def contourf_latday(var,
is_precip=False,
clev=None,
cticks=None,
climits=None,
nc_pref=40,
grp=None,
xlims=(-120, 200),
xticks=np.arange(-120, 201, 30),
ylims=(-60, 60),
yticks=np.arange(-60, 61, 20),
dlist=None,
grid=False,
ind_nm='onset',
xlabels=True):
"""Create a filled contour plot of data on latitude-day grid.
"""
var = atm.subset(var, {'lat': ylims})
vals = var.values.T
lat = atm.get_coord(var, 'lat')
days = atm.get_coord(var, 'dayrel')
if var.min() < 0:
symmetric = True
else:
symmetric = False
if is_precip:
cmap = 'PuBuGn'
extend = 'max'
else:
cmap = 'RdBu_r'
extend = 'both'
if clev == None:
cint = atm.cinterval(vals, n_pref=nc_pref, symmetric=symmetric)
clev = atm.clevels(vals, cint, symmetric=symmetric)
elif len(atm.makelist(clev)) == 1:
if is_precip:
clev = np.arange(0, 10 + clev / 2.0, clev)
else:
clev = atm.clevels(vals, clev, symmetric=symmetric)
plt.contourf(days, lat, vals, clev, cmap=cmap, extend=extend)
plt.colorbar(ticks=cticks)
plt.clim(climits)
atm.ax_lims_ticks(xlims, xticks, ylims, yticks)
plt.grid(grid)
if dlist is not None:
for d0 in dlist:
plt.axvline(d0, color='k')
if xlabels:
plt.gca().set_xticklabels(xticks)
plt.xlabel('Days Since ' + ind_nm.capitalize())
else:
plt.gca().set_xticklabels([])
if grp is not None and grp.col == 0:
plt.ylabel('Latitude')
return None
def contourf_latday(var, clev=None, title='', nc_pref=40, grp=None,
xlims=(-120, 200), xticks=np.arange(-120, 201, 30),
ylims=(-60, 60), yticks=np.arange(-60, 61, 20),
ssn_length=None):
vals = var.values.T
lat = atm.get_coord(var, 'lat')
days = atm.get_coord(var, 'dayrel')
if var.name.lower() == 'precip':
cmap = 'hot_r'
extend = 'max'
else:
cmap = 'RdBu_r'
extend = 'both'
if clev == None:
symmetric = atm.symm_colors(vals)
cint = atm.cinterval(vals, n_pref=nc_pref, symmetric=symmetric)
clev = atm.clevels(vals, cint, symmetric=symmetric)
cticks_dict = {'precip' : np.arange(0, 13, 2),
'T200' : np.arange(-208, 227, 2),
'U200' : np.arange(-60, 61, 10),
'PSI500' : np.arange(-800, 801, 200)}
cticks = cticks_dict.get(var.name)
plt.contourf(days, lat, vals, clev, cmap=cmap, extend=extend)
plt.colorbar(ticks=cticks)
fmt_axes(xlims, xticks, ylims, yticks)
plt.grid()
plt.title(title)
plt.axvline(0, color='k')
if ssn_length is not None:
plt.axvline(ssn_length, color='k')
if grp is not None and grp.row == grp.ncol - 1:
plt.xlabel('Rel Day')
if grp is not None and grp.col == 0:
plt.ylabel('Latitude')
def contourf_latday(var, clev=None, title='', nc_pref=40, grp=None,
xlims=(-120, 200), xticks=np.arange(-120, 201, 30),
ylims=(-60, 60), yticks=np.arange(-60, 61, 20),
dlist=None, grid=False):
vals = var.values.T
lat = atm.get_coord(var, 'lat')
days = atm.get_coord(var, 'dayrel')
if var.min() >= 0:
cmap, extend, symmetric = 'PuBuGn', 'max', False
else:
