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Commit 2b2e5969 authored by Florian Obersteiner's avatar Florian Obersteiner :octopus:
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revise callbacks

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CHANGELOG.md
+ 9
− 1
View file @ 2b2e5969
......@@ -15,11 +15,14 @@ Types of changes
## TODOs
- drop boxes: brighter highlighting of selected element
- add sources for BB tagging and ACN background
- investigate if data caching is necessary (load-from-thredds)?
- scatter-plot: plot as line if sufficient data is available?
## v0.1.0 release
- when trajectory plotting is implemented?
## Backlog
- use a polars dataframe for better efficiency - if that turns out to be a bottleneck. (!) Keep this in mind when using pandas-specific functions.
......@@ -31,6 +34,11 @@ Types of changes
## [Unreleased]
### Changed
- revised callbacks; separate the one big figure-callback into multiple callbacks, in a separate file `./src/callbacks.py
- tweak css for dropboxes
## v0.0.15 - 2025-03-26
### Added
......
main.py
+ 10
− 167
View file @ 2b2e5969
# -*- coding: utf-8 -*-
#
# SPDX-FileCopyrightText: 2025 Florian Obersteiner <f.obersteiner@kit.edu>
#
# SPDX-License-Identifier: GPL-3.0-or-later
# -*- coding: utf-8 -*-
import logging as log
from pathlib import Path
import dash_bootstrap_components as dbc
import pandas as pd
import plotly.graph_objects as go
from dash import Dash
from dash.dependencies import Input, Output
from plotly.subplots import make_subplots
from src.callbacks import (
register_info_updaters,
register_map_plot,
register_timeseries_plot,
)
from src.config import DotDict, get_latest_semantic_version_tag
from src.data import load_from_disk, load_from_thredds
from src.layout import create_layout
from src.thredds import get_datasets
# BEGIN state structures
appconfig: DotDict = DotDict.from_toml_file("./config/env.toml")
appconfig.VERSION = get_latest_semantic_version_tag() or appconfig.VERSION
......@@ -38,7 +39,6 @@ data, ap_info = (
else load_from_disk(Path("./testdata").glob("MS_*.nc"), appconfig, airportsconfig, True) # type: ignore
)
log.debug(f"Data loaded. Used THREDDS: {appconfig.USE_THREDDS}")
# END state structures
# fmt: off
app = Dash(
......@@ -56,166 +56,9 @@ app.layout = create_layout(data, appconfig)
server = app.server # for deployment via gunicorn / WSGI server
@app.callback(Output("var-info", "children"), Input("variable-dropdown", "value"))
def set_var_info(selected_variable: str) -> str:
return varconfig.loc[selected_variable, :].Long_Name
@app.callback(Output("second-var-info", "children"), Input("second-variable-dropdown", "value"))
def set_second_var_info(secondary_variable: str) -> str:
return (
varconfig.loc[secondary_variable, :].Long_Name
if secondary_variable in varconfig.index
else ""
)
@app.callback(Output("flight-dep-dest", "children"), Input("flight-dropdown", "value"))
def set_flight_dep_dest(selected_flight: int) -> str:
return ap_info.get(selected_flight, "?!")
@app.callback(
[
Output("fig-map", "figure"),
Output("fig-ts", "figure"),
],
[
Input("flight-dropdown", "value"),
Input("variable-dropdown", "value"),
Input("second-variable-dropdown", "value"),
],
)
def update_plots(selected_flight: int, primary_variable: str, secondary_variable: str):
filtered_df = data[data["flight_number"] == selected_flight]
valid_indices = filtered_df[primary_variable].notna()
unit_primary = varconfig.loc[primary_variable, :].Unit
unit_secondary = (
varconfig.loc[secondary_variable, :].Unit if secondary_variable in varconfig.index else "-"
)
fig_map = go.Figure(
go.Scattermap(
lon=filtered_df.loc[valid_indices, "lon"],
lat=filtered_df.loc[valid_indices, "lat"],
mode="markers",
marker={
"color": filtered_df.loc[valid_indices, primary_variable],
"colorscale": "Rainbow",
"colorbar": {
"x": 0.995,
