update pages

pages/2_FIT utilities.py

@@ -0,0 +1,28 @@
+
+import streamlit as st
+from pyfitness.load_data import fitfileinfo, fit2df
+"""
+# Welcome to Vincent's experiments with cycling data files
+
+#### Fit file utilities
+- See fit file details
+- Export to CSV
+Questions, comments, contact me on discord: [Vincent.Davis](discordapp.com/users/vincent.davis)
+"""
+
+with st.form(key="FIT file upload"):
+    fit_buffer_1 = st.file_uploader("Upload a FIT file", type=["fit", "FIT"], key="fit_file1")
+    submit_button = st.form_submit_button(label='Submit')
+if submit_button:
+    with st.spinner("Processing..."):
+        fit_file = fit_buffer_1.getbuffer()
+        df = fit2df(fit_file)
+        with st.expander("Expand file details"):
+            if fit_file is not None:
+                ffi1 = fitfileinfo(fit_file)
+                st.write(ffi1)
+        st.download_button(label="Download FIT file as CSV",
+                           data=df.to_csv(index=False).encode('utf-8'),
+                           file_name="fit_to_csv.csv",
+                           mime='text/csv')
+

pages/3_Compare Fit files.py

@@ -0,0 +1,90 @@
+import pandas as pd
+import streamlit as st
+import plotly.express as px
+from pyfitness.load_data import fitfileinfo, fit2df
+
+"""
+# Welcome to Vincent's experiments with cycling data files
+
+#### Compare interesting stats between two fit files
+Questions, comments, contact me on discord: [Vincent.Davis](discordapp.com/users/vincent.davis)
+"""
+
+def fit_stats(df: pd.DataFrame):
+    """Display the stats of a dataframe"""
+    st.write("Preview of the FIT file.\nYou can expand this")
+    st.write(df.head(10))
+    st.write("Detailed stats of for each fields")
+    st.write(df.describe())
+    for field in ['heart_rate', 'power', 'cadence', 'speed', 'distance', 'altitude', 'temperature']:
+        try:
+            st.write(f"{field} mean, without zeros: {df[df[field] > 0][field].mean()}")
+            st.write(f"{field} max: {df[field].max()}")
+            st.write(f"{field} max change: {df[field].diff().max()}")
+            fig1 = px.histogram(df[df[f"{field}"] > 0], x=f"{field}", nbins=50,
+                                title=f"{field} distribution", histnorm='probability density')
+            st.plotly_chart(fig1, theme="streamlit", use_container_width=True)
+            fig2 = px.histogram(df[df[f"{field}"] > 0][f"{field}"].diff(), nbins=50,
+                                title=f"{field} change distribution", histnorm='probability density')
+            st.plotly_chart(fig2, theme="streamlit", use_container_width=True)
+        except Exception as e:
+            st.write(f" Error with Field name: {field}\nError:\n{e}.")
+
+
+col1, col2 = st.columns(2)
+
+with col1:
+    fit_buffer_1 = st.file_uploader("Upload a FIT file", type=["fit", "FIT"], key="fit_file1")
+    if fit_buffer_1 is not None:
+        fit_file1 = fit_buffer_1.getbuffer()
+        # Provide a CSV download option
+        # st.download_button(label="Download FIT file as CSV",
+        #                    data=fit_file1.to_csv(index=False).encode('utf-8'),
+        #                    file_name="fit_file1.csv",
+        #                    mime='text/csv')
+
+        with st.expander("Expand file details"):
+            if fit_file1 is not None:
+                ffi1 = fitfileinfo(fit_file1)
+                st.write(ffi1)
+        df1 = fit2df(fit_file1)
+        df1['seconds'] = pd.to_datetime(df1.index).astype(int) / 10 ** 9
+        df1['seconds'] = df1['seconds'].max() - df1['seconds']
+        st.write("Enter start and end times")
+        st.write("These values will be applied to the stats below")
+        start_time = st.number_input('Start time in seconds', min_value=0, max_value=int(df1.seconds.max()), value=0,
+                                     step=1)
+        end_time = st.number_input('End time in seconds', min_value=0, max_value=int(df1.seconds.max()),
+                                   value=int(df1.seconds.max()), step=1)
+        df_filtered = df1[(df1.seconds >= start_time) & (df1.seconds <= end_time)]
+        fig = px.line(df_filtered, x="seconds", y="power")
+        st.plotly_chart(fig, theme="streamlit", use_container_width=True)
+        fit_stats(df_filtered)
+
+with col2:
+    fit_buffer_2 = st.file_uploader("Upload a FIT file", type=["fit", "FIT"], key="fit_file2")
+    if fit_buffer_2 is not None:
+        fit_file2 = fit_buffer_2.getbuffer()
+
+        with st.expander("Expand file details"):
+            if fit_file2 is not None:
+                ffi2 = fitfileinfo(fit_file2)
+                st.write(ffi2)
+        df2 = fit2df(fit_file2)
+        df2['seconds'] = pd.to_datetime(df2.index).astype(int) / 10 ** 9
+        df2['seconds'] = df2['seconds'].max() - df2['seconds']
+        st.write("Enter start and end times")
+        st.write("These values will be applied to the stats below")
+        start_time = st.number_input('Start time in seconds', min_value=0, max_value=int(df2.seconds.max()), value=0,
+                                     step=1)
+        end_time = st.number_input('End time in seconds', min_value=0, max_value=int(df2.seconds.max()),
+                                   value=int(df2.seconds.max()), step=1)
+        df_filtered = df2[(df2.seconds >= start_time) & (df2.seconds <= end_time)]
+        fig = px.line(df_filtered, x="seconds", y="power")
+        st.plotly_chart(fig, theme="streamlit", use_container_width=True)
+        fit_stats(df_filtered)
+        # Provide a CSV download option
+        # st.download_button(label="Download FIT file as CSV",
+        #                    data=fit_file2.to_csv(index=False).encode('utf-8'),
+        #                    file_name="fit_file2.csv",
+        #                    mime='text/csv')

