def plot_map(lat, lon, data, normalized=False):
"""Plots data on a Basemap.
Arguments:
lat: array of lat locations of data
lon: array of lon locations of other axis of data
data: 2D lat-lon grid of data to put on map
Keyword Arguments:
normalized: if True, show a 0:1 map of ratios of max value
Returns:
Nothing
"""
bm = Basemap(projection = 'mill', llcrnrlon=min(lon),
llcrnrlat=min(lat), urcrnrlon=max(lon),
urcrnrlat=max(lat))
lons, lats = np.meshgrid(lon, lat)
x, y = bm(lons, lats)
pl.figure(figsize=(18,14))
ax = pl.gca()
bm.drawcoastlines(linewidth=1.25, color='white')
bm.drawparallels(np.array([-70,-50,-30,-10,10,30,50,70]),
labels=[1,0,0,0])
bm.drawmeridians(np.arange(min(lon),max(lon),60),labels=[0,0,0,1])
if normalized:
bm.pcolor(x,y,data.T/np.abs(np.max(data)))
else:
bm.pcolor(x,y,data.T)
if MAL:
divider = mal(ax)
cax = divider.append_axes("right", size='5%', pad=0.05)
pl.colorbar(cax=cax)
else:
pl.colorbar()
return
def summaryplot(f,
plate=None,
ifu=None,
smearing=True,
stellar=False,
maxr=None,
cen=True,
fixcent=True,
save=False,
clobber=False,
remotedir=None,
gal=None,
relative_pab=False):
"""
Make a summary plot for a `nirvana` output file with MaNGA velocity
field.
Shows the values for the global parameters of the galaxy, the rotation
curves (with 1-sigma lower and upper bounds) for the different velocity
components, then comparisons of the MaNGA data, the model, and the
residuals for the rotational velocity and the velocity dispersion.
Args:
f (:obj:`str`, `dynesty.NestedSampler`_, `dynesty.results.Results`_):
`.fits` file, sampler, results, `.nirv` file of dumped results
from :func:`~nirvana.fitting.fit`. If this is in the regular
format from the automatic outfile generator in
:func:`~nirvana.scripts.nirvana.main` then it will fill in most
of the rest of the parameters by itself.
plate (:obj:`int`, optional):
MaNGA plate number for desired galaxy. Can be auto filled by `f`.
ifu (:obj:`int`, optional):
MaNGA IFU number for desired galaxy. Can be auto filled by `f`.
smearing (:obj:`bool`, optional):
Whether or not to apply beam smearing to models. Can be auto
filled by `f`.
stellar (:obj:`bool`, optional):
Whether or not to use stellar velocity data instead of gas. Can
be auto filled by `f`.
maxr (:obj:`float`, optional):
Maximum radius to make edges go out to in units of effective
radii. Can be auto filled by `f`.
cen (:obj:`bool`, optional):
Whether the position of the center was fit. Can be auto filled by
`f`.
fixcent (:obj:`bool`, optional):
Whether the center velocity bin was held at 0 in the fit. Can be
auto filled by `f`.
save (:obj:`bool`, optional):
Flag for whether to save the plot. Will save as a pdf in the same
directory as `f` is in but inside a folder called `plots`.
clobber (:obj:`bool`, optional):
Flag to overwrite plot file if it already exists. Only matters if
`save=True`
remotedir (:obj:`str`, optional):
Directory to load MaNGA data files from, or save them if they are
not found and are remotely downloaded.
