Spaces:
Sleeping
Sleeping
Lode Nachtergaele
commited on
Commit
•
e39eb6b
1
Parent(s):
812bb44
downgrade to Altair 4.2.2
Browse files- app.py +150 -33
- poetry.lock +18 -8
- pyproject.toml +1 -1
- requirements.txt +4 -4
app.py
CHANGED
@@ -5,15 +5,21 @@ from typing import List
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from urllib.request import pathname2url
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from xml.dom import minidom
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import numpy as np
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import pandas as pd
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from scipy.signal import find_peaks
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import streamlit as st
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-
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-
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import altair as alt
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from io import StringIO
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def get_gpx(uploaded_file):
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@@ -176,49 +182,129 @@ def generate_height_profile_json(df: pd.DataFrame) -> str:
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df["smoothed_grade_color"] = df["smoothed_grade"].map(grade_to_color)
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# df["grade_color"] = df["grade"].map(grade_to_color)
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elevation = (
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alt.Chart(
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)
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.mark_bar()
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.encode(
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x=alt.X(
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),
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color=alt.Color("smoothed_grade_color").scale(None),
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)
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)
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df_peaks_filtered = find_climbs(df)
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line_peaks = (
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alt.Chart(df_peaks_filtered[["distance_from_start", "elev", "max_elevation"]])
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.mark_rule(color="red")
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.encode(
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x=alt.X(
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y="elev",
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y2="max_elevation",
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)
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)
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chart = (
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(elevation + line_peaks)
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-
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.configure_view(
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strokeWidth=0,
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)
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)
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return chart
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gpx_file = st.file_uploader("Upload gpx file", type=["gpx"])
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@@ -226,14 +312,45 @@ gpx_file = st.file_uploader("Upload gpx file", type=["gpx"])
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if gpx_file is not None:
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ave_lat, ave_lon, lon_list, lat_list, h_list = get_gpx(gpx_file)
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df = pd.DataFrame({"lon": lon_list, "lat": lat_list, "elev": h_list})
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-
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chart = generate_height_profile_json(df)
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st.altair_chart(chart, use_container_width=True)
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from urllib.request import pathname2url
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from xml.dom import minidom
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from folium.plugins import BeautifyIcon
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from folium.features import DivIcon
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# import folium.plugins as plugins
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import numpy as np
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import pandas as pd
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from scipy.signal import find_peaks
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import streamlit as st
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import folium
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from streamlit_folium import st_folium
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import altair as alt
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from io import StringIO
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import branca
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def get_gpx(uploaded_file):
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df["smoothed_grade_color"] = df["smoothed_grade"].map(grade_to_color)
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# df["grade_color"] = df["grade"].map(grade_to_color)
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# elevation = (
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# alt.Chart(
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# df[["distance_from_start", "smoothed_elevation", "smoothed_grade_color"]]
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# )
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# .mark_bar()
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# .encode(
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# x=alt.X("distance_from_start")
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# .axis(
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# grid=False,
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# tickCount=10,
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# labelExpr="datum.label + ' km'",
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# title=None,
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# )
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# .scale(domain=(0, total_distance_round)),
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# y=alt.Y("smoothed_elevation").axis(
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# domain=False,
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# ticks=False,
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# tickCount=5,
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# labelExpr="datum.label + ' m'",
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# title=None,
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# ),
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# color=alt.Color("smoothed_grade_color").scale(None),
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# )
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# )
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max_elevation = df["elev"].max().round(-1)
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elevation = (
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alt.Chart(df)
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.mark_area(
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color=alt.Gradient(
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gradient="linear",
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stops=[
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alt.GradientStop(color="lightgrey", offset=0),
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alt.GradientStop(color="darkgrey", offset=1),
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],
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x1=1,
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x2=1,
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y1=1,
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y2=0,
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),
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line={"color": "darkgreen"},
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)
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.encode(
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x=alt.X(
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"distance_from_start",
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axis=alt.Axis(
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domain=False,
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ticks=False,
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tickCount=10,
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labelExpr="datum.label + ' km'",
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),
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scale=alt.Scale(domain=(0, total_distance_round)),
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),
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y=alt.Y(
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"elev",
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axis=alt.Axis(
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domain=False,
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ticks=False,
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tickCount=5,
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labelExpr="datum.label + ' m'",
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),
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scale=alt.Scale(domain=(0, max_elevation)),
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),
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)
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)
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df_peaks_filtered = find_climbs(df)
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# line_peaks = (
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# alt.Chart(df_peaks_filtered[["distance_from_start", "elev", "max_elevation"]])
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# .mark_rule(color="red")
