def plot_time_series(varname='salt',
x=-123.1126,
y=47.4218,
dir='.',
seconds=3600,
filelist=None,
imgfile='~/tmp/rompy.time_series.png',
title=None,
dt0=None,
dt1=None):
if filelist == None or filelist == []:
filelist = glob.glob(os.path.join(dir, 'ocean_his*.nc'))
# lat lon points for Hoodsport ORCA buoy
x = [x]
y = [y]
clim_map = {
'temp': [0, 8, 20, 20],
'salt': [0, 21, 33, 33],
'U': [-2, -2, 2, 2]
}
clabel_map = {'temp': u'\u00B0 C', 'salt': 'psu', 'U': 'm/s'}
#(data, coords) = rompy.extract('ocean_his_1000.nc', varname='salt', extraction_type='profile', x=x, y=y)
# (data, time,z) = extract_from_series(filelist,varname=varname,extraction_type='profile',x=x,y=y,freq=dt.timedelta(seconds=seconds))
if dt0 is None:
dt0 = dt.datetime(2006, 06, 01, 0, 0, 0)
else:
dt0 = dt.datetime.strptime(dt0, '%Y%m%d%H%M')
if dt1 is None:
dt1 = dt.datetime(2006, 07, 01, 0, 0, 0)
else:
dt1 = dt.datetime.strptime(dt1, '%Y%m%d%H%M')
(data, time, z) = extract_from_two_datetimes(x=x,
y=y,
dt0=dt0,
dt1=dt1,
varname=varname,
interval=seconds,
basedir=dir)
if not os.path.exists(os.path.dirname(imgfile)):
os.makedirs(os.path.dirname(imgfile))
plot_utils.plot_time_series_profile(time,
z,
data,
filename=imgfile,
clim=clim_map[varname],
varname=varname,
title=title,
caxis_label=clabel_map[varname])
def plot_time_series(varname='salt', x=-123.1126, y=47.4218, dir='.', seconds=3600, filelist=None, imgfile='~/tmp/rompy.time_series.png',title=None, dt0=None, dt1=None):
if filelist == None or filelist == []:
filelist = glob.glob(os.path.join(dir,'ocean_his*.nc'))
# lat lon points for Hoodsport ORCA buoy
x = [x]
y = [y]
clim_map = {
'temp':[0,8,20,20],
'salt':[0,21,33,33],
'U':[-2,-2,2,2]
}
clabel_map = {
'temp': u'\u00B0 C',
'salt': 'psu',
'U': 'm/s'
}
#(data, coords) = rompy.extract('ocean_his_1000.nc', varname='salt', extraction_type='profile', x=x, y=y)
# (data, time,z) = extract_from_series(filelist,varname=varname,extraction_type='profile',x=x,y=y,freq=dt.timedelta(seconds=seconds))
if dt0 is None:
dt0 = dt.datetime(2006,06,01,0,0,0)
else:
dt0 = dt.datetime.strptime(dt0,'%Y%m%d%H%M')
if dt1 is None:
dt1 = dt.datetime(2006,07,01,0,0,0)
else:
dt1 = dt.datetime.strptime(dt1,'%Y%m%d%H%M')
(data, time,z) = extract_from_two_datetimes(x=x,
y=y,
dt0=dt0,
dt1=dt1,
varname=varname,
interval=seconds,
basedir=dir)
if not os.path.exists(os.path.dirname(imgfile)):
os.makedirs(os.path.dirname(imgfile))
plot_utils.plot_time_series_profile(time,z,data,
filename=imgfile,
clim=clim_map[varname],
varname=varname,
title=title,
caxis_label=clabel_map[varname])
#---------------------------------------------------------------------------------------------------
filelist = glob.glob('ocean_his*.nc')
#x,y = utils.station_to_lat_lon([20])
x = [-122.3904]
y = [47.6108]
varname='salt'
clim_map = {
'temp':[0,8,20,20],
'salt':[0,21,33,33],
'U':[-2,-2,2,2]
}
#(data, coords) = rompy.extract('ocean_his_1000.nc', varname='salt', extraction_type='profile', x=x, y=y)
(data, time,z) = extract_from_series(filelist,varname=varname,extraction_type='profile',x=x,y=y,freq=dt.timedelta(seconds=1800))
plot_time_series_profile(time,z,data,clim=clim_map[varname],varname=varname)
#print(len(time),len(time[0]))
#print(data)
#print(z)
#
# fontsize = 8
#
# clim = [0,21,33,33]
# cmap = banas_hsv_cm(clim[0],clim[1],clim[2],clim[3])
# norm = Normalize(vmin=clim[0],vmax=clim[-1],clip=False)
# sm = ScalarMappable(norm=norm,cmap=cmap)
# sm.set_clim(vmin=clim[0],vmax=clim[-1])
# sm.set_array(np.array([0]))
#
clim_map = {
'temp': [0, 8, 20, 20],
'salt': [0, 21, 33, 33],
'U': [-2, -2, 2, 2]
}
#(data, coords) = rompy.extract('ocean_his_1000.nc', varname='salt', extraction_type='profile', x=x, y=y)
(data, time, z) = extract_from_series(filelist,
varname=varname,
extraction_type='profile',
x=x,
y=y,
freq=dt.timedelta(seconds=1800))
plot_time_series_profile(time,
z,
data,
clim=clim_map[varname],
varname=varname)
#print(len(time),len(time[0]))
#print(data)
#print(z)
#
# fontsize = 8
#
# clim = [0,21,33,33]
# cmap = banas_hsv_cm(clim[0],clim[1],clim[2],clim[3])
# norm = Normalize(vmin=clim[0],vmax=clim[-1],clip=False)
# sm = ScalarMappable(norm=norm,cmap=cmap)
# sm.set_clim(vmin=clim[0],vmax=clim[-1])
#x = [-122.3904]
#y = [47.6108]
#x,y = station_to_lat_lon(['admiralty inlet'])
x,y = station_to_lat_lon([4])
dt0 = dt.datetime(2006,06,11,0,0,0)
dt1 = dt.datetime(2006,06,13,0,0,0)
interval = 3600 # seconds
varname='salt'
clim_map = {
'temp':[0,8,20,20],
'salt':[0,21,33,33],
'U':[-2,-2,2,2]
}
d,t,z = extract_from_series.extract_from_two_datetimes(x,y,dt0,dt1,varname=varname,interval=interval)
#print('z')
#print(z)
#print('time')
#print(t)
#print('data')
#print(d)
plot_time_series_profile(t,z,d,clim=clim_map[varname],varname=varname,filename='/Users/lederer/tmp/rompy.arbitrary_time_series_profile.png')
interval = 3600 # seconds
varname = 'salt'
clim_map = {
'temp': [0, 8, 20, 20],
'salt': [0, 21, 33, 33],
'U': [-2, -2, 2, 2]
}
d, t, z = extract_from_series.extract_from_two_datetimes(x,
y,
dt0,
dt1,
varname=varname,
interval=interval)
#print('z')
#print(z)
#print('time')
#print(t)
#print('data')
#print(d)
plot_time_series_profile(
t,
z,
d,
clim=clim_map[varname],
varname=varname,
filename='/Users/lederer/tmp/rompy.arbitrary_time_series_profile.png')
