iss #309 improved display by changing font size autmoatically, and ad…

…ded test to test_plot.py

brightwind/analyse/analyse.py

@@ -1112,17 +1112,17 @@ def sector_ratio(wspd_1, wspd_2, wdir, sectors=72, min_wspd=3, direction_bin_arr
     """
     Calculates the wind speed ratio of two wind speed time series and plots this ratio, averaged by direction sector,
     in a polar plot using a wind direction time series. The averaged ratio by sector can be optionally returned
-    in a pd.DataFrame.
+    in a pd.DataFrame. If provided with multiple time series, multiple subplots will be produced.
 
     If boom directions are specified, these will be overlaid on the plot. A boom direction of '-1' assumes top
     mounted and so doesn't plot.
 
-    :param wspd_1: First wind speed time series. This is divisor.
-    :type: wspd_1: pandas.Series
-    :param wspd_2: Second wind speed time series, dividend.
-    :type: wspd_2: pandas.Series
-    :param wdir: Series of wind directions
-    :type wdir: pandas.Series
+    :param wspd_1: First wind speed time series. One or more wind speeds can be accepted. This is the divisor.
+    :type: wspd_1: pandas.Series or pandas.DataFrame
+    :param wspd_2: Second wind speed time series, the dividend. One or more wind speeds can be accepted.
+    :type: wspd_2: pandas.Series or pandas.DataFrame
+    :param wdir: Time series of wind directions. One or more can be accepted.
+    :type wdir: pandas.Series or pandas.DataFrame
     :param sectors: Set the number of direction sectors. Usually 12, 16, 24, 36 or 72.
     :type sectors: int
     :param min_wspd: Minimum wind speed to be used.
@@ -1191,11 +1191,10 @@ def sector_ratio(wspd_1, wspd_2, wdir, sectors=72, min_wspd=3, direction_bin_arr
         raise ValueError('Number of anemometers is uneven. ' +
                          'Please ensure same number of anemometers in wspd_1 and wspd_2.')
 
-    if len(wd.columns) != 1:
-        if len(wd.columns) != len(ws_1.columns):
-            raise ValueError('Number of anemometers does not match number of wind vanes. ' +
-                             'Please ensure there is one direction vane per anemometer pair or ' +
-                             'include one direcion vane only to be used for all anemometer pairs.')
+    if (len(wd.columns) != 1) & (len(wd.columns) != len(ws_1.columns)):
+        raise ValueError('Number of anemometers does not match number of wind vanes. ' +
+                         'Please ensure there is one direction vane per anemometer pair or ' +
+                         'include one direcion vane only to be used for all anemometer pairs.')
 
     keys = range(len(ws_1.columns))
     sec_rats = {}
@@ -1221,13 +1220,13 @@ def sector_ratio(wspd_1, wspd_2, wdir, sectors=72, min_wspd=3, direction_bin_arr
                                                         aggregation_method='mean',
                                                         direction_bin_array=direction_bin_array,
                                                         direction_bin_labels=None, return_data=True)
-        matplotlib.pyplot.close()
+
         sec_rat_dist = sec_rat_dist.rename('Mean_Sector_Ratio').to_frame()
         sec_rats_dists[sensor_pair] = sec_rat_dist
 
         fig = plt.plot_sector_ratio(sec_ratio=sec_rats, wdir=wdir, sec_ratio_dist=sec_rats_dists, col_names=col_names,
-                                boom_dir_1=boom_dir_1, boom_dir_2=boom_dir_2,
-                                radial_limits=radial_limits, figure_size=figure_size)
+                                    boom_dir_1=boom_dir_1, boom_dir_2=boom_dir_2,
+                                    radial_limits=radial_limits, figure_size=figure_size)
 
     if return_data:
         if len(sec_rats_dists) == 1:

brightwind/analyse/plot.py

@@ -21,7 +21,8 @@
            'plot_scatter',
            'plot_scatter_wspd',
            'plot_scatter_wdir',
-           'plot_scatter_by_sector']
+           'plot_scatter_by_sector',
+           'plot_sector_ratio']
 #
 # try:
 #     if 'Gotham Rounded' in \
@@ -1009,6 +1010,8 @@ def plot_sector_ratio(sec_ratio, wdir, sec_ratio_dist, col_names, boom_dir_1=-1,
     :type boom_dir_2: float
     :param radial_limits: the min and max values of the radial axis. Defaults to +0.05 of max ratio and -0.1 of min.
     :type radial_limits: tuple or list
+    :param figure_size: Figure size in tuple format (width, height)
+    :type figure_size: tuple
 
     :returns A speed ratio plot showing average speed ratio by sector and scatter of individual data points.
 
@@ -1022,7 +1025,7 @@ def plot_sector_ratio(sec_ratio, wdir, sec_ratio_dist, col_names, boom_dir_1=-1,
     if len(wdir.columns) != 1:
         if len(wdir.columns) != len(sec_ratio):
             raise ValueError('Number of anemometers does not match number of wind vanes. Please ensure there is one ' +
-                             'direction vane per anemometer pair or include one direcion vane only to be used for ' +
+                             'direction vane per anemometer pair or include one direction vane only to be used for ' +
                              'all anemometer pairs.')
 
     row, col = _get_best_row_col_number_for_subplot(len(sec_ratio))
@@ -1043,13 +1046,14 @@ def plot_sector_ratio(sec_ratio, wdir, sec_ratio_dist, col_names, boom_dir_1=-1,
 
         _plot_sector_ratio_subplot(sec_ratio[pair].loc[common_idx], wd.loc[common_idx], sec_ratio_dist[pair],
                                    col_names[pair], boom_dir_1=boom_dir_1, boom_dir_2=boom_dir_2,
-                                   ax=axes[pair], radial_limits=radial_limits)
+                                   ax=axes[pair], radial_limits=radial_limits, figure_size=figure_size,
+                                   subplot_dimension=[row,col])
         plt.close()
 
     return fig
 
 def _plot_sector_ratio_subplot(sec_ratio, wdir, sec_ratio_dist, col_names, boom_dir_1=-1, boom_dir_2=-1,
-                               ax=None, radial_limits=None):
+                               ax=None, radial_limits=None, figure_size=(10,10), subplot_dimension=(1,1)):
     """
     Accepts a ratio of anemometers per sector, a wind direction, a distribution of anemometer ratios per sector,
     along with 2 anemometer names, and returns an axis object to plot the speed ratio by sector. Optionally can
@@ -1068,10 +1072,14 @@ def _plot_sector_ratio_subplot(sec_ratio, wdir, sec_ratio_dist, col_names, boom_
     :type boom_dir_1: float
     :param boom_dir_2: Boom direction in degrees of speed_col_name_2. Defaults to -1.
     :type boom_dir_2: float
-    :param ax: Subplot axes to which the subplot is assinged in a plot. If None subplot is displayed on its own.
+    :param ax: Subplot axes to which the subplot is assigned in a plot. If None subplot is displayed on its own.
     :type ax: matplotlib.axes._subplots.AxesSubplot or None
     :param radial_limits: the min and max values of the radial axis. Defaults to +0.05 of max ratio and -0.1 of min.
     :type radial_limits: tuple or list
+    :param figure_size: Size of radial plot. Defaults to (10,10).
+    :type figure_size: tuple
+    :param subplot_dimension: Dimensions of subplots by (row,column), if applicable. Defaults to 1 row x 1 column.
+    :type subplot_dimension: tuple or list
 
     :returns A speed ratio plot showing average speed ratio by sector and scatter of individual data points.
 
@@ -1119,9 +1127,12 @@ def _plot_sector_ratio_subplot(sec_ratio, wdir, sec_ratio_dist, col_names, boom_
                                                                            col_names[0], boom_dir_1)
         annotate = True
     if annotate:
-        ax.set_title(annotation_text, y=-0.1, fontsize=plt.rcParams['ytick.labelsize'])
+        ax.set_title(annotation_text, y=0.004*min(figure_size)/subplot_dimension[0]/subplot_dimension[1]-0.15)
     ax.scatter(np.radians(wdir), sec_ratio, color=COLOR_PALETTE.secondary, alpha=0.3, s=1)
 
+    for item in ([ax.title] + ax.get_xticklabels() + ax.get_yticklabels()):
+        item.set_fontsize(min(figure_size)/subplot_dimension[0]/subplot_dimension[1]+2.5)
+
     return ax
 
 

tests/test_plot.py

@@ -6,6 +6,24 @@
 WSPD_COLS = ['Spd80mN', 'Spd80mS', 'Spd60mN', 'Spd60mS', 'Spd40mN', 'Spd40mS']
 WDIR_COLS = ['Dir78mS', 'Dir58mS', 'Dir38mS']
 
+def test_plot_sector_ratio():
+    wspd_1 = bw.utils.utils._convert_df_to_series(DATA['Spd80mN']).dropna()
+    wspd_2 = bw.utils.utils._convert_df_to_series(DATA['Spd80mS']).dropna()
+    wdir = bw.utils.utils._convert_df_to_series(DATA['Dir78mS']).dropna()
+
+    sec_rats = {}
+    sec_rats_dists = {}
+
+    sec_rat = bw.analyse.analyse._calc_ratio(wspd_1, wspd_2, 3)
+    common_idx = sec_rat.index.intersection(wdir.index)
+    sec_rat_plot, sec_rat_dist = bw.dist_by_dir_sector(sec_rat.loc[common_idx], wdir.loc[common_idx], return_data=True)
+    sec_rat_dist = sec_rat_dist.rename('Mean_Sector_Ratio').to_frame()
+    sec_rats[0] = sec_rat
+    sec_rats_dists[0] = sec_rat_dist
+
+    fig = bw.plot_sector_ratio(sec_rats, DATA['Dir78mS'], sec_rats_dists, [DATA['Spd80mN'].name, DATA['Spd80mS'].name],
+                         boom_dir_1=-1, boom_dir_2=-1, radial_limits=None, figure_size=(10, 10))
+
 
 def test_plot_timeseries():
     bw.plot_timeseries(DATA[['Spd40mN', 'Spd60mS', 'T2m']])