def setUp(self) -> None:
self.testfile = '3-GLDAS.SoilMoi0_10cm_inst_with_1-C3S.sm_with_2-SMOS.Soil_Moisture.nc'
self.testfile_path = os.path.join(os.path.dirname(__file__), '..','tests',
'test_data', 'tc', self.testfile)
self.plotdir = tempfile.mkdtemp()
self.img = QA4SMImg(self.testfile_path)
self.plotter = QA4SMPlotter(self.img, self.plotdir)
def setUp(self) -> None:
self.testfile = '0-ISMN.soil moisture_with_1-C3S.sm.nc'
self.testfile_path = os.path.join(os.path.dirname(__file__), '..','tests',
'test_data', 'basic', self.testfile)
self.plotdir = tempfile.mkdtemp()
self.img = QA4SMImg(self.testfile_path)
self.plotter = QA4SMPlotter(self.img, self.plotdir)
def plot_all(filepath,
metrics=None,
extent=None,
out_dir=None,
out_type='png',
boxplot_kwargs=dict(),
mapplot_kwargs=dict()):
"""
Creates boxplots for all metrics and map plots for all variables. Saves the output in a folder-structure.
Parameters
----------
filepath : str
Path to the *.nc file to be processed.
metrics : set or list, optional (default: None)
metrics to be plotted, if None are passed, all are plotted (that have data)
extent : list
[x_min,x_max,y_min,y_max] to create a subset of the values
out_dir : [ None | str ], optional
Parrent directory where to generate the folder structure for all plots.
If None, defaults to the current working directory.
The default is None.
out_types : list, optional (default: [png, svg])
File types, e.g. 'png', 'pdf', 'svg', 'tiff'...
A list, a plot is saved for each type.
**boxplot_kwargs : dict, optional
Additional keyword arguments that are passed to the boxplot function.
**mapplot_kwargs : dict, optional
Additional keyword arguments that are passed to the mapplot function.
"""
if not out_dir:
out_dir = os.path.join(os.getcwd(), os.path.basename(filepath))
img = QA4SMImg(filepath, extent=extent, ignore_empty=True)
plotter = QA4SMPlotter(image=img, out_dir=out_dir)
# === Metadata ===
if not metrics:
metrics = img.ls_metrics(False)
fnames_maps, fnames_boxes = [], []
for metric in metrics:
# === load values and metadata ===
if metric not in globals.metric_groups[3]:
fns_box = plotter.boxplot_basic(metric,
out_type=out_type,
**boxplot_kwargs)
else:
fns_box = plotter.boxplot_tc(metric,
out_type=out_type,
**boxplot_kwargs)
fns_maps = plotter.mapplot(metric, out_type=out_type, **mapplot_kwargs)
plt.close('all')
for fn in fns_box:
fnames_boxes.append(fn)
for fn in fns_maps:
fnames_maps.append(fn)
return fnames_boxes, fnames_maps
def setUp(self) -> None:
self.testfile = "0-ERA5.swvl1_with_1-ESA_CCI_SM_combined.sm_with_2-ESA_CCI_SM_combined.sm_with_3-ESA_CCI_SM_combined.sm_with_4-ESA_CCI_SM_combined.sm.CI.nc"
self.testfile_path = os.path.join(os.path.dirname(__file__), '..',
'tests', 'test_data', 'tc',
self.testfile)
self.plotdir = tempfile.mkdtemp()
self.img = QA4SMImg(self.testfile_path)
self.plotter = QA4SMPlotter(self.img, self.plotdir)
def get_img_stats(filepath, extent=None):
"""
Creates a dataframe containing summary statistics of the result metrics
values which is rendered in the file
qa4sm/validator/templates/validator/results.html
Parameters
----------
filepath : str
Path to the *.nc file to be processed.
extent : list, optional
[x_min,x_max,y_min,y_max] to create a subset of the values. The default is None.
Returns
-------
table : pd.DataFrame
Quick inspection table of the results.
