def mapplot(ifile, varkey, options, before='', after=''):
"""
ifile - a pseudonetcdf file
varkey - the variable to plot
options - argparse name space with mapping options
"""
import matplotlib.pyplot as plt
from matplotlib.colors import Normalize, LogNorm
outpath = getattr(options, 'outpath', '.')
map = cu.getmap(ifile)
if map.projection == 'cyl':
latb, latunit = cu.getlatbnds(ifile)[:]
lonb, lonunit = cu.getlonbnds(ifile)[:]
else:
latb, latunit = cu.getybnds(ifile)[:]
lonb, lonunit = cu.getxbnds(ifile)[:]
if latb.ndim == lonb.ndim and lonb.ndim == 2:
LON, LAT = lonb, latb
else:
LON, LAT = np.meshgrid(lonb, latb)
ax = plt.gca()
if options.logscale:
norm = LogNorm()
else:
norm = Normalize()
var = ifile.variables[varkey]
exec(before)
ax = plt.gca()
vunit = getattr(var, 'units', 'unknown').strip()
print(varkey, end='')
try:
if options.coastlines:
map.drawcoastlines(ax=ax)
if options.countries:
map.drawcountries(ax=ax)
if options.states:
map.drawstates(ax=ax)
if options.counties:
map.drawcounties(ax=ax)
except Exception:
print('nomap')
pass
patches = map.pcolor(LON, LAT, var[:].squeeze(), norm=norm, ax=ax)
if lonunit == 'x (LCC m)':
ax.xaxis.get_major_formatter().set_scientific(True)
ax.xaxis.get_major_formatter().set_powerlimits((-3, 3))
if latunit == 'y (LCC m)':
ax.yaxis.get_major_formatter().set_scientific(True)
ax.yaxis.get_major_formatter().set_powerlimits((-3, 3))
ax.set_xlabel(lonunit)
ax.set_ylabel(latunit)
height = LAT.max() - LAT.min()
width = LON.max() - LON.min()
if width > height:
orientation = 'horizontal'
else:
orientation = 'vertical'
cbar = plt.gcf().colorbar(patches, orientation=orientation)
cbar.set_label(varkey + ' (' + vunit + ')')
if orientation == 'vertical':
cbar.ax.text(.5, 1, '%.2g' % var[:].max(
), horizontalalignment='center', verticalalignment='bottom')
cbar.ax.text(.5, 0, '%.2g' % var[:].min(
), horizontalalignment='center', verticalalignment='top')
else:
cbar.ax.text(1, .5, '%.2g' % var[:].max(
), verticalalignment='center', horizontalalignment='left')
cbar.ax.text(0, .5, '%.2g' % var[:].min(
), verticalalignment='center', horizontalalignment='right')
try:
cbar.formatter.set_scientific(True)
cbar.formatter.set_powerlimits((-3, 3))
except Exception:
pass
cbar.update_ticks()
fmt = 'png'
figpath = os.path.join(outpath + '_map_' + varkey + '.' + fmt)
exec(after)
plt.savefig(figpath)
print('Saved fig', figpath)
return figpath
def makemap(ifiles, options):
fig = pl.gcf()
ax = pl.gca()
map = options.map
nborders = len(ax.collections)
for fi, ifile in enumerate(ifiles):
if map.projection == 'lcc':
lat = ifile.variables['latitude']
lon = ifile.variables['longitude']
latb, latunit = getybnds(ifile)[:]
lonb, lonunit = getxbnds(ifile)[:]
else:
lat = ifile.variables['latitude']
lon = ifile.variables['longitude']
latb, latunit = getlatbnds(ifile)[:]
lonb, lonunit = getlonbnds(ifile)[:]
if latb.ndim == lonb.ndim and lonb.ndim == 2:
LON, LAT = lonb, latb
else:
LON, LAT = np.meshgrid(lonb, latb)
variables = options.variables
if variables is None:
variables = [key for key, var in ifile.variables.items() if len(set(['latitude', 'longitude']).intersection(getattr(var, 'coordinates', '').split())) == 2]
