MBE, so number of subplots is reduced.

Code/investigation_set.py

@@ -15,8 +15,8 @@ import cartopy.io.shapereader as shpreader
 #from geopandas.tools import sjoin
 
 
-dType = 'TMP'   #data type
-year = '2013'
+dType = 'ASWDIR'   #data type
+year = '2015'
 
 path = 'D:/WetterdatenPamore/' + year + '/' \
                + year + '_'+ dType + '.h5'
@@ -54,4 +54,10 @@ with h5py.File(path, 'r') as f:
    ax.scatter(refPos[1], refPos[0], transform=data_crs, c='black')
    ax.scatter(posRight[1], posRight[0], transform=data_crs, c='red')
    ax.scatter(posDown[1], posDown[0], transform=data_crs, c='blue')
+   
+   print('Top left - Lat:', lat[0,0], "   Lon:", lon[0,0])
+   print('Top Right - Lat:', lat[0,len(lat[0]) - 1], "   Lon:", lon[0,len(lon[0]) - 1])
+   print('Bottom left - Lat:', lat[len(lat) - 1,0], "   Lon:", lon[len(lon) - 1,0])
+   print('Bottom Right - Lat:', lat[len(lat) - 1,len(lat[0]) - 1], "   Lon:",  lon[len(lon) - 1,len(lon[0]) - 1])
+   
    plt.show()
\ No newline at end of file

Code/station.py

@@ -19,6 +19,7 @@ import h5py
 import math
 import numpy as np
 import matplotlib.pyplot as plt
+import seaborn as sns
 
 class WeatherStation:
     # member variables ---------------------
@@ -414,3 +415,102 @@ class WeatherStation:
             fig.set_xlabel('m / s')
             if printAxis:
                 fig.set_ylabel('m / s')
+                
+    def createDistPlots(self, fig):
+        """(matplotlib.axes, bool) -> (void)
+            creates a scatter plot of obersvation data and model data (x and y,
+            repsectively). the scatter plot is added to the matplotlib axes given
+            at function call.
+            @remark: this re-uses some code of the differences() function. may be
+            this can be done less verbose and more well structed"""
+        differences = self.getDifferences();
+        valuesObs = []
+        valuesObsBounds = []
+        valuesMod = []
+        xAxis = []
+        histBins = []
+        i = 0
+        total = len(self.observationData)
+        if (len(self.modelData) < total): total = len(self.modelData)
+        if self.type == 'solar' \
+                 or self.type == 'diffuseIrridiation' \
+                 or self.type == 'globalIrridiation':
+            histBins = [0, 25, 50, 75, 100, 125, 150, 175, 200, 225, 250, \
+                        275, 300, 325, 350, 375, 400, 425, 450, 475, 500, 525,\
+                        575, 600, 625, 650, 675, 700, 725, 750, 775, 800, 825,\
+                        850, 875, 900, 925, 950, 975, 1000]
+            for i in range(0, total):
+                if (self.observationData[i] > -500. \
+                    and self.observationData[i] < 2000.):
+                    valuesObs.append(self.observationData[i])
+                    valuesObsBounds.append(self.error)
+                    valueMod = self.modelData[i]
+                    if self.type == 'solar' \
+                         or self.type == 'diffuseIrridiation' \
+                         or self.type == 'globalIrridiation':
+                        joulePerCm2ToWhPerM2 = 1. * 10000. / 3600.
+                        valuesObs[-1] *= joulePerCm2ToWhPerM2
+                        valueMod = 0.
+                        if i > 0 :
+                            valueMod= self.modelData[i]       \
+                                      * self.minuteIndicator[i] / 60. \
+                                      + self.modelData[i - 1] \
+                                      * (60 - self.minuteIndicator[i - 1]) / 60.
+                    valuesMod.append(valueMod)
+                    xAxis.append(i)
+        else:
+            if self.type == 'temperature':                
+                histBins = [-15, -14, -13, -12, -11, -10, -9, -8, -7, -6, \
+                            -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9,\
+                            10, 11, 12, 13, 14, 15, 16, 17, 18, 19, \
+                            20, 21, 22, 23, 24, 25, 26, 27, 28, 29, \
+                            30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40]
+            elif self.type == 'windDirection':
+                histBins = [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, \
+                            100, 110, 120, 130, 140, 150, 160, 170, 180, 190, \
+                            200, 210, 220, 230, 240, 250, 260, 270, 280, 290, \
+                            300, 310, 320, 330, 340, 350, 360]
+            else:               
+                histBins = [0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5,\
+                            6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10, 10.5, \
+                            11, 11.5, 12, 12.5, 13, 13.5, 14, 14.5, 15, 15.5,\
+                            16, 16.5, 17, 17.5, 18, 18.5, 19, 19.5, 20, 20.5,\
+                            21, 21.5, 22, 22.5, 23, 23.5, 24, 24.5, 25, 25.5,\
+                            26, 26.5, 27, 27.5, 28, 28.5, 29, 29.5, 30, 30.5,\
+                            31, 31.5, 32, 32.5, 33, 33.5, 34, 34.5, 35]
+            for i in range(0, total):
+                if (self.observationData[i] > -500. \
+                    and self.observationData[i] < 2000.):
+                    valuesObs.append(self.observationData[i])
+                    valuesMod.append(self.modelData[i])
+        # plt.plot(differences, label = "diff")
+        # plt.plot(valuesObs, label = "measure")
+        # plt.plot(valuesMod, label = "model")
+        # upper = np.array(valuesObs) + np.array(valuesObsBounds)
+        # lower = np.array(valuesObs) - np.array(valuesObsBounds)
+        # plt.fill_between(xAxis, lower, upper)
+        # plt.title(self.getName() + ' ' + self.type + ' Run')
+        # plt.legend()
+        # plt.show()
+        # plt.figure()
+        #ax = plt.subplots()
+        #ax1 = sns.distplot(valuesObs, color="tab:orange", label='Observation')
+        #ax2 = sns.distplot(valuesMod, color="tab:blue", label='Model')
+        fig.hist(valuesObs, bins=histBins, color="tab:orange", 
+                 histtype='step', density=True, label='Observation')
+        fig.hist(valuesMod, bins=histBins, color="tab:blue",
+                 histtype='step', density=True, label='Model')
+        fig.set_title(self.getName())
+        if self.type == 'temperature':
+            fig.set_xlabel("Temperature in °C")
+        elif self.type == 'solar' \
+                 or self.type == 'diffuseIrridiation':
+            fig.set_xlabel('DHI in W / m$^2$')
+        elif self.type == 'globalIrridiation':
+            fig.set_xlabel('GHI in W / m$^2$')
+        elif self.type == 'windDirection':
+            fig.set_xlabel('Wind Direction in Deg')
+        else:
+            fig.set_xlabel('Wind speed in m / s')
+        fig.set_ylabel('Relative Occurences in -')
+        fig.legend()