gal (:class:`~nirvana.data.fitargs.FitArgs`, optional):
Pre existing galaxy object to use instead of loading from scratch
"""
#check if plot file already exists
if save and not clobber:
path = f[:f.rfind('/') + 1]
fname = f[f.rfind('/') + 1:-5]
if os.path.isfile(f'{path}/plots/{fname}.pdf'):
raise ValueError('Plot file already exists')
#unpack input file into useful objects
args, resdict = fileprep(f,
plate,
ifu,
smearing,
stellar,
maxr,
cen,
fixcent,
remotedir=remotedir,
gal=gal)
#generate velocity models
velmodel, sigmodel = bisym_model(args,
resdict,
plot=True,
relative_pab=relative_pab)
vel_r = args.kin.remap('vel')
sig_r = np.sqrt(args.kin.remap('sig_phys2')) if hasattr(
args.kin, 'sig_phys2') else args.kin.remap('sig')
if args.kin.vel_ivar is None:
args.kin.vel_ivar = np.ones_like(args.kin.vel)
if args.kin.sig_ivar is None:
args.kin.sig_ivar = np.ones_like(args.kin.sig)
#calculate chisq maps
vel_ivar = args.kin.remap('vel_ivar')
sig_ivar = args.kin.remap('sig_phys2_ivar')**.5
if args.scatter:
vel_ivar = 1 / (1 / vel_ivar + resdict['vel_scatter']**2)
sig_ivar = 1 / (1 / sig_ivar + resdict['sig_scatter']**2)
velchisq = (vel_r - velmodel)**2 * vel_ivar
sigchisq = (sig_r - sigmodel)**2 * sig_ivar
#print global parameters on figure
fig = plt.figure(figsize=(12, 9))
plt.subplot(3, 4, 1)
ax = plt.gca()
infobox(ax, resdict, args, cen, relative_pab)
#image
plt.subplot(3, 4, 2)
if args.kin.image is not None: plt.imshow(args.kin.image)
else:
plt.text(.5,
.5,
'No image found',
horizontalalignment='center',
transform=plt.gca().transAxes,
size=14)
plt.axis('off')
#Radial velocity profiles
plt.subplot(3, 4, 3)
ls = [r'$V_t$', r'$V_{2t}$', r'$V_{2r}$']
for i, v in enumerate(['vt', 'v2t', 'v2r']):
plt.plot(args.edges, resdict[v], label=ls[i])
errors = [[resdict['vtl'], resdict['vtu']],
[resdict['v2tl'], resdict['v2tu']],
[resdict['v2rl'], resdict['v2ru']]]
for i, p in enumerate(errors):
plt.fill_between(args.edges, p[0], p[1], alpha=.5)
plt.ylim(bottom=0)
plt.legend(loc=2)
plt.xlabel('Radius (arcsec)')
plt.ylabel(r'$v$ (km/s)')
plt.title('Velocity Profiles')
#dispersion profile
plt.subplot(3, 4, 4)
plt.plot(args.edges, resdict['sig'])
plt.fill_between(args.edges, resdict['sigl'], resdict['sigu'], alpha=.5)
plt.ylim(bottom=0)
plt.title('Velocity Dispersion Profile')
plt.xlabel('Radius (arcsec)')
plt.ylabel(r'$v$ (km/s)')
#MaNGA Ha velocity field
plt.subplot(3, 4, 5)
plt.title(f"{resdict['type']} Velocity Data")
vmax = min(np.max(np.abs(vel_r)), 300)
plt.imshow(vel_r, cmap='jet', origin='lower', vmin=-vmax, vmax=vmax)
plt.tick_params(left=False,
bottom=False,
labelleft=False,
labelbottom=False)
cax = mal(plt.gca()).append_axes('right', size='5%', pad=.05)
cb = plt.colorbar(cax=cax)
cb.set_label('km/s', labelpad=-10)
#Vel model from dynesty fit
plt.subplot(3, 4, 6)
plt.title('Velocity Model')
plt.imshow(velmodel, 'jet', origin='lower', vmin=-vmax, vmax=vmax)
plt.tick_params(left=False,
bottom=False,
labelleft=False,
labelbottom=False)
cax = mal(plt.gca()).append_axes('right', size='5%', pad=.05)
plt.colorbar(label='km/s', cax=cax)
cb = plt.colorbar(cax=cax)
cb.set_label('km/s', labelpad=-10)
#Residuals from vel fit
plt.subplot(3, 4, 7)
plt.title('Velocity Residuals')
resid = vel_r - velmodel
vmax = min(np.abs(vel_r - velmodel).max(), 50)
plt.imshow(vel_r - velmodel, 'jet', origin='lower', vmin=-vmax, vmax=vmax)
plt.tick_params(left=False,
bottom=False,
labelleft=False,
labelbottom=False)
