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schlunmavaleriupredoi
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valeriupredoi
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Added option to plot horizontal lines in monitoring line plots (#3977)
Co-authored-by: Valeriu Predoi <[email protected]>
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‎esmvaltool/diag_scripts/monitor/multi_datasets.py‎

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@@ -161,6 +161,11 @@
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Optional keyword arguments for grid lines. By default, ``color: lightgrey,
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alpha: 0.5`` are used. Use ``gridline_kwargs: false`` to not show grid
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lines.
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hlines: list of dict, optional
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Horizontal lines to show in plot. Each list element corresponds to one
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line, and each list element should contain a dictionary with keywords
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arguments passed to :meth:`matplotlib.axes.Axes.axhline`. Example: ``[{y:
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0}, {y: 1, color: 'red'}]``.
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legend_kwargs: dict, optional
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Optional keyword arguments for :func:`matplotlib.pyplot.legend`. Use
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``legend_kwargs: false`` to not show legends.
@@ -194,6 +199,11 @@
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Optional keyword arguments for grid lines. By default, ``color: lightgrey,
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alpha: 0.5`` are used. Use ``gridline_kwargs: false`` to not show grid
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lines.
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hlines: list of dict, optional
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Horizontal lines to show in plot. Each list element corresponds to one
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line, and each list element should contain a dictionary with keywords
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arguments passed to :meth:`matplotlib.axes.Axes.axhline`. Example: ``[{y:
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0}, {y: 1, color: 'red'}]``.
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legend_kwargs: dict, optional
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Optional keyword arguments for :func:`matplotlib.pyplot.legend`. Use
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``legend_kwargs: false`` to not show legends.
@@ -403,6 +413,11 @@
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Optional keyword arguments for grid lines. By default, ``color: lightgrey,
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alpha: 0.5`` are used. Use ``gridline_kwargs: false`` to not show grid
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lines.
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hlines: list of dict, optional
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Horizontal lines to show in plot. Each list element corresponds to one
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line, and each list element should contain a dictionary with keywords
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arguments passed to :meth:`matplotlib.axes.Axes.axhline`. Example: ``[{y:
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0}, {y: 1, color: 'red'}]``.
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legend_kwargs: dict, optional
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Optional keyword arguments for :func:`matplotlib.pyplot.legend`. Use
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``legend_kwargs: false`` to not show legends.
@@ -440,6 +455,11 @@
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Optional keyword arguments for grid lines. By default, ``color: lightgrey,
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alpha: 0.5`` are used. Use ``gridline_kwargs: false`` to not show grid
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lines.
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hlines: list of dict, optional
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Horizontal lines to show in plot. Each list element corresponds to one
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line, and each list element should contain a dictionary with keywords
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arguments passed to :meth:`matplotlib.axes.Axes.axhline`. Example: ``[{y:
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0}, {y: 1, color: 'red'}]``.
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legend_kwargs: dict, optional
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Optional keyword arguments for :func:`matplotlib.pyplot.legend`. Use
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``legend_kwargs: false`` to not show legends.
@@ -922,6 +942,7 @@ def __init__(self, config):
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if plot_type == "timeseries":
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self.plots[plot_type].setdefault("annual_mean_kwargs", {})
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self.plots[plot_type].setdefault("gridline_kwargs", {})
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self.plots[plot_type].setdefault("hlines", [])
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self.plots[plot_type].setdefault("legend_kwargs", {})
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self.plots[plot_type].setdefault("plot_kwargs", {})
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self.plots[plot_type].setdefault("pyplot_kwargs", {})
@@ -930,31 +951,36 @@ def __init__(self, config):
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elif plot_type == "benchmarking_timeseries":
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self.plots[plot_type].setdefault("annual_mean_kwargs", {})
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self.plots[plot_type].setdefault("gridline_kwargs", {})
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self.plots[plot_type].setdefault("hlines", [])
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self.plots[plot_type].setdefault("legend_kwargs", {})
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self.plots[plot_type].setdefault("plot_kwargs", {})
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self.plots[plot_type].setdefault("pyplot_kwargs", {})
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self.plots[plot_type].setdefault("time_format", None)
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elif plot_type == "annual_cycle":
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self.plots[plot_type].setdefault("gridline_kwargs", {})
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self.plots[plot_type].setdefault("hlines", [])
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self.plots[plot_type].setdefault("legend_kwargs", {})
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self.plots[plot_type].setdefault("plot_kwargs", {})
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self.plots[plot_type].setdefault("pyplot_kwargs", {})
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elif plot_type == "benchmarking_annual_cycle":
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self.plots[plot_type].setdefault("gridline_kwargs", {})
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self.plots[plot_type].setdefault("hlines", [])
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self.plots[plot_type].setdefault("legend_kwargs", {})
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self.plots[plot_type].setdefault("plot_kwargs", {})
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self.plots[plot_type].setdefault("pyplot_kwargs", {})
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elif plot_type == "diurnal_cycle":
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self.plots[plot_type].setdefault("gridline_kwargs", {})
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self.plots[plot_type].setdefault("hlines", [])
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self.plots[plot_type].setdefault("legend_kwargs", {})
