Implemented animation of depth dependent timeseries

* animate_depth_timeseries creates aplotly animation of a timeseries
* doc/animate has an example
* test-data/animate/animate_depth_timeseries_expected contains expected frames
* Added dependency on plotly and dash
* Added test dependency on kaleido for testing plotly animation

daisy_vis/animate/__init__.py

@@ -0,0 +1,2 @@
+'''Functions for animating dlf data'''
+from .animate_depth_timeseries import *

daisy_vis/animate/animate_depth_timeseries.py

@@ -0,0 +1,60 @@
+# pylint: disable=missing-module-docstring
+import plotly.express as px
+from daisy_vis.transform import daisy_time_to_timestamp, depth_wide_to_long
+
+__all__ = [
+    'animate_depth_timeseries'
+]
+
+def animate_depth_timeseries(var_name, dlf, *,
+                             figsize=(1000,1000),
+                             title=None,
+                             var_lim=None,
+                             depth_lim=None
+                             ):
+    # pylint: disable=too-many-arguments
+    '''
+    Parameters
+    ----------
+    var_name : str
+
+    dlf : daisy_vis.io.dlf.Dlf
+
+    figsize : tuple of int, optional
+      (width, height) of figure in pixels
+
+    title : str, optional
+      Title of figure
+
+    var_lim : (float, float), optional
+      Limit of `var_name` values that are plotted. If None it is set to the data limit with a 10%
+      margin.
+
+    depth_lim : (float,float), optional
+      Limit of depth. If None it is set to the (lowest depth - 10, 10)    
+
+    Returns
+    -------
+    plotly.graph_objs.Figure
+    '''
+    dlf = daisy_time_to_timestamp(dlf, 'time')
+    dlf = depth_wide_to_long(dlf, var_name, 'time', 'z')
+    if figsize is None:
+        width, height = None, None
+    else:
+        width, height = figsize
+    if var_lim is None:
+        var_min = dlf.body[var_name].min()        
+        var_max = dlf.body[var_name].max()
+        var_lim = var_min - abs(var_min)*0.1, var_max + abs(var_max)*0.1
+    if depth_lim is None:
+        depth_lim = dlf.body['z'].min() - 10, 10
+    return px.scatter(dlf.body,
+                      x=var_name,
+                      y='z',
+                      animation_frame='time',
+                      title=title,
+                      width=width,
+                      height=height,
+                      range_x=var_lim,
+                      range_y=depth_lim,)

daisy_vis/animate/test/conftest.py

@@ -0,0 +1,18 @@
+'''Test data for tests in the amimate module'''
+import pytest
+from daisy_vis.io.dlf import read_dlf
+
+@pytest.fixture
+def depth_timeseries():
+    '''A depth time series'''
+    return  read_dlf('test-data/daily/DailyP/DailyP-Daily-WaterFlux.dlf')
+
+@pytest.fixture
+def depth_timeseries_outdir():
+    '''Outdir for generated files'''
+    return 'test-data/animate/animate_depth_timeseries_actual'
+
+@pytest.fixture
+def depth_timeseries_expected_dir():
+    '''Outdir for reference files'''
+    return 'test-data/animate/animate_depth_timeseries_expected'

daisy_vis/animate/test/test_animate_depth_timeseries.py

@@ -0,0 +1,36 @@
+'''Test animate_depth_timeseries'''
+import os
+import filecmp
+import pytest
+import plotly
+from daisy_vis.animate import animate_depth_timeseries
+
+@pytest.mark.filterwarnings(r'ignore:setDaemon\(\) is deprecated, set the daemon attribute instead')
+def test_png_rendering_is_the_same(depth_timeseries,
+                                   depth_timeseries_outdir,
+                                   depth_timeseries_expected_dir):
+    '''Save animated timeseries as a series of png files and compare with an existing reference'''
+    os.makedirs(depth_timeseries_outdir, exist_ok=True)
+    fig = animate_depth_timeseries('q', depth_timeseries)
+    actual_files = set()
+    for frame in range(len(fig.frames)):
+        fig.layout['sliders'][0]['active'] = frame
+        fig = plotly.graph_objects.Figure(data=fig['frames'][frame]['data'],
+                                          frames=fig['frames'],
+                                          layout=fig.layout)
+        fname = f'frame-{frame:02d}.png'
+        fig.write_image(os.path.join(depth_timeseries_outdir, fname))
+        actual_files.add(fname)
+
+    expected_files = {
+        entry.name for entry in os.scandir(depth_timeseries_expected_dir) if entry.is_file()
+    }
+    assert actual_files <= expected_files <= actual_files
+
+    match, mismatch, errors = filecmp.cmpfiles(depth_timeseries_outdir,
+                                               depth_timeseries_expected_dir,
+                                               expected_files,
+                                               shallow=False)
+    assert len(match) == len(expected_files)
+    assert len(mismatch) == 0
+    assert len(errors) == 0

doc/README.md

@@ -8,3 +8,8 @@
 
  * [Plot annual values](plot/plot_annual_values.py). Also available as a [jupyter notebook](plot/plot_annual_values.ipynb) [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/daisy-model/daisy-vis/main?labpath=doc%2Fplot%2Fplot_annual_values.ipynb)
  * [Plot daily values](plot/plot_daily_values.py). Also available as a [jupyter notebook](plot/plot_daily_values.ipynb) [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/daisy-model/daisy-vis/main?labpath=doc%2Fplot%2Fplot_daily_values.ipynb)
+
+## Animation
+Requires plotly and dash (for running outside a notebook)
+
+  * [Annimate depth dependent time series](animate/animate_depth_dependent.py). Also available as a [jupyter notebook](animate/animate_depth_dependent.py)

doc/animate/animate_depth_dependent.py

@@ -0,0 +1,30 @@
+'''Animate daily waterflux'''
+import os
+import sys
+from dash import Dash, dcc, html
+from daisy_vis.io.dlf import read_dlf
+from daisy_vis.animate import animate_depth_timeseries
+
+def main():
+    '''Run as `python <path/to/animate_depth_dependent.py>`'''
+    dirname = os.path.dirname(os.path.realpath(sys.argv[0]))
+    path = os.path.join(
+        dirname, '..', '..', 'test-data', 'daily', 'DailyP', 'DailyP-Daily-WaterFlux.dlf'
+    )
+    dlf = read_dlf(path)
+    var_name = 'q'
+    fig = animate_depth_timeseries(var_name, dlf)
+
+    app = Dash(__name__)
+    app.layout = html.Div(children=[
+        html.H1(children='DailyP'),
+        html.Div(children='Daily logged waterflux'),
+        dcc.Graph(
+            id='daily-waterflux',
+            figure=fig
+        )
+    ])        
+    app.run(debug=True)
+
+if __name__ == '__main__':
+    main()

requirements.txt

@@ -1,2 +1,4 @@
 pandas
 matplotlib
+plotly
+dash

requirements_test.txt

@@ -1,2 +1,3 @@
 pytest
 pytest-mpl
+kaleido

setup.cfg

@@ -26,6 +26,8 @@ platforms = any
 install_requires =
     pandas
     matplotlib
+    plotly
+    dash
 packages = find_namespace:
 package_dir =
     =.

test-data/animate/.gitignore

@@ -0,0 +1 @@
+animate_depth_timeseries_actual