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Resolve "release v1.4.0"

Merged Ghost User requested to merge release_v1.4.0 into master
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@@ -762,8 +762,7 @@ class PlotCompetitiveSkillScore(AbstractPlotClass):
showmeans=True, meanprops={"markersize": 3, "markeredgecolor": "k"}, flierprops={"marker": "."},
order=order)
ax.axhline(y=0, color="grey", linewidth=.5)
ax.set(ylabel="skill score", xlabel="competing models", title="summary of all stations", ylim=self._lim())
ax.set(ylabel="skill score", xlabel="competing models", title="summary of all stations", ylim=self._lim(data))
handles, _ = ax.get_legend_handles_labels()
plt.xticks(rotation=90)
ax.legend(handles, self._labels)
@@ -777,9 +776,8 @@ class PlotCompetitiveSkillScore(AbstractPlotClass):
sns.boxplot(y="comparison", x="data", hue="ahead", data=data, whis=1., ax=ax, palette="Blues_d",
showmeans=True, meanprops={"markersize": 3, "markeredgecolor": "k"}, flierprops={"marker": "."},
order=order)
# ax.axhline(x=0, color="grey", linewidth=.5)
ax.axvline(x=0, color="grey", linewidth=.5)
ax.set(xlabel="skill score", ylabel="competing models", title="summary of all stations", xlim=self._lim())
ax.set(xlabel="skill score", ylabel="competing models", title="summary of all stations", xlim=self._lim(data))
handles, _ = ax.get_legend_handles_labels()
ax.legend(handles, self._labels)
plt.tight_layout()
@@ -795,7 +793,8 @@ class PlotCompetitiveSkillScore(AbstractPlotClass):
filtered_headers = list(filter(lambda x: "nn-" in x, data.comparison.unique()))
return data[data.comparison.isin(filtered_headers)]
def _lim(self) -> Tuple[float, float]:
@staticmethod
def _lim(data) -> Tuple[float, float]:
"""
Calculate axis limits from data (Can be used to set axis extend).
@@ -805,8 +804,8 @@ class PlotCompetitiveSkillScore(AbstractPlotClass):
:return:
"""
limit = 5
lower = np.max([-limit, np.min([0, helpers.float_round(self._data.min()[2], 2) - 0.1])])
upper = np.min([limit, helpers.float_round(self._data.max()[2], 2) + 0.1])
lower = np.max([-limit, np.min([0, helpers.float_round(data.min()[2], 2) - 0.1])])
upper = np.min([limit, helpers.float_round(data.max()[2], 2) + 0.1])
return lower, upper
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