def test_generate_longitudinal_level_title():
grid_shape = (1, 1, 1)
grid_limits = ((0, 1), (0, 1), (0, 1))
grid = pyart.testing.make_empty_grid(grid_shape, grid_limits)
grid.metadata['instrument_name'] = 'bar'
grid.fields['foo'] = {}
title = common.generate_longitudinal_level_title(grid, 'foo', 0)
assert title == ('bar 0.0 km east of origin 2000-01-01T00:00:00Z \nFoo')
grid.x['data'][0] = -1000.
title = common.generate_longitudinal_level_title(grid, 'foo', 0)
assert title == ('bar 1.0 km west of origin 2000-01-01T00:00:00Z \nFoo')
def test_generate_longitudinal_level_title():
grid_shape = (1, 1, 1)
grid_limits = ((0, 1), (0, 1), (0, 1))
grid = pyart.testing.make_empty_grid(grid_shape, grid_limits)
grid.metadata['instrument_name'] = 'bar'
grid.fields['foo'] = {}
title = common.generate_longitudinal_level_title(grid, 'foo', 0)
assert title == (
'bar 0.0 km east of origin 2000-01-01T00:00:00Z \nFoo')
grid.x['data'][0] = -1000.
title = common.generate_longitudinal_level_title(grid, 'foo', 0)
assert title == (
'bar 1.0 km west of origin 2000-01-01T00:00:00Z \nFoo')
def generate_longitudinal_level_title(self, field, level):
"""
Generate a title for a plot.
Parameters
----------
field : str
Field plotted.
level : int
Longitudinal level plotted.
Returns
-------
title : str
Plot title.
"""
return common.generate_longitudinal_level_title(
self.grid, field, level)
def plot_longitudinal_level(self,
field,
x_index,
vmin=None,
vmax=None,
norm=None,
cmap=None,
mask_outside=False,
title=None,
title_flag=True,
axislabels=(None, None),
axislabels_flag=True,
colorbar_flag=True,
colorbar_label=None,
colorbar_orient='vertical',
edges=True,
ax=None,
fig=None,
ticks=None,
ticklabs=None,
**kwargs):
"""
Plot a slice along a given longitude.
Additional arguments are passed to Basemaps's pcolormesh function.
Parameters
----------
field : str
Field to be plotted.
x_index : float
Index of the longitudinal level to plot.
vmin, vmax : float
Lower and upper range for the colormesh. If either parameter is
None, a value will be determined from the field attributes (if
available) or the default values of -8, 64 will be used.
Parameters are ignored is norm is not None.
norm : Normalize or None, optional
matplotlib Normalize instance used to scale luminance data. If not
None the vmax and vmin parameters are ignored. If None, vmin and
vmax are used for luminance scaling.
cmap : str or None
Matplotlib colormap name. None will use the default colormap for
the field being plotted as specified by the Py-ART configuration.
mask_outside : bool
True to mask data outside of vmin, vmax. False performs no
masking.
title : str
Title to label plot with, None to use default title generated from
the field and lat,lon parameters. Parameter is ignored if
title_flag is False.
title_flag : bool
True to add a title to the plot, False does not add a title.
axislabels : (str, str)
2-tuple of x-axis, y-axis labels. None for either label will use
the default axis label. Parameter is ignored if axislabels_flag is
False.
axislabels_flag : bool
True to add label the axes, False does not label the axes.
colorbar_flag : bool
True to add a colorbar with label to the axis. False leaves off
the colorbar.
colorbar_label : str
Colorbar label, None will use a default label generated from the
field information.
colorbar_orient : 'vertical' or 'horizontal'
Colorbar orientation.
edges : bool
True will interpolate and extrapolate the gate edges from the
range, azimuth and elevations in the radar, treating these
as specifying the center of each gate. False treats these
coordinates themselved as the gate edges, resulting in a plot
in which the last gate in each ray and the entire last ray are not
not plotted.
ax : Axis
Axis to plot on. None will use the current axis.
fig : Figure
Figure to add the colorbar to. None will use the current figure.
ticks : array
Colorbar custom tick label locations.
ticklabs : array
Colorbar custom tick labels.
"""
# parse parameters
ax, fig = common.parse_ax_fig(ax, fig)
vmin, vmax = common.parse_vmin_vmax(self.grid, field, vmin, vmax)
cmap = common.parse_cmap(cmap, field)
data = self.grid.fields[field]['data'][:, :, x_index]
# mask the data where outside the limits
if mask_outside:
data = np.ma.masked_invalid(data)
data = np.ma.masked_outside(data, vmin, vmax)
# plot the grid
y_1d = self.grid.y['data'] / 1000
z_1d = self.grid.z['data'] / 1000
if edges:
if len(y_1d) > 1:
y_1d = _interpolate_axes_edges(y_1d)
if len(z_1d) > 1:
z_1d = _interpolate_axes_edges(z_1d)
xd, yd = np.meshgrid(y_1d, z_1d)
if norm is not None: # if norm is set do not override with vmin, vmax
vmin = vmax = None
pm = ax.pcolormesh(xd,
yd,
data,
vmin=vmin,
vmax=vmax,
norm=norm,
cmap=cmap,
**kwargs)
self.mappables.append(pm)
self.fields.append(field)
if title_flag:
if title is None:
ax.set_title(
common.generate_longitudinal_level_title(
self.grid, field, x_index))
else:
ax.set_title(title)
if axislabels_flag:
self._label_axes_longitude(axislabels, ax)
if colorbar_flag:
self.plot_colorbar(mappable=pm,
label=colorbar_label,
orientation=colorbar_orient,
field=field,
ax=ax,
fig=fig,
ticks=ticks,
ticklabs=ticklabs)
return