diff --git a/mlair/plotting/data_insight_plotting.py b/mlair/plotting/data_insight_plotting.py index 8e6328e96492b8b6e0fc51d2ac4bd87156551bd2..6180493741c030d5dfdfcfa8972035619632c8aa 100644 --- a/mlair/plotting/data_insight_plotting.py +++ b/mlair/plotting/data_insight_plotting.py @@ -967,14 +967,11 @@ class PlotClimateFirFilter(AbstractPlotClass): def _plot(self, plot_dict, sampling, new_dim="window"): td_type = {"1d": "D", "1H": "h"}.get(sampling) for var, viz_date_dict in plot_dict.items(): - print(var) # TODO remove for it0, t0 in enumerate(viz_date_dict.keys()): - print(it0) # TODO remove viz_data = viz_date_dict[t0] residuum_true = None try: for ifilter in sorted(viz_data.keys()): - print(ifilter) # TODO remove data = viz_data[ifilter] filter_input = data["filter_input"] filter_input_nc = data["filter_input_nc"] if residuum_true is None else residuum_true.sel( @@ -986,26 +983,20 @@ class PlotClimateFirFilter(AbstractPlotClass): fig, ax = plt.subplots() # plot backgrounds - print("plot_valid_area") # TODO remove self._plot_valid_area(ax, t0, valid_range, td_type) - print("plot_t0") # TODO remove self._plot_t0(ax, t0) # original data - print("plot_original_data") # TODO remove self._plot_original_data(ax, time_axis, filter_input_nc) # clim apriori - print("plot_apriori") # TODO remove self._plot_apriori(ax, time_axis, filter_input, new_dim, ifilter) # clim filter response - print("plot_clim_filter") # TODO remove residuum_estimated = self._plot_clim_filter(ax, time_axis, filter_input, new_dim, h, output_dtypes=filter_input.dtype) # ideal filter response - print("plot_ideal_filter") # TODO remove residuum_true = self._plot_ideal_filter(ax, time_axis, filter_input_nc, new_dim, h, output_dtypes=filter_input.dtype)