Merge pull request #243 from jkittner/calm_fix

fix y-axis scaling when `calm_limit` is provided

Author: ocefpaf

tests/output/oo/test_filled_with_colormap_calm_limit.png

@@ -45,6 +45,24 @@ def test_windrose_stacked_histogram_not_normed_binned():
     return ax.figure
 
 
+@pytest.mark.mpl_image_compare(baseline_dir="output/oo", tolerance=6.5)
+def test_windrose_stacked_histogram_not_normed_binned_calm_limit():
+    # Another stacked histogram representation, not normed, with bins limits and a calm limit
+    ax = WindroseAxes.from_ax()
+    ax.box(wd, ws, bins=bins, calm_limit=0.2)
+    ax.set_legend()
+    return ax.figure
+
+
+@pytest.mark.mpl_image_compare(baseline_dir="output/oo", tolerance=15.5)
+def test_windrose_stacked_histogram_normed_calm_limit():
+    # windrose like a stacked histogram with normed (displayed in percent) results and a calm limit
+    ax = WindroseAxes.from_ax()
+    ax.bar(wd, ws, normed=True, opening=0.8, edgecolor="white", calm_limit=0.2)
+    ax.set_legend()
+    return ax.figure
+
+
 @pytest.mark.mpl_image_compare(baseline_dir="output/oo")
 def test_filled_with_colormap():
     # A windrose in filled representation, with a controlled colormap
@@ -54,6 +72,15 @@ def test_filled_with_colormap():
     return ax.figure
 
 
+@pytest.mark.mpl_image_compare(baseline_dir="output/oo")
+def test_filled_with_colormap_calm_limit():
+    # A windrose in filled representation, with a controlled colormap and a calm limit
+    ax = WindroseAxes.from_ax()
+    ax.contourf(wd, ws, bins=bins, cmap=cm.hot, calm_limit=0.2)
+    ax.set_legend()
+    return ax.figure
+
+
 @pytest.mark.mpl_image_compare(baseline_dir="output/oo")
 def test_filled_with_colormap_contours():
     # Same as above, but with contours over each filled region...
@@ -64,6 +91,16 @@ def test_filled_with_colormap_contours():
     return ax.figure
 
 
+@pytest.mark.mpl_image_compare(baseline_dir="output/oo")
+def test_filled_with_colormap_contours_calm_limit():
+    # Same as above, but with contours over each filled region...
+    ax = WindroseAxes.from_ax()
+    ax.contourf(wd, ws, bins=bins, cmap=cm.hot, calm_limit=0.2)
+    ax.contour(wd, ws, bins=bins, colors="black", calm_limit=0.2)
+    ax.set_legend()
+    return ax.figure
+
+
 @pytest.mark.mpl_image_compare(baseline_dir="output/oo")
 def test_without_filled_with_colormap_contours():
     ax = WindroseAxes.from_ax()
@@ -72,6 +109,14 @@ def test_without_filled_with_colormap_contours():
     return ax.figure
 
 
+@pytest.mark.mpl_image_compare(baseline_dir="output/oo")
+def test_without_filled_with_colormap_contours_calm_limit():
+    ax = WindroseAxes.from_ax()
+    ax.contour(wd, ws, bins=bins, cmap=cm.hot, lw=3, calm_limit=0.2)
+    ax.set_legend()
+    return ax.figure
+
+
 @pytest.mark.mpl_image_compare(baseline_dir="output/oo")
 def test_pdf():
     ax = WindAxes.from_ax()

tests/output/oo/test_filled_with_colormap_contours_calm_limit.png

@@ -14,8 +14,6 @@
 DIR_DEFAULT = "direction"
 FIGSIZE_DEFAULT = (8, 8)
 DPI_DEFAULT = 80
-CALM_CIRCLE_COLOR = "red"
-CALM_CIRCLE_ALPHA = 0.4
 DEFAULT_THETA_LABELS = ["E", "N-E", "N", "N-W", "W", "S-W", "S", "S-E"]
 
