# (C) British Crown Copyright 2017, Met Office
#
# This code is free software: you can redistribute it and/or modify it under
# the terms of the GNU Lesser General Public License as published by the
# Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This code is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Lesser General Public License for more details.
#
# Combination scatter+contour plot
import iris
import DWR
import numpy
import collections
import matplotlib
from matplotlib.patches import Circle
import cartopy
import cartopy.crs as ccrs
import Meteorographica as mg
from .scatter import plot_scatter
from .contour import plot_contour
[docs]def plot_scatter_contour(fig,field,obs_r,dwr_obs,dte,**kwargs):
"""Make a combined contour-plot and scatter plot
Args:
fig (:`matplotlib.figure`): Figure to hold the plot
field (:obj:`iris.Cube.cube`): Reanalysis mslp ensemble
obs_r (:obj:`pandas.DataFrame`): Reanalysis observations.
dwr_obs (:obj:`pandas.DataFrame`): DWR observations.
dte (:obj:`datetime.datetime`): Time of data to plot
Kwargs:
projection (:obj:`cartopy.crs`): Map projection to use, default UKV.
scale (:obj:`float`): Map scale - latitude range, default 20.
pressure_range (:obj:`list`): (min,max) pressure for scatterplot, default [945,1045].
obs_radius (:obj:`float`): Reanalysis obs plot size, default 0.15.
contour_levels (:obj:`list`): Values to plot contours at, default numpy.arange(870,1050,10).
contour_width (:obj:`float`): Width of member contour lines, default 0.1.
contour_mask (:obj:`float`): Plot mean contours where spread < this, default 3.
n_contours (:obj:`int`): Max. number of member contour to plot, default None - all members.
dwr_color (:obj:`str`): Either a color name, or the string 'anomaly' (default) to color by pressure anomaly.
dwr_anomaly_range (:obj:`float`): Anomaly color scale factor, default 20.
dwr_radius (:obj:`float`): DWR obs plot size, default 0.25.
xlabel (:obj:`str`): x-axis label for scatter plot, default 'MSLP (hPa)'.
scatter_point_size (:obj:`float`): Size of ensemble dots in scatter plot (pts), default 25.
scatter_alpha (:obj:`float`): Alpha transparency of ensemble dots in scatter plot (pts), default 0.5.
stations (:obj:`list`): Names of DWR stations to plot, if missing, taken from dwr_obs.
station_latlon (:obj:`dict`): Positions of DWR stations to plot (each station entry a dictionary with 'latitude' and 'longitude'), if missing, taken from dwr_obs.
|
"""
# Set keyword argument defaults
kwargs.setdefault('projection',ccrs.RotatedPole(pole_longitude=177.5,
pole_latitude=35.5))
kwargs.setdefault('scale',20.0)
kwargs.setdefault('stations',list(collections.OrderedDict.fromkeys(
dwr_obs.loc[:,'name']).keys()))
kwargs.setdefault('stations',list(collections.OrderedDict.fromkeys(
dwr_obs.loc[:,'name']).keys()))
if 'station_latlon' not in kwargs:
latlon={}
for station in kwargs.get('stations'):
latlon[station]=DWR.get_station_location(dwr_obs,station)
kwargs['station_latlon']=latlon
ax_map=fig.add_axes([0.01,0.01,0.485,0.98],
projection=kwargs.get('projection'))
aspect=fig.get_size_inches()[1]/(fig.get_size_inches()[0]/2.0)
extent=[kwargs.get('scale')*-1,kwargs.get('scale'),
kwargs.get('scale')*-1*aspect,kwargs.get('scale')*aspect]
if kwargs.get('stations') is None:
stations=list(collections.OrderedDict.fromkeys(
dwr_obs.loc[:,'name']).keys())
plot_contour(ax_map,extent,dte,field,obs_r,dwr_obs,**kwargs)
# Label with the date
mg.utils.plot_label(ax_map,
'%04d-%02d-%02d:%02d' % (dte.year,dte.month,
dte.day,dte.hour),
facecolor=fig.get_facecolor(),
x_fraction=0.02,
horizontalalignment='left')
ax_scp=fig.add_axes([0.6,0.06,0.39,0.93])
plot_scatter(ax_scp,field,dwr_obs,dte,**kwargs)
# Join each station name to its location on the map
# Need another axes, filling the whole fig
ax_full=fig.add_axes([0,0,1,1])
ax_full.patch.set_alpha(0.0) # Transparent background
# Map location of a station in ax_full coordinates
def pos_left(idx):
station=kwargs.get('stations')[idx]
latlon=kwargs.get('station_latlon')[station]
rp=ax_map.projection.transform_points(ccrs.PlateCarree(),
numpy.asarray(latlon['longitude']),
numpy.asarray(latlon['latitude']))
new_lon=rp[:,0]
new_lat=rp[:,1]
result={}
scale=kwargs.get('scale')
result['x']=0.01+0.485*((new_lon-(scale*-1))/(scale*2))
result['y']=0.01+0.98*((new_lat-(scale*aspect*-1))/
(scale*2*aspect))
return result
# Label location of a station in ax_full coordinates
def pos_right(idx):
result={}
result['x']=0.51
result['y']=0.06+(0.93/len(kwargs.get('stations')))*(idx+0.5)
return result
for i in range(0,len(kwargs.get('stations'))):
p_left=pos_left(i)
p_right=pos_right(i)
ax_full.add_patch(Circle((p_right['x'],
p_right['y']),
radius=0.001,
facecolor=(1,0,0,1),
edgecolor=(0,0,0,1),
alpha=1,
zorder=1))
ax_full.add_line(matplotlib.lines.Line2D(
xdata=(p_left['x'],p_right['x']),
ydata=(p_left['y'],p_right['y']),
linestyle='solid',
linewidth=0.2,
color=(1,0,0,0.5),
zorder=1))