cax = mal(plt.gca()).append_axes('right', size='5%', pad=.05)
plt.colorbar(label='km/s', cax=cax)
cb = plt.colorbar(cax=cax)
cb.set_label('km/s', labelpad=-10)
#Chisq from vel fit
plt.subplot(3, 4, 8)
plt.title('Velocity Chi Squared')
plt.imshow(velchisq, 'jet', origin='lower', vmin=0, vmax=50)
plt.tick_params(left=False,
bottom=False,
labelleft=False,
labelbottom=False)
cax = mal(plt.gca()).append_axes('right', size='5%', pad=.05)
plt.colorbar(cax=cax)
#MaNGA Ha velocity disp
plt.subplot(3, 4, 9)
plt.title(f"{resdict['type']} Dispersion Data")
vmax = min(np.max(sig_r), 200)
plt.imshow(sig_r, cmap='jet', origin='lower', vmax=vmax, vmin=0)
plt.tick_params(left=False,
bottom=False,
labelleft=False,
labelbottom=False)
cax = mal(plt.gca()).append_axes('right', size='5%', pad=.05)
cb = plt.colorbar(cax=cax)
cb.set_label('km/s', labelpad=0)
#disp model from dynesty fit
plt.subplot(3, 4, 10)
plt.title('Dispersion Model')
plt.imshow(sigmodel, 'jet', origin='lower', vmin=0, vmax=vmax)
plt.tick_params(left=False,
bottom=False,
labelleft=False,
labelbottom=False)
cax = mal(plt.gca()).append_axes('right', size='5%', pad=.05)
cb = plt.colorbar(cax=cax)
cb.set_label('km/s', labelpad=0)
#Residuals from disp fit
plt.subplot(3, 4, 11)
plt.title('Dispersion Residuals')
resid = sig_r - sigmodel
vmax = min(np.abs(sig_r - sigmodel).max(), 50)
plt.imshow(sig_r - sigmodel, 'jet', origin='lower', vmin=-vmax, vmax=vmax)
plt.tick_params(left=False,
bottom=False,
labelleft=False,
labelbottom=False)
cax = mal(plt.gca()).append_axes('right', size='5%', pad=.05)
cb = plt.colorbar(cax=cax)
cb.set_label('km/s', labelpad=-10)
#Chisq from sig fit
plt.subplot(3, 4, 12)
plt.title('Dispersion Chi Squared')
plt.imshow(sigchisq, 'jet', origin='lower', vmin=0, vmax=50)
plt.tick_params(left=False,
bottom=False,
labelleft=False,
labelbottom=False)
cax = mal(plt.gca()).append_axes('right', size='5%', pad=.05)
plt.colorbar(cax=cax)
plt.tight_layout()
if save:
path = f[:f.rfind('/') + 1]
fname = f[f.rfind('/') + 1:-5]
plt.savefig(f'{path}plots/{fname}.pdf', format='pdf')
plt.close()
print(resdict)
return fig
def separate_components(f,
plate=None,
ifu=None,
smearing=True,
stellar=False,
maxr=None,
cen=True,
fixcent=True,
save=False,
clobber=False,
remotedir=None,
gal=None,
relative_pab=False,
cmap='RdBu'):
"""
Make a plot `nirvana` output file with the different velocity components
searated.
Plot the first order velocity component and the two second order velocity
components next to each other along with the full model, data, image, and
global parameters
The created plot contains the global parameters of the galaxy, the image
of the galaxy, and the data of the velocity field on the first row. The
second row is the full model followed by the different components broken
out with + and = signs between.
Args:
f (:class:`dynesty.NestedSampler`, :obj:`str`, :class:`dynesty.results.Results`):
Sampler, results, or file of dumped results from `dynesty` fit.
plate (:obj:`int`, optional):
MaNGA plate number for desired galaxy. Must be specified if
`auto=False`.
ifu (:obj:`int`, optional):
MaNGA IFU design number for desired galaxy. Must be specified if
`auto=False`.
smearing (:obj:`bool`, optional):
Flag for whether or not to apply beam smearing to models.
stellar (:obj:`bool`, optional):
Flag for whether or not to use stellar velocity data instead of
gas.
cen (:obj:`bool`, optional):
Flag for whether the position of the center was fit.
