Merge pull request #23 from INGEOTEC/develop

Version - 0.1.9

Author: mgraffg

CompStats/__init__.py

@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-__version__ = '0.1.8'
+__version__ = '0.1.9'
 from CompStats.bootstrap import StatisticSamples
 from CompStats.measurements import CI, SE, difference_p_value
 from CompStats.performance import performance, difference, all_differences, plot_performance, plot_difference

CompStats/interface.py

@@ -606,7 +606,8 @@ def dataframe(self, value_name:str='Score',
                   alg_legend:str='Algorithm',
                   sig_legend:str='Significant',
                   perf_names:str=None,
-                  CI:float=0.05):
+                  right:bool=True,
+                  alpha:float=0.05):
         """Dataframe"""
         if perf_names is None and isinstance(self.best, np.ndarray):
             perf_names = [f'{alg}({k})'
@@ -617,18 +618,18 @@ def dataframe(self, value_name:str='Score',
                        perf_names=perf_names)
         df[sig_legend] = False
         if isinstance(self.best, str):
-            for name, p in self.p_value().items():
-                if p >= CI:
+            for name, p in self.p_value(right=right).items():
+                if p >= alpha:
                     continue
                 df.loc[df[alg_legend] == name, sig_legend] = True
         else:
-            p_values = self.p_value()
+            p_values = self.p_value(right=right)
             systems = list(p_values.keys())
             p_values = np.array([p_values[k] for k in systems])
             for name, p_value in zip(perf_names, p_values.T):
                 mask = df[var_name] == name
                 for alg, p in zip(systems, p_value):
-                    if p >= CI:
+                    if p >= alpha:
                         continue
                     _ = mask & (df[alg_legend] == alg)
                     df.loc[_, sig_legend] = True
@@ -639,7 +640,8 @@ def plot(self, value_name:str='Difference',
              alg_legend:str='Algorithm',
              sig_legend:str='Significant',
              perf_names:list=None,
-             CI:float=0.05,
+             alpha:float=0.05,
+             right:bool=True,
              kind:str='point', linestyle:str='none',
              col_wrap:int=3, capsize:float=0.2,
              set_refline:bool=True,
@@ -668,12 +670,12 @@ def plot(self, value_name:str='Difference',
                             alg_legend=alg_legend,
                             sig_legend=sig_legend,
                             perf_names=perf_names,
-                            CI=CI)
-        title = var_name                            
+                            alpha=alpha, right=right)
+        title = var_name         
         if var_name not in df.columns:
             var_name = None
             col_wrap = None
-        ci = lambda x: measurements.CI(x, alpha=CI)
+        ci = lambda x: measurements.CI(x, alpha=2*alpha)
         f_grid = sns.catplot(df, x=value_name, errorbar=ci,
                              y=alg_legend, col=var_name,
                              kind=kind, linestyle=linestyle,