本文整理汇总了Python中seaborn.light_palette方法的典型用法代码示例。如果您正苦于以下问题：Python seaborn.light_palette方法的具体用法？Python seaborn.light_palette怎么用？Python seaborn.light_palette使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类seaborn的用法示例。
在下文中一共展示了seaborn.light_palette方法的3个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: __init__
# 需要导入模块: import seaborn [as 别名]
# 或者: from seaborn import light_palette [as 别名]
def __init__(self,
observation_space,
substation_layout=None,
radius_sub=25.,
load_prod_dist=70.,
bus_radius=4.):
"""
Parameters
----------
substation_layout: ``list``
List of tupe given the position of each of the substation of the powergrid.
observation_space: :class:`grid2op.Observation.ObservationSpace`
BaseObservation space
"""
BasePlot.__init__(self,
substation_layout=substation_layout,
observation_space=observation_space,
radius_sub=radius_sub,
load_prod_dist=load_prod_dist,
bus_radius=bus_radius)
if not can_plot:
raise PlotError("Impossible to plot as plotly cannot be imported. Please install \"plotly\" and "
"\"seaborn\" with \"pip install --update plotly seaborn\"")
# define a color palette, whatever...
sns.set()
pal = sns.light_palette("darkred", 8)
self.cols = pal.as_hex()[1:]
self.col_line = "royalblue"
self.col_sub = "red"
self.col_load = "black"
self.col_gen = "darkgreen"
self.default_color = "black"
self.type_fig_allowed = go.Figure 示例2: colors
# 需要导入模块: import seaborn [as 别名]
# 或者: from seaborn import light_palette [as 别名]
def colors():
if Driver.Colors is None or len(Driver.Colors) != Driver.MaxSourceSupport:
cp = sns.light_palette("darkred", n_colors=Driver.MaxSourceSupport+1)
# for r, g, b, _ in cp:
# cs.append("#{0:02x}{1:02x}{2:02x}".format(clamp(r), clamp(g), clamp(b)))
Driver.Colors = cp
return Driver.Colors 示例3: _plot_kde
# 需要导入模块: import seaborn [as 别名]
# 或者: from seaborn import light_palette [as 别名]
def _plot_kde(output_res, pick_rows, color_palette, alpha=0.5):
num_clusters = len(set(pick_rows))
for ci in range(num_clusters):
cur_plot_rows = pick_rows == ci
cur_cmap = sns.light_palette(color_palette[ci], as_cmap=True)
sns.kdeplot(output_res[cur_plot_rows, 0], output_res[cur_plot_rows, 1], cmap=cur_cmap, shade=True, alpha=alpha,
shade_lowest=False)
centroid = output_res[cur_plot_rows, :].mean(axis=0)
plt.annotate('%s' % ci, xy=centroid, xycoords='data', alpha=0.5,
horizontalalignment='center', verticalalignment='center')