"""
args, resdict = fileprep(f,
plate,
ifu,
smearing,
stellar,
maxr,
cen,
fixcent,
remotedir=remotedir,
gal=gal)
z = np.zeros(len(resdict['vt']))
vtdict, v2tdict, v2rdict = [resdict.copy(), resdict.copy(), resdict.copy()]
vtdict['v2t'] = z
vtdict['v2r'] = z
v2tdict['vt'] = z
v2tdict['v2r'] = z
v2rdict['vt'] = z
v2rdict['v2t'] = z
if maxr is not None:
r, th = projected_polar(args.kin.x, args.kin.y,
*np.radians((resdict['pa'], resdict['inc'])))
rmask = r > maxr
args.kin.vel_mask |= rmask
args.kin.sig_mask |= rmask
velmodel, sigmodel = bisym_model(args, resdict, plot=True)
vtmodel, sigmodel = bisym_model(args, vtdict, plot=True)
v2tmodel, sigmodel = bisym_model(args, v2tdict, plot=True)
v2rmodel, sigmodel = bisym_model(args, v2rdict, plot=True)
vel_r = args.kin.remap('vel')
#must set all masked areas to 0 or else vmax calculations barf
for v in [vel_r, velmodel, vtmodel, v2tmodel, v2rmodel]:
v.data[v.mask] = 0
v -= resdict['vsys'] #recenter at 0
v2model = v2tmodel + v2rmodel
v2model.data[v2model.mask] = 0
velresid = vel_r - velmodel
vtresid = vel_r - v2tmodel - v2rmodel
v2tresid = vel_r - vtmodel - v2rmodel
v2rresid = vel_r - vtmodel - v2tmodel
v2resid = vel_r - vtmodel
datavmax = min(np.max(np.abs([vel_r, velmodel])), 300)
velvmax = min(np.max(np.abs(velresid)), 300)
vtvmax = min(np.max(np.abs([vtmodel, vtresid])), 300)
v2tvmax = min(np.max(np.abs([v2tmodel, v2tresid])), 300)
v2rvmax = min(np.max(np.abs([v2rmodel, v2rresid])), 300)
v2vmax = min(np.max(np.abs([v2model, v2resid])), 300)
plt.figure(figsize=(15, 9))
plt.subplot(3, 5, 1)
ax = plt.gca()
infobox(ax, resdict, args)
#image
plt.subplot(3, 5, 2)
plt.imshow(args.kin.image)
plt.axis('off')
#MaNGA Ha velocity field
plt.subplot(3, 5, 3)
plt.title(r'Velocity Data')
plt.imshow(vel_r, cmap=cmap, origin='lower', vmin=-datavmax, vmax=datavmax)
plt.tick_params(left=False,
bottom=False,
labelleft=False,
labelbottom=False)
cax = mal(plt.gca()).append_axes('bottom', size='5%', pad=0)
cb = plt.colorbar(cax=cax, orientation='horizontal')
cax.tick_params(direction='in')
cb.set_label('km/s', labelpad=-2)
#Radial velocity profiles
plt.subplot(3, 5, 4)
ls = [r'$V_t$', r'$V_{2t}$', r'$V_{2r}$']
for i, v in enumerate(['vt', 'v2t', 'v2r']):
plt.plot(args.edges, resdict[v], label=ls[i])
errors = [[resdict['vtl'], resdict['vtu']],
[resdict['v2tl'], resdict['v2tu']],
[resdict['v2rl'], resdict['v2ru']]]
for i, p in enumerate(errors):
plt.fill_between(args.edges, p[0], p[1], alpha=.5)
plt.ylim(bottom=0)
plt.legend(loc=2)
plt.xlabel('Radius (arcsec)', labelpad=-1)
plt.ylabel(r'$v$ (km/s)')
plt.title('Velocity Profiles')
plt.gca().tick_params(direction='in')
plt.subplot(3, 5, 6)
plt.imshow(velmodel,
cmap=cmap,
origin='lower',
vmin=-datavmax,
vmax=datavmax)
plt.tick_params(left=False,
bottom=False,
labelleft=False,
labelbottom=False)
#plt.text(1.15,.5,'=', transform=plt.gca().transAxes, size=30)
plt.title(r'Model', fontsize=16)
cax = mal(plt.gca()).append_axes('bottom', size='5%', pad=0)
cb = plt.colorbar(cax=cax, orientation='horizontal')
cax.tick_params(direction='in')
cb.set_label('km/s', labelpad=-2)
plt.subplot(3, 5, 7)
plt.imshow(vtmodel, cmap=cmap, origin='lower', vmin=-vtvmax, vmax=vtvmax)
plt.tick_params(left=False,
bottom=False,
labelleft=False,
labelbottom=False)
#plt.text(1.15,.5,'+', transform=plt.gca().transAxes, size=30)
plt.title(r'$V_t$', fontsize=16)
cax = mal(plt.gca()).append_axes('bottom', size='5%', pad=0)
cb = plt.colorbar(cax=cax, orientation='horizontal')
cax.tick_params(direction='in')
cb.set_label('km/s', labelpad=-2)
plt.subplot(3, 5, 8)
plt.imshow(v2tmodel,
cmap=cmap,
origin='lower',
vmin=-v2tvmax,
vmax=v2tvmax)
plt.tick_params(left=False,
bottom=False,
labelleft=False,
labelbottom=False)