pages/5_Efficiency.py

@@ -0,0 +1,9 @@
+
+import streamlit as st
+"""
+# Welcome to Vincent's experiments with cycling data files
+
+#### Something cool coming soon.
+
+Questions, comments, contact me on discord: [Vincent.Davis](discordapp.com/users/vincent.davis)
+"""

streamlit_app.py

@@ -10,86 +10,9 @@
 
 This is a work in progress. 
 
-You can also contact me on discord: [Vincent](discordapp.com/users/vincent.davis)
+Questions, comments, contact me on discord: [Vincent.Davis](discordapp.com/users/vincent.davis)
 
+See option in left menu
 """
 
 
-def fit_stats(df: pd.DataFrame):
-    """Display the stats of a dataframe"""
-    st.write("Preview of the FIT file.\nYou can expand this")
-    st.write(df.head(10))
-    st.write("Detailed stats of for each fields")
-    st.write(df.describe())
-    for field in ['heart_rate', 'power', 'cadence', 'speed', 'distance', 'altitude', 'temperature']:
-        try:
-            st.write(f"{field} mean, without zeros: {df[df[field] > 0][field].mean()}")
-            st.write(f"{field} max: {df[field].max()}")
-            st.write(f"{field} max change: {df[field].diff().max()}")
-            fig1 = px.histogram(df[df[f"{field}"] > 0], x=f"{field}", nbins=50,
-                                title=f"{field} distribution", histnorm='probability density')
-            st.plotly_chart(fig1, theme="streamlit", use_container_width=True)
-            fig2 = px.histogram(df[df[f"{field}"] > 0][f"{field}"].diff(), nbins=50,
-                                title=f"{field} change distribution", histnorm='probability density')
-            st.plotly_chart(fig2, theme="streamlit", use_container_width=True)
-        except Exception as e:
-            st.write(f" Error with Field name: {field}\nError:\n{e}.")
-
-
-col1, col2 = st.columns(2)
-
-with col1:
-    fit_buffer_1 = st.file_uploader("Upload a FIT file", type=["fit", "FIT"], key="fit_file1")
-    if fit_buffer_1 is not None:
-        fit_file1 = fit_buffer_1.getbuffer()
-        # Provide a CSV download option
-        # st.download_button(label="Download FIT file as CSV",
-        #                    data=fit_file1.to_csv(index=False).encode('utf-8'),
-        #                    file_name="fit_file1.csv",
-        #                    mime='text/csv')
-
-        with st.expander("Expand file details"):
-            if fit_file1 is not None:
-                ffi1 = fitfileinfo(fit_file1)
-                st.write(ffi1)
-        df1 = fit2df(fit_file1)
-        df1['seconds'] = pd.to_datetime(df1.index).astype(int) / 10 ** 9
-        df1['seconds'] = df1['seconds'].max() - df1['seconds']
-        st.write("Enter start and end times")
-        st.write("These values will be applied to the stats below")
-        start_time = st.number_input('Start time in seconds', min_value=0, max_value=int(df1.seconds.max()), value=0,
-                                     step=1)
-        end_time = st.number_input('End time in seconds', min_value=0, max_value=int(df1.seconds.max()),
-                                   value=int(df1.seconds.max()), step=1)
-        df_filtered = df1[(df1.seconds >= start_time) & (df1.seconds <= end_time)]
-        fig = px.line(df_filtered, x="seconds", y="power")
-        st.plotly_chart(fig, theme="streamlit", use_container_width=True)
-        fit_stats(df_filtered)
-
-with col2:
-    fit_buffer_2 = st.file_uploader("Upload a FIT file", type=["fit", "FIT"], key="fit_file2")
-    if fit_buffer_2 is not None:
-        fit_file2 = fit_buffer_2.getbuffer()
-
-        with st.expander("Expand file details"):
-            if fit_file2 is not None:
-                ffi2 = fitfileinfo(fit_file2)
-                st.write(ffi2)
-        df2 = fit2df(fit_file2)
-        df2['seconds'] = pd.to_datetime(df2.index).astype(int) / 10 ** 9
-        df2['seconds'] = df2['seconds'].max() - df2['seconds']
-        st.write("Enter start and end times")
-        st.write("These values will be applied to the stats below")
-        start_time = st.number_input('Start time in seconds', min_value=0, max_value=int(df2.seconds.max()), value=0,
-                                     step=1)
-        end_time = st.number_input('End time in seconds', min_value=0, max_value=int(df2.seconds.max()),
-                                   value=int(df2.seconds.max()), step=1)
-        df_filtered = df2[(df2.seconds >= start_time) & (df2.seconds <= end_time)]
-        fig = px.line(df_filtered, x="seconds", y="power")
-        st.plotly_chart(fig, theme="streamlit", use_container_width=True)
-        fit_stats(df_filtered)
-        # Provide a CSV download option
-        # st.download_button(label="Download FIT file as CSV",
-        #                    data=fit_file2.to_csv(index=False).encode('utf-8'),
-        #                    file_name="fit_file2.csv",
-        #                    mime='text/csv')