def extract(files,**kwargs):
if files.__class__ == str:
if kwargs.has_key('x') and kwargs.has_key('y'):
(data, coords) = extract_from_file.extract_from_file(file=files, **kwargs)
else:
(data, coords) = extract_from_file.extract_from_file(files, **kwargs)
elif files.__class__ == list:
(data, coords) = extract_from_series.extract_from_series(files, **kwargs)
else:
raise TypeError('wrong type sent to the extractor')
return False
return (data,coords)
def extract(files,**kwargs):
if files.__class__ == str:
if kwargs.has_key('x') and kwargs.has_key('y'):
(data, coords) = extract_from_file.extract_from_file(file=files, **kwargs)
else:
(data, coords) = extract_from_file.extract_from_file(files, **kwargs)
elif files.__class__ == list:
(data, coords) = extract_from_series.extract_from_series(files, **kwargs)
else:
raise TypeError('wrong type sent to the extractor')
return False
return (data,coords)
def extract_from_series(file_list,
extraction_type='point',
varname='zeta',
**kwargs):
UTC = pytz.timezone('UTC')
pacific = pytz.timezone('US/Pacific')
#print('Hello from extractFromSeries')
if extraction_type == 'point':
# assume var is a 2d var for now
file_list.sort()
x = kwargs['x']
y = kwargs['y']
data = np.zeros((len(file_list), len(x)))
for i in range(len(x)):
data[0, i], junk = extract_from_file.extract_from_file(
file_list[0],
varname=varname,
extraction_type='point',
x=x[i],
y=y[i])
f1 = file_list[0]
f2 = file_list[1]
time_list = [extract_utils.file_time(file_list[0])]
for i in range(1, len(file_list)):
for j in range(len(x)):
data[i, j], junk = extract_from_file.extract_from_file(
file_list[i],
varname=varname,
extraction_type='point',
x=x[j],
y=y[j])
time_list.append(extract_utils.file_time(file_list[i]))
return (data, time_list)
# for i in range(1,ntimes):
# time_list.append(time_list[-1]+freq)
if extraction_type == 'profile':
file_list.sort()
ocean_time = None
data = None
z = None
x = kwargs['x']
y = kwargs['y']
if len(x) > 1:
x = np.array(x[0])
else:
x = np.array(x)
if len(y) > 1:
y = np.array(y[0])
else:
y = np.array(y)
for i in range(len(file_list)):
file = file_list[i]
if not os.path.exists(file):
raise IOError(
'File %s could not be located on the filesystem' % file)
ncf = nc.Dataset(file, mode='r')
if varname not in ncf.variables:
raise IOError('File %s does not have a variable named %s' %
(file, varname))
ncf.close()
d, junk = extract_from_file.extract_from_file(
file_list[i],
varname=varname,
extraction_type='profile',
x=x,
y=y)
if data == None:
data = np.zeros((d.shape[0], len(file_list)))
data[:, i] = d.T
if z == None:
z = np.zeros(data.shape)
z[:, i] = junk['zm'].T
# ocean_time = np.zeros(data.shape)
if ocean_time == None:
ocean_time = np.zeros(data.shape)
ot = extract_utils.file_timestamp(file_list[i])
# ot = file_time(file)
for j in range(data.shape[0]):
ocean_time[j, i] = ot
return (data, ocean_time, z)
return
def extract_from_series(file_list,extraction_type='point',varname='zeta',**kwargs):
UTC = pytz.timezone('UTC')
pacific = pytz.timezone('US/Pacific')
#print('Hello from extractFromSeries')
if extraction_type == 'point':
# assume var is a 2d var for now
file_list.sort()
x = kwargs['x']
y = kwargs['y']
data = np.zeros((len(file_list),len(x)))
for i in range(len(x)):
data[0,i],junk = extract_from_file.extract_from_file(file_list[0],varname=varname,extraction_type='point',x=x[i],y=y[i])
f1 = file_list[0]
f2 = file_list[1]
time_list = [extract_utils.file_time(file_list[0])]
for i in range(1,len(file_list)):
for j in range(len(x)):
data[i,j],junk = extract_from_file.extract_from_file(file_list[i],varname=varname,extraction_type='point',x=x[j],y=y[j])
time_list.append(extract_utils.file_time(file_list[i]))
return (data,time_list)
# for i in range(1,ntimes):
# time_list.append(time_list[-1]+freq)
if extraction_type == 'profile':
file_list.sort()
ocean_time = None
data = None
z = None
x = kwargs['x']
y = kwargs['y']
if len(x) > 1:
x = np.array(x[0])
else:
x = np.array(x)
if len(y) > 1:
y = np.array(y[0])
else:
y = np.array(y)
for i in range(len(file_list)):
file = file_list[i]
if not os.path.exists(file):
raise IOError('File %s could not be located on the filesystem' %file)
ncf = nc.Dataset(file,mode='r')
if varname not in ncf.variables:
raise IOError('File %s does not have a variable named %s' % (file, varname))
ncf.close()
d,junk = extract_from_file.extract_from_file(file_list[i],varname=varname,extraction_type='profile',x=x,y=y)
if data == None:
data = np.zeros((d.shape[0],len(file_list)))
data[:,i] = d.T
if z == None:
z = np.zeros(data.shape)
z[:,i] = junk['zm'].T
# ocean_time = np.zeros(data.shape)
if ocean_time == None:
ocean_time = np.zeros(data.shape)
ot = extract_utils.file_timestamp(file_list[i])
# ot = file_time(file)
for j in range(data.shape[0]):
ocean_time[j,i] = ot
return (data, ocean_time,z)
return