 
@@ -309,6 +307,20 @@ def _init_plot(self, direction, var, **kwargs):
             Any argument accepted by :obj:`matplotlib.pyplot.plot`.
         """
 
+        normed = kwargs.pop("normed", False)
+        blowto = kwargs.pop("blowto", False)
+
+        # Calm condition, mask data if needed
+        calm_limit = kwargs.pop("calm_limit", None)
+        total = len(var)
+        if calm_limit is not None:
+            mask = var > calm_limit
+            self.calm_count = len(var) - np.count_nonzero(mask)
+            if normed:
+                self.calm_count = self.calm_count * 100 / len(var)
+            var = var[mask]
+            direction = direction[mask]
+
         # if weibull factors are entered overwrite direction and var
         if "weibull_factors" in kwargs or "mean_values" in kwargs:
             if "weibull_factors" in kwargs and "mean_values" in kwargs:
@@ -383,19 +395,6 @@ def _init_plot(self, direction, var, **kwargs):
         # Building the angles list
         angles = np.arange(0, -2 * np.pi, -2 * np.pi / nsector) + np.pi / 2
 
-        normed = kwargs.pop("normed", False)
-        blowto = kwargs.pop("blowto", False)
-
-        # Calm condition
-        calm_limit = kwargs.pop("calm_limit", None)
-        if calm_limit is not None:
-            mask = var > calm_limit
-            self.calm_count = len(var) - np.count_nonzero(mask)
-            if normed:
-                self.calm_count = self.calm_count * 100 / len(var)
-            var = var[mask]
-            direction = direction[mask]
-
         # Set the global information dictionary
         self._info["dir"], self._info["bins"], self._info["table"] = histogram(
             direction,
@@ -404,25 +403,15 @@ def _init_plot(self, direction, var, **kwargs):
             nsector,
             normed,
             blowto,
+            total,
         )
 
         return bins, nbins, nsector, colors, angles, kwargs
 
     def _calm_circle(self):
-        """
-        Draw the calm centered circle
-        and return the initial offset for plots methods
-        """
+        """Draw the calm centered circle"""
         if self.calm_count and self.calm_count > 0:
-            circle = mpl.patches.Circle(
-                (0.0, 0.0),
-                self.calm_count,
-                transform=self.transData._b,
-                color=CALM_CIRCLE_COLOR,
-                alpha=CALM_CIRCLE_ALPHA,
-            )
-            self.add_artist(circle)
-        return self.calm_count or 0
+            self.set_rorigin(-(np.sqrt(self.calm_count / np.pi)))
 
     def contour(self, direction, var, **kwargs):
         """
@@ -440,9 +429,9 @@ def contour(self, direction, var, **kwargs):
 
         Other Parameters
         ----------------
-        sector : integer, optional
+        nsector : integer, optional
             number of sectors used to compute the windrose table. If not set,
-            nsectors=16, then each sector will be 360/16=22.5°, and the
+            nsector=16, then each sector will be 360/16=22.5°, and the
             resulting computed table will be aligned with the cardinals points.
         bins : 1D array or integer, optional
             number of bins, or a sequence of bins variable. If not set, bins=6,
@@ -482,10 +471,11 @@ def contour(self, direction, var, **kwargs):
             ),
         )
 