"title": {"text": f"{primary_variable} {unit_primary}", "side": "right"},
},
"showscale": True,
},
connectgaps=False,
hoverinfo="text",
hovertext=[f"{v:.1f}" for v in filtered_df[primary_variable]],
name="Flight Path",
)
)
fig_map.add_trace( # marker to indicate departure airport
go.Scattermap(
lat=[filtered_df.lat.iloc[0]],
lon=[filtered_df.lon.iloc[0]],
mode="markers",
marker={"size": 15, "allowoverlap": True, "symbol": "airport", "angle": 55},
marker_symbol="airport",
text=["departure airport"],
hoverinfo="text",
name="departure",
)
)
fig_map.add_trace( # marker to indicate destination airport
go.Scattermap(
lat=[filtered_df.lat.iloc[-1]],
lon=[filtered_df.lon.iloc[-1]],
mode="markers",
marker={"size": 15, "allowoverlap": True, "symbol": "airport", "angle": 235},
text=["destination airport"],
hoverinfo="text",
name="destination",
)
)
fig_map.update_layout(
map={
"style": "outdoors",
"zoom": 1.7,
"center": {"lat": filtered_df.lat.mean(), "lon": filtered_df.lon.mean()},
},
margin={"l": 0, "r": 10, "t": 0, "b": 0},
showlegend=False,
)
fig_ts = make_subplots(specs=[[{"secondary_y": True}]])
fig_ts.add_trace(
go.Scatter(
x=filtered_df.index[valid_indices & ~filtered_df["BB_flag"]],
y=filtered_df.loc[valid_indices & ~filtered_df["BB_flag"], primary_variable],
mode="markers",
marker={
"size": 3,
"color": "blue",
"showscale": False,
},
showlegend=False,
)
)
fig_ts.add_trace(
go.Scatter(
x=filtered_df.index[valid_indices & filtered_df["BB_flag"]],
y=filtered_df.loc[valid_indices & filtered_df["BB_flag"], primary_variable],
mode="markers",
marker={
"size": 3,
"color": "red",
"showscale": False,
},
name="flagged 'biomass burning'",
)
)
if secondary_variable != "None":
fig_ts.add_trace(
go.Scatter(
x=filtered_df.index,
y=filtered_df[secondary_variable],
mode="markers",
marker={
"size": 2,
"color": "black",
"showscale": False,
},
name=secondary_variable,
),
secondary_y=True,
)
fig_ts.update_layout(
paper_bgcolor="#e8e8e8",
margin={"l": 45, "r": 10, "t": 20, "b": 50},
legend={
"x": 0.01,
"y": 0.99,
"xanchor": "left",
"yanchor": "top",
"bgcolor": "rgba(255, 255, 255, 0.7)",
"bordercolor": "rgba(0, 0, 0, 0.2)",
"borderwidth": 1,
},
)
fig_ts.update_xaxes(title="UTC")
fig_ts.update_yaxes(title=f"{primary_variable} {unit_primary}")
fig_ts.update_yaxes(title=f"{secondary_variable} {unit_secondary}", secondary_y=True)
set_var_info(primary_variable)
set_second_var_info(secondary_variable)
set_flight_dep_dest(selected_flight)
return [
fig_map,
fig_ts,
]
register_info_updaters(app, varconfig, ap_info)
register_map_plot(app, data, varconfig)
register_timeseries_plot(app, data, varconfig)
if __name__ == "__main__":
......
src/callbacks.py 0 → 100644
+ 196
− 0
View file @ 2b2e5969
import pandas as pd
import plotly.graph_objects as go
from dash import Dash
from dash.dependencies import Input, Output
from plotly.subplots import make_subplots
def register_info_updaters(app: Dash, var_info: pd.DataFrame, ap_info: dict[int, str]):
"""
Register callbacks for updating flight- and variable information.
html fields / ids to update:
- flight-dep-dest
- var-info
- second-var-info
"""
@app.callback(Output("flight-dep-dest", "children"), Input("flight-dropdown", "value"))
def set_flight_dep_dest(selected_flight: int) -> str:
return ap_info.get(selected_flight, "?!")
@app.callback(Output("var-info", "children"), Input("variable-dropdown", "value"))
def set_var_info(selected_variable: str) -> str:
return var_info.loc[selected_variable, :].Long_Name
@app.callback(Output("second-var-info", "children"), Input("second-variable-dropdown", "value"))
def set_second_var_info(secondary_variable: str) -> str:
return (
var_info.loc[secondary_variable, :].Long_Name
if secondary_variable in var_info.index
else ""
)
def register_map_plot(app: Dash, timeseries_data: pd.DataFrame, var_info: pd.DataFrame):
"""
Register callbacks for updating map plot.
