Merge pull request #115 from bubbleli/xueqi_proportional_data

Added plotting function for unpaired proportional data

Author: josesho

dabest/_api.py

@@ -5,7 +5,7 @@
 
 
 def load(data, idx, x=None, y=None, paired=False, id_col=None,
-        ci=95, resamples=5000, random_seed=12345):
+        ci=95, resamples=5000, random_seed=12345, proportional=False):
     '''
     Loads data in preparation for estimation statistics.
 
@@ -34,6 +34,7 @@ def load(data, idx, x=None, y=None, paired=False, id_col=None,
         This integer is used to seed the random number generator during
         bootstrap resampling, ensuring that the confidence intervals
         reported are replicable.
+    proportional : boolean, default False. 
 
     Returns
     -------
@@ -62,4 +63,4 @@ def load(data, idx, x=None, y=None, paired=False, id_col=None,
     '''
     from ._classes import Dabest
 
-    return Dabest(data, idx, x, y, paired, id_col, ci, resamples, random_seed)
+    return Dabest(data, idx, x, y, paired, id_col, ci, resamples, random_seed, proportional)

dabest/_classes.py

@@ -10,7 +10,7 @@ class Dabest(object):
     """
 
     def __init__(self, data, idx, x, y, paired, id_col, ci, resamples,
-                random_seed):
+                random_seed, proportional):
 
         """
         Parses and stores pandas DataFrames in preparation for estimation
@@ -30,6 +30,7 @@ def __init__(self, data, idx, x, y, paired, id_col, ci, resamples,
         self.__is_paired   = paired
         self.__resamples   = resamples
         self.__random_seed = random_seed
+        self.__proportional = proportional
 
         # Make a copy of the data, so we don't make alterations to it.
         data_in = data.copy()
@@ -183,7 +184,8 @@ def __init__(self, data, idx, x, y, paired, id_col, ci, resamples,
 
         EffectSizeDataFrame_kwargs = dict(ci=ci, is_paired=paired,
                                            random_seed=random_seed,
-                                           resamples=resamples)
+                                           resamples=resamples,
+                                           proportional=proportional)
 
         self.__mean_diff    = EffectSizeDataFrame(self, "mean_diff",
                                                 **EffectSizeDataFrame_kwargs)
@@ -535,6 +537,15 @@ def _plot_data(self):
         """
         return self.__plot_data
 
+    
+    @property
+    def proportional(self):
+        """
+        Returns the proportional parameter
+        class.
+        """
+        return self.__proportional
+
     @property
     def _all_plot_groups(self):
         """
@@ -546,7 +557,6 @@ def _all_plot_groups(self):
 
 
 
-
 class TwoGroupsEffectSize(object):
 
     """
@@ -1313,7 +1323,7 @@ class EffectSizeDataFrame(object):
     sizes for several comparisons."""
 
     def __init__(self, dabest, effect_size,
-                 is_paired, ci=95,
+                 is_paired, ci=95, proportional=False,
                  resamples=5000, 
                  permutation_count=5000,
                  random_seed=12345):
@@ -1329,6 +1339,7 @@ def __init__(self, dabest, effect_size,
         self.__resamples         = resamples
         self.__permutation_count = permutation_count
         self.__random_seed       = random_seed
+        self.__proportional      = proportional
 
 
     def __pre_calc(self):
@@ -1501,10 +1512,10 @@ def plot(self, color_col=None,
 
             raw_marker_size=6, es_marker_size=9,
 
-            swarm_label=None, contrast_label=None,
-            swarm_ylim=None, contrast_ylim=None,
+            swarm_label=None, barchart_label=None, contrast_label=None,
+            swarm_ylim=None, barchart_ylim=None, contrast_ylim=None,
 
-            custom_palette=None, swarm_desat=0.5, halfviolin_desat=1,
+            custom_palette=None, swarm_desat=0.5, barchart_desat=0.5, halfviolin_desat=1,
             halfviolin_alpha=0.8, 
 
             float_contrast=True,
@@ -1516,6 +1527,8 @@ def plot(self, color_col=None,
             dpi=100,
             ax=None,
 
+
+            barchartplot_kwargs=None,
             swarmplot_kwargs=None,
             violinplot_kwargs=None,
             slopegraph_kwargs=None,
@@ -1682,19 +1695,35 @@ def plot(self, color_col=None,
 
         """
 
-        from .plotter import EffectSizeDataFramePlotter
+        from .plotter import EffectSizeDataFramePlotter, ProportionalDataFramePlotter
+
 
         if hasattr(self, "results") is False:
             self.__pre_calc()
 
+        if self.__proportional:
+            raw_marker_size = 0.01
+            
         all_kwargs = locals()
         del all_kwargs["self"]
 
+        if self.__proportional:
+            out = ProportionalDataFramePlotter(self, **all_kwargs)
+            return out
+
         out = EffectSizeDataFramePlotter(self, **all_kwargs)
 
         return out
 
 
+    @property
+    def proportional(self):
+        """
+        Returns the proportional parameter
+        class.
+        """
+        return self.__proportional
+
     @property
     def results(self):
         """Prints all pairwise comparisons nicely."""
@@ -1780,7 +1809,14 @@ def dabest_obj(self):
         class.
         """
         return self.__dabest_obj
-        
+
+    @property
+    def proportional(self):
+        """
+        Returns the proportional parameter
+        class.
+        """
+        return self.__proportional
 
     @property
     def lqrt(self):
@@ -1795,6 +1831,7 @@ def lqrt(self):
             self.__calc_lqrt()
             return self.__lqrt_results
 
+