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# .encode(
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# x=alt.X("distance_from_start:Q").scale(domain=(0, total_distance_round)),
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# y="elev",
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# y2="max_elevation",
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# )
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# )
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line_peaks = (
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alt.Chart(df_peaks_filtered[["distance_from_start", "elev", "max_elevation"]])
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.mark_rule(color="red")
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.encode(
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x=alt.X(
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"distance_from_start:Q",
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scale=alt.Scale(domain=(0, total_distance_round)),
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),
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y="elev",
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y2="max_elevation",
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)
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)
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df_annot = (
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df_peaks_filtered.reset_index(drop=True)
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.assign(number=lambda df_: df_.index + 1)
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.assign(circle_pos=lambda df_: df_["max_elevation"] + 20)[
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["distance_from_start", "max_elevation", "circle_pos", "number"]
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]
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)
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# annotation = (
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# alt.Chart(df_annot)
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# .mark_text(align="center", baseline="bottom", fontSize=16, dy=-10)
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# .encode(
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# x=alt.X("distance_from_start:Q").scale(domain=(0, total_distance_round)),
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# y="max_elevation",
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# text="number",
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# )
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# )
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annotation = (
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alt.Chart(df_annot)
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.mark_text(align="center", baseline="bottom", fontSize=16, dy=-10)
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.encode(
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x=alt.X(
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"distance_from_start:Q",
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scale=alt.Scale(domain=(0, total_distance_round)),
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),
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y="max_elevation",
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text="number",
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)
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)
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chart = (
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(elevation + line_peaks + annotation)
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.properties(width="container")
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.configure_view(
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strokeWidth=0,
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)
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)
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return chart, df_peaks_filtered
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gpx_file = st.file_uploader("Upload gpx file", type=["gpx"])
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if gpx_file is not None:
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ave_lat, ave_lon, lon_list, lat_list, h_list = get_gpx(gpx_file)
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df = pd.DataFrame({"lon": lon_list, "lat": lat_list, "elev": h_list})
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route_map = folium.Map(
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location=[ave_lat, ave_lon],
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zoom_start=12,
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)
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folium.PolyLine(
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list(zip(lat_list, lon_list)), color="red", weight=2.5, opacity=1
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).add_to(route_map)
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chart, df_peaks = generate_height_profile_json(df)
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for index, row in df_peaks.reset_index(drop=True).iterrows():
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icon = BeautifyIcon(
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icon="arrow-down",
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icon_shape="marker",
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number=str(index + 1),
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border_color="red",
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background_color="white",
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)
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icon_div = DivIcon(
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icon_size=(150, 36),
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icon_anchor=(7, 20),
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html=f"<div style='font-size: 18pt; color : black'>{index+1}</div>",
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)
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length = (
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f"{row['length']:.1f} km"
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if row["length"] >= 1
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else f"{row['length']*1000:.0f} m"
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)
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popup_text = f"""Lenght: {length}<br>
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Avg. grade: {row['grade']/1000:.1f}%"""
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popup = folium.Popup(popup_text, min_width=100, max_width=200)
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folium.Marker(
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[row["lat"], row["lon"]],
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popup=popup,
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icon=icon_div,
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).add_to(route_map)
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route_map.add_child(folium.CircleMarker([row["lat"], row["lon"]], radius=15))
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st.table(df_peaks)
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st_data = st_folium(route_map, height=450, width=850)
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st.altair_chart(chart, use_container_width=True)
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poetry.lock
CHANGED
@@ -2,26 +2,25 @@
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[[package]]
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name = "altair"
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version = "
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description = "
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optional = false
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python-versions = ">=3.7"
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files = [
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{file = "altair-
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{file = "altair-
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]
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[package.dependencies]
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jinja2 = "*"
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jsonschema = ">=3.0"
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numpy = "*"
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pandas = ">=0.18"
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toolz = "*"
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typing-extensions = {version = ">=4.0.1", markers = "python_version < \"3.11\""}
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[package.extras]
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dev = ["black
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doc = ["docutils", "geopandas", "jinja2", "myst-parser", "numpydoc", "pillow", "pydata-sphinx-theme", "sphinx", "sphinx-copybutton", "sphinx-design", "sphinxext-altair"]
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[[package]]
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name = "attrs"
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{file = "distlib-0.3.6.tar.gz", hash = "sha256:14bad2d9b04d3a36127ac97f30b12a19268f211063d8f8ee4f47108896e11b46"},
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]
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[[package]]
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name = "exceptiongroup"
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version = "1.1.2"
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[metadata]
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lock-version = "2.0"
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python-versions = ">=3.10,<3.13"
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-
content-hash = "
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[[package]]
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name = "altair"
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version = "4.2.2"
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description = "Altair: A declarative statistical visualization library for Python."
