matplotlib / matplotlib/pytest-mpl
Colormap not preserved in scatter plot when generating baseline plot.
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- Python
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Descripción
Hello, when we are trying to create a baseline for a unit test that uses a scatter plot, we have noticed that pytest-mpl has not been preserving the colormap used in our scatter plot.
For example, the plot we wish to compare against is this:

When we run the unittest through simply doing an import and showing the resulting figure we get the figure above. However, whenever we use pytest to generate the baseline figure, we get the below figure:

Main test:
@pytest.mark.mpl_image_compare(tolerance=30)
def test_time_height_scatter():
sonde_ds = arm.read_netcdf(
sample_files.EXAMPLE_SONDE1)
display = TimeSeriesDisplay({'sgpsondewnpnC1.b1': sonde_ds},
figsize=(7, 3))
display.time_height_scatter('tdry', day_night_background=True)
sonde_ds.close()
return display.fig
time_height_scatter routine:
def time_height_scatter(
self, data_field=None, dsname=None, cmap='rainbow',
alt_label=None, alt_field='alt', cb_label=None, **kwargs):
"""
Create a time series plot of altitued and data varible with
color also indicating value with a color bar. The Color bar is
positioned to serve both as the indicator of the color intensity
and the second y-axis.
Parameters
----------
data_field: str
Name of data field in the object to plot on second y-axis
height_field: str
Name of height field in the object to plot on first y-axis.
dsname: str or None
The name of the datastream to plot
cmap: str
Colorbar corlor map to use.
alt_label: str
Altitued first y-axis label to use. If not set will try to use
long_name and units.
alt_field: str
Label for field in the object to plot on first y-axis.
cb_label: str
Colorbar label to use. If not set will try to use
long_name and units.
**kwargs: keyword arguments
Any other keyword arguments that will be passed
into TimeSeriesDisplay.plot module when the figure
is made.
"""
if dsname is None and len(self._arm.keys()) > 1:
raise ValueError(("You must choose a datastream when there are 2 "
"or more datasets in the TimeSeriesDisplay "
"object."))
elif dsname is None:
dsname = list(self._arm.keys())[0]
# Get data and dimensions
data = self._arm[dsname][data_field]
altitude = self._arm[dsname][alt_field]
dim = list(self._arm[dsname][data_field].dims)
xdata = self._arm[dsname][dim[0]]
if alt_label is None:
try:
alt_label = (altitude.attrs['long_name'] +
''.join([' (', altitude.attrs['units'], ')']))
except KeyError:
alt_label = alt_field
if cb_label is None:
try:
cb_label = (data.attrs['long_name'] +
''.join([' (', data.attrs['units'], ')']))
except KeyError:
cb_label = data_field
colorbar_map = plt.cm.get_cmap(cmap)
self.fig.subplots_adjust(left=0.1, right=0.86,
bottom=0.16, top=0.91)
ax1 = self.plot(alt_field, color='black', **kwargs)
ax1.set_ylabel(alt_label)
ax2 = ax1.twinx()
sc = ax2.scatter(xdata.values, data.values, c=data.values,
marker='.', cmap=colorbar_map)
cbaxes = self.fig.add_axes(
[self.fig.subplotpars.right + 0.02, self.fig.subplotpars.bottom,
0.02, self.fig.subplotpars.top - self.fig.subplotpars.bottom])
cbar = plt.colorbar(sc, cax=cbaxes)
ax2.set_ylim(cbar.get_clim())
cbar.ax.set_ylabel(cb_label)
ax2.set_yticklabels([])
return self.axes[0]
Any help you could provide on this would be appreciated.
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Primeros pasos
- Lee el issue completo y luego la guía de contribución del proyecto.
- Comenta en el issue que vas a ocuparte — evita que dos personas hagan lo mismo.
- Haz un fork del repositorio y trabaja en una rama.
- Abre un pull request que haga referencia al número del issue.
Línea de trabajo
Comienza con el ejemplo mostrado de test_time_height_scatter y la rutina time_height_scatter, y después compara la figura mostrada directamente con la baseline generada mediante pytest-mpl. Rastrea cómo se capturan el gráfico de dispersión y su mapa de colores durante la generación de la baseline; se considera terminado cuando la baseline generada conserva el mapa de colores mostrado por la figura directa.
Escrito por el modelo de indexación a partir del texto del issue.
Evaluación
- Stack tecnológico
- matplotlib, python
- Área
- data-visualization, testing-qa
- Tipo de issue
- Error
- Dificultad
- 4/5
- Tiempo estimado
- 3-5 días
- Estado de actividad
- Estancado
- Claridad
- Bastante claro
- Aptitud para principiantes
- 42/100