def main(test, hours=24):
inifiles = _get_files(
'/home/okada/ism-i/apps/OB500P/testDA/{}/output/ob500_ini_*.nc'.format(
test),
hours=hours)
figfile = '/home/okada/Dropbox/Figures/2016_param/tplot_param_{}.png'.format(
test)
if test == 'param2':
fig, ax = plt.subplots(2, 1)
tplot_param(inifiles, 'P01', ax=ax[0])
tplot_param(inifiles, 'P04', ax=ax[1])
ax[0].set_title('4dvar(ini+param), window=1day, pfactor=0.1')
elif 'param3' in test:
ax = _plot6(inifiles)
pfactor = _get_pfactor(test)
ax[0].set_title(
'4dvar(ini+param), window=1day, pfactor={}'.format(pfactor))
elif 'param4' in test:
ax = _plot6(inifiles)
pfactor = _get_pfactor(test)
ax[0].set_title(
'4dvar(param), window=1day, pfactor={}'.format(pfactor))
elif 'param5' in test:
ax = _plot6(inifiles)
pfactor = '*'
ax[0].set_title(
'4dvar(ini+param), window=1day, pfactor={}'.format(pfactor))
elif 'param6' in test:
ax = _plot6(inifiles)
pfactor = '*'
ax[0].set_title(
'4dvar(param), window=7day, pfactor={}'.format(pfactor))
romspy.savefig(figfile)
def main(test):
if test == 'param2':
inifiles = ['/home/okada/ism-i/apps/OB500P/testDA/{}/output/ob500_ini_{}.nc'.format(test, i) for i in range(0,8712,24)]
title = '4dvar(ini+param), window=1day, pfactor=0.1'
for vid in [1,4]:
vname = 'P{:02d}'.format(vid)
figfile = '/home/okada/Dropbox/Figures/2016_param/plot_pdf_param_{test}_{vname}.png'.format(**locals())
plt.cla()
plot_pdf_param(inifiles, vname)
plt.title(title)
romspy.savefig(figfile)
def main(test):
if test == 'param2':
inifiles = [
'/home/okada/ism-i/apps/OB500P/testDA/{}/output/ob500_ini_{}.nc'.
format(test, i) for i in range(0, 8712, 24)
]
title = '4dvar(ini+param), window=1day, pfactor=0.1'
for vid in [1, 4]:
vname = 'P{:02d}'.format(vid)
figfile = '/home/okada/Dropbox/Figures/2016_param/plot_pdf_param_{test}_{vname}.png'.format(
**locals())
plt.cla()
plot_pdf_param(inifiles, vname)
plt.title(title)
romspy.savefig(figfile)
def _plot_col(df, vname, fname, title):
if vname == 'temp':
vmin, vmax = 0, 35
elif vname == 'DO':
vmin, vmax = 0, 12
elif vname == 'COD':
vmin, vmax = 0, 12
plt.figure(figsize=(6, 6))
plt.scatter(df[vname].values, df.ts.values, alpha=0.5)
plt.plot([vmin, vmax], [vmin, vmax], 'k-', alpha=0.5)
plt.xlim(vmin, vmax)
plt.ylim(vmin, vmax)
plt.xlabel('observations')
plt.ylabel('trend+seasonal')
plt.title(title)
col_png = fname + '_col.png'
sk._mkdir(col_png)
romspy.savefig(col_png)
def plot_stations(stafile):
df = _read_stations(stafile)
plt.figure(figsize=(8,8))
plt.scatter(df.lon.values, df.lat.values)
for i in df.index:
#plt.text(df.lon[i], df.lat[i], df.id[i], backgroundcolor='w')
plt.annotate(str(df.id[i]), xy=(df.lon[i], df.lat[i]),
xycoords='data',
xytext=(df.lon[i]-0.025, df.lat[i]+0.015),
#textcoords='offset points',
arrowprops=dict(arrowstyle="-")
)
romspy.basemap(mapfile)
plt.gca().patch.set_facecolor('gray')
plt.gca().patch.set_alpha(0.2)
pngfile = stafile.replace('csv', 'png')
romspy.savefig(pngfile)
plt.show()
def _plot_col(df, vname, fname, title):
if vname == 'temp':
vmin, vmax = 0, 35
elif vname == 'DO':
vmin, vmax = 0, 12
elif vname == 'COD':
vmin, vmax = 0, 12
plt.figure(figsize=(6,6))
plt.scatter(df[vname].values, df.ts.values, alpha=0.5)
plt.plot([vmin,vmax], [vmin,vmax], 'k-', alpha=0.5)
plt.xlim(vmin, vmax)
plt.ylim(vmin, vmax)
plt.xlabel('observations')
plt.ylabel('trend+seasonal')
plt.title(title)
col_png = fname+'_col.png'
sk._mkdir(col_png)
romspy.savefig(col_png)
def plot_osaka():
plt.figure(figsize=(15,10))
plt.subplot(2,3,1)
plots(3)
plt.subplot(2,3,2)
plots(4)
plt.subplot(2,3,3)
plots2(5)
plt.subplot(2,3,4)
plots(6)
plt.subplot(2,3,5)
plots(12)
plt.subplot(2,3,6)
plots(13)
import romspy
plt.suptitle('osaka, 2012')
romspy.savefig('F:/okada/Dropbox/Figures/analysis_mp/osaka2012_light_chlo.png')
def plot_stations(stafile):
df = _read_stations(stafile)
plt.figure(figsize=(8, 8))
plt.scatter(df.lon.values, df.lat.values)