"""
img = QA4SMImg(filepath, extent=extent, ignore_empty=True)
table = img.stats_df()
return table
def get_img_stats(
filepath:str,
extent:tuple=None
) -> pd.DataFrame:
"""
Creates a dataframe containing summary statistics for each metric
Parameters
----------
filepath : str
path to the *.nc file to be processed.
extent : list
list(x_min, x_max, y_min, y_max) to create a subset of the values
Returns
-------
table : pd.DataFrame
Quick inspection table of the results.
"""
img = QA4SMImg(filepath, extent=extent, ignore_empty=True)
table = img.stats_df()
return table
def setUp(self) -> None:
self.testfile = '3-ERA5_LAND.swvl1_with_1-C3S.sm_with_2-SMOS.Soil_Moisture.nc'
self.testfile_path = os.path.join(os.path.dirname(__file__), '..',
'tests', 'test_data', 'basic',
self.testfile)
self.img = QA4SMImg(self.testfile_path, ignore_empty=False)
def plot_all(
filepath:str,
metrics:list=None,
extent:tuple=None,
out_dir:str=None,
out_type:str='png',
save_all:bool=True,
**plotting_kwargs
) -> (list, list):
"""
Creates boxplots for all metrics and map plots for all variables.
Saves the output in a folder-structure.
Parameters
----------
filepath : str
path to the *.nc file to be processed.
metrics : set or list, optional (default: None)
metrics to be plotted. If None, all metrics with data are plotted
extent : tuple, optional (default: None)
Area to subset the values for -> (min_lon, max_lon, min_lat, max_lat)
out_dir : str, optional (default: None)
Path to output generated plot. If None, defaults to the current working directory.
out_type: str or list
extensions which the files should be saved in
save_all: bool, optional. Default is True.
all plotted images are saved to the output directory
plotting_kwargs: arguments for plotting functions.
Returns
-------
fnames_boxplots: list
fnames_mapplots: list
lists of filenames for created mapplots and boxplots
"""
# initialise image and plotter
fnames_bplot, fnames_mapplot = [], []
periods = extract_periods(filepath)
for period in periods:
img = QA4SMImg(
filepath,
period=period,
extent=extent,
ignore_empty=True
)
plotter = QA4SMPlotter(
image=img,
out_dir=os.path.join(out_dir, str(period)) if period else out_dir
)
if metrics is None:
metrics = img.metrics
# iterate metrics and create files in output directory
for metric in metrics:
metric_bplots, metric_mapplots = plotter.plot_metric(
metric=metric,
out_types=out_type,
save_all=save_all,
**plotting_kwargs
)
# there can be boxplots with no mapplots
if metric_bplots:
fnames_bplot.extend(metric_bplots)
if metric_mapplots:
fnames_mapplot.extend(metric_mapplots)
return fnames_bplot, fnames_mapplot
def test_metrics(self):
metrics = QA4SMImg(self.testfile_path, metrics=['R'])
assert metrics.common != self.img.common
assert metrics.double != self.img.double
assert 'R' in metrics.double.keys()
def test_extent(self):
extent = QA4SMImg(self.testfile_path,
extent=(113.7, 123.7, -19.8, -9.8))
assert self.img.extent != extent.extent
assert self.img.extent == (113.7, 153.5, -43.1, -9.8)
def setUp(self) -> None:
self.testfile = "0-ERA5.swvl1_with_1-ESA_CCI_SM_combined.sm_with_2-ESA_CCI_SM_combined.sm_with_3-ESA_CCI_SM_combined.sm_with_4-ESA_CCI_SM_combined.sm.CI.nc"
self.testfile_path = os.path.join(os.path.dirname(__file__), '..',
'tests', 'test_data', 'tc',
self.testfile)
self.img = QA4SMImg(self.testfile_path, ignore_empty=False)
def test_load_data(self):
unloaded = QA4SMImg(self.testfile_path, load_data=False)
assert 'varnames' not in unloaded.__dict__.keys()