EPMCTDM-7116: Label NaN in reports is replaced (#473)

* Label No value instead of nan in reports * A comment is added * Nan labels from dataset are passed to accuracy plots * comment is removed * Version is upgraded * fix the process of providing the information of the schema depending on the format of the generated data * file is removed * Version is upgraded * update 'VERSION' --------- Co-authored-by: Roman Nemuchynskyi <[email protected]> Co-authored-by: Hanna Imshenetska <[email protected]@EVZZAMZSA0021.epam.com> Co-authored-by: Hanna Imshenetska <[email protected]>
tdspora · Oct 23, 2024 · ac1fd9c · ac1fd9c
1 parent b24affb
commit ac1fd9c
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Showing 4 changed files with 27 additions and 15 deletions.
diff --git a/src/syngen/VERSION b/src/syngen/VERSION
@@ -1 +1 @@
-0.9.46
+0.9.47
diff --git a/src/syngen/ml/metrics/accuracy_test/accuracy_test.py b/src/syngen/ml/metrics/accuracy_test/accuracy_test.py
@@ -113,9 +113,11 @@ def __init__(
         paths: dict,
         table_name: str,
         infer_config: Dict,
+        columns_nan_labels: Dict,
     ):
         super().__init__(original, synthetic, paths, table_name, infer_config)
         self.reports_path = f"{self.paths['reports_path']}/accuracy"
+        self.columns_nan_labels = columns_nan_labels
         self.univariate = UnivariateMetric(
             self.original,
             self.synthetic,
@@ -126,7 +128,8 @@ def __init__(
             self.original,
             self.synthetic,
             self.plot_exists,
-            self.reports_path
+            self.reports_path,
+            self.columns_nan_labels
         )
         self.correlations = Correlations(
             self.original,

diff --git a/src/syngen/ml/metrics/metrics_classes/metrics.py b/src/syngen/ml/metrics/metrics_classes/metrics.py
@@ -338,9 +338,11 @@ def __init__(
         synthetic: pd.DataFrame,
         plot: bool,
         reports_path: str,
+        columns_nan_labels: Dict,
     ):
         super().__init__(original, synthetic, plot, reports_path)
         self.cmap = LinearSegmentedColormap.from_list("rg", ["#0D5598", "#3E92E0", "#E8F4FF"])
+        self.columns_nan_labels = columns_nan_labels
 
     @staticmethod
     def _format_date_labels(heatmap_orig_data, heatmap_synthetic_data, axis):
@@ -442,9 +444,15 @@ def calculate_all(
                     heatmap_orig_data, heatmap_synthetic_data, "y"
                 )
 
-            self._plot_heatmap(heatmap_orig_data, 0, heatmap_min, heatmap_max, cbar=False)
+            self._plot_heatmap(heatmap_orig_data, plt_index=0,
+                               vrange=(heatmap_min, heatmap_max),
+                               features=(first_col, second_col),
+                               cbar=False)
 
-            self._plot_heatmap(heatmap_synthetic_data, 1, heatmap_min, heatmap_max, cbar=True)
+            self._plot_heatmap(heatmap_synthetic_data, plt_index=1,
+                               vrange=(heatmap_min, heatmap_max),
+                               features=(first_col, second_col),
+                               cbar=True)
             # first_col is x axis, second_col is y axis
             title = f"{first_col} vs. {second_col}"
             path_to_image = (
@@ -463,31 +471,31 @@ def get_common_min_max(original, synthetic):
         return vmin, vmax
 
     @staticmethod
-    def __format_float_tick_labels(labels: List) -> List:
+    def __format_float_tick_labels(labels: List, nan_label: str = 'NaN') -> List:
+        labels = [nan_label if pd.isna(l) else l for l in labels]
         if all([isinstance(i, float) for i in labels]) and (
             max(labels) > 1e5 or min(labels) < 1e-03
         ):
-            labels = [f"{label:.4e}" for label in labels]
-            return labels
+            return [f"{label:.4e}" for label in labels]
         if all([isinstance(i, float) for i in labels]):
-            labels = [f"{round(i, 4)}" for i in labels]
-            return labels
-        else:
-            return labels
+            return [f"{round(i, 4)}" for i in labels]
+        return labels
 
     def _plot_heatmap(
         self,
         heatmap_data: List,
         plt_index: int,
-        vmin: float,
-        vmax: float,
+        vrange: tuple[float],
+        features: tuple[str],
         cbar=True,
     ):
+        vmin, vmax = vrange
+        xfeature, yfeature = features
         ax = self._axes.flat[plt_index]
         ax.tick_params(labelsize=14)
         heatmap, x_tick_labels, y_tick_labels = heatmap_data
-        x_tick_labels = self.__format_float_tick_labels(x_tick_labels)
-        y_tick_labels = self.__format_float_tick_labels(y_tick_labels)
+        x_tick_labels = self.__format_float_tick_labels(x_tick_labels, self.columns_nan_labels.get(xfeature, 'NaN'))
+        y_tick_labels = self.__format_float_tick_labels(y_tick_labels, self.columns_nan_labels.get(yfeature, 'NaN'))
         ax = sns.heatmap(
             heatmap,
             xticklabels=x_tick_labels,

diff --git a/src/syngen/ml/reporters/reporters.py b/src/syngen/ml/reporters/reporters.py
@@ -295,6 +295,7 @@ def report(self):
             self.paths,
             self.table_name,
             self.config,
+            self.columns_nan_labels,
         )
         accuracy_test.report(
             cont_columns=list(float_columns | int_columns),