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Commit d0c8f3ce authored by Felix Kleinert's avatar Felix Kleinert
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update data avail plots and docu

parent 1043377b
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2 merge requests!171Develop intelli o3 ts,!166Resolve "Add additional data plot (histogram)"
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src/plotting/postprocessing_plotting.py
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...@@ -861,45 +861,70 @@ class PlotAvailability(AbstractPlotClass): ...@@ -861,45 +861,70 @@ class PlotAvailability(AbstractPlotClass):
@TimeTrackingWrapper @TimeTrackingWrapper
class PlotAvailabilityHistogram(AbstractPlotClass): class PlotAvailabilityHistogram(AbstractPlotClass):
""" """
Create data availability plots as histogram.
Each entry of each generator is checked for `notnull()` values along all the datetime axis (boolean).
Calling this class creates two different types of histograms where each generator
1) data_availability_histogram: datetime (xaxis) vs. number of stations with availabile data (yaxis)
2) data_availability_histogram_cumulative: number of samples (xaxis) vs. number of stations having at least number
of samples (yaxis)
""" """
def __init__(self, generators: Dict[str, DataGenerator], plot_folder: str = ".", sampling="daily"): def __init__(self, generators: Dict[str, DataGenerator], plot_folder: str = ".", sampling="daily",
subset_dim: str = 'DataSet', temporal_dim: str = 'datetime', history_dim: str = 'window',
station_dim: str = 'Stations'):
super().__init__(plot_folder, "data_availability_histogram") super().__init__(plot_folder, "data_availability_histogram")
self.freq = self._get_sampling(sampling) self.freq = self._get_sampling(sampling)
self.subset_dim = subset_dim
self.temporal_dim = temporal_dim
self.history_dim = history_dim
self.station_dim = station_dim
self._prepare_data(generators) self._prepare_data(generators)
self._plot(plt_type='hist')
self._save() for plt_type in self.allowed_plot_types:
self.plot_name += '_cumulative' plot_name_tmp = self.plot_name
self._plot(plt_type='hist_cum') self.plot_name += '_' + plt_type
self._plot(plt_type=plt_type)
self._save() self._save()
self.plot_name = plot_name_tmp
@property
def allowed_plot_types(self):
plot_types = ['hist', 'hist_cum']
return plot_types
def _prepare_data(self, generators: Dict[str, DataGenerator]): def _prepare_data(self, generators: Dict[str, DataGenerator]):
"""
Prepares data to be used by plot methods.
Creates xarrays which are sums of valid data (boolean sums) across i) station_dim and ii) temporal_dim
"""
avail_data_time_sum = {} avail_data_time_sum = {}
avail_data_station_sum = {} avail_data_station_sum = {}
dataset_time_interval = {} dataset_time_interval = {}
for subset, generator in generators.items(): for subset, generator in generators.items():
avail_list = [] avail_list = []
for station in generator.stations: for station in generator.stations:
station_data_X, _ = generator[station] station_data_x, _ = generator[station]
station_data_X = station_data_X.loc[{'window': 0, # select recent window frame station_data_x = station_data_x.loc[{self.history_dim: 0, # select recent window frame
generator.target_dim: generator.variables[0]}] generator.target_dim: generator.variables[0]}]
avail_list.append(station_data_X.notnull()) avail_list.append(station_data_x.notnull())
avail_data = xr.concat(avail_list, dim='Stations').notnull() avail_data = xr.concat(avail_list, dim=self.station_dim).notnull()
avail_data_time_sum[subset] = avail_data.sum(dim='Stations') avail_data_time_sum[subset] = avail_data.sum(dim=self.station_dim)
avail_data_station_sum[subset] = avail_data.sum(dim='datetime') avail_data_station_sum[subset] = avail_data.sum(dim=self.temporal_dim)
dataset_time_interval[subset] = self._get_first_and_last_indexelement_from_xarray( dataset_time_interval[subset] = self._get_first_and_last_indexelement_from_xarray(
avail_data_time_sum[subset], dim_name='datetime', return_type='as_dict' avail_data_time_sum[subset], dim_name=self.temporal_dim, return_type='as_dict'
) )
avail_data_amount = xr.concat(avail_data_time_sum.values(), pd.Index(avail_data_time_sum.keys(), avail_data_amount = xr.concat(avail_data_time_sum.values(), pd.Index(avail_data_time_sum.keys(),
