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Drop nan values with histogram display (#484)
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* drop nan values with histogram display

* add missing data array subset in

* fix datasets without time
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@mgrover1
mgrover1 authored Jun 23, 2022
1 parent 320b799 commit 014a5c9
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Showing 2 changed files with 30 additions and 24 deletions.
22 changes: 14 additions & 8 deletions act/plotting/histogramdisplay.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -83,6 +83,11 @@ def set_yrng(self, yrng, subplot_index=(0,)):
self.axes[subplot_index].set_ylim(yrng)
self.yrng[subplot_index, :] = yrng

def _get_data(self, dsname, fields):
if isinstance(fields, str):
fields = [fields]
return self._obj[dsname][fields].dropna('time')

def plot_stacked_bar_graph(
self,
field,
Expand Down Expand Up @@ -139,16 +144,17 @@ def plot_stacked_bar_graph(
elif dsname is None:
dsname = list(self._obj.keys())[0]

xdata = self._obj[dsname][field]
if sortby_field is not None:
ds = self._get_data(dsname, [field, sortby_field])
xdata, ydata = ds[field], ds[sortby_field]
else:
xdata = self._get_data(dsname, field)[field]

if 'units' in xdata.attrs:
xtitle = ''.join(['(', xdata.attrs['units'], ')'])
else:
xtitle = field

if sortby_field is not None:
ydata = self._obj[dsname][sortby_field]

if bins is not None and sortby_bins is None and sortby_field is not None:
# We will defaut the y direction to have the same # of bins as x
sortby_bins = np.linspace(ydata.values.min(), ydata.values.max(), len(bins))
Expand Down Expand Up @@ -268,7 +274,7 @@ def plot_size_distribution(
elif dsname is None:
dsname = list(self._obj.keys())[0]

xdata = self._obj[dsname][field]
xdata = self._get_data(dsname, field)[field]

if isinstance(bins, str):
bins = self._obj[dsname][bins]
Expand Down Expand Up @@ -380,7 +386,7 @@ def plot_stairstep_graph(
elif dsname is None:
dsname = list(self._obj.keys())[0]

xdata = self._obj[dsname][field]
xdata = self._get_data(dsname, field)[field]

if 'units' in xdata.attrs:
xtitle = ''.join(['(', xdata.attrs['units'], ')'])
Expand Down Expand Up @@ -522,13 +528,13 @@ def plot_heatmap(
elif dsname is None:
dsname = list(self._obj.keys())[0]

xdata = self._obj[dsname][x_field]
ds = self._get_data(dsname, [x_field, y_field])
xdata, ydata = ds[x_field], ds[y_field]

if 'units' in xdata.attrs:
xtitle = ''.join(['(', xdata.attrs['units'], ')'])
else:
xtitle = x_field
ydata = self._obj[dsname][y_field]

if x_bins is not None and y_bins is None:
# We will defaut the y direction to have the same # of bins as x
Expand Down
32 changes: 16 additions & 16 deletions act/tests/test_plotting.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -171,13 +171,13 @@ def test_histogram_errors():
mu = 50
bins = np.linspace(0, 100, 50)
ydata = 1 / (sigma * np.sqrt(2 * np.pi)) * np.exp(-((bins - mu) ** 2) / (2 * sigma**2))
y_array = xr.DataArray(ydata, dims={'bins': bins})
bins = xr.DataArray(bins, dims={'bins': bins})
my_fake_ds = xr.Dataset({'bins': bins, 'ydata': y_array})
y_array = xr.DataArray(ydata, dims={'time': bins})
bins = xr.DataArray(bins, dims={'time': bins})
my_fake_ds = xr.Dataset({'time': bins, 'ydata': y_array})
histdisplay = HistogramDisplay(my_fake_ds)
histdisplay.axes = None
histdisplay.fig = None
histdisplay.plot_size_distribution('ydata', 'bins', set_title='Fake distribution.')
histdisplay.plot_size_distribution('ydata', 'time', set_title='Fake distribution.')
assert histdisplay.fig is not None
assert histdisplay.axes is not None

Expand Down Expand Up @@ -549,11 +549,11 @@ def test_size_distribution():
mu = 50
bins = np.linspace(0, 100, 50)
ydata = 1 / (sigma * np.sqrt(2 * np.pi)) * np.exp(-((bins - mu) ** 2) / (2 * sigma**2))
y_array = xr.DataArray(ydata, dims={'bins': bins})
bins = xr.DataArray(bins, dims={'bins': bins})
my_fake_ds = xr.Dataset({'bins': bins, 'ydata': y_array})
y_array = xr.DataArray(ydata, dims={'time': bins})
bins = xr.DataArray(bins, dims={'time': bins})
my_fake_ds = xr.Dataset({'time': bins, 'ydata': y_array})
histdisplay = HistogramDisplay(my_fake_ds)
histdisplay.plot_size_distribution('ydata', 'bins', set_title='Fake distribution.')
histdisplay.plot_size_distribution('ydata', 'time', set_title='Fake distribution.')
try:
return histdisplay.fig
finally:
Expand Down Expand Up @@ -948,12 +948,13 @@ def test_time_plot2():
@pytest.mark.mpl_image_compare(tolerance=30)
def test_y_axis_flag_meanings():
variable = 'detection_status'
obj = arm.read_netcdf(sample_files.EXAMPLE_CEIL1,
keep_variables=[variable, 'lat', 'lon', 'alt'])
obj = arm.read_netcdf(
sample_files.EXAMPLE_CEIL1, keep_variables=[variable, 'lat', 'lon', 'alt']
)
obj.clean.clean_arm_state_variables(variable, override_cf_flag=True)

display = TimeSeriesDisplay(obj, figsize=(12, 8), subplot_shape=(1,))
display.plot(variable, subplot_index=(0, ), day_night_background=True, y_axis_flag_meanings=18)
display.plot(variable, subplot_index=(0,), day_night_background=True, y_axis_flag_meanings=18)
display.fig.subplots_adjust(left=0.15, right=0.95, bottom=0.1, top=0.94)

return display.fig
Expand All @@ -969,13 +970,12 @@ def test_colorbar_labels():

y_axis_labels = {}
flag_colors = ['white', 'green', 'blue', 'red', 'cyan', 'orange', 'yellow', 'black', 'gray']
for value, meaning, color in zip(obj[variable].attrs['flag_values'],
obj[variable].attrs['flag_meanings'],
flag_colors):
for value, meaning, color in zip(
obj[variable].attrs['flag_values'], obj[variable].attrs['flag_meanings'], flag_colors
):
y_axis_labels[value] = {'text': meaning, 'color': color}

display.plot(variable, subplot_index=(0, ), colorbar_labels=y_axis_labels,
cbar_h_adjust=0)
display.plot(variable, subplot_index=(0,), colorbar_labels=y_axis_labels, cbar_h_adjust=0)
display.fig.subplots_adjust(left=0.08, right=0.88, bottom=0.1, top=0.94)

return display.fig

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