"""
Class for creating plots from Airborne Radar objects.
"""
import numpy as np
from ..core import transforms
from ..core.transforms import antenna_to_cartesian, antenna_to_cartesian_track_relative
from . import common
from .radardisplay import RadarDisplay
[docs]class AirborneRadarDisplay(RadarDisplay):
"""
A display object for creating plots from data in a airborne radar object.
Parameters
----------
radar : Radar
Radar object to use for creating plots, should be an airborne radar.
shift : (float, float)
Shifts in km to offset the calculated x and y locations.
Attributes
----------
plots : list
List of plots created.
plot_vars : list
List of fields plotted, order matches plot list.
cbs : list
List of colorbars created.
origin : str
'Origin' or 'Radar'.
shift : (float, float)
Shift in meters.
loc : (float, float)
Latitude and Longitude of radar in degrees.
fields : dict
Radar fields.
scan_type : str
Scan type.
ranges : array
Gate ranges in meters.
azimuths : array
Azimuth angle in degrees.
elevations : array
Elevations in degrees.
fixed_angle : array
Scan angle in degrees.
rotation : array
Rotation angle in degrees.
roll : array
Roll angle in degrees.
drift : array
Drift angle in degrees.
tilt : array
Tilt angle in degrees.
heading : array
Heading angle in degrees.
pitch : array
Pitch angle in degrees.
altitude : array
Altitude angle in meters.
"""
def __init__(self, radar, shift=(0.0, 0.0)):
"""Initialize the object."""
self.fixed_angle = radar.fixed_angle["data"][0]
self.rotation = radar.rotation["data"]
self.roll = radar.roll["data"]
self.drift = radar.drift["data"]
self.tilt = radar.tilt["data"]
self.heading = radar.heading["data"]
self.pitch = radar.pitch["data"]
self.altitude = radar.altitude["data"]
super().__init__(radar, shift)
# radar location in latitude and longitude
middle_lat = int(radar.latitude["data"].shape[0] / 2)
middle_lon = int(radar.longitude["data"].shape[0] / 2)
lat = float(radar.latitude["data"][middle_lat])
lon = float(radar.longitude["data"][middle_lon])
self.loc = (lat, lon)
####################
# Plotting methods #
####################
[docs] def plot(self, field, sweep=0, **kwargs):
"""
Create a plot appropiate for the radar.
This function calls the plotting function corresponding to
the scan_type of the radar. Additional keywords can be passed to
customize the plot, see the appropiate plot function for the
allowed keywords.
Parameters
----------
field : str
Field to plot.
sweep : int
Sweep number to plot, not used for VPT scans.
See Also
--------
plot_ppi : Plot a PPI scan
plot_sweep_grid : Plot a RHI or VPT scan
"""
if self.scan_type == "ppi":
self.plot_ppi(field, sweep, **kwargs)
elif self.scan_type == "rhi":
self.plot_sweep_grid(field, sweep, **kwargs)
elif self.scan_type == "vpt":
self.plot_sweep_grid(field, sweep, **kwargs)
else:
raise ValueError("unknown scan_type % s" % (self.scan_type))
return
[docs] def plot_sweep_grid(
self,
field,
sweep=0,
ignoreTilt=False,
mask_tuple=None,
vmin=None,
vmax=None,
cmap=None,
norm=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,
filter_transitions=True,
ax=None,
fig=None,
gatefilter=None,
raster=False,
ticks=None,
ticklabs=None,
**kwargs
):
"""
Plot a sweep as a grid.
Additional arguments are passed to Matplotlib's pcolormesh function.
Parameters
----------
field : str
Field to plot.
sweep : int, optional
Sweep number to plot.
Other Parameters
----------------
ignoreTilt : bool
True to ignore tilt angle when running the
antenna_to_cartesian_track_relative coordinate transformation (by
setting tilt angle to 0), effectively plotting data relative to
slant range (the same plotting method utilized by the NCAR
soloii/3 software). False (default) plots relative to the aircraft
longitudinal axis.
mask_tuple : (str, float)
Tuple containing the field name and value below which to mask
field prior to plotting, for example to mask all data where
NCP < 0.5 set mask_tuple to ['NCP', 0.5]. None performs no masking.
vmin : float
Luminance minimum value, None for default value.
Parameter is ignored is norm is not None.
vmax : float
Luminance maximum value, None for default value.
Parameter is 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 sweep 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
plotted.
gatefilter : GateFilter
GateFilter instance. None will result in no gatefilter mask being
applied to data.
filter_transitions : bool
True to remove rays where the antenna was in transition between
sweeps from the plot. False will include these rays in the plot.
No rays are filtered when the antenna_transition attribute of the
underlying radar is not present.
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.
raster : bool
False by default. Set to true to render the display as a raster
rather than a vector in call to pcolormesh. Saves time in plotting
high resolution data over large areas. Be sure to set the dpi
of the plot for your application if you save it as a vector format
(i.e., pdf, eps, svg).