#plt.text(1.15,.5,'+', transform=plt.gca().transAxes, size=30)
plt.title(r'$V_{2t}$', fontsize=16)
cax = mal(plt.gca()).append_axes('bottom', size='5%', pad=0)
cb = plt.colorbar(cax=cax, orientation='horizontal')
cax.tick_params(direction='in')
cb.set_label('km/s', labelpad=-2)
plt.subplot(3, 5, 9)
plt.imshow(v2rmodel,
cmap=cmap,
origin='lower',
vmin=-v2rvmax,
vmax=v2rvmax)
plt.tick_params(left=False,
bottom=False,
labelleft=False,
labelbottom=False)
plt.title(r'$V_{2r}$', fontsize=16)
cax = mal(plt.gca()).append_axes('bottom', size='5%', pad=0)
cb = plt.colorbar(cax=cax, orientation='horizontal')
cax.tick_params(direction='in')
cb.set_label('km/s', labelpad=-2)
plt.subplot(3, 5, 10)
plt.imshow(v2model, cmap=cmap, origin='lower', vmin=-v2vmax, vmax=v2vmax)
plt.tick_params(left=False,
bottom=False,
labelleft=False,
labelbottom=False)
plt.title(r'$V_{2t} + V_{2r}$', fontsize=16)
cax = mal(plt.gca()).append_axes('bottom', size='5%', pad=0)
cb = plt.colorbar(cax=cax, orientation='horizontal')
cax.tick_params(direction='in')
cb.set_label('km/s', labelpad=-2)
plt.subplot(3, 5, 11)
plt.imshow(velresid,
cmap=cmap,
origin='lower',
vmin=-velvmax,
vmax=velvmax)
plt.tick_params(left=False,
bottom=False,
labelleft=False,
labelbottom=False)
plt.title(r'Data $-$ Model', fontsize=16)
cax = mal(plt.gca()).append_axes('bottom', size='5%', pad=0)
cb = plt.colorbar(cax=cax, orientation='horizontal')
cax.tick_params(direction='in')
cb.set_label('km/s', labelpad=-2)
plt.subplot(3, 5, 12)
plt.imshow(vtresid, cmap=cmap, origin='lower', vmin=-vtvmax, vmax=vtvmax)
plt.tick_params(left=False,
bottom=False,
labelleft=False,
labelbottom=False)
plt.title(r'Data$- (V_{2t} + V_{2r})$', fontsize=16)
cax = mal(plt.gca()).append_axes('bottom', size='5%', pad=0)
cb = plt.colorbar(cax=cax, orientation='horizontal')
cax.tick_params(direction='in')
cb.set_label('km/s', labelpad=-2)
plt.subplot(3, 5, 13)
plt.imshow(v2tresid,
cmap=cmap,
origin='lower',
vmin=-v2tvmax,
vmax=v2tvmax)
plt.tick_params(left=False,
bottom=False,
labelleft=False,
labelbottom=False)
plt.title(r'Data$- (V_t + V_{2r})$', fontsize=16)
cax = mal(plt.gca()).append_axes('bottom', size='5%', pad=0)
cb = plt.colorbar(cax=cax, orientation='horizontal')
cax.tick_params(direction='in')
cb.set_label('km/s', labelpad=-2)
plt.subplot(3, 5, 14)
plt.imshow(v2rresid,
cmap=cmap,
origin='lower',
vmin=-v2rvmax,
vmax=v2rvmax)
plt.tick_params(left=False,
bottom=False,
labelleft=False,
labelbottom=False)
plt.title(r'Data$- (V_t + V_{2t})$', fontsize=16)
cax = mal(plt.gca()).append_axes('bottom', size='5%', pad=0)
cb = plt.colorbar(cax=cax, orientation='horizontal')
cax.tick_params(direction='in')
cb.set_label('km/s', labelpad=-2)
plt.subplot(3, 5, 15)
plt.imshow(v2resid, cmap=cmap, origin='lower', vmin=-v2vmax, vmax=v2vmax)
plt.tick_params(left=False,
bottom=False,
labelleft=False,
labelbottom=False)
plt.title(r'Data$- V_t$', fontsize=16)
cax = mal(plt.gca()).append_axes('bottom', size='5%', pad=0)
cb = plt.colorbar(cax=cax, orientation='horizontal')
cax.tick_params(direction='in')
cb.set_label('km/s', labelpad=-2)
plt.tight_layout(pad=-.025)
if save:
path = f[:f.rfind('/') + 1]
fname = f[f.rfind('/') + 1:-5]
plt.savefig(f'{path}plots/sepcomp_{fname}.pdf', format='pdf')
plt.close()
def geosmap(lon, lat, data, proj = 'mill',
colorticks=None, colormap='seismic',
colortick_labels=None,
colorbar_orientation='vertical',
figsize=(18,14),
latlines=None, lonlines=None,
minlat=None, maxlat=None,
minlon=None, maxlon=None,
ortho0=None,
colorlimits=None,
coastlines=True,
countries=False,
states=False,
title=None,
titlefontsize=20.,
coastcolor='white',
bordercolor='white',
plottype='pcolor',
fontname='Arial',
savefig=False,
outfile=None):
"""Plot data on map with lon-lat grid.
