def _plot(df):
import matplotlib.pyplot as plt
plt.figure(figsize=(10,10))
romspy.basemap()
df2 = df['2012-08-01']
ax = plt.gca()
ax.quiver(df2.lon.values, df2.lat.values, df2.u.values, df2.v.values)
plt.show()
def _plot(df):
import matplotlib.pyplot as plt
plt.figure(figsize=(10, 10))
romspy.basemap()
df2 = df['2012-08-01']
ax = plt.gca()
ax.quiver(df2.lon.values, df2.lat.values, df2.u.values, df2.v.values)
plt.show()
def hview(self,
vname,
time=-1,
k=20,
fmt='%i',
cff=None,
unit='g',
cblabel=None,
levels=None,
step=3,
scale=5,
method='pcolor'):
"""
2015-11-08 ベクトルに対応させるために ax_heatmap と ax_vecmap を追加
"""
print '{}, time={}, k={}, fmt={},'.format(vname, time, k, fmt),
if cff is None:
cff = romspy.unit2cff(vname, unit)
if levels is None:
levels = romspy.levels(vname, unit)
if cblabel is None:
cblabel = vname
print 'cff={}'.format(cff)
if vname == 'velocity':
var = self.nc.variables['u']
else:
var = self.nc.variables[vname]
if var.ndim > 2:
t, dtime = self.get_time(time)
if vname == 'velocity':
self.add_quiver(vname, t, k, cff, step, scale)
else:
if 'pcolor' in method:
self.add_pcolor(vname, t, k, cff, levels, cblabel, fmt)
if 'contour' in method:
self.add_contour(vname, t, k, cff, levels, cblabel, fmt)
if 'fill' in method:
self.add_contourf(vname, t, k, cff, levels, cblabel, fmt)
# basemap
if self.mapfile is not None:
romspy.basemap(self.mapfile)
# finalize
if var.ndim == 2:
plt.title('Model domein & bathymetry')
elif ('avg' in self.ncfile) or ('dia' in self.ncfile):
time_string = datetime.datetime.strftime(dtime, '%Y-%m')
plt.title('Average ({})'.format(time_string))
else:
plt.title(datetime.datetime.strftime(dtime, '%Y-%m-%d %H:%M:%S'))
return plt.gca()
def hview(self, vname, **kw):
"""
2015-11-08 ベクトルに対応させるために ax_heatmap と ax_vecmap を追加
"""
time = kw.pop('time', -1)
k = kw.pop('k', 20)
cff = kw.pop('cff', None)
method = kw.pop('method', 'pcolor')
unit = kw.pop('unit', 'g')
levels = kw.pop('levels', None)
if cff is None:
cff = romspy.unit2cff(vname, unit)
if levels is None:
levels = romspy.levels(vname, unit)
print 'cff={}'.format(cff)
if vname == 'velocity':
var = self.nc.variables['u']
else:
var = self.nc.variables[vname]
if var.ndim > 2:
t, dtime = self.get_time(time)
if vname == 'velocity':
self.add_quiver(vname, t, k, **kw)
elif method == 'limit':
self.add_pcolor_limit(vname, t, k, **kw)
else:
if 'rbf' in method:
self.add_contourf_rbf(vname, t, k, cff, levels, **kw)
if 'pcolor' in method:
self.add_pcolor(vname, t, k, cff, levels, **kw)
if 'contour' in method:
self.add_contour(vname, t, k, cff, levels, **kw)
if 'fill' in method:
self.add_contourf(vname, t, k, cff, levels, **kw)
if self.mapfile is not None:
romspy.basemap(self.mapfile)
if k == 20:
plt.text(135.25, 34.25, 'surface layer')
elif k == 1:
plt.text(135.25, 34.25, 'bottom layer')
if var.ndim == 2:
plt.title('Model domein & bathymetry')
elif ('avg' in self.ncfile) or ('dia' in self.ncfile):
time_string = datetime.datetime.strftime(dtime,'%Y-%m')
