update docs

docs/source/plots/get_started.rst

@@ -60,25 +60,26 @@ Make a plot
     We regularly update the list of available plots. Make sure that you have the last version of seismograph.
 
 
-Pearson filter gap
-------------------
+Outlier filtering
+-----------------
 
-- **pearson_filter_gap**: float, default=1
-    Outlier filtering
-    -----------------
+- **pearson_filter_gap**: float, default=None
+    This parameter allows filtering out outliers by setting a minimal gap between the Pearson correlation of the data 
+    with the outlier and the Pearson correlation of the data without the outlier. If the difference is higher than 
+    this value, the outlier is removed from the Pearson correlation calculation. 
 
-    - **outlier_filter_gap**: float, default=0.5
-        This parameter allows filtering out outliers by setting a minimal gap between the Pearson correlation of the data 
-        with the outlier and the Pearson correlation of the data without the outlier. If the difference is higher than 
-        this value, the outlier is removed from the Pearson correlation calculation.
+    If the parameter is set to None (default), no outlier filtering is applied.
+
+    Example:
+
+    .. code::
 
-        Example:
-        Consider the following data:
         reference_data = [1.1, 1.8, 2.9, 4.1, 5.2, 6.0]
         data_with_outlier = [1., 2., 3., 4., 5., 100.]
 
-        If outlier_filter_gap is set to 0.5, the outlier (100.) will be removed from the Pearson correlation calculation 
-        because the difference between the correlation with and without the outlier is greater than 0.5.
+
+    If outlier_filter_gap is set to 0.5, the outlier (100.) will be removed from the Pearson correlation calculation 
+    because the difference between the correlation with and without the outlier is greater than 0.5.
 
 
 Normalize
@@ -88,9 +89,13 @@ Normalize
     If you have multiple samples and this parameter is set to True, the data of the samples are divided by the 
     slope of the linear regression between the data of the first sample and the data of each other samples.
 
-    Ex: 
-    sample_1 = [1, 2, 3, 4, 5]
-    sample_2 = [2, 4, 6, 8, 10]
+    Example:
+
+    .. code::
+
+        sample_1 = [1, 2, 3, 4, 5]
+        sample_2 = [2, 4, 6, 8, 10]
+
 
     If normalize is set to True, the data of sample_2 will be divided by 2.