Arguments:
lon - array-like longitude points
lat - array-like latitude points
data - 2D array of points to plot on lon-lat grid
Keyword Arguments:
proj - type of projection to plot map on
colormap - color scheme of color axis
colorbar_orientation - vertical (default) or horizontal
colorticks - points to label on color axis
colortick_labels - labels for colorticks (list of strings)
colorlimits - (min,max) tuple: saturation colors for color axis
if None, use limits of colorticks
latlines - latitudes at which to draw lines
lonlines - longitudes at which to draw lines
minlat - minimum latitude to map. If None, use min of given lat
maxlat - maximum latitude to map. If None, use max of given lat
minlon - minimum longitude to map. If None, use min of given lon
maxlon - maximum longitude to map. If None, use max of given lon
figsize - size of figure frame
ortho0 - (lon,lat) point to center ortho projection on
coastlines - whether to draw coastlines, default True
countries - whether to draw country borders, default False
states - whether to draw sub-country borders (NA only?), default False
coastcolor - color to make drawn coastlines
bordercolor - color to make drawn national and state borders
title - title to put above plot (string)
fontname - font name (use matplotlib font manager to check
available fonts)
savefig - whether or not to save output to file, default False
outfile - name of output file if savefig is True
"""
# Set font name
mpl.rcParams['font.family'] = fontname
assert len(lon) in data.shape, 'lon mismatch with data to plot dimension'
assert len(lat) in data.shape, 'lat mismatch with data to plot dimension'
if colortick_labels:
assert colorticks, 'Must specify colorticks if specifying labels'
assert len(colorticks) == len(colortick_labels), 'colorticks and '\
'colortick labels must be same size'
# Set up projection parameters
if not minlat:
minlat = min(lat)
if not maxlat:
maxlat = max(lat)
if not minlon:
minlon = min(lon)
if not maxlon:
maxlon = max(lon)
if proj == 'mill':
bmargs = {'projection' : 'mill',
'llcrnrlon' : minlon,
'llcrnrlat' : minlat,
'urcrnrlon' : maxlon,
'urcrnrlat' : maxlat
}
elif proj == 'ortho':
if ortho0:
assert type(ortho0) in [list, tuple, np.array], 'wrong type for ortho0'
assert len(ortho0) == 2, 'ortho0 must be in the form [lon0, lat0]'
lon0 = ortho0[0]
lat0 = ortho0[1]
else:
lon0 = lon[len(lon)/2]
lat0 = lat[len(lat)/2]
bmargs = {'projection' : 'ortho',
'lon_0' : lon0,
'lat_0' : lat0,
}
else:
print "Projection not recognized"
return
####################
# General figure details
bm = Basemap(**bmargs)
lons, lats = np.meshgrid(lon, lat)
x, y = bm(lons, lats)
fig = pl.figure(figsize=figsize)
ax = pl.gca()
if coastlines:
bm.drawcoastlines(linewidth=1.25, color=coastcolor)
if countries:
bm.drawcountries(linewidth=1, color=bordercolor)
if states:
bm.drawstates(linewidth=1, color=bordercolor)
if latlines != None:
parallels = latlines
else:
parallels = np.array([-60,-30,0,30,60])
if not proj in ['ortho']:
bm.drawparallels(parallels, labels=[1,0,0,0], fontsize=20)
if lonlines != None:
meridians = lonlines
else:
meridians = np.arange(min(lon),max(lon),60)
bm.drawmeridians(meridians, labels=[0,0,1,0], fontsize=20)
####################
# Plotting and colorbar
if colormap == 'WhGrYlRd':
WhGrYlRd_scheme = np.genfromtxt('WhGrYlRd.txt',delimiter=' ')
colormap = mpl.colors.ListedColormap(WhGrYlRd_scheme/255)
if colorticks:
tiks = colorticks
else:
tiks = np.linspace(np.min(data),np.max(data),10)
if colorlimits:
vmin, vmax = colorlimits
else:
vmin, vmax = min(tiks), max(tiks)
if plottype == 'pcolor':
bm.pcolor(x,y,data, cmap=colormap, vmin=vmin, vmax=vmax)