cmap, extend, symmetric = 'RdBu_r', 'both', True
if clev == None:
cint = atm.cinterval(vals, n_pref=nc_pref, symmetric=symmetric)
clev = atm.clevels(vals, cint, symmetric=symmetric)
elif len(atm.makelist(clev)) == 1:
if var.name == 'PREC':
clev = np.arange(0, 10 + clev/2.0, clev)
else:
clev = atm.clevels(vals, clev, symmetric=symmetric)
cticks_dict = {'PRECTOT' : np.arange(0, 13, 2),
'PREC' : np.arange(0, 11, 2),
'T200' : np.arange(-208, 227, 2),
'U200' : np.arange(-60, 61, 10),
'PSI500' : np.arange(-800, 801, 200)}
cticks = cticks_dict.get(var.name)
plt.contourf(days, lat, vals, clev, cmap=cmap, extend=extend)
plt.colorbar(ticks=cticks)
atm.ax_lims_ticks(xlims, xticks, ylims, yticks)
plt.grid(grid)
plt.title(title)
if dlist is not None:
for d0 in dlist:
plt.axvline(d0, color='k')
if grp is not None and grp.row == grp.ncol - 1:
plt.xlabel('Rel Day')
if grp is not None and grp.col == 0:
plt.ylabel('Latitude')
def contour_londay(var, clev=None, grp=None,n_pref=40,
yticks=np.arange(-120, 201, 30)):
lon = atm.get_coord(var, 'lon')
days = atm.get_coord(var, 'dayrel')
if clev is None:
cint = atm.cinterval(var, n_pref=n_pref, symmetric=True)
clev = atm.clevels(var, cint, symmetric=True)
plt.contourf(lon, days, var, clev, cmap='RdBu_r', extend='both')
plt.grid()
plt.colorbar()
#plt.gca().invert_yaxis()
plt.yticks(yticks)
plt.axhline(0, color='k')
if grp is not None and grp.row == grp.nrow - 1:
plt.xlabel('Longitude')
if grp is not None and grp.col == 0:
plt.ylabel('Rel Day')
def contourf_londay(var,
clev=None,
grp=None,
n_pref=40,
yticks=np.arange(-120, 201, 30)):
"""Create a filled contour plot of data on longitude-day grid.
"""
lon = atm.get_coord(var, 'lon')
days = atm.get_coord(var, 'dayrel')
if clev is None:
cint = atm.cinterval(var, n_pref=n_pref, symmetric=True)
clev = atm.clevels(var, cint, symmetric=True)
plt.contourf(lon, days, var, clev, cmap='RdBu_r', extend='both')
plt.colorbar()
plt.yticks(yticks)
plt.axhline(0, color='0.5', linestyle='--', dashes=[6, 1])
if grp is not None and grp.row == grp.nrow - 1:
plt.xlabel('Longitude')
if grp is not None and grp.col == 0:
plt.ylabel('Days Since Onset')
def contourf_lat_time(lat, days, plotdata, clev=None, title='', cmap='RdBu_r',
onset_nm='', zero_line=False, ax=None):
if ax is None:
ax = plt.gca()
vals = plotdata.values.T
vals = np.ma.array(vals, mask=np.isnan(vals))
ncont = 40
symmetric = atm.symm_colors(plotdata)
if clev == None:
cint = atm.cinterval(vals, n_pref=ncont, symmetric=symmetric)
clev = atm.clevels(vals, cint, symmetric=symmetric)
cf = ax.contourf(days, lat, vals, clev, cmap=cmap)
plt.colorbar(mappable=cf, ax=ax)
#plot_colorbar(symmetric, ax=ax, mappable=cf)
if symmetric and zero_line:
ax.contour(days, lat, vals, [0], colors='k')
ax.grid(True)
ax.set_ylabel('Latitude')