if len(variables) == 0:
raise ValueError('Unable to heuristically determin plottable variables; use -v to specify variables for plotting')
for varkey in variables:
ax = pl.gca()
if not options.overlay:
del ax.collections[nborders:]
var = ifile.variables[varkey]
vals = var[:].squeeze()
vmin, vmax = vals.min(), vals.max()
if options.normalize is None:
from scipy.stats import normaltest
if normaltest(vals.ravel())[1] < 0.05:
cvals = np.ma.compressed(vals)
boundaries = np.percentile(cvals, np.arange(0, 110, 10))
warn('Autoselect deciles colormap of %s; override width --norm' % varkey)
else:
boundaries = np.linspace(vmin, vmax, num = 11)
warn('Autoselect linear colormap of %s; override width --norm' % varkey)
if (boundaries.max() / np.ma.masked_values(boundaries, 0).min()) > 10000:
formatter = LogFormatter(labelOnlyBase = False)
else:
formatter = None
norm = BoundaryNorm(boundaries, ncolors = 256)
else:
norm = eval(options.normalize)
formatter = None
if not options.colorbarformatter is None:
try:
formatter = eval(options.colorbarformatter)
except:
formatter = options.colorbarformatter
vmin, vmax = norm.vmin, norm.vmax
varunit = getattr(var, 'units', 'unknown').strip()
print(varkey, sep = '')
if vals.ndim == 1:
patches = map.scatter(lon[:], lat[:], c = vals, s = 24, norm = norm, ax = ax)
else:
patches = map.pcolor(LON, LAT, vals, norm = norm, ax = ax)
if lonunit == 'x (LCC m)':
ax.xaxis.get_major_formatter().set_scientific(True)
ax.xaxis.get_major_formatter().set_powerlimits((-3, 3))
if latunit == 'y (LCC m)':
ax.yaxis.get_major_formatter().set_scientific(True)
ax.yaxis.get_major_formatter().set_powerlimits((-3, 3))
ax.set_xlabel(lonunit)
ax.set_ylabel(latunit)
height = LAT.max() - LAT.min()
width = LON.max() - LON.min()
if width >= height:
orientation = 'horizontal'
else:
orientation = 'vertical'
try:
cax = cbar.ax
cax.cla()
except:
cax = None
if vals.max() > vmax and vals.min() < vmin:
extend = 'both'
elif vals.max() > vmax:
extend = 'max'
elif vals.min() < vmin:
extend = 'min'
else:
extend = 'neither'
cbar = pl.gcf().colorbar(patches, orientation = orientation, cax = cax, extend = extend, format = formatter)
del cbar.ax.texts[:]
cbar.set_label(varkey + ' (' + varunit + '; min=%.3g; max=%.3g)' % (var[:].min(), var[:].max()))
# if orientation == 'vertical':
# cbar.ax.text(.5, 1.05, '%.3g' % var[:].max(), horizontalalignment = 'center', verticalalignment = 'bottom')
# cbar.ax.text(.5, -.06, '%.3g ' % var[:].min(), horizontalalignment = 'center', verticalalignment = 'top')
# else:
# cbar.ax.text(1.05, .5, ' %.3g' % var[:].max(), verticalalignment = 'center', horizontalalignment = 'left')
# cbar.ax.text(-.06, .5, '%.3g ' % var[:].min(), verticalalignment = 'center', horizontalalignment = 'right')
cbar.update_ticks()
fmt = 'png'
outpath = options.outpath
if len(ifiles) > 1:
outpath += ('_%%0%dd' % len(str(len(ifiles)))) % fi
figpath = os.path.join(outpath + varkey + '.' + fmt)
if options.interactive:
csl = PNCConsole(locals = globals())
csl.interact()
pl.savefig(figpath)
print('Saved fig', figpath)
def makemaps(args):
ifiles = args.ifiles
