Added GeoArray.show_histogram().

geoarray/baseclasses.py

@@ -1213,6 +1213,43 @@ class GeoArray(object):
         return m
 
 
+    def show_histogram(self, band=1, bins=200, normed=False, exclude_nodata=True, vmin=None, vmax=None, figsize=None):
+        # type: (int, int, bool, bool, float, float, tuple) -> None
+
+        """Show a histogram of a given band.
+
+        :param band:            the band to be used to plot the histogram
+        :param bins:            number of bins to plot (default: 200)
+        :param normed:          whether to normalize the y-axis or not (default: False)
+        :param exclude_nodata:  whether tp exclude nodata value from the histogram
+        :param vmin:            minimum value for the x-axis of the histogram
+        :param vmax:            maximum value for the x-axis of the histogram
+        :param figsize:         figure size (tuple)
+        """
+
+        if self.nodata is not None and exclude_nodata:
+            data = np.ma.masked_equal(self[band], self.nodata)
+            data = data.compressed()
+        else:
+            data = self[band]
+
+        vmin = vmin if vmin is not None else np.percentile(data, 1)
+        vmax = vmax if vmax is not None else np.percentile(data, 99)
+        image2plot = data
+
+        plt.figure(figsize=figsize)
+        plt.hist(list(image2plot.flat), normed=normed, bins=bins, color='gray', range=[vmin, vmax])
+        plt.xlabel('Pixel value')
+        plt.ylabel('Probabilty' if normed else 'Count')
+        plt.show()
+
+        if not self.q:
+            print('STD:', np.std(data))
+            print('MEAN:', np.mean(data))
+            print('2 % percentile:', np.percentile(data, 2))
+            print('98 % percentile:', np.percentile(data, 98))
+
+
     def get_mapPos(self, mapBounds, mapBounds_prj, band2get=None, out_prj=None, arr_gt=None, arr_prj=None, fillVal=None,
                    rspAlg='near', progress=None, v=False): # TODO implement slice for indexing bands
         # type: (tuple, str, int, str, tuple, str, int, str, bool, bool) -> (np.ndarray, tuple, str)