ax.set_xlabel('Day Relative to %s Onset' % onset_nm)
ax.set_title(title)
xmin, xmax = ax.get_xlim()
if xmax > 60:
ax.set_xticks(range(int(xmin), int(xmax) + 1, 30))
plt.draw()
topo = atm.get_ps_clim(lat, lon) / 100
topo.units = 'hPa'
# ----------------------------------------------------------------------
# Correct for topography
u_orig = u
u = atm.correct_for_topography(u_orig, topo)
# ----------------------------------------------------------------------
# Zonal mean zonal wind
season = 'jjas'
lon1, lon2 = 60, 100
cint = 5
months = atm.season_months(season)
uplot = atm.subset(u, 'lon', lon1, lon2, 'mon', months)
uplot = uplot.mean(['lon', 'mon'])
ps_plot = atm.subset(topo, 'lon', lon1, lon2)
ps_plot = ps_plot.mean('lon')
plt.figure()
cs = atm.contour_latpres(uplot, clev=cint, topo=ps_plot)
clev = atm.clevels(uplot, cint, omitzero=True)
plt.clabel(cs, clev[::2], fmt='%02d')
plt.figure()
atm.contourf_latpres(uplot, clev=cint, topo=ps_plot)
# 1-d timeseries
var = data['U200'].sel(dayrel=day)
ts = atm.mean_over_geobox(var, 10, 30, 60, 100)
ts_reg = atm.Linreg(onset, ts)
ts_reg2 = atm.regress_field(ts, onset)
print(ts_reg.r, ts_reg2.r.values)
print(ts_reg.slope, ts_reg2.m.values)
print(ts_reg.p, ts_reg2.p.values)
# x-y data
regdays = [-60, -30, 0, 30, 60]
plotdays = [-60, -30]
clev_r = np.arange(-1.0, 1.01, 0.05)
for nm in varnms:
print(nm)
var = data[nm].sel(dayrel=regdays)
reg_daily = atm.regress_field(var, onset, axis=0)
for day in plotdays:
reg = reg_daily.sel(dayrel=day)
title = '%s day %d vs. Onset ' % (var.name, day)
cint_m = atm.cinterval(reg.m)
clev_m = atm.clevels(reg.m, cint_m, symmetric=True)
plt.figure(figsize=(11, 8))
plt.subplot(1, 2, 1)
atm.contourf_latlon(reg['r'], clev=clev_r, cmap='RdBu_r')
plt.title(title + ' - Corr Coeff')
plt.subplot(1, 2, 2)
atm.contourf_latlon(reg['m'], clev=clev_m, cmap='RdBu_r')
plt.title(title + ' - Reg Coeff')
# 1-d timeseries
var = data['U200'].sel(dayrel=day)
ts = atm.mean_over_geobox(var, 10, 30, 60, 100)
ts_reg = atm.Linreg(onset, ts)
ts_reg2 = atm.regress_field(ts, onset)
print(ts_reg.r, ts_reg2.r.values)
print(ts_reg.slope, ts_reg2.m.values)
print(ts_reg.p, ts_reg2.p.values)
# x-y data
regdays = [-60, -30, 0, 30, 60]
plotdays = [-60, -30]
clev_r = np.arange(-1.0, 1.01, 0.05)
for nm in varnms:
print(nm)
var = data[nm].sel(dayrel=regdays)
reg_daily = atm.regress_field(var, onset, axis=0)
for day in plotdays:
reg = reg_daily.sel(dayrel=day)
title = '%s day %d vs. Onset ' % (var.name, day)
cint_m = atm.cinterval(reg.m)
clev_m = atm.clevels(reg.m, cint_m, symmetric=True)
plt.figure(figsize=(11, 8))
plt.subplot(1, 2, 1)
atm.contourf_latlon(reg['r'], clev=clev_r, cmap='RdBu_r')
plt.title(title + ' - Corr Coeff')
plt.subplot(1, 2, 2)
atm.contourf_latlon(reg['m'], clev=clev_m, cmap='RdBu_r')
plt.title(title + ' - Reg Coeff')