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optional = false
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python-versions = ">=3.7"
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files = [
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{file = "altair-4.2.2-py3-none-any.whl", hash = "sha256:8b45ebeaf8557f2d760c5c77b79f02ae12aee7c46c27c06014febab6f849bc87"},
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{file = "altair-4.2.2.tar.gz", hash = "sha256:39399a267c49b30d102c10411e67ab26374156a84b1aeb9fcd15140429ba49c5"},
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]
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[package.dependencies]
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entrypoints = "*"
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jinja2 = "*"
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jsonschema = ">=3.0"
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numpy = "*"
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pandas = ">=0.18"
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toolz = "*"
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[package.extras]
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dev = ["black", "docutils", "flake8", "ipython", "m2r", "mistune (<2.0.0)", "pytest", "recommonmark", "sphinx", "vega-datasets"]
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[[package]]
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name = "attrs"
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{file = "distlib-0.3.6.tar.gz", hash = "sha256:14bad2d9b04d3a36127ac97f30b12a19268f211063d8f8ee4f47108896e11b46"},
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]
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+
[[package]]
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name = "entrypoints"
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version = "0.4"
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description = "Discover and load entry points from installed packages."
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optional = false
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python-versions = ">=3.6"
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files = [
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{file = "entrypoints-0.4-py3-none-any.whl", hash = "sha256:f174b5ff827504fd3cd97cc3f8649f3693f51538c7e4bdf3ef002c8429d42f9f"},
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+
{file = "entrypoints-0.4.tar.gz", hash = "sha256:b706eddaa9218a19ebcd67b56818f05bb27589b1ca9e8d797b74affad4ccacd4"},
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+
]
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+
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[[package]]
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name = "exceptiongroup"
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version = "1.1.2"
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[metadata]
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lock-version = "2.0"
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python-versions = ">=3.10,<3.13"
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content-hash = "b34d5fefcbbd82b4d635d5e7d866bde0aa6dbf2f7d5a59bb4ab832bac56622a2"
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pyproject.toml
CHANGED
@@ -11,10 +11,10 @@ readme = "README.md"
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python = ">=3.10,<3.13"
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streamlit = "1.24.0"
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scipy = "1.11.1"
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-
altair = "5.0.1"
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watchdog = "^3.0.0"
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folium = "^0.14.0"
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streamlit-folium = "^0.12.0"
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[tool.poetry.group.dev.dependencies]
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python = ">=3.10,<3.13"
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streamlit = "1.24.0"
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scipy = "1.11.1"
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watchdog = "^3.0.0"
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folium = "^0.14.0"
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streamlit-folium = "^0.12.0"
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altair = "4.2.2"
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[tool.poetry.group.dev.dependencies]
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requirements.txt
CHANGED
@@ -1,6 +1,6 @@
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1 |
-
streamlit==1.24.0
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2 |
-
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3 |
-
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4 |
-
# altair==
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5 |
# pandas==2.0.3
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6 |
scipy==1.11.1
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1 |
+
# streamlit==1.24.0
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2 |
+
folium==0.14.0
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3 |
+
streamlit-folium==0.12.0
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4 |
+
# altair==4.2.2
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5 |
# pandas==2.0.3
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6 |
scipy==1.11.1
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