我有一个包含10个略有重叠的图形的Seaborn FacetGrid图表。 我想改变整个图形的大小。 当我在下面的代码中使用g.fig.subplots(figsize =(12,12))时,我会收到错误消息“TypeError:subplots()得到了一个意外的关键字参数'size'”。
此外,我会收到一个警告:“UserWarning:未应用紧凑布局。tight_layout无法使轴高度足够小以容纳所有轴装饰self.fig.tight_layout()”
我没有在代码中看到任何地方引用tight_layout()。 它嵌入在模块中:C:\Anaconda3\lib\site-packages\seaborn\axisgrid.py:848。 我不想在网站包模块中混乱。 我该如何调整参数,以便不会收到此警告。
我想解决问题,而不仅仅是抑制此警告。 我对Seaborn和Matplotlib的内部不够了解,无法修复此错误并消除警告。
我尝试添加g.fig.subplots(figsize =(12,12))来更改图形大小。 显然,FacetGrid绘图不包含在一个图中,或者我错误地引用了图边界框对象。
此外,我会收到一个警告:“UserWarning:未应用紧凑布局。tight_layout无法使轴高度足够小以容纳所有轴装饰self.fig.tight_layout()”
我没有在代码中看到任何地方引用tight_layout()。 它嵌入在模块中:C:\Anaconda3\lib\site-packages\seaborn\axisgrid.py:848。 我不想在网站包模块中混乱。 我该如何调整参数,以便不会收到此警告。
我想解决问题,而不仅仅是抑制此警告。 我对Seaborn和Matplotlib的内部不够了解,无法修复此错误并消除警告。
我尝试添加g.fig.subplots(figsize =(12,12))来更改图形大小。 显然,FacetGrid绘图不包含在一个图中,或者我错误地引用了图边界框对象。
"""
FacetGrid Plot Showing Overlapping Distributions (Densities) Offset by ('ridge plot')
====================================
"""
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
sns.set(style="white", rc={"axes.facecolor": (0, 0, 0, 0)})
# Create some random distribution data and labels, and store them in a dataframe
rs = np.random.RandomState(1979)
x = rs.randn(500)
g = np.tile(list("ABCDEFGHIJ"), 50)
df = pd.DataFrame(dict(x=x, g=g))
m = df.g.map(ord)
df["x"] += m
# Initialize the FacetGrid chart object
pal = sns.cubehelix_palette(10, rot=-.25, light=.7)
g = sns.FacetGrid(df, row="g", hue="g", aspect=15, height=.5, palette=pal)
# Draw the densities in a few steps
g.map(sns.kdeplot, "x", clip_on=False, shade=True, alpha=1, lw=1.5, bw=.2)
g.map(sns.kdeplot, "x", clip_on=False, color="w", lw=2, bw=.2)
g.map(plt.axhline, y=0, lw=2, clip_on=False)
# Define and use a simple function to label the plot in axes coordinates
def label(x, color, label):
ax = plt.gca()
ax.text(0, .2, label, fontweight="bold", color=color,
ha="left", va="center", transform=ax.transAxes)
# Use ``map()`` to calculate the label positions
g.map(label, "x")
# Set the subplots to overlap slightly on their vertical direction
g.fig.subplots_adjust(hspace=-.3)
# Remove axes details that don't play well with overlap
g.set_titles("")
g.set(yticks=[])
g.despine(bottom=True, left=True)
g.fig.subplots(figsize=(12,12)) # Don't know how to change figure size for a set of overlapping Seaborn plots
我得到了以下警告,随后是错误消息,然后FacetedGrid图表显示而未改变其大小。
警告信息:Original Answer
错误信息:请检查您的代码并确保正确使用了大小参数。
self.fig.tight_layout()
C:\Anaconda3\lib\site-packages\seaborn\axisgrid.py:848: UserWarning: Tight layout not applied. tight_layout cannot make axes height small enough to accommodate all axes decorations
self.fig.tight_layout()
C:\Anaconda3\lib\site-packages\seaborn\axisgrid.py:848: UserWarning: Tight layout not applied. tight_layout cannot make axes height small enough to accommodate all axes decorations
self.fig.tight_layout()
<ipython-input-25-a661dbef6e83> in <module>
43 g.set(yticks=[])
44 g.despine(bottom=True, left=True)
---> 45 g.fig.subplots(size=(12,12)) # Don't know how to change figure size for a set of overlapping Seaborn plots
TypeError: subplots() got an unexpected keyword argument 'size'
将所有评论整合后,以下是一个优秀的、紧凑的情节源代码,没有警告或错误:
最初的回答:
`# -*- coding: utf-8 -*-
""" Created on Mon Jun 24 12:21:40 2019 @author: rlysak01
FacetGrid Plot Showing Overlapping Distributions (Densities) Offset by ('ridge plot')
"""
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
sns.set(style="white", rc={"axes.facecolor": (0, 0, 0, 0)})
# Create some random distribution data and labels, and store them in a dataframe
rs = np.random.RandomState(1979)
x = rs.randn(500)
g = np.tile(list("ABCDEFGHIJ"), 50)
df = pd.DataFrame(dict(x=x, g=g))
m = df.g.map(ord)
df["x"] += m
# Initialize the FacetGrid chart object
pal = sns.cubehelix_palette(10, rot=-.25, light=.7)
# g = sns.FacetGrid(df, row="g", hue="g", aspect=6, height=1.0, palette=pal)
g = sns.FacetGrid(df, row="g", hue="g", palette=pal)
''' Alternatively set figsize using the following 2 parameters.'''
g.fig.set_figheight(5.5)
g.fig.set_figwidth(7)
# or use plt.gcf().set_size_inches(12, 12)
# Draw the densities in a few steps
g.map(sns.kdeplot, "x", clip_on=False, shade=True, alpha=1, lw=1.5, bw=.2)
g.map(sns.kdeplot, "x", clip_on=False, color="w", lw=2, bw=.2)
g.map(plt.axhline, y=0, lw=2, clip_on=False)
# Define and use a simple function to label the plot in axes coordinates
# Values x,y in ax.text(x,y, ...) controls the x,y offset from the x axis.
def label(x, color, label):
ax = plt.gca()
ax.text(0, .2, label, fontweight="bold", color=color,
ha="left", va="center", transform=ax.transAxes)
# Use ``map()`` to calculate the label positions
g.map(label, "x")
# Set the subplots to overlap slightly on their vertical direction
g.fig.subplots_adjust(hspace=-0.5)
# Remove axes details that don't play well with overlap
g.set_titles("")
g.set(yticks=[])
g.despine(bottom=True, left=True)
`