Adjust demo notebook

Akshay-a-j · Oct 8, 2020 · ba6eeea · ba6eeea
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Showing 17 changed files with 87 additions and 108 deletions.
diff --git a/README.md b/README.md
@@ -8,6 +8,6 @@ A given example instance is perturbed (i.e. parts of its features are 'switched
 
 The LIME package only supports image, text and tabular data. We extended it to be able to deal with time series data.
 
-![Results on the coffee dataset](/demo/results/coffee/coffee_24_10_noise.JPG)
+## Demo
 
-![Results on the ecg dataset](/demo/results/ecg/ecg_17_5_total_mean.JPG)
+See the demo [notebook](demo/LIME-Pipeline.ipynb) for how to use the module.
diff --git a/demo/LIME-Pipeline.ipynb b/demo/LIME-Pipeline.ipynb
diff --git a/demo/results/coffee/coffee_10_5_noise.JPG b/demo/results/coffee/coffee_10_5_noise.JPG
diff --git a/demo/results/coffee/coffee_12_5_mean.JPG b/demo/results/coffee/coffee_12_5_mean.JPG
diff --git a/demo/results/coffee/coffee_12_5_noise.JPG b/demo/results/coffee/coffee_12_5_noise.JPG
diff --git a/demo/results/coffee/coffee_12_5_total_mean.JPG b/demo/results/coffee/coffee_12_5_total_mean.JPG
diff --git a/demo/results/coffee/coffee_24_10_mean.JPG b/demo/results/coffee/coffee_24_10_mean.JPG
diff --git a/demo/results/coffee/coffee_24_10_noise.JPG b/demo/results/coffee/coffee_24_10_noise.JPG
diff --git a/demo/results/coffee/coffee_24_10_total_mean.JPG b/demo/results/coffee/coffee_24_10_total_mean.JPG
diff --git a/demo/results/coffee/coffee_50_20_noise.JPG b/demo/results/coffee/coffee_50_20_noise.JPG
diff --git a/demo/results/coffee_dataset_plot.JPG b/demo/results/coffee_dataset_plot.JPG
diff --git a/demo/results/ecg/ecg_17_5_mean.JPG b/demo/results/ecg/ecg_17_5_mean.JPG
diff --git a/demo/results/ecg/ecg_17_5_noise.JPG b/demo/results/ecg/ecg_17_5_noise.JPG
diff --git a/demo/results/ecg/ecg_17_5_total_mean.JPG b/demo/results/ecg/ecg_17_5_total_mean.JPG
diff --git a/demo/results/ecg_dataset_plot.JPG b/demo/results/ecg_dataset_plot.JPG
diff --git a/demo/results/total_mean_plot.JPG b/demo/results/total_mean_plot.JPG
diff --git a/lime_timeseries.py b/lime_timeseries.py
@@ -132,17 +132,19 @@ def distance_fn(x):
         values_per_slice = math.ceil(len(timeseries) / num_slices)
         deact_per_slice = np.random.randint(1, num_slices + 1, num_samples - 1)
         perturbation_matrix = np.ones((num_samples, num_slices))
+        features_range = range(num_slices)
         original_data = [timeseries.copy()]
 
         for i, num_inactive in enumerate(deact_per_slice, start=1):
             # choose random slices indexes to deactivate
-            inactive_idxs = np.random.choice(len(num_slices), num_inactive, replace=False)
+            inactive_idxs = np.random.choice(features_range, num_inactive, replace=False)
             perturbation_matrix[i, inactive_idxs] = 0
             tmp_series = timeseries.copy()
 
             for idx in inactive_idxs:
                 start_idx = idx * values_per_slice
                 end_idx = start_idx + values_per_slice
+                end_idx = min(end_idx, len(timeseries))
 
                 if replacement_method == 'mean':
                     # use mean of slice as inactive
@@ -152,7 +154,7 @@ def distance_fn(x):
                     tmp_series[start_idx:end_idx] = np.random.uniform(
                                                         tmp_series.min(),
                                                         tmp_series.max(),
-                                                        values_per_slice)
+                                                        end_idx - start_idx)
                 elif replacement_method == 'total_mean':
                     # use total series mean as inactive
                     tmp_series[start_idx:end_idx] = tmp_series.mean()