bigger fonts

__init__.py

@@ -1,3 +1,6 @@
+import matplotlib as mpl
+mpl.rc('font', size=14)
+
 from matplotlib import use as plt_use
 import matplotlib.pyplot as plt
 from pandas.plotting import register_matplotlib_converters

core/compare_infill.py

@@ -125,7 +125,7 @@ def _plot_comparison(
                       (nse, ln_nse, kge))
         title_str += (('Pearson correlation: %0.2f, Spearman correlation: '
                        '%0.2f)') % (correl_pe, correl_sp))
-        plt.suptitle(title_str)
+        plt.suptitle(title_str, y=1.005)
         infill_ax.set_xlim(self.infill_dates[0], self.infill_dates[-1])
         plt.grid()
         plt.legend(framealpha=0.5, loc=0)
@@ -148,14 +148,12 @@ def _plot_infill_vs_obs_cdf_time_sers(
         plt.figure(figsize=(6, 5.5))
         infill_ax = plt.subplot(111)
 
-        infill_ax.plot(
+        infill_ax.scatter(
             infill_probs,
             orig_probs,
             alpha=alpha,
-            lw=lw,
-            ls='-',
             marker='o',
-            ms=lw)
+            s=lw)
 
         infill_ax.plot(
             orig_probs,
@@ -286,7 +284,7 @@ def _plot_obs_vs_infill_dists(
                           (vals_wtn_rng, 100 * (1.0 - self.ks_alpha)))
             title_str += (('\nOut of %d, %d values below and %d above '
                            'limits') % (n_vals, n_ks_fl_l, n_ks_fu_g))
-            plt.suptitle(title_str)
+            plt.suptitle(title_str, y=1.05)
 
             _ = out_compar_plot_loc[:-(len(self.out_fig_fmt) + 1)]
             out_freq_compare_loc = _ + '_obs_probs_cdf.' + self.out_fig_fmt
@@ -494,7 +492,7 @@ def plot_all(self, args):
          out_add_info_df,
          self.update_summary_df_only) = args
 
-        lw, alpha = 0.8, 0.7
+        lw, alpha = 1.4, 0.7
 
         interp_data_idxs = logical_or(
             isnan(act_var),

ecops/plot_ecops.py

@@ -201,7 +201,7 @@ def _plot_ecop(
             ecop_raw_ax.set_xlim(0, 1)
             ecop_raw_ax.set_ylim(0, 1)
             ecop_raw_ax.grid()
-            ecop_raw_ax.set_title('Empirical Copula - Scatter')
+            ecop_raw_ax.set_title('Empirical Copula - Scatter', size=12)
 
             # Empirical copula - gridded
             cop_dict = bi_var_copula(prob_i, prob_j, self.cop_bins)
@@ -251,12 +251,16 @@ def _plot_ecop(
 
             emp_title_str = ''
             emp_title_str += 'Empirical copula - Gridded'
-            emp_title_str += ('\n(asymm_1: %1.1E, asymm_2: %1.1E)' %
-                              (emp_asymm_1, emp_asymm_2))
-            emp_title_str += ('\n(asymm_1: %s, asymm_2: %s)' %
-                              (asymm_1_str, asymm_2_str))
 
-            ecop_grid_ax.set_title(emp_title_str)
+            emp_title_str += (
+                '\n(asymm_1: %1.1E, asymm_2: %1.1E)' %
+                (emp_asymm_1, emp_asymm_2))
+
+            emp_title_str += (
+                '\n(asymm_1: %s, asymm_2: %s)' %
+                (asymm_1_str, asymm_2_str))
+
+            ecop_grid_ax.set_title(emp_title_str, size=12)
 
             # Corresponding gaussian grid
             # TODO: adjust for precipitation case i.e. 0 and 1 ppt
@@ -282,13 +286,16 @@ def _plot_ecop(
 
             gau_title_str = ''
             gau_title_str += 'Gaussian copula'
-            gau_title_str += (('\n(min asymm_1: %1.1E, '
-                               'max asymm_1: %1.1E)') % (
-                                   min_asymm_1, max_asymm_1))
-            gau_title_str += (('\n(min asymm_2: %1.1E, '
-                               'max asymm_2: %1.1E)') % (
-                                   min_asymm_2, max_asymm_2))
-            gau_cop_ax.set_title(gau_title_str)
+
+            gau_title_str += (
+                ('\nasymm_1 (min, max): %1.1E, %1.1E') %
+                (min_asymm_1, max_asymm_1))
+
+            gau_title_str += (
+                ('\nasymm_2 (min, max): %1.1E, %1.1E') %
+                (min_asymm_2, max_asymm_2))
+
+            gau_cop_ax.set_title(gau_title_str, size=12)
 
             leg_ax.set_axis_off()
             cb = plt.colorbar(_cb, cax=cax)
@@ -310,9 +317,10 @@ def _plot_ecop(
                           (prob_i.shape[0], correl, self.cop_bins))
             title_str += ('\n(rho: %0.3f, tau: %0.3f, lag: %d)' % (
                 correl, tau, curr_lag))
-            plt.suptitle(title_str)
 
-            plt.subplots_adjust(hspace=0.15, wspace=1.5, top=0.75)
+            plt.suptitle(title_str, y=1.005)
+
+            plt.subplots_adjust(hspace=0.15, wspace=1.2, top=0.75)
 
             out_ecop_fig_name = 'ecop_%s_vs_%s.%s' % (
                     infill_stn, other_stn, self.out_fig_fmt)

misc/plot_stats.py

@@ -62,14 +62,14 @@ def plot_stats(self):
 
         self.stats_df = self.stats_df.apply(lambda x: to_numeric(x))
 
-        tick_font_size = 5
+        tick_font_size = 6
         stats_arr = self.stats_df.values
         n_stns = stats_arr.shape[0]
         n_cols = stats_arr.shape[1]
 
-        _, stats_ax = plt.subplots(1,
-                                     1,
-                                     figsize=(0.45 * n_stns, 0.8 * n_cols))
+        _, stats_ax = plt.subplots(
+            1, 1, figsize=(0.45 * n_stns, 0.8 * n_cols))
+
         stats_ax.matshow(stats_arr.T,
                          cmap=plt.get_cmap('Blues'),
                          vmin=0,
@@ -83,7 +83,8 @@ def plot_stats(self):
                           ('%0.2f' % stats_arr[s[0], s[1]]).rstrip('0'),
                           va='center',
                           ha='center',
-                          fontsize=tick_font_size)
+                          fontsize=tick_font_size,
+                          rotation=45)
 
         stats_ax.set_xticks(list(range(0, n_stns)))
         stats_ax.set_xticklabels(self.stats_df.index)

misc/summary.py

@@ -347,7 +347,7 @@ def plot_summary(self):
 
         clr_alpha = 0.4
         n_segs = 100
-        font_size = 6
+        font_size = 8
         max_columns_per_fig = 15
 
         cmap_name = 'my_clr_list'

nebors/nrst_nebs.py

@@ -276,7 +276,7 @@ def _plot_nrst_stns(args):
          out_nebor_plots_dir,
          out_fig_dpi) = args
 
-        tick_font_size = 5
+        tick_font_size = 7
         n_nebs = len(nebs)
 
         nrst_stns_ax = plt.subplot(111)
@@ -316,15 +316,14 @@ def _plot_nrst_stns(args):
 
         adjust_text(plt_texts, only_move={'points': 'y', 'text': 'y'})
         nrst_stns_ax.grid()
-        nrst_stns_ax.set_xlabel('Eastings', size=tick_font_size)
-        nrst_stns_ax.set_ylabel('Northings', size=tick_font_size)
+        nrst_stns_ax.set_xlabel('Eastings')
+        nrst_stns_ax.set_ylabel('Northings')
         nrst_stns_ax.legend(framealpha=0.5, loc=0)
 
         nrst_stns_ax.set_xlim(0.995 * xs.min(), 1.005 * xs.max())
         nrst_stns_ax.set_ylim(0.995 * ys.min(), 1.005 * ys.max())
 