plt.title('Average ({})'.format(time_string))
else:
plt.title(datetime.datetime.strftime(dtime,'%Y-%m-%d %H:%M:%S'))
return plt.gca()
def hview(self, vname, time=-1, k=20, fmt='%i', cff=None, unit='g',
cblabel=None, levels=None, step=3, scale=5, method='pcolor'):
"""
2015-11-08 ベクトルに対応させるために ax_heatmap と ax_vecmap を追加
"""
print '{}, time={}, k={}, fmt={},'.format(vname, time, k, fmt),
if cff is None:
cff = romspy.unit2cff(vname, unit)
if levels is None:
levels = romspy.levels(vname, unit)
if cblabel is None:
cblabel = vname
print 'cff={}'.format(cff)
if vname == 'velocity':
var = self.nc.variables['u']
else:
var = self.nc.variables[vname]
if var.ndim > 2:
t, dtime = self.get_time(time)
if vname == 'velocity':
self.add_quiver(vname, t, k, cff, step, scale)
else:
if 'pcolor' in method:
self.add_pcolor(vname, t, k, cff, levels, cblabel, fmt)
if 'contour' in method:
self.add_contour(vname, t, k, cff, levels, cblabel, fmt)
if 'fill' in method:
self.add_contourf(vname, t, k, cff, levels, cblabel, fmt)
# basemap
if self.mapfile is not None:
romspy.basemap(self.mapfile)
# print layer
if k == 20:
plt.text(135.25, 34.25, 'surface layer')
elif k == 1:
plt.text(135.25, 34.25, 'bottom layer')
# finalize
if var.ndim == 2:
plt.title('Model domein & bathymetry')
elif ('avg' in self.ncfile) or ('dia' in self.ncfile):
time_string = datetime.datetime.strftime(dtime,'%Y-%m')
plt.title('Average ({})'.format(time_string))
else:
plt.title(datetime.datetime.strftime(dtime,'%Y-%m-%d %H:%M:%S'))
return plt.gca()
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_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 hview(self, var2d, vname, t, title, **kw):
alpha = kw.pop('alpha', 0.5)
fmt = kw.pop('fmt', '%i') # %.1f
label = kw.pop('label', None)
contour = kw.pop('contour', True)
contourf = kw.pop('contourf', True)
clabel = kw.pop('clabel', True)
linewidths = kw.pop('linewiths', 0.5)
kw['extend'] = kw.pop('extend', 'both')
ax = plt.gca()
if contourf:
CF = ax.contourf(self.X, self.Y, var2d, alpha=alpha, **kw)
CB = plt.colorbar(CF)
if contour:
C = ax.contour(self.X, self.Y, var2d, colors='k', linewidths=linewidths, **kw)
if clabel:
C.clabel(colors='k', fmt=fmt)
if label is not None:
CB.ax.set_ylabel(label)
title = label + title
ax.set_title(title)
romspy.basemap(self.mapfile)
def _plot_map(ts, post_tmp, *args, **kw):
"""
plot for "ts" dataframe
ts: input DataFrame
post_tmp: output file
"""
start, end, vname, layer, stafile = args
sta = _read_stations(stafile)
if vname == 'DO':
vmin, vmax = 0, 10
elif vname == 'COD':
vmin, vmax = 0, 8
elif vname == 'temp':
vmin, vmax = 10, 30
for t in ts.index:
time_str = datetime.datetime.strftime(t, '%Y-%m')
s2 = pd.concat([sta, ts[time_str].T], axis=1).dropna()
if len(s2) > 0:
xs = s2.lon.values
ys = s2.lat.values
zs = s2.ix[:,-1].values
x, y, z = _rbf(xs, ys, zs, **kw)
#x, y, z = _grid(xs, ys, zs, bin=50)
plt.pcolor(x, y, z, vmin=vmin, vmax=vmax)
plt.colorbar()