name='DataSet') name=self.subset_dim)
) )
full_time_index = self._make_full_time_index(avail_data_amount.coords['datetime'].values, freq=self.freq) full_time_index = self._make_full_time_index(avail_data_amount.coords[self.temporal_dim].values, freq=self.freq)
self.avail_data_cum_sum = xr.concat(avail_data_station_sum.values(), pd.Index(avail_data_station_sum.keys(), self.avail_data_cum_sum = xr.concat(avail_data_station_sum.values(), pd.Index(avail_data_station_sum.keys(),
name='DataSet')) name=self.subset_dim))
self.avail_data_amount = avail_data_amount.reindex({'datetime': full_time_index}) self.avail_data_amount = avail_data_amount.reindex({self.temporal_dim: full_time_index})
self.dataset_time_interval = dataset_time_interval self.dataset_time_interval = dataset_time_interval
@staticmethod @staticmethod
...@@ -930,19 +955,19 @@ class PlotAvailabilityHistogram(AbstractPlotClass): ...@@ -930,19 +955,19 @@ class PlotAvailabilityHistogram(AbstractPlotClass):
raise ValueError(f"plt_type mus be 'hist' or 'hist_cum', but is {type}") raise ValueError(f"plt_type mus be 'hist' or 'hist_cum', but is {type}")
def _plot_hist(self, *args): def _plot_hist(self, *args):
# for dataset in
colors = self.get_dataset_colors() colors = self.get_dataset_colors()
fig, axes = plt.subplots(figsize=(10, 3)) fig, axes = plt.subplots(figsize=(10, 3))
for i, subset in enumerate(self.dataset_time_interval.keys()): for i, subset in enumerate(self.dataset_time_interval.keys()):
plot_dataset = self.avail_data_amount.sel({'DataSet': subset, plot_dataset = self.avail_data_amount.sel({self.subset_dim: subset,
'datetime': slice(self.dataset_time_interval[subset]['first'], self.temporal_dim: slice(
self.dataset_time_interval[subset]['first'],
self.dataset_time_interval[subset]['last'] self.dataset_time_interval[subset]['last']
) )
} }
) )
plot_dataset.plot.step(color=colors[subset], ax=axes, label=subset) plot_dataset.plot.step(color=colors[subset], ax=axes, label=subset)
plt.fill_between(plot_dataset.coords['datetime'].values, plot_dataset.values, color=colors[subset]) plt.fill_between(plot_dataset.coords[self.temporal_dim].values, plot_dataset.values, color=colors[subset])
lgd = fig.legend(loc="upper right", ncol=len(self.dataset_time_interval)) lgd = fig.legend(loc="upper right", ncol=len(self.dataset_time_interval))
for lgd_line in lgd.get_lines(): for lgd_line in lgd.get_lines():
...@@ -957,25 +982,28 @@ class PlotAvailabilityHistogram(AbstractPlotClass): ...@@ -957,25 +982,28 @@ class PlotAvailabilityHistogram(AbstractPlotClass):
fig, axes = plt.subplots(figsize=(10, 3)) fig, axes = plt.subplots(figsize=(10, 3))
n_bins = int(self.avail_data_cum_sum.max().values) n_bins = int(self.avail_data_cum_sum.max().values)
bins = np.arange(0, n_bins+1) bins = np.arange(0, n_bins+1)
descending_subsets = self.avail_data_cum_sum.max(dim='Stations').sortby( descending_subsets = self.avail_data_cum_sum.max(dim=self.station_dim).sortby(
self.avail_data_cum_sum.max(dim='Stations'), ascending=False self.avail_data_cum_sum.max(dim=self.station_dim), ascending=False
).coords['DataSet'].values ).coords[self.subset_dim].values
for subset in descending_subsets: for subset in descending_subsets:
self.avail_data_cum_sum.sel({'DataSet': subset}).plot.hist(ax=axes, self.avail_data_cum_sum.sel({self.subset_dim: subset}).plot.hist(ax=axes,
bins=bins, bins=bins,
label=subset, label=subset,
cumulative=-1, cumulative=-1,
color=colors[subset], color=colors[subset],
alpha=.6) # alpha=.5
)
lgd = fig.legend(loc="upper right", ncol=len(self.dataset_time_interval)) lgd = fig.legend(loc="upper right", ncol=len(self.dataset_time_interval),
facecolor='white', framealpha=1, edgecolor='black')
plt.title('') plt.title('')
plt.ylabel('Number of stations') plt.ylabel('Number of stations')
plt.xlabel('Number of samples') plt.xlabel('Number of samples')
plt.xlim((bins[0], bins[-1])) plt.xlim((bins[0], bins[-1]))
plt.tight_layout() plt.tight_layout()
if __name__ == "__main__": if __name__ == "__main__":
stations = ['DEBW107', 'DEBY081', 'DEBW013', 'DEBW076', 'DEBW087'] stations = ['DEBW107', 'DEBY081', 'DEBW013', 'DEBW076', 'DEBW087']
path = "../../testrun_network/forecasts" path = "../../testrun_network/forecasts"
......
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