-        plt.setp(nrst_stns_ax.get_xticklabels(), size=tick_font_size)
-        plt.setp(nrst_stns_ax.get_yticklabels(), size=tick_font_size)
+        plt.setp(nrst_stns_ax.get_xticklabels(), rotation=90)
 
         plt.savefig(
             os_join(out_nebor_plots_dir, '%s_neibor_stns.png' % infill_stn),

nebors/rank_corr_nebs.py

@@ -21,7 +21,6 @@
 from adjustText import adjust_text
 from pandas import DataFrame, Series
 
-# from .nrst_nebs import NrstStns
 from ..misc.misc_ftns import (
     get_norm_rand_symms, get_lag_ser, as_err, ret_mp_idxs)
 from ..cyth import get_asymms_sample, get_corrcoeff
@@ -508,7 +507,7 @@ def _plot_hi_corr_stns(args):
          out_fig_dpi,
          lags) = args
 
-        tick_font_size = 5
+        tick_font_size = 7
         n_nebs = len(nebs)
 
         hi_corr_stns_ax = plt.subplot(111)
@@ -557,15 +556,14 @@ def _plot_hi_corr_stns(args):
 
         adjust_text(plt_texts, only_move={'points': 'y', 'text': 'y'})
         hi_corr_stns_ax.grid()
-        hi_corr_stns_ax.set_xlabel('Eastings', size=tick_font_size)
-        hi_corr_stns_ax.set_ylabel('Northings', size=tick_font_size)
+        hi_corr_stns_ax.set_xlabel('Eastings')
+        hi_corr_stns_ax.set_ylabel('Northings')
         hi_corr_stns_ax.legend(framealpha=0.5, loc=0)
 
         hi_corr_stns_ax.set_xlim(0.999 * xs.min(), 1.001 * xs.max())
         hi_corr_stns_ax.set_ylim(0.999 * ys.min(), 1.001 * ys.max())
 
-        plt.setp(hi_corr_stns_ax.get_xticklabels(), size=tick_font_size)
-        plt.setp(hi_corr_stns_ax.get_yticklabels(), size=tick_font_size)
+        plt.setp(hi_corr_stns_ax.get_xticklabels(), rotation=90)
 
         plt.savefig(
             os_join(out_rank_corr_plots_dir,
@@ -588,7 +586,7 @@ def _plot_long_term_corr(args):
          lags) = args
 
         # TODO: have 15 stns at max on a row
-        tick_font_size = 6
+        tick_font_size = 8
 
         corrs_ctr_ser[isnan(corrs_ctr_ser)] = 0
 
@@ -613,7 +611,8 @@ def _plot_long_term_corr(args):
                         int(lags[neb])),
                     va='center',
                     ha='center',
-                    fontsize=tick_font_size)
+                    fontsize=tick_font_size,
+                    rotate=45)
 
             else:
                 corrs_ax.text(
@@ -623,7 +622,8 @@ def _plot_long_term_corr(args):
                         corrs_ser[neb], int(corrs_ctr_ser[neb])),
                     va='center',
                     ha='center',
-                    fontsize=tick_font_size)
+                    fontsize=tick_font_size,
+                    rotate=45)
 
         corrs_ax.set_yticks([])
         corrs_ax.set_yticklabels([])

test/normcopula_infill_template.py

@@ -132,22 +132,8 @@
 #     infill_cop.max_time_lag_corr = 1
 #     infill_cop.cut_cdf_thresh = 0.5
 
-#     _beg = timeit.default_timer()
 #     infill_cop.cmpt_plot_nrst_stns()
-#     _end = timeit.default_timer()
-#     _tot = (_end - _beg)
-#     print('Took %0.4f secs!' % _tot)
-#
-#     time.sleep(10)
-#
-#     _beg = timeit.default_timer()
 #     infill_cop.cmpt_plot_rank_corr_stns()
-#     _end = timeit.default_timer()
-#     _tot = (_end - _beg)
-#     print('Took %0.4f secs!' % _tot)
-#
-#     time.sleep(10)
-
 #     infill_cop.plot_stats()
 #     infill_cop.plot_ecops()
     infill_cop.infill()