html field / id to update:
- fig-plot
"""
@app.callback(
[Output("fig-map", "figure")],
[Input("flight-dropdown", "value"), Input("variable-dropdown", "value")],
)
def update_map_plot(selected_flight: int, primary_variable: str):
filtered_df = timeseries_data[timeseries_data["flight_number"] == selected_flight]
valid_indices = filtered_df[primary_variable].notna()
unit_primary = var_info.loc[primary_variable, :].Unit
fig_map = go.Figure(
go.Scattermap(
lon=filtered_df.loc[valid_indices, "lon"],
lat=filtered_df.loc[valid_indices, "lat"],
mode="markers",
marker={
"color": filtered_df.loc[valid_indices, primary_variable],
"colorscale": "Rainbow",
"colorbar": {
"x": 0.995,
"title": {"text": f"{primary_variable} {unit_primary}", "side": "right"},
},
"showscale": True,
},
connectgaps=False,
hoverinfo="text",
hovertext=[f"{v:.1f}" for v in filtered_df[primary_variable]],
name="Flight Path",
)
)
fig_map.add_trace( # marker to indicate departure airport
go.Scattermap(
lat=[filtered_df.lat.iloc[0]],
lon=[filtered_df.lon.iloc[0]],
mode="markers",
marker={"size": 15, "allowoverlap": True, "symbol": "airport", "angle": 55},
marker_symbol="airport",
text=["departure airport"],
hoverinfo="text",
name="departure",
)
)
fig_map.add_trace( # marker to indicate destination airport
go.Scattermap(
lat=[filtered_df.lat.iloc[-1]],
lon=[filtered_df.lon.iloc[-1]],
mode="markers",
marker={"size": 15, "allowoverlap": True, "symbol": "airport", "angle": 235},
text=["destination airport"],
hoverinfo="text",
name="destination",
)
)
fig_map.update_layout(
map={
"style": "outdoors",
"zoom": 1.7,
"center": {"lat": filtered_df.lat.mean(), "lon": filtered_df.lon.mean()},
},
margin={"l": 0, "r": 10, "t": 0, "b": 0},
showlegend=False,
)
return [fig_map]
def register_timeseries_plot(app: Dash, timeseries_data: pd.DataFrame, var_info: pd.DataFrame):
"""
Register a callback for timeseries plot.
html field / id to update:
- fig_ts
"""
@app.callback(
[Output("fig-ts", "figure")],
[
Input("flight-dropdown", "value"),
Input("variable-dropdown", "value"),
Input("second-variable-dropdown", "value"),
],
)
def update_ts_plot(selected_flight: int, primary_variable: str, secondary_variable: str):
filtered_df = timeseries_data[timeseries_data["flight_number"] == selected_flight]
valid_indices = filtered_df[primary_variable].notna()
unit_primary = var_info.loc[primary_variable, :].Unit
unit_secondary = (
var_info.loc[secondary_variable, :].Unit
if secondary_variable in var_info.index
else "-"
)
fig_ts = make_subplots(specs=[[{"secondary_y": True}]])
fig_ts.add_trace(
go.Scatter(
x=filtered_df.index[valid_indices & ~filtered_df["BB_flag"]],
y=filtered_df.loc[valid_indices & ~filtered_df["BB_flag"], primary_variable],
mode="markers",
marker={
"size": 3,
"color": "blue",
"showscale": False,
},
showlegend=False,
)
)
fig_ts.add_trace(
go.Scatter(
x=filtered_df.index[valid_indices & filtered_df["BB_flag"]],
y=filtered_df.loc[valid_indices & filtered_df["BB_flag"], primary_variable],
mode="markers",
marker={
"size": 3,
"color": "red",
"showscale": False,
},
name="flagged 'biomass burning'",
)
)
if secondary_variable != "None":
fig_ts.add_trace(
go.Scatter(
x=filtered_df.index,
y=filtered_df[secondary_variable],
mode="markers",
marker={
"size": 2,
"color": "black",
"showscale": False,
},
name=secondary_variable,
),
secondary_y=True,
)
fig_ts.update_layout(
paper_bgcolor="#e8e8e8",
margin={"l": 45, "r": 10, "t": 20, "b": 50},
legend={
"x": 0.01,
"y": 0.99,
"xanchor": "left",
"yanchor": "top",
"bgcolor": "rgba(255, 255, 255, 0.7)",
"bordercolor": "rgba(0, 0, 0, 0.2)",
"borderwidth": 1,
},
)
fig_ts.update_xaxes(title="UTC")
fig_ts.update_yaxes(title=f"{primary_variable} {unit_primary}")
fig_ts.update_yaxes(title=f"{secondary_variable} {unit_secondary}", secondary_y=True)
return [fig_ts]
uv.lock
+ 9
− 9
View file @ 2b2e5969
......@@ -80,7 +80,7 @@ wheels = [
[[package]]
name = "caribic-dash"
version = "0.0.13"
version = "0.0.16"
source = { virtual = "." }
dependencies = [
{ name = "dash" },
......@@ -554,16 +554,16 @@ wheels = [
[[package]]
name = "protobuf"
version = "6.30.1"
version = "6.30.2"
source = { registry = "https://pypi.org/simple" }
sdist = { url = "https://files.pythonhosted.org/packages/55/de/8216061897a67b2ffe302fd51aaa76bbf613001f01cd96e2416a4955dd2b/protobuf-6.30.1.tar.gz", hash = "sha256:535fb4e44d0236893d5cf1263a0f706f1160b689a7ab962e9da8a9ce4050b780", size = 429304 }
sdist = { url = "https://files.pythonhosted.org/packages/c8/8c/cf2ac658216eebe49eaedf1e06bc06cbf6a143469236294a1171a51357c3/protobuf-6.30.2.tar.gz", hash = "sha256:35c859ae076d8c56054c25b59e5e59638d86545ed6e2b6efac6be0b6ea3ba048", size = 429315 }
wheels = [
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[[package]]
......
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