def test_1dtimeseries(directory, sourcefiles, var, cwd):
""" Tests plot_realizations_1d for a timeseries plot
Parameters
----------
directory : string
the directory to link the files to
sourcefiles : list
a list of the locations of the files to link
var : string
the variable plotted
cwd : string
directory of the test modules
"""
ctt.loadtestfiles(directory, sourcefiles)
filepattern = '*.nc'
ens = cd.mkensemble(filepattern)
data = cd.loadfiles(ens, var, cdostr='-fldmean -yearmean', toDatetime=True)
fig, axt = plt.subplots(1, 1, figsize=(8, 8))
cd.plot_realizations_1d(data,
var,
'time',
ax=axt,
pdf='tsplot',
kwargs={
'color': 'r',
'alpha': 0.3
})
plotcompare(directory, cwd, 'tsplot')
os.system('rm tsplot.pdf')
def save_cmip5_trends(ens, var, start_date, end_date, datapath='./'):
"""Compute trends and save as np array in HDF5.
"""
# Compute the trends using cmipdata/cdo
ens1 = cd.trends(ens, start_date=start_date,
end_date=end_date, delete=False)
# keep only the slope files, delete the intercept files
for model, experiment, realization, variable, files in ens1.iterate():
for file in files:
if 'intercept' in file:
variable.del_filename(file)
# load the slope files into a np array
slopes = cd.loadfiles(ens1, var)
# Store the DataFrame in HDF5
out_file = os.path.join(datapath, 'cmip5_trends.h5')
h5f = h5py.File(out_file, 'a')
sy = start_date.split('-')[0]
ey = end_date.split('-')[0]
ds_path = os.path.join(var, sy + '_' + ey)
ds_name = os.path.join(ds_path, 'c5_' + var + '_trend_' + sy + '_' + ey)
h5f.create_dataset(ds_name, data=slopes)
model_names = [ model.name for model in ens1.models]
h5f.create_dataset(ds_path + '/model_names', data=model_names)
#h5f[ds_name].dims.create_scale(h5f[ds_path + 'model_names'], 'model_names')
#f[ds_name].dims[2].attach_scale(h5f[ds_path + 'model_names'])
h5f.close()
# clean up
trash_files = glob.glob('slope*.nc')
trash_files.extend(glob.glob('intercept*.nc'))
for f in trash_files:
os.remove(f)
def test_loadingtools(directory, sourcefiles, var):
""" Loads the data from a set of files
"""
ctt.loadtestfiles(directory, sourcefiles)
filepattern = '*.nc'
ens = cd.mkensemble(filepattern)
data = hashlib.sha1(cd.loadfiles(ens,var)['data']).hexdigest()
return {var: data}
def test_1dtimeseries(directory, sourcefiles, var, cwd):
""" Tests plot_realizations_1d for a timeseries plot
Parameters
----------
directory : string
the directory to link the files to
sourcefiles : list
a list of the locations of the files to link
var : string
the variable plotted
cwd : string
directory of the test modules
"""
ctt.loadtestfiles(directory, sourcefiles)
filepattern = '*.nc'
ens = cd.mkensemble(filepattern)
data = cd.loadfiles(ens, var, cdostr='-fldmean -yearmean', toDatetime=True)
fig, axt = plt.subplots(1, 1, figsize=(8, 8))
cd.plot_realizations_1d(data, var, 'time', ax=axt, pdf='tsplot',
kwargs={'color': 'r', 'alpha': 0.3})
plotcompare(directory, cwd, 'tsplot')
os.system('rm tsplot.pdf')