add config for changing heatmap bin size

lux-org · Feb 7, 2021 · dfb9bce · dfb9bce
1 parent 13af5cb
commit dfb9bce
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Showing 3 changed files with 14 additions and 2 deletions.
diff --git a/doc/source/reference/config.rst b/doc/source/reference/config.rst
@@ -206,3 +206,14 @@ If you would like to turn off the selection criteria completely and display ever
     lux.config.topk = False
 
 Beware that this may generate large numbers of visualizations (e.g., for 10 quantitative variables, this will generate 45 scatterplots in the Correlation action!)
+
+Changing heatmap bin resolution
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+In Lux, large scatterplots are displayed as heatmaps that are 40x40 by default. You can increase or decrease the heatmap resolution NxN by changing the bin size N:
+
+.. code-block:: python 
+
+    lux.config.heatmap_bin_size = 100
+
+This generates heatmap visualizations that are binned into a 100x100 grid. 
diff --git a/lux/_config/config.py b/lux/_config/config.py
@@ -34,6 +34,7 @@ def __init__(self):
         self._sort = "descending"
         self._pandas_fallback = True
         self._interestingness_fallback = True
+        self.heatmap_bin_size = 40
 
     @property
     def topk(self):

diff --git a/lux/executor/PandasExecutor.py b/lux/executor/PandasExecutor.py
@@ -352,8 +352,8 @@ def execute_2D_binning(vis: Vis):
             x_attr = vis.get_attr_by_channel("x")[0].attribute
             y_attr = vis.get_attr_by_channel("y")[0].attribute
 
-            vis._vis_data["xBin"] = pd.cut(vis._vis_data[x_attr], bins=40)
-            vis._vis_data["yBin"] = pd.cut(vis._vis_data[y_attr], bins=40)
+            vis._vis_data["xBin"] = pd.cut(vis._vis_data[x_attr], bins=lux.config.heatmap_bin_size)
+            vis._vis_data["yBin"] = pd.cut(vis._vis_data[y_attr], bins=lux.config.heatmap_bin_size)
 
             color_attr = vis.get_attr_by_channel("color")
             if len(color_attr) > 0: