again altair 5

app.py

@@ -182,92 +182,92 @@ def generate_height_profile_json(df: pd.DataFrame) -> str:
     df["smoothed_grade_color"] = df["smoothed_grade"].map(grade_to_color)
     # df["grade_color"] = df["grade"].map(grade_to_color)
 
-    # elevation = (
-    #     alt.Chart(
-    #         df[["distance_from_start", "smoothed_elevation", "smoothed_grade_color"]]
-    #     )
-    #     .mark_bar()
-    #     .encode(
-    #         x=alt.X("distance_from_start")
-    #         .axis(
-    #             grid=False,
-    #             tickCount=10,
-    #             labelExpr="datum.label + ' km'",
-    #             title=None,
-    #         )
-    #         .scale(domain=(0, total_distance_round)),
-    #         y=alt.Y("smoothed_elevation").axis(
-    #             domain=False,
-    #             ticks=False,
-    #             tickCount=5,
-    #             labelExpr="datum.label + ' m'",
-    #             title=None,
-    #         ),
-    #         color=alt.Color("smoothed_grade_color").scale(None),
-    #     )
-    # )
-    max_elevation = df["elev"].max().round(-1)
     elevation = (
-        alt.Chart(df)
-        .mark_area(
-            color=alt.Gradient(
-                gradient="linear",
-                stops=[
-                    alt.GradientStop(color="lightgrey", offset=0),
-                    alt.GradientStop(color="darkgrey", offset=1),
-                ],
-                x1=1,
-                x2=1,
-                y1=1,
-                y2=0,
-            ),
-            line={"color": "darkgreen"},
+        alt.Chart(
+            df[["distance_from_start", "smoothed_elevation", "smoothed_grade_color"]]
         )
+        .mark_bar()
         .encode(
-            x=alt.X(
-                "distance_from_start",
-                axis=alt.Axis(
-                    domain=False,
-                    ticks=False,
-                    tickCount=10,
-                    labelExpr="datum.label + ' km'",
-                ),
-                scale=alt.Scale(domain=(0, total_distance_round)),
-            ),
-            y=alt.Y(
-                "elev",
-                axis=alt.Axis(
-                    domain=False,
-                    ticks=False,
-                    tickCount=5,
-                    labelExpr="datum.label + ' m'",
-                ),
-                scale=alt.Scale(domain=(0, max_elevation)),
+            x=alt.X("distance_from_start")
+            .axis(
+                grid=False,
+                tickCount=10,
+                labelExpr="datum.label + ' km'",
+                title=None,
+            )
+            .scale(domain=(0, total_distance_round)),
+            y=alt.Y("smoothed_elevation").axis(
+                domain=False,
+                ticks=False,
+                tickCount=5,
+                labelExpr="datum.label + ' m'",
+                title=None,
             ),
+            color=alt.Color("smoothed_grade_color").scale(None),
         )
     )
-    df_peaks_filtered = find_climbs(df)
-    # line_peaks = (
-    #     alt.Chart(df_peaks_filtered[["distance_from_start", "elev", "max_elevation"]])
-    #     .mark_rule(color="red")
+    max_elevation = df["elev"].max().round(-1)
+    # elevation = (
+    #     alt.Chart(df)
+    #     .mark_area(
+    #         color=alt.Gradient(
+    #             gradient="linear",
+    #             stops=[
+    #                 alt.GradientStop(color="lightgrey", offset=0),
+    #                 alt.GradientStop(color="darkgrey", offset=1),
+    #             ],
+    #             x1=1,
+    #             x2=1,
+    #             y1=1,
+    #             y2=0,
+    #         ),
+    #         line={"color": "darkgreen"},
+    #     )
     #     .encode(
-    #         x=alt.X("distance_from_start:Q").scale(domain=(0, total_distance_round)),
-    #         y="elev",
-    #         y2="max_elevation",
+    #         x=alt.X(
+    #             "distance_from_start",
+    #             axis=alt.Axis(
+    #                 domain=False,
+    #                 ticks=False,
+    #                 tickCount=10,
+    #                 labelExpr="datum.label + ' km'",
+    #             ),
+    #             scale=alt.Scale(domain=(0, total_distance_round)),
+    #         ),
+    #         y=alt.Y(
+    #             "elev",
+    #             axis=alt.Axis(
+    #                 domain=False,
+    #                 ticks=False,
+    #                 tickCount=5,
+    #                 labelExpr="datum.label + ' m'",
+    #             ),
+    #             scale=alt.Scale(domain=(0, max_elevation)),
+    #         ),
     #     )
     # )
+    df_peaks_filtered = find_climbs(df)
     line_peaks = (
         alt.Chart(df_peaks_filtered[["distance_from_start", "elev", "max_elevation"]])
         .mark_rule(color="red")
         .encode(
-            x=alt.X(
-                "distance_from_start:Q",
-                scale=alt.Scale(domain=(0, total_distance_round)),
-            ),
+            x=alt.X("distance_from_start:Q").scale(domain=(0, total_distance_round)),
             y="elev",
             y2="max_elevation",
         )
     )
+    # line_peaks = (
+    #     alt.Chart(df_peaks_filtered[["distance_from_start", "elev", "max_elevation"]])
+    #     .mark_rule(color="red")
+    #     .encode(
+    #         x=alt.X(
+    #             "distance_from_start:Q",
+    #             scale=alt.Scale(domain=(0, total_distance_round)),
+    #         ),
+    #         y="elev",
+    #         y2="max_elevation",
+    #     )
+    # )
     df_annot = (
         df_peaks_filtered.reset_index(drop=True)
         .assign(number=lambda df_: df_.index + 1)

