xdat - pypi Package Compare versions

Comparing version 0.1.299 to 0.1.300

PKG-INFO

 Metadata-Version: 2.4
 Name: xdat
-Version: 0.1.299
+Version: 0.1.300
 Summary: eXtended Data Analysis Toolkit
@@ -5,0 +5,0 @@ Home-page: https://bitbucket.org/hermetric/xdat/

xdat.egg-info/PKG-INFO

 Metadata-Version: 2.4
 Name: xdat
-Version: 0.1.299
+Version: 0.1.300
 Summary: eXtended Data Analysis Toolkit
@@ -5,0 +5,0 @@ Home-page: https://bitbucket.org/hermetric/xdat/

xdat/VERSION

@@ -1,1 +0,1 @@
-0.1.299
+0.1.300

xdat/x1d.py

@@ -10,2 +10,3 @@ import inspect
 from scipy import signal
+from scipy import stats
 from munch import Munch as MunchDict
@@ -205,1 +206,19 @@
     return matches
+
+
+def x_mode_kde(a, kde_cov=0.25, grid_size=1024):
+    if len(a) == 0:
+        return None
+
+    elif len(a) == 1:
+        return a[0]
+
+    elif len(a) == 2:
+        return np.mean(a)
+
+    kde = stats.gaussian_kde(a)
+    kde.covariance_factor = lambda: kde_cov
+    kde._compute_covariance()
+
+    xs = np.linspace(a.min(), a.max(), grid_size)
+    return xs[np.argmax(kde(xs))]

xdat/xagg.py

@@ -66,2 +66,15 @@ import numpy as np
 
+class ModeKDE(_Agg):
+    def __init__(self, col_name, kde_cov=0.25, grid_size=1024):
+        super().__init__(col_name)
+        self.kde_cov = kde_cov
+        self.grid_size = grid_size
+
+        from . import x1d
+        self.x_mode_kde = x1d.x_mode_kde
+
+    def _get_func(self):
+        return lambda a: self.x_mode_kde(a, kde_cov=self.kde_cov, grid_size=self.grid_size)
+
+
 class Percentile(_Agg):
@@ -68,0 +81,0 @@ def __init__(self, col_name, percentile=50.0):

xdat/xplots.py

@@ -373,3 +373,4 @@ from contextlib import contextmanager
     df = pd.DataFrame({'Target': y_true, 'Model Score': y_score})
-    sns.histplot(data=df, x='Model Score', hue='Target', element="step", common_norm=False, stat='percent', bins=bins)
+    ax = sns.histplot(data=df, x='Model Score', hue='Target', element="step", common_norm=False, stat='percent', bins=bins)
+    ax.axvline(x=0.5, ls=':', color='grey')
 
@@ -1160,3 +1161,3 @@ title2 = 'Histogram of model scores'
 
-def plot_multi(df, kind=None, plot_func=None, x=None, y=None, var_name='variable', value_name='value', plot_on=None, group_on=None, color_on=None, annotate_on=None, cmap=None, label_on=None, style_on=None, size_on=None, figsize=(10,6), alpha=1.0, hdi_probs=(0.1, 0.25, 0.5, 0.8, 0.999), kde_cov=0.25, x_kde=False, kde_percentile=None, hist_calc='perc', hist_type='step', hist_bins=10, hist_range=None, title='', x_axis_type=None, y_axis_type=None, x_axis_fmt=None, y_axis_fmt=None, invert_yaxis=False, legend_loc='best', xlim=None, ylim=None, save_to=None, clear_folder=False, add_date=True, add_counts=True, plot_decorate_func=None, drop_na=True, as_xpptx=None, desc='', slide_note='', reset_colors=False, show=True, web=False, tooltip_on=None, **kwargs):
+def plot_multi(df, kind=None, plot_func=None, x=None, y=None, var_name='variable', value_name='value', plot_on=None, group_on=None, color_on=None, annotate_on=None, cmap=None, label_on=None, style_on=None, size_on=None, figsize=(10,6), alpha=1.0, hdi_probs=(0.1, 0.25, 0.5, 0.8, 0.999), kde_cov=0.25, x_kde=False, kde_percentile=None, hist_calc='perc', hist_type='step', hist_bins=10, hist_range=None, title='', x_axis_type=None, y_axis_type=None, x_axis_fmt=None, y_axis_fmt=None, x_axis_rotation=None, invert_yaxis=False, legend_loc='best', xlim=None, ylim=None, save_to=None, clear_folder=False, add_date=True, add_counts=True, plot_decorate_func=None, drop_na=True, as_xpptx=None, desc='', slide_note='', reset_colors=False, show=True, web=False, tooltip_on=None, **kwargs):
     """
@@ -1682,2 +1683,5 @@ :param df: input dataframe
 
+        if x_axis_rotation:
+            ax.tick_params(axis="x", labelrotation=x_axis_rotation)
+
         if invert_yaxis:
@@ -1684,0 +1688,0 @@ plt.gca().invert_yaxis()

xdat/xpptx.py

@@ -49,2 +49,5 @@ """
 
+    def __repr__(self):
+        return f'<Presentation title={self.title} fake={self.fake}>'
+
     def add_slide(self, layout_name, **kwargs):
@@ -51,0 +54,0 @@ add_slide(self.prs, layout_name, **kwargs)

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Improved metrics

Total package byte prevSize

934260

0.11%

Lines of code

9094

0.29%