cbar = None
ifile = ifiles[0]
if args.iter != []:
ifile, = ifiles
ifiles = []
for dimk in args.iter:
ifiles += [
slice_dim(getvarpnc(ifile, None), '%s,%d' % (dimk, i))
for i in range(len(ifile.dimensions[dimk]))
]
ax = plt.gca()
map = getmap(ifile, resolution=args.resolution)
if args.coastlines:
map.drawcoastlines(ax=ax)
if args.countries:
map.drawcountries(ax=ax)
if args.states:
map.drawstates(ax=ax)
if args.counties:
map.drawcounties(ax=ax)
for si, shapefile in enumerate(args.shapefiles):
shapeopts = shapefile.split(',')
shapepath = shapeopts[0]
shapeoptdict = eval('dict(' + ','.join(shapeopts[1:]) + ')')
shapename = os.path.basename(shapepath)[:-3] + str(si)
map.readshapefile(shapepath, shapename, ax=ax, **shapeoptdict)
args.map = map
fig = plt.gcf()
if len(args.figure_keywords) > 0:
plt.setp(fig, **args.figure_keywords)
ax = plt.gca()
if len(args.axes_keywords) > 0:
plt.setp(ax, **args.axes_keywords)
map = args.map
nborders = len(ax.collections)
for fi, ifile in enumerate(ifiles):
if map.projection in ('lcc', 'merc'):
lat = ifile.variables['latitude']
lon = ifile.variables['longitude']
latb, latunit = getybnds(ifile)[:]
lonb, lonunit = getxbnds(ifile)[:]
else:
lat = ifile.variables['latitude']
lon = ifile.variables['longitude']
latb, latunit = getlatbnds(ifile)[:]
lonb, lonunit = getlonbnds(ifile)[:]
if latb.ndim == lonb.ndim and lonb.ndim == 2:
LON, LAT = lonb, latb
else:
LON, LAT = np.meshgrid(lonb.view(np.ndarray),
latb.view(np.ndarray))
variables = args.variables
if variables is None:
def isgeo(var):
geo2d = set(['latitude', 'longitude'])
vard = getattr(var, 'coordinates', '').split()
hasgeo2d = len(geo2d.intersection(vard)) == 2
return hasgeo2d
variables = [
key for key, var in ifile.variables.items() if isgeo(var)
]
if len(variables) == 0:
raise ValueError('Unable to heuristically determin plottable ' +
'variables; use -v to specify variables for ' +
'plotting')
for varkey in variables:
ax = plt.gca()
if not args.overlay:
del ax.collections[nborders:]
var = ifile.variables[varkey]
if args.squeeze:
vals = var[:].squeeze()
else:
vals = var[:]
vmin, vmax = vals.min(), vals.max()
if args.normalize is None:
from scipy.stats import normaltest
if normaltest(vals.ravel())[1] < 0.001:
cvals = np.ma.compressed(vals)
boundaries = np.percentile(cvals, np.arange(0, 110, 10))
warn('Autoselect deciles colormap of %s; override ' +
'width --norm' % varkey)
else:
boundaries = np.linspace(vmin, vmax, num=11)
warn(('Autoselect linear colormap of %s; override ' +
'width --norm') % varkey)
ordermag = (boundaries.max() /
np.ma.masked_values(boundaries, 0).min())
if (ordermag) > 10000:
formatter = LogFormatter(labelOnlyBase=False)
else:
formatter = None
norm = BoundaryNorm(boundaries, ncolors=256)
else:
norm = eval(args.normalize)
formatter = None
if args.colorbarformatter is not None:
try:
formatter = eval(args.colorbarformatter)
except Exception:
formatter = args.colorbarformatter
if norm.vmin is not None:
vmin = norm.vmin
if norm.vmax is not None:
vmax = norm.vmax
varunit = getattr(var, 'units', 'unknown').strip()
if args.verbose > 0:
print(varkey, sep='')
if vals.ndim == 1:
notmasked = ~(np.ma.getmaskarray(lon[:]) | np.ma.getmaskarray(
lat[:]) | np.ma.getmaskarray(vals[:]))
scatlon = lon[:][notmasked]
scatlat = lat[:][notmasked]
scatvals = vals[:][notmasked]
patches = map.scatter(scatlon[:],
scatlat[:],
c=scatvals,
edgecolors='none',
s=24,
norm=norm,
ax=ax,
zorder=2)
else:
if vals.ndim != 2:
dimlendictstr = str(dict(zip(var.dimensions, var.shape)))
warn('Maps require 2-d data; values right now %s %s' %
(str(vals.shape), dimlendictstr))
patches = map.pcolor(LON, LAT, vals, norm=norm, ax=ax)
if lonunit == 'x (m)':
ax.xaxis.get_major_formatter().set_scientific(True)
ax.xaxis.get_major_formatter().set_powerlimits((-3, 3))
if latunit == 'y (m)':
ax.yaxis.get_major_formatter().set_scientific(True)
ax.yaxis.get_major_formatter().set_powerlimits((-3, 3))
ax.set_xlabel(lonunit)
ax.set_ylabel(latunit)
height = np.abs(np.diff(ax.get_ylim()))
width = np.abs(np.diff(ax.get_xlim()))
if width >= height:
orientation = 'horizontal'
else:
orientation = 'vertical'
if cbar is None:
cax = None
else:
cax = cbar.ax
cax.cla()
if vals.max() > vmax and vals.min() < vmin:
extend = 'both'
elif vals.max() > vmax:
extend = 'max'
elif vals.min() < vmin:
extend = 'min'
else:
extend = 'neither'
cbar = plt.gcf().colorbar(patches,
orientation=orientation,
cax=cax,
extend=extend,
format=formatter,
spacing='proportional')
del cbar.ax.texts[:]
varminmaxtxt = ('; min=%.3g; max=%.3g)' %
(var[:].min(), var[:].max()))
cbar.set_label(varkey + ' (' + varunit + varminmaxtxt)
# if orientation == 'vertical':
# cbar.ax.text(.5, 1.05, '%.3g' % var[:].max(),
# horizontalalignment = 'center',
# verticalalignment = 'bottom')
# cbar.ax.text(.5, -.06, '%.3g ' % var[:].min(),
# horizontalalignment = 'center',
# verticalalignment = 'top')
# else:
# cbar.ax.text(1.05, .5, ' %.3g' % var[:].max(),
# verticalalignment = 'center',
# horizontalalignment = 'left')
# cbar.ax.text(-.06, .5, '%.3g ' % var[:].min(),
# verticalalignment = 'center',
# horizontalalignment = 'right')
cbar.update_ticks()
fmt = args.figformat
outpath = args.outpath
if len(ifiles) > 1:
lstr = str(fi).rjust(len(str(len(ifiles))), '0')
if args.verbose > 0:
print('adding numeric suffix for file', lstr)
else:
lstr = ''
figpath = os.path.join(outpath + varkey + lstr + '.' + fmt)
if args.interactive:
csl = PNCConsole(locals=globals())
csl.interact()
for cmd in args.plotcommands:
exec(cmd)
plt.savefig(figpath)
if args.verbose > 0:
print('Saved fig', figpath)
def makemap(ifiles, options):
fig = pl.gcf()
ax = pl.gca()
map = options.map
nborders = len(ax.collections)
for fi, ifile in enumerate(ifiles):
if map.projection == 'lcc':
lat = ifile.variables['latitude']
lon = ifile.variables['longitude']
latb, latunit = getybnds(ifile)[:]
lonb, lonunit = getxbnds(ifile)[:]
else:
lat = ifile.variables['latitude']
lon = ifile.variables['longitude']
latb, latunit = getlatbnds(ifile)[:]
lonb, lonunit = getlonbnds(ifile)[:]
if latb.ndim == lonb.ndim and lonb.ndim == 2:
LON, LAT = lonb, latb
else:
LON, LAT = np.meshgrid(lonb, latb)
variables = options.variables
if variables is None:
variables = [
key for key, var in ifile.variables.items() if len(