poetry.lock

@@ -2,25 +2,26 @@
 
 [[package]]
 name = "altair"
-version = "4.2.2"
-description = "Altair: A declarative statistical visualization library for Python."
+version = "5.0.1"
+description = "Vega-Altair: A declarative statistical visualization library for Python."
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "altair-4.2.2-py3-none-any.whl", hash = "sha256:8b45ebeaf8557f2d760c5c77b79f02ae12aee7c46c27c06014febab6f849bc87"},
-    {file = "altair-4.2.2.tar.gz", hash = "sha256:39399a267c49b30d102c10411e67ab26374156a84b1aeb9fcd15140429ba49c5"},
+    {file = "altair-5.0.1-py3-none-any.whl", hash = "sha256:9f3552ed5497d4dfc14cf48a76141d8c29ee56eae2873481b4b28134268c9bbe"},
+    {file = "altair-5.0.1.tar.gz", hash = "sha256:087d7033cb2d6c228493a053e12613058a5d47faf6a36aea3ff60305fd8b4cb0"},
 ]
 
 [package.dependencies]
-entrypoints = "*"
 jinja2 = "*"
 jsonschema = ">=3.0"
 numpy = "*"
 pandas = ">=0.18"
 toolz = "*"
+typing-extensions = {version = ">=4.0.1", markers = "python_version < \"3.11\""}
 
 [package.extras]
-dev = ["black", "docutils", "flake8", "ipython", "m2r", "mistune (<2.0.0)", "pytest", "recommonmark", "sphinx", "vega-datasets"]
+dev = ["black (<24)", "hatch", "ipython", "m2r", "mypy", "pandas-stubs", "pytest", "pytest-cov", "ruff", "types-jsonschema", "types-setuptools", "vega-datasets", "vl-convert-python"]
+doc = ["docutils", "geopandas", "jinja2", "myst-parser", "numpydoc", "pillow", "pydata-sphinx-theme", "sphinx", "sphinx-copybutton", "sphinx-design", "sphinxext-altair"]
 
 [[package]]
 name = "attrs"
@@ -277,17 +278,6 @@ files = [
     {file = "distlib-0.3.6.tar.gz", hash = "sha256:14bad2d9b04d3a36127ac97f30b12a19268f211063d8f8ee4f47108896e11b46"},
 ]
 
-[[package]]
-name = "entrypoints"
-version = "0.4"
-description = "Discover and load entry points from installed packages."
-optional = false
-python-versions = ">=3.6"
-files = [
-    {file = "entrypoints-0.4-py3-none-any.whl", hash = "sha256:f174b5ff827504fd3cd97cc3f8649f3693f51538c7e4bdf3ef002c8429d42f9f"},
-    {file = "entrypoints-0.4.tar.gz", hash = "sha256:b706eddaa9218a19ebcd67b56818f05bb27589b1ca9e8d797b74affad4ccacd4"},
-]
-
 [[package]]
 name = "exceptiongroup"
 version = "1.1.2"
@@ -1503,4 +1493,4 @@ testing = ["big-O", "flake8 (<5)", "jaraco.functools", "jaraco.itertools", "more
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.10,<3.13"
-content-hash = "b34d5fefcbbd82b4d635d5e7d866bde0aa6dbf2f7d5a59bb4ab832bac56622a2"
+content-hash = "748a07a0f37a12766536420ac445825e1cabd04ca2fb89f4038c9dd55e1cd57b"

pyproject.toml

@@ -14,7 +14,7 @@ scipy = "1.11.1"
 watchdog = "^3.0.0"
 folium = "^0.14.0"
 streamlit-folium = "^0.12.0"
-altair = "4.2.2"
+altair = "5.0.1"
 
 
 [tool.poetry.group.dev.dependencies]

requirements.txt

@@ -1,6 +1,6 @@
 # streamlit==1.24.0
 folium==0.14.0
 streamlit-folium==0.12.0
-# altair==4.2.2
+altair==5.0.1
 # pandas==2.0.3
 scipy==1.11.1