elif plottype == 'contourf':
bm.contourf(x,y,data, vmin=vmin, vmax=vmax, cmap=colormap)
else:
print "plottype not recognized"
raise TypeError
if title and (colorbar_orientation in ['horizontal','bottom']):
fig.suptitle(title,fontsize=titlefontsize)
elif title:
fig.suptitle(title,fontsize=titlefontsize)
divider = mal(ax)
if not colortick_labels:
tiklabs = ['%.2f'%ti for ti in tiks]
else:
tiklabs = colortick_labels
if colorbar_orientation in ['vertical','right']:
cax = divider.append_axes('right', size='5%', pad=0.05)
cbar = pl.colorbar(orientation='vertical',cax=cax,ticks=tiks)
cbar.ax.set_yticklabels(tiklabs, fontsize=20)
elif colorbar_orientation in ['horizontal','bottom']:
cax = divider.append_axes('bottom', size='10%', pad=0.1)
cbar = pl.colorbar(orientation='horizontal',cax=cax,ticks=tiks)
cbar.ax.set_xticklabels(tiklabs, fontsize=20)
if savefig:
if outfile !=None:
fig.savefig(outfile)
else:
print "No outfile name given"
def geosmap(lon, lat, data, proj = 'mill',
colorticks=None, colormap='seismic',
colortick_labels=None,
colorbar_orientation='vertical',
figsize=(18,14),
latlines=None, lonlines=None,
minlat=None, maxlat=None,
minlon=None, maxlon=None,
ortho0=None,
colorbins=None,
colorlimits=None,
coastlines=True,
countries=False,
states=False,
title=None,
titlefontsize=20.,
coastcolor='white',
bordercolor='white',
plottype='pcolor',
fontname='sans-serif',
savefig=False,
outfile=None,
subplot=False,
subplot_position=None,
subplot_title=None,
fig=None,
meridianlabels='bottom',
parallellabels='left',
hide_colorbar=False,
tight=False,
):
"""Plot data on map with lon-lat grid.
Arguments:
lon - array-like longitude points
lat - array-like latitude points
data - 2D array of points to plot on lon-lat grid
Keyword Arguments:
proj - type of projection to plot map on
colormap - color scheme of color axis
colorbar_orientation - vertical (default) or horizontal
colorticks - points to label on color axis
colortick_labels - labels for colorticks (list of strings)
colorlimits - (min,max) tuple: saturation colors for color axis
if None, use limits of colorticks
latlines - latitudes at which to draw lines
lonlines - longitudes at which to draw lines
minlat - minimum latitude to map. If None, use min of given lat
maxlat - maximum latitude to map. If None, use max of given lat
minlon - minimum longitude to map. If None, use min of given lon
maxlon - maximum longitude to map. If None, use max of given lon
figsize - size of figure frame
ortho0 - (lon,lat) point to center ortho projection on
coastlines - whether to draw coastlines, default True
countries - whether to draw country borders, default False
states - whether to draw sub-country borders (NA only?), default False
coastcolor - color to make drawn coastlines
bordercolor - color to make drawn national and state borders
title - title to put above plot (string)
titlefontsize - font size for color
fontname - font name (use matplotlib font manager to check
available fonts)
savefig - whether or not to save output to file, default False
outfile - name of output file if savefig is True
subplot - whether to plot subplots,
subplot_position - relative location of each subplot,[nrows,ncols,plot_number]
fig - create a figure outside of geosplot when subplot is active
tight - Flag for using the tight_layout call. default False
hide_colorbar - Flag to supress drawing the colorbar. default False
parallellabels - What side of the map to draw parallel labels on. default 'left'
If not 'left' or 'right', will not draw labels.
meridianlabels - What side of the map to draw meridian labels on. default 'top'
If not 'top' or 'bottom', will not draw labels.
