Use plotly instead of altair

Much more flexibility in plotting

distribution_zoo/cont_uni/normal.py

@@ -1,6 +1,6 @@
 from distribution_zoo import BaseDistribution
 
-import altair as alt
+import plotly.graph_objects as go
 import numpy as np
 import pandas as pd
 import scipy.stats as stats
@@ -45,13 +45,12 @@ def update_range(self):
         mean = st.session_state['normal_mean'] if 'normal_mean' in st.session_state else self.param_mean
         std = st.session_state['normal_std'] if 'normal_std' in st.session_state else self.param_std
 
-        new_lower = round(stats.norm(loc=mean, scale=std).ppf(0.0001), 1)
-        new_upper = round(stats.norm(loc=mean, scale=std).ppf(0.9999), 1)
+        new_lower = max(round(stats.norm(loc=mean, scale=std).ppf(0.0001), 1), self.range_min)
+        new_upper = min(round(stats.norm(loc=mean, scale=std).ppf(0.9999), 1), self.range_max)
         st.session_state['normal_range'] = (new_lower, new_upper)
 
     def plot(self):
-
-        x = np.linspace(self.range_min, self.range_max, 1000)
+        x = np.linspace(self.param_range_start, self.param_range_end, 1000)
 
         chart_data = pd.DataFrame(
             {
@@ -61,31 +60,37 @@ def plot(self):
             }
         )
 
-        # Define the initial x-axis range for the view
-        initial_x_range = [self.param_range_start, self.param_range_end]
+        line_data = pd.DataFrame(
+            {
+                'x': [self.param_mean, self.param_mean],
+                'z': [0.0, 0.0],
+                'pdf': [0.0, max(chart_data['pdf'])],
+                'cdf': [0.0, max(chart_data['cdf'])],
+            }
+        )
 
-        # Create an Altair chart for the PDF
-        pdf_chart = alt.Chart(chart_data).mark_line().encode(
-            x=alt.X('x:Q', scale=alt.Scale(domain=initial_x_range)),
-            y='pdf:Q',
-            tooltip=['x', 'pdf']
-        ).interactive()
+        # Create Plotly chart for the PDF
+        pdf_chart = go.Figure(go.Scatter(x=chart_data['x'], y=chart_data['pdf'], mode='lines', name='PDF'))
+        pdf_chart.add_trace(go.Scatter(x=line_data['x'], y=line_data['pdf'], mode='lines', name=f'Mean ({self.param_mean})', line=dict(color='orange', width=2)))
+        pdf_chart.add_trace(go.Scatter(x=line_data['z'], y=line_data['pdf'], mode='lines', name='Zero', line=dict(color='green', width=2, dash='dot')))
+        pdf_chart.update_layout(xaxis_title='x', yaxis_title='pdf', margin=dict(l=20, r=20, t=20, b=20))
 
-        # Create an Altair chart for the CDF
-        cdf_chart = alt.Chart(chart_data).mark_line().encode(
-            x=alt.X('x:Q', scale=alt.Scale(domain=initial_x_range)),
-            y='cdf:Q',
-            tooltip=['x', 'cdf']
-        ).interactive()
+        # Create Plotly chart for the CDF
+        cdf_chart = go.Figure(go.Scatter(x=chart_data['x'], y=chart_data['cdf'], mode='lines', name='CDF'))
+        cdf_chart.add_trace(go.Scatter(x=line_data['x'], y=line_data['cdf'], mode='lines', name=f'Mean ({self.param_mean})', line=dict(color='orange', width=2)))
+        cdf_chart.add_trace(go.Scatter(x=line_data['z'], y=line_data['cdf'], mode='lines', name=r'Zero', line=dict(color='green', width=2, dash='dot')))
+        cdf_chart.update_layout(xaxis_title='x', yaxis_title='cdf', margin=dict(l=20, r=20, t=20, b=20))
 
+        # Streamlit columns for displaying the charts
         pdf_col, cdf_col = st.columns(2)
 
         with pdf_col:
             st.subheader('Probability density function')
-            st.altair_chart(pdf_chart, use_container_width=True)
+            st.plotly_chart(pdf_chart, use_container_width=True)
+
         with cdf_col:
             st.subheader('Cumulative distribution function')
-            st.altair_chart(cdf_chart, use_container_width=True)
+            st.plotly_chart(cdf_chart, use_container_width=True)
 
     def update_code_substitutions(self):
         self.code_substitutions.add(r'{{{mean}}}', str(self.param_mean))

pyproject.toml

@@ -11,8 +11,8 @@ numpy = "^1.26.2"
 scipy = "^1.11.4"
 inflection = "^0.5.1"
 pandas = "^2.1.4"
-altair = "^5.2.0"
 requests = "^2.31.0"
+plotly = "^5.18.0"
 
 [tool.poetry.group.dev.dependencies]
 flake8 = "^6.1.0"