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self.plots[plot_type].setdefault("plot_kwargs", {})
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self.plots[plot_type].setdefault("pyplot_kwargs", {})
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elif plot_type == "benchmarking_diurnal_cycle":
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self.plots[plot_type].setdefault("gridline_kwargs", {})
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self.plots[plot_type].setdefault("hlines", [])
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self.plots[plot_type].setdefault("legend_kwargs", {})
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self.plots[plot_type].setdefault("plot_kwargs", {})
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self.plots[plot_type].setdefault("pyplot_kwargs", {})
@@ -1073,6 +1099,7 @@ def __init__(self, config):
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elif plot_type == "1d_profile":
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self.plots[plot_type].setdefault("aspect_ratio", 1.5)
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self.plots[plot_type].setdefault("gridline_kwargs", {})
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self.plots[plot_type].setdefault("hlines", [])
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self.plots[plot_type].setdefault("legend_kwargs", {})
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self.plots[plot_type].setdefault("log_x", False)
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self.plots[plot_type].setdefault("log_y", True)
@@ -1084,6 +1111,7 @@ def __init__(self, config):
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elif plot_type == "variable_vs_lat":
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self.plots[plot_type].setdefault("gridline_kwargs", {})
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self.plots[plot_type].setdefault("hlines", [])
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self.plots[plot_type].setdefault("legend_kwargs", {})
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self.plots[plot_type].setdefault("plot_kwargs", {})
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self.plots[plot_type].setdefault("pyplot_kwargs", {})
@@ -2841,6 +2869,10 @@ def create_timeseries_plot(self, datasets):
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plot_kwargs.update(annual_mean_kwargs)
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iris.plot.plot(annual_mean_cube, **plot_kwargs)
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# Plot horizontal lines
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for hline_kwargs in self.plots[plot_type]["hlines"]:
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axes.axhline(**hline_kwargs)
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# Default plot appearance
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multi_dataset_facets = self._get_multi_dataset_facets(datasets)
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axes.set_title(multi_dataset_facets["long_name"])
@@ -2953,6 +2985,10 @@ def create_benchmarking_timeseries(self, datasets):
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alpha=0.8,
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)
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# Plot horizontal lines
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for hline_kwargs in self.plots[plot_type]["hlines"]:
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axes.axhline(**hline_kwargs)
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# Default plot appearance
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multi_dataset_facets = self._get_multi_dataset_facets(datasets)
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axes.set_title(multi_dataset_facets["long_name"])
@@ -3035,6 +3071,10 @@ def create_annual_cycle_plot(self, datasets):
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plot_kwargs["axes"] = axes
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iris.plot.plot(cube, **plot_kwargs)
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# Plot horizontal lines
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for hline_kwargs in self.plots[plot_type]["hlines"]:
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axes.axhline(**hline_kwargs)
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# Default plot appearance
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multi_dataset_facets = self._get_multi_dataset_facets(datasets)
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axes.set_title(multi_dataset_facets["long_name"])
@@ -3134,6 +3174,10 @@ def create_benchmarking_annual(self, datasets):
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alpha=0.8,
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)
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# Plot horizontal lines
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for hline_kwargs in self.plots[plot_type]["hlines"]:
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axes.axhline(**hline_kwargs)
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# Default plot appearance
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multi_dataset_facets = self._get_multi_dataset_facets(datasets)
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axes.set_title(multi_dataset_facets["long_name"])
@@ -3213,6 +3257,10 @@ def create_diurnal_cycle_plot(self, datasets):
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plot_kwargs["axes"] = axes
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iris.plot.plot(cube, **plot_kwargs)
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# Plot horizontal lines
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for hline_kwargs in self.plots[plot_type]["hlines"]:
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axes.axhline(**hline_kwargs)
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# Default plot appearance
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multi_dataset_facets = self._get_multi_dataset_facets(datasets)
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axes.set_title(multi_dataset_facets["long_name"])
@@ -3313,6 +3361,10 @@ def create_benchmarking_diurnal(self, datasets):
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alpha=0.8,
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)
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# Plot horizontal lines
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for hline_kwargs in self.plots[plot_type]["hlines"]:
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axes.axhline(**hline_kwargs)
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# Default plot appearance
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multi_dataset_facets = self._get_multi_dataset_facets(datasets)
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axes.set_title(multi_dataset_facets["long_name"])
@@ -3776,6 +3828,10 @@ def create_1d_profile_plot(self, datasets):
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iris.plot.plot(cube, **plot_kwargs)
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# Plot horizontal lines
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for hline_kwargs in self.plots[plot_type]["hlines"]:
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axes.axhline(**hline_kwargs)
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# Default plot appearance
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axes.set_title(multi_dataset_facets["long_name"])
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axes.set_xlabel(
@@ -3876,6 +3932,10 @@ def create_variable_vs_lat_plot(self, datasets):
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plot_kwargs["axes"] = axes
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iris.plot.plot(cube, **plot_kwargs)
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# Plot horizontal lines
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for hline_kwargs in self.plots[plot_type]["hlines"]:
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axes.axhline(**hline_kwargs)
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# Default plot appearance
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multi_dataset_facets = self._get_multi_dataset_facets(datasets)
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axes.set_title(multi_dataset_facets["long_name"])

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