Add filtering lesser as well as greater

app.py

@@ -50,11 +50,11 @@ for name in dataset_names:
         "check_compression_ratio_criteria": np.array(ds["check_compression_ratio_criteria"]),
     }
 
-def plt_plot(criteria, dataset, threshold):
+def plt_plot(criteria, dataset, threshold, greater_than=True):
     plt.close("all")
     x = dataset_data[dataset][criteria]
     # calculate percentage of data that will be removed given threshold
-    perc = np.sum(x > threshold) / len(x)
+    perc = np.sum(x > threshold if greater_than else x < threshold) / len(x)
     # create a figure
     fig = plt.figure()
     # add a subplot
@@ -72,10 +72,12 @@ def plt_plot(criteria, dataset, threshold):
     plt.tight_layout()
     return fig
 
-def check_filtered(criteria, dataset, threshold):
+def check_filtered(criteria, dataset, threshold, greater_than=True):
     ds = dataset_data[dataset]["ds"]
 
-    filtered_ds = ds.filter(lambda x: x[criteria] > threshold)
+    filtered_ds = ds.filter(
+        lambda x: x[criteria] > threshold if greater_than else x[criteria] < threshold
+    )
     if len(filtered_ds) == 0:
         return "No examples found"
     # get random sample of 1
@@ -161,9 +163,17 @@ with gr.Blocks() as demo:
         calculate = gr.Button("Calculate")
         check = gr.Button("Check Filtered Data")
         filtered_data = gr.Textbox(lines=5, label="Filtered Data")
-        plot_fn = partial(plt_plot, "check_compression_ratio_criteria")
+        plot_fn = partial(
+            plt_plot,
+            "check_compression_ratio_criteria",
+            greater_than=False
+        )
         calculate.click(plot_fn, [dataset, threshold], plot)
-        check_fn = partial(check_filtered, "check_compression_ratio_criteria")
+        check_fn = partial(
+            check_filtered,
+            "check_compression_ratio_criteria",
+            greater_than=False
+        )
         check.click(check_fn, [dataset, threshold], filtered_data)
 
 if __name__ == "__main__":