def test_pretty_plot():
image = os.path.join(root_path.test_root, '00_testdata', 'plot',
'ESACCI-SOILMOISTURE-L3S-SSMV-COMBINED-20100701000000-fv04.5.nc')
ds = Dataset(image)
dat = ds.variables['sm'][:]
dat = dat.filled(np.nan).flatten()
_, resampled_lons, resampled_lats, _ = SMECV_Grid_v052(None).get_grid_points()
index =pd.MultiIndex.from_arrays(np.array([resampled_lats, resampled_lons]),
names=['lats', 'lons'])
df = pd.DataFrame(index=index, data={'sm': dat}).dropna()
f, imax, im = cp_map(df, 'sm', resxy=(0.25,0.25), cbrange=(0,50.), veg_mask=True,
cmap=cm_sm, projection=ccrs.Sinusoidal(),
title='Overloaded Plot with too much Information',
ocean=True, land='grey', gridspace=(60,20), states=True,
borders=True, llc=(-179.9999, -90.), urc=(179.9999, 90),
cb_label='ESA CCI SM [$m^3/m^3$]', cb_labelsize=7, scale_factor=100,
grid_label_loc='0111', coastline_size='110m', cb_extend='both',
cb_ext_label_min='DRY', cb_ext_label_max='WET', cb_loc='right')
out_dir = tempfile.mkdtemp()
try:
filename = 'pretty_plot.png'
f.savefig(os.path.join(out_dir, 'pretty_plot.png'), dpi=200)
assert os.path.isfile(os.path.join(out_dir, filename))
finally:
shutil.rmtree(out_dir)
def test_area_gpi():
with TemporaryDirectory() as out_dir:
gpis = np.arange(346859, 374200)
df = pd.DataFrame(index=gpis)
df['data'] = np.random.rand(df.index.size)
f, imax, im = cp_map(df, 'data', resxy=(0.25,0.25))
filename = 'plot_area_gpi.png'
f.savefig(os.path.join(out_dir, filename))
assert os.path.isfile(os.path.join(out_dir, filename))
def plot_variable(self,
variable,
time=None,
interface=True,
transparent=False,
plotfile_name=None,
file_format='png',
**plot_kwargs):
"""Plot a single variable from a certain time"""
self.read(time)
df = self.df.copy()
if not interface:
plot_kwargs['show_cbar'] = False
plot_kwargs['title'] = None
if self.irregular:
lons = df[self.index_name[1]].values if self.index_name[1] in df.columns \
else df.index.get_level_values(self.index_name[1])
lats = df[self.index_name[0]].values if self.index_name[0] in df.columns \
else df.index.get_level_values(self.index_name[0])
f, imax, im = cp_scatter_map(lons, lats, df[variable].values,
**plot_kwargs)
else:
f, imax, im = cp_map(df, variable, resxy=self.resxy, **plot_kwargs)
if not plotfile_name:
if self.time not in [None, datetime(1900, 1, 1)]:
plotfile_name = '{var}_at_{time}_from_{file}'.format(
var=variable,
time=str(self.time.date())
if not isinstance(self.time, str) else self.time,
file=self.filename)
else:
plotfile_name = '{var}_from_{file}'.format(var=variable,
file=self.filename)
if not interface:
plt.tight_layout(pad=3)
if not os.path.exists(self.out_dir):
os.makedirs(self.out_dir)
plt.savefig(os.path.join(self.out_dir,
plotfile_name + '.{}'.format(file_format)),
dpi=self.dpi,
transparent=transparent,
bbox_inches='tight')
plt.close('all')
def test_area_multiindex():
with TemporaryDirectory() as out_dir:
lons = np.linspace(-20, 20, 41)
lats = np.linspace(20, -20, 41).transpose()
lons, lats = np.meshgrid(lons, lats)
# multiindex: lats, lons
index =pd.MultiIndex.from_arrays(np.array([lats.flatten(), lons.flatten()]),
names=['lats', 'lons'])
df = pd.DataFrame(index=index)
df['data'] = np.random.rand(df.index.size)
f, imax, im = cp_map(df, 'data', resxy=(1,1), offset=(0,0))
filename = 'plot_area_multiindex.png'
f.savefig(os.path.join(out_dir, filename))
print('Stored plot in {}')
assert os.path.isfile(os.path.join(out_dir, filename))
def plot_comb_variable(self,
vards1,
vards2,
time1=None,
time2=None,
metric='-',
interface=True,
transparent=False,
plotfile_name=None,
file_format='png',
**plot_kwargs):
"""
Plot a single variable from a certain time
Parameters
---------
vards1 : str
Name of the variable to use in the first file
vards2 : str
Name of the variable to use in the second file
time1 : datetime or str, optional (default: None)
Date of the variable in the first file to use. If there are no
dates, pass None.
time2 : datetime or str, optional (default: None)
Date of the variable in the second file to use. If there are no
dates, pass None
metric : str, optional (default: -)
Metric to combine the 2 variables
Difference, AbsDiff, Ratio, Product, Sum, or Mask1
interface: bool, optional (default: True)
Plot elements such as colorbar and title
transparent: bool, optional (default: True)
Make the background of the plot transparent.
plotfile_name : str, optional (default: None)
File name to store the plot, if this is None, we create a file name.
file_format : str, optional (default: 'png')
Format in which the plot is stored (e.g. pdf or svg for vector format)
Returns
---------
ds : pd.Series
The created comb data frame, e.g. for calculating stats according to
the plotted data.
f : plt.figure
The Figure that is created.
imax : plt.Axes
The axes of the map plot.
"""
plt.close('all')
self.times = self._load_times(time1, time2, vards1, vards2)
# calc variable1 *metric* variable2
s1 = self.ds1.df[vards1]
s2 = self.ds2.df[vards2]
# make sure the two have the same index names
if self.ds1.index_name != self.ds2.index_name:
s2.rename_axis(
index=dict(zip(self.ds2.index_name, self.ds1.index_name)))
cds, smetric = self._usemetric(s1, s2, metric)
name = '{}_between_{}_and_{}'.format(smetric, vards1, vards2)
df = cds.to_frame(name)
if not interface:
plot_kwargs['show_cbar'] = False
if not self.ds1.irregular and not self.ds2.irregular:
f, imax, im = cp_map(df, name, resxy=self.resxy, **plot_kwargs)
else:
f, imax, im = cp_scatter_map(
lats=df.index.get_level_values(self.ds1.index_name[0]),
lons=df.index.get_level_values(self.ds1.index_name[1]),
values=df[name].values,
**plot_kwargs)
if not plotfile_name:
plotfile_name = name
if self.times in [[None, None],
[datetime(1900, 1, 1),
datetime(1900, 1, 1)]]:
pass
else:
plotfile_name += 'at_{t1}_and_{t2}'.format(
t1=str(self.times[0]), t2=str(self.times[1]))
if not os.path.exists(self.out_dir):
os.makedirs(self.out_dir)
plt.savefig(os.path.join(self.out_dir,
plotfile_name + '.{}'.format(file_format)),
dpi=self.dpi,
transparent=transparent,
bbox_inches='tight')
return df[name], f, imax