romspy.basemap(mapfile)
plt.scatter(xs, ys, c=zs, s=30, vmin=vmin, vmax=vmax)
else:
romspy.basemap(mapfile)
figfile = post_tmp.format(**locals())
_mkdir(figfile)
plt.title('{vname} (layer={layer}) {time_str}'.format(**locals()))
plt.savefig(figfile, bbox_inches='tight')
plt.clf()
import numpy as np
import matplotlib.pyplot as plt
import romspy
inifile = '/home/okada/Data/ob500_ini_param6-ini_20120101.nc'
grdfile = '/home/okada/Data/ob500_grd-11_3.nc'
ini = netCDF4.Dataset(inifile, 'r')
grd = netCDF4.Dataset(grdfile, 'r')
h = grd['h'][:]
cs_r = grd['Cs_r'][:]
x_rho = grd['lon_rho'][0, :]
y_rho = grd['lat_rho'][:, 0]
X, Y = np.meshgrid(x_rho, y_rho)
zeta = ini['zeta'][0, :, :]
temp = ini['temp'][0, :, :, :]
N, M, L = temp.shape
depth = np.zeros_like(temp)
for n in range(N):
depth[n, :, :] = cs_r[n] * (zeta + h)
temp10 = romspy.zslice(temp, depth, -1)
fig, ax = plt.subplots(1, 1, figsize=(6, 5))
romspy.basemap()
C = ax.contourf(X, Y, temp10)
#C.label()
CB = plt.colorbar(C)
def reshape_wind(windfiles,
stafiles,
grdfile,
method='kriging',
smooth=1,
plot=False):
u, v = {}, {}
timedelta = datetime.timedelta(hours=3)
for windfile in windfiles:
print windfile
if 'mp' in windfile:
names = ['name', 'date', 'direction', 'wind']
df = pd.read_csv(windfile,
encoding='Shift_JIS',
names=names,
skiprows=1,
na_values='*',
index_col='date')
df['u'] = -np.sin(math.pi * df.direction / 180.0) * df.wind
df['v'] = -np.cos(math.pi * df.direction / 180.0) * df.wind
df.index = df.index.map(
lambda t: datetime.datetime.strptime(t, '%Y/%m/%d %H:%M'))
df = df.resample('12H', how='mean', loffset=timedelta)
#df = df.resample('H', how='mean')
station = int(windfile[-26:-24])
u[station] = df.u.dropna()
v[station] = df.v.dropna()
elif 'jma' in windfile:
df = pd.read_csv(windfile,
encoding='Shift_JIS',
na_values='--',
index_col='id')
df['u'] = -np.sin(
math.pi * df.wind_direction / 180.0) * df.wind_velocity
df['v'] = -np.cos(
math.pi * df.wind_direction / 180.0) * df.wind_velocity
df.index = df.index.map(
lambda t: datetime.datetime.strptime(t, '%Y/%m/%d %H:%M'))
df = df.resample('12H', how='mean', loffset=timedelta)
#df = df.resample('H', how='mean')
station = windfile[windfile.find('jma_') + 4:-22]
u[station] = df.u.dropna()
v[station] = df.v.dropna()
sta_mp = pd.read_csv(stafiles['mp'], index_col='station')
sta_jma = pd.read_csv(stafiles['jma'], index_col='station')
grd = netCDF4.Dataset(grdfile, 'r')
xmesh = grd.variables['lon_rho'][:, :]
ymesh = grd.variables['lat_rho'][:, :]
grd.close()
xgrid = xmesh[0, :]
ygrid = ymesh[:, 0]
td = len(df)
xd = len(xgrid)
yd = len(ygrid)
u3d = np.zeros(shape=[td, yd, xd])
v3d = np.zeros_like(u3d)
time_wind = np.zeros(shape=[td])
for i, t in enumerate(df.index):
X, Y, U, V = [], [], [], []
for station in u.keys():
try:
U.append(u[station][t])
V.append(v[station][t])
if type(station) == int:
X.append(sta_mp.lon[station])
Y.append(sta_mp.lat[station])
elif type(station) == str:
X.append(sta_jma.x[station])