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._radar, field, vmin, vmax)
cmap = common.parse_cmap(cmap, field)
# get data for the plot
data = self._get_data(field, sweep, mask_tuple, filter_transitions, gatefilter)
x, z = self._get_x_z(sweep, edges, filter_transitions, ignoreTilt=ignoreTilt)
# 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 data
if norm is not None: # if norm is set do not override with vmin/vmax
vmin = vmax = None
pm = ax.pcolormesh(
x, z, data, vmin=vmin, vmax=vmax, cmap=cmap, norm=norm, **kwargs
)
if raster:
pm.set_rasterized(True)
if title_flag:
self._set_title(field, sweep, title, ax)
if axislabels_flag:
self._label_axes_rhi(axislabels, ax)
# add plot and field to lists
self.plots.append(pm)
self.plot_vars.append(field)
# colorbar options
if colorbar_flag:
self.plot_colorbar(
mappable=pm,
label=colorbar_label,
orient=colorbar_orient,
field=field,
ax=ax,
fig=fig,
ticks=ticks,
ticklabs=ticklabs,
)
[docs] def label_xaxis_x(self, ax=None):
"""Label the xaxis with the default label for x units."""
ax = common.parse_ax(ax)
ax.set_xlabel("Horizontal distance from " + self.origin + " (km)")
[docs] def label_yaxis_y(self, ax=None):
"""Label the yaxis with the default label for y units."""
ax = common.parse_ax(ax)
ax.set_ylabel("Horizontal distance from " + self.origin + " (km)")
[docs] def label_yaxis_z(self, ax=None):
"""Label the yaxis with the default label for z units."""
ax = common.parse_ax(ax)
ax.set_ylabel("Distance Above " + self.origin + " (km)")
def _get_x_z(self, sweep, edges, filter_transitions, ignoreTilt=False):
"""Retrieve and return x and z coordinate in km."""
x, _, z = self._get_x_y_z(
sweep, edges, filter_transitions, ignoreTilt=ignoreTilt
)
return x, z
def _get_x_y_z(self, sweep, edges, filter_transitions, ignoreTilt=False):
"""Retrieve and return x, y, and z coordinate in km."""
sweep_slice = self._radar.get_slice(sweep)
if self._radar.metadata["platform_type"] == "aircraft_belly":
if filter_transitions and self.antenna_transition is not None:
in_trans = self.antenna_transition[sweep_slice]
ranges = self.ranges
azimuths = self.azimuths[in_trans == 0]
elevations = self.elevations[in_trans == 0]
else:
ranges = self.ranges
azimuths = self.azimuths[sweep_slice]
elevations = self.elevations[sweep_slice]
if edges:
if len(ranges) != 1:
ranges = transforms._interpolate_range_edges(ranges)
if len(elevations) != 1:
elevations = transforms._interpolate_elevation_edges(elevations)
if len(azimuths) != 1:
azimuths = transforms._interpolate_azimuth_edges(azimuths)
rg, azg = np.meshgrid(ranges, azimuths)
rg, eleg = np.meshgrid(ranges, elevations)
x, y, z = antenna_to_cartesian(rg / 1000.0, azg, eleg)
else:
if filter_transitions and self.antenna_transition is not None:
in_trans = self.antenna_transition[sweep_slice]
ranges = self.ranges
rotation = self.rotation[in_trans == 0]
roll = self.roll[in_trans == 0]
drift = self.drift[in_trans == 0]
tilt = self.tilt[in_trans == 0]
pitch = self.pitch[in_trans == 0]
else:
ranges = self.ranges
rotation = self.rotation[sweep_slice]
roll = self.roll[sweep_slice]
drift = self.drift[sweep_slice]
tilt = self.tilt[sweep_slice]
pitch = self.pitch[sweep_slice]
if ignoreTilt:
tilt = tilt * 0.0
if edges:
if len(ranges) != 1:
ranges = transforms._interpolate_range_edges(ranges)
if len(rotation) != 1:
rotation = transforms._interpolate_azimuth_edges(rotation)
roll = transforms._interpolate_azimuth_edges(roll)
drift = transforms._interpolate_azimuth_edges(drift)
tilt = transforms._interpolate_azimuth_edges(tilt)
pitch = transforms._interpolate_azimuth_edges(pitch)
rg, rotg = np.meshgrid(ranges, rotation)
rg, rollg = np.meshgrid(ranges, roll)
rg, driftg = np.meshgrid(ranges, drift)
rg, tiltg = np.meshgrid(ranges, tilt)
rg, pitchg = np.meshgrid(ranges, pitch)
x, y, z = antenna_to_cartesian_track_relative(
rg / 1000.0, rotg, rollg, driftg, tiltg, pitchg
)
x = (x + self.shift[0]) / 1000.0
y = (y + self.shift[1]) / 1000.0
z = z / 1000.0
return x, y, z