set(['latitude', 'longitude']).intersection(
getattr(var, 'coordinates', '').split())) == 2
]
if len(variables) == 0:
raise ValueError(
'Unable to heuristically determin plottable variables; use -v to specify variables for plotting'
)
for varkey in variables:
ax = pl.gca()
if not options.overlay:
del ax.collections[nborders:]
var = ifile.variables[varkey]
vals = var[:].squeeze()
vmin, vmax = vals.min(), vals.max()
if options.normalize is None:
from scipy.stats import normaltest
if normaltest(vals.ravel())[1] < 0.05:
cvals = np.ma.compressed(vals)
boundaries = np.percentile(cvals, np.arange(0, 110, 10))
warn(
'Autoselect deciles colormap of %s; override width --norm'
% varkey)
else:
boundaries = np.linspace(vmin, vmax, num=11)
warn(
'Autoselect linear colormap of %s; override width --norm'
% varkey)
if (boundaries.max() /
np.ma.masked_values(boundaries, 0).min()) > 10000:
formatter = LogFormatter(labelOnlyBase=False)
else:
formatter = None
norm = BoundaryNorm(boundaries, ncolors=256)
else:
norm = eval(options.normalize)
formatter = None
if not options.colorbarformatter is None:
try:
formatter = eval(options.colorbarformatter)
except:
formatter = options.colorbarformatter
vmin, vmax = norm.vmin, norm.vmax
varunit = getattr(var, 'units', 'unknown').strip()
print(varkey, sep='')
if vals.ndim == 1:
patches = map.scatter(lon[:],
lat[:],
c=vals,
s=24,
norm=norm,
ax=ax)
else:
patches = map.pcolor(LON, LAT, vals, norm=norm, ax=ax)
if lonunit == 'x (LCC m)':
ax.xaxis.get_major_formatter().set_scientific(True)
ax.xaxis.get_major_formatter().set_powerlimits((-3, 3))
if latunit == 'y (LCC m)':
ax.yaxis.get_major_formatter().set_scientific(True)
ax.yaxis.get_major_formatter().set_powerlimits((-3, 3))
ax.set_xlabel(lonunit)
ax.set_ylabel(latunit)
height = LAT.max() - LAT.min()
width = LON.max() - LON.min()
if width >= height:
orientation = 'horizontal'
else:
orientation = 'vertical'
try:
cax = cbar.ax
cax.cla()
except:
cax = None
if vals.max() > vmax and vals.min() < vmin:
extend = 'both'
elif vals.max() > vmax:
extend = 'max'
elif vals.min() < vmin:
extend = 'min'
else:
extend = 'neither'
cbar = pl.gcf().colorbar(patches,
orientation=orientation,
cax=cax,
extend=extend,
format=formatter)
del cbar.ax.texts[:]
cbar.set_label(varkey + ' (' + varunit + '; min=%.3g; max=%.3g)' %
(var[:].min(), var[:].max()))
# if orientation == 'vertical':
# cbar.ax.text(.5, 1.05, '%.3g' % var[:].max(), horizontalalignment = 'center', verticalalignment = 'bottom')
# cbar.ax.text(.5, -.06, '%.3g ' % var[:].min(), horizontalalignment = 'center', verticalalignment = 'top')
# else:
# cbar.ax.text(1.05, .5, ' %.3g' % var[:].max(), verticalalignment = 'center', horizontalalignment = 'left')
# cbar.ax.text(-.06, .5, '%.3g ' % var[:].min(), verticalalignment = 'center', horizontalalignment = 'right')
cbar.update_ticks()
fmt = 'png'
outpath = options.outpath
if len(ifiles) > 1:
outpath += ('_%%0%dd' % len(str(len(ifiles)))) % fi
figpath = os.path.join(outpath + varkey + '.' + fmt)
if options.interactive:
csl = PNCConsole(locals=globals())
csl.interact()
pl.savefig(figpath)
print('Saved fig', figpath)