for i in df.index:
#plt.text(df.lon[i], df.lat[i], df.id[i], backgroundcolor='w')
plt.annotate(
str(df.id[i]),
xy=(df.lon[i], df.lat[i]),
xycoords='data',
xytext=(df.lon[i] - 0.025, df.lat[i] + 0.015),
#textcoords='offset points',
arrowprops=dict(arrowstyle="-"))
romspy.basemap(mapfile)
plt.gca().patch.set_facecolor('gray')
plt.gca().patch.set_alpha(0.2)
pngfile = stafile.replace('csv', 'png')
romspy.savefig(pngfile)
plt.show()
resample = 'H'
# outpt directories
outdir = os.path.dirname(modfiles[0]).replace('ism-i/apps', 'Dropbox/Figures')
outdir = outdir.replace('/output', '')
if not os.path.exists(outdir):
print 'mkdir', outdir
os.makedirs(outdir)
# plot cost functions
if plot_cost:
romspy.plot_cost(modfiles, Ninner)
outfile = os.path.join(outdir, plot_costfile)
print outfile
plt.suptitle(case)
romspy.savefig(outfile)
# plot time series of mod files
assimilation = True
if tplot_valification:
for varid in varids:
fig, axes = plt.subplots(3, 2, figsize=[12, 12])
axlist = [axes[y][x] for x in range(2) for y in range(3)]
for station, ax in zip(stations, axlist):
romspy.tplot_valification(obsfile,
modfile,
varid,
station,
dates,
assimilation=assimilation,
ax=ax,
ax[1].scatter(mod_value, obs_value)
for i in range(2):
ax[i].plot([0,100], [0,100], 'k-', alpha=0.5)
ax[i].set_xlabel('Model')
ax[i].set_xlim(lim)
ax[i].set_ylim(lim)
ax[0].set_ylabel('Observation')
ax[0].set_title('Background')
ax[1].set_title('Assimilation')
plt.suptitle(title)
if __name__ == '__main__':
#import seaborn as sns
romspy.cmap('jet')
case = 'case28/DA0-3.1'
varids = [6,7,10,15]
#varids = [6,7]
#varids = [6]
obsfile = '/home/okada/Data/ob500_obs_2012_mp-2.nc'
#obsfile = '/home/okada/Data/ob500_obs_2012_mp-1_ts.nc'
#modfile = '/home/okada/ism-i/apps/OB500P/{}/output/ob500_mod_0.nc'.format(case)
modfiles = ['/home/okada/ism-i/apps/OB500P/{}/output/ob500_mod_{}.nc'.format(case, i*24) for i in range(0,7)]
for varid in varids:
tplot_rmse(obsfile, modfiles, varid)
#plt.show()
romspy.savefig('/home/okada/Dropbox/Figures/OB500P/{}/tplot_rmse_{}.png'.format(case, varid))
resample = 'H'
# outpt directories
outdir = os.path.dirname(modfiles[0]).replace('ism-i/apps', 'Dropbox/Figures')
outdir = outdir.replace('/output', '')
if not os.path.exists(outdir):
print 'mkdir', outdir
os.makedirs(outdir)
# plot cost functions
if plot_cost:
romspy.plot_cost(modfiles, Ninner)
outfile = os.path.join(outdir, plot_costfile)
print outfile
plt.suptitle(case)
romspy.savefig(outfile)
# plot time series of mod files
assimilation = True
if tplot_valification:
for varid in varids:
fig, axes = plt.subplots(3,2, figsize=[12,12])
axlist = [axes[y][x] for x in range(2) for y in range(3)]
for station, ax in zip(stations, axlist):
romspy.tplot_valification(obsfile, modfile, varid, station, dates, assimilation=assimilation, ax=ax, date_format=date_format, resample=resample)
if varid == 6:
ax.set_ylim(5, 30)
elif varid == 7:
ax.set_ylim(23, 33)
elif varid == 10:
ax.set_ylim(0, 30)
ax[i].plot([0,100], [0,100], 'k-', alpha=0.5)
ax[i].set_xlabel('Model')
ax[i].set_xlim(lim)
ax[i].set_ylim(lim)
ax[0].set_ylabel('Observation')
ax[0].set_title('Background')
ax[1].set_title('Assimilation')
plt.suptitle(title)
if __name__ == '__main__':
#import seaborn as sns
romspy.cmap('jet')
case = 'case28/DA0-3.1'
#how = 'scatter2d'
how = 'scatter2d_gaussian'
#how = 'hist2d'
varids = [6,7,10,15]
#varids = [6,7]
#varids = [6]
obsfile = '/home/okada/Data/ob500_obs_2012_mp-2.nc'
#obsfile = '/home/okada/Data/ob500_obs_2012_mp-1_ts.nc'
#modfile = '/home/okada/ism-i/apps/OB500P/{}/output/ob500_mod_0.nc'.format(case)
modfiles = ['/home/okada/ism-i/apps/OB500P/{}/output/ob500_mod_{}.nc'.format(case, i*24) for i in range(0,7)]
for varid in varids:
plot_hist2d(obsfile, modfiles, varid, how)
#plt.show()
romspy.savefig('/home/okada/Dropbox/Figures/OB500P/{}/{}_{}.png'.format(case, how, varid))