Y.append(sta_jma.y[station])
except:
pass
print i, t, len(Y)
if method == 'kriging_gaussian':
ukrig = OrdinaryKriging(X,
Y,
U,
variogram_model='gaussian',
verbose=False,
enable_plotting=False)
vkrig = OrdinaryKriging(X,
Y,
V,
variogram_model='gaussian',
verbose=False,
enable_plotting=False)
umesh, ss = ukrig.execute('grid', xgrid, ygrid)
vmesh, ss = vkrig.execute('grid', xgrid, ygrid)
elif method == 'kriging_linear':
ukrig = OrdinaryKriging(X,
Y,
U,
variogram_model='linear',
verbose=False,
enable_plotting=False)
vkrig = OrdinaryKriging(X,
Y,
V,
variogram_model='linear',
verbose=False,
enable_plotting=False)
umesh, ss = ukrig.execute('grid', xgrid, ygrid)
vmesh, ss = vkrig.execute('grid', xgrid, ygrid)
elif method == 'rbf':
urbf = Rbf(X, Y, U)
vrbf = Rbf(X, Y, V)
umesh = urbf(xmesh, ymesh)
vmesh = vrbf(xmesh, ymesh)
elif method == 'rbf_gaussian':
urbf = Rbf(X, Y, U, function='inverse')
vrbf = Rbf(X, Y, V, function='inverse')
umesh = urbf(xmesh, ymesh)
vmesh = vrbf(xmesh, ymesh)
elif method == 'rbf_linear':
urbf = Rbf(X, Y, U, function='inverse')
vrbf = Rbf(X, Y, V, function='inverse')
umesh = urbf(xmesh, ymesh)
vmesh = vrbf(xmesh, ymesh)
elif method == 'rbf_inverse':
urbf = Rbf(X, Y, U, function='inverse')
vrbf = Rbf(X, Y, V, function='inverse')
umesh = urbf(xmesh, ymesh)
vmesh = vrbf(xmesh, ymesh)
elif method == 'rbf_inverse_smooth':
urbf = Rbf(X, Y, U, function='inverse', smooth=smooth)
vrbf = Rbf(X, Y, V, function='inverse', smooth=smooth)
umesh = urbf(xmesh, ymesh)
vmesh = vrbf(xmesh, ymesh)
if plot == 'pcolor' and i == 0:
plt.figure(figsize=[15, 5])
plt.subplot(1, 2, 1)
plt.pcolor(xmesh, ymesh, umesh, vmin=-1, vmax=1)
plt.colorbar()
plt.subplot(1, 2, 2)
plt.pcolor(xmesh, ymesh, vmesh, vmin=-1, vmax=1)
plt.colorbar()
plt.show()
elif plot == 'quiver' and i == 0:
plt.figure(figsize=[10, 10])
romspy.basemap('F:/okada/notebook/deg_OsakaBayMap_okada.bln')
plt.quiver(xmesh[::3, ::3],
ymesh[::3, ::3],
umesh[::3, ::3],
vmesh[::3, ::3],
units='width',
angles='xy',
scale=100)
plt.quiver(X,
Y,
U,
V,
color='r',
units='xy',
angles='xy',
scale=100)
plt.show()
u3d[i, :, :] = umesh
v3d[i, :, :] = vmesh
time_wind[i] = netCDF4.date2num(t, romspy.JST_days)
return u3d, v3d, time_wind
lon, lat = x, y
except:
lon, lat = xy2lonlat(x, y, grdfile)
if type == varid:
if not lon in check.keys():
print i, t, x, y, z, type, v
check[lon] = z
sc = ax.scatter(lon, lat, c=v*cff, vmin=vmin, vmax=vmax, s=200)
#plt.text(lon-0.01, lat-0.02, str(round(v,1)))
elif z < check[lon]:
print i, t, x, y, z, type, v
check[lon] = z
sc = ax.scatter(lon, lat, c=v*cff, vmin=vmin, vmax=vmax, s=200)
return sc
if __name__ == '__main__':
import datetime
romspy.cmap('jet')
obsfile = '/home/okada/Data/ob500_obs_2012_mp-2.nc'
varid = 15
plotdate = datetime.datetime(2012,8,3,0)
vmin = 0
vmax = 10
cff = romspy.mol2g_O2
romspy.basemap()
sc = hplot_values(obsfile, varid, plotdate, vmin=vmin, vmax=vmax, cff=cff)
plt.colorbar(sc)
plt.show()