-        offset = self._calm_circle()
+        self._calm_circle()
+        origin = 0
         for i in range(nbins):
-            val = vals[i, :] + offset
-            offset += vals[i, :]
+            val = vals[i, :] + origin
+            origin += vals[i, :]
             zorder = ZBASE + nbins - i
             patch = self.plot(angles, val, color=colors[i], zorder=zorder, **kwargs)
             self.patches_list.extend(patch)
@@ -509,7 +499,7 @@ def contourf(self, direction, var, **kwargs):
         ----------------
         nsector: integer, optional
             number of sectors used to compute the windrose table. If not set,
-            nsectors=16, then each sector will be 360/16=22.5°, and the
+            nsector=16, then each sector will be 360/16=22.5°, and the
             resulting computed table will be aligned with the cardinals points.
         bins : 1D array or integer, optional
             number of bins, or a sequence of bins variable. If not set, bins=6,
@@ -550,10 +540,11 @@ def contourf(self, direction, var, **kwargs):
                 ),
             ),
         )
-        offset = self._calm_circle()
+        self._calm_circle()
+        origin = 0
         for i in range(nbins):
-            val = vals[i, :] + offset
-            offset += vals[i, :]
+            val = vals[i, :] + origin
+            origin += vals[i, :]
             zorder = ZBASE + nbins - i
             patch = self.fill(
                 np.append(angles, 0),
@@ -582,7 +573,7 @@ def bar(self, direction, var, **kwargs):
         ----------------
         nsector : integer, optional
             number of sectors used to compute the windrose table. If not set,
-            nsectors=16, then each sector will be 360/16=22.5°, and the
+            nsector=16, then each sector will be 360/16=22.5°, and the
             resulting computed table will be aligned with the cardinals points.
         bins : 1D array or integer, optional
             number of bins, or a sequence of bins variable. If not set, bins=6
@@ -624,17 +615,17 @@ def bar(self, direction, var, **kwargs):
         dtheta = 2 * np.pi / nsector
         opening = dtheta * opening
 
-        offs = self._calm_circle()
+        self._calm_circle()
 
         for j in range(nsector):
-            offset = offs
+            origin = 0
             for i in range(nbins):
                 if i > 0:
-                    offset += self._info["table"][i - 1, j]
+                    origin += self._info["table"][i - 1, j]
                 val = self._info["table"][i, j]
                 zorder = ZBASE + nbins - i
                 patch = mpl.patches.Rectangle(
-                    (angles[j] - opening / 2, offset),
+                    (angles[j] - opening / 2, origin),
                     opening,
                     val,
                     facecolor=colors[i],
@@ -663,7 +654,7 @@ def box(self, direction, var, **kwargs):
         ----------------
         nsector: integer, optional
             number of sectors used to compute the windrose table. If not set,
-            nsectors=16, then each sector will be 360/16=22.5°, and the
+            nsector=16, then each sector will be 360/16=22.5°, and the
             resulting computed table will be aligned with the cardinals points.
         bins : 1D array or integer, optional
             number of bins, or a sequence of bins variable. If not set, bins=6
@@ -698,17 +689,17 @@ def box(self, direction, var, **kwargs):
                 raise ValueError("edgecolor must be a string color")
         opening = np.linspace(0.0, np.pi / 16, nbins)
 
-        offs = self._calm_circle()
+        self._calm_circle()
 
         for j in range(nsector):
-            offset = offs
+            origin = 0
             for i in range(nbins):
                 if i > 0:
-                    offset += self._info["table"][i - 1, j]
+                    origin += self._info["table"][i - 1, j]
                 val = self._info["table"][i, j]
                 zorder = ZBASE + nbins - i
                 patch = mpl.patches.Rectangle(
-                    (angles[j] - opening[i] / 2, offset),
+                    (angles[j] - opening[i] / 2, origin),
                     opening[i],
                     val,
                     facecolor=colors[i],
@@ -769,7 +760,7 @@ def pdf(
         return (self, params)
 
 
-def histogram(direction, var, bins, nsector, normed=False, blowto=False):
+def histogram(direction, var, bins, nsector, normed=False, blowto=False, total=0):
     """
     Returns an array where, for each sector of wind
     (centred on the north), we have the number of time the wind comes with a
@@ -819,7 +810,7 @@ def histogram(direction, var, bins, nsector, normed=False, blowto=False):
     # and remove the last col
     table = table[:, :-1]
     if normed:
-        table = table * 100 / table.sum()
+        table = table * 100 / total
 
     return dir_edges, var_bins, table