"""
# Set font name
mpl.rcParams['font.family'] = fontname
assert len(lon) in data.shape, 'lon mismatch with data to plot dimension'
assert len(lat) in data.shape, 'lat mismatch with data to plot dimension'
if colortick_labels:
assert colorticks or colorbins, 'Must specify colorticks or colorbins '\
'if specifying labels'
if colorticks:
assert len(colorticks) == len(colortick_labels), 'colorticks and '\
'colortick labels must be same size'
elif colorbins:
assert len(colorbins) == len(colortick_labels)
# Set up projection parameters
if not minlat:
minlat = min(lat)
if not maxlat:
maxlat = max(lat)
if not minlon:
minlon = min(lon)
if not maxlon:
maxlon = max(lon)
if proj == 'mill':
bmargs = {'projection' : 'mill',
'llcrnrlon' : minlon,
'llcrnrlat' : minlat,
'urcrnrlon' : maxlon,
'urcrnrlat' : maxlat
}
elif proj == 'ortho':
if ortho0:
assert type(ortho0) in [list, tuple, np.array], 'wrong type for ortho0'
assert len(ortho0) == 2, 'ortho0 must be in the form [lon0, lat0]'
lon0 = ortho0[0]
lat0 = ortho0[1]
else:
lon0 = lon[len(lon)/2]
lat0 = lat[len(lat)/2]
bmargs = {'projection' : 'ortho',
'lon_0' : lon0,
'lat_0' : lat0,
}
else:
print "Projection not recognized"
return
####################
# subplot arguments; figure need to be created outside of geosplot for the this to work
if not fig:
fig = pl.figure(figsize=figsize)
if subplot:
assert subplot_position is not None, "subplot_position not specified"
nrows, ncols, plot_number = subplot_position
axi = fig.add_subplot(nrows, ncols, plot_number)
if subplot_title:
axi.set_title(subplot_title)
if tight:
fig.tight_layout()
ax = pl.gca()
# General figure details
bm = Basemap(**bmargs)
lons, lats = np.meshgrid(lon, lat)
x, y = bm(lons, lats)
if coastlines:
bm.drawcoastlines(linewidth=1.25, color=coastcolor)
if countries:
bm.drawcountries(linewidth=1, color=bordercolor)
if states:
bm.drawstates(linewidth=1, color=bordercolor)
if latlines != None:
parallels = latlines
else:
parallels = np.array([-60,-30,0,30,60])
if not proj in ['ortho']:
if parallellabels == 'left':
bm.drawparallels(parallels, labels=[1,0,0,0], fontsize=20)
elif parallellabels == 'right':
bm.drawparallels(parallels, labels=[0,1,0,0], fontsize=20)
else:
bm.drawparallels(parallels, labels=[0,0,0,0], fontsize=20)
if lonlines != None:
meridians = lonlines
else:
meridians = np.arange(min(lon),max(lon),60)
if meridianlabels == 'bottom':
bm.drawmeridians(meridians, labels=[0,0,0,1], fontsize=20)
elif meridianlabels == 'top':
bm.drawmeridians(meridians, labels=[0,0,1,0], fontsize=20)
else:
bm.drawmeridians(meridians, labels=[0,0,0,0])
####################
# Plotting and colorbar
if colormap == 'WhGrYlRd':
WhGrYlRd_scheme = np.genfromtxt('WhGrYlRd.txt',delimiter=' ')
colormap = mpl.colors.ListedColormap(WhGrYlRd_scheme/255)
NORM = None
if colorbins:
tiks = colorbins
NORM = mpl.colors.BoundaryNorm(tiks,mpl.colors.Colormap(colormap).N)
if colorticks:
tiks = colorticks
elif not colorbins:
tiks = np.linspace(np.min(data),np.max(data),10)
if colorlimits:
vmin, vmax = colorlimits
else:
vmin, vmax = min(tiks), max(tiks)
if plottype == 'pcolor':
bm.pcolor(x,y,data, cmap=colormap, vmin=vmin, vmax=vmax,
norm=NORM)
elif plottype == 'contourf':
bm.contourf(x,y,data, vmin=vmin, vmax=vmax, cmap=colormap,
norm=NORM)
else:
print "plottype not recognized"
raise TypeError
if title and not (colorbar_orientation in ['top']):
ax.set_title(title,fontsize=titlefontsize)
elif title:
pass
#ax.set_title(title,fontsize=titlefontsize)
divider = mal(ax)
if not colortick_labels:
strs = ['%.2G'%ti for ti in tiks]
brks = [s.split('E') for s in strs]
tiklabs = []
for br in brks:
if len(br) > 1:
t = '%s x10$ ^{%s} $'%(br[0],int(br[1]))
else:
t = br[0]
tiklabs.append(t)
else:
tiklabs = colortick_labels
if not hide_colorbar:
if colorbar_orientation in ['vertical','right']:
cax = divider.append_axes('right', size='5%', pad=0.05)
cbar = pl.colorbar(orientation='vertical',cax=cax,ticks=tiks)
cbar.ax.set_yticklabels(tiklabs, fontsize=20)
elif colorbar_orientation in ['horizontal','bottom']:
cax = divider.append_axes('bottom', size='10%', pad=0.1)
cbar = pl.colorbar(orientation='horizontal',cax=cax,ticks=tiks)
cbar.ax.set_xticklabels(tiklabs, fontsize=20)
if savefig:
if outfile !=None:
fig.savefig(outfile)
else:
print "No outfile given: fig not saved"
return fig
