pandas 我应该如何通过函数传递 matplotlib 对象；作为轴，轴或图形？
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How should I pass a matplotlib object through a function; as Axis, Axes or Figure?
提问by Keith
Sorry in advance if this is a little long winded but if I cut it down too much the problem is lost. I am trying to make a module on top of pandas and matplotlib which will give me the ability to make profile plots and profile matrices analogous to scatter_matrix. I am pretty sure my problem comes down to what object I need to return from Profile() so that I can handle Axes manipulation in Profile_Matrix(). Then the question is what to return form Profile_Matrix() so I can edit subplots.
如果这有点冗长，请提前抱歉，但如果我将其削减太多，问题就会丢失。我正在尝试在 pandas 和 matplotlib 之上制作一个模块，这将使我能够制作类似于 scatter_matrix 的剖面图和剖面矩阵。我很确定我的问题归结为我需要从 Profile() 返回什么对象，以便我可以在 Profile_Matrix() 中处理 Axes 操作。那么问题是从 Profile_Matrix() 返回什么，以便我可以编辑子图。
My module (ProfileModule.py) borrows a lot from https://github.com/pydata/pandas/blob/master/pandas/tools/plotting.pyand looks like:
我的模块 (ProfileModule.py) 从https://github.com/pydata/pandas/blob/master/pandas/tools/plotting.py借用了很多，看起来像：
import pandas as pd
from pandas import Series, DataFrame
import numpy as np
import matplotlib.pyplot as plt
def Profile(x,y,nbins,xmin,xmax):
df = DataFrame({'x' : x , 'y' : y})
binedges = xmin + ((xmax-xmin)/nbins) * np.arange(nbins+1)
df['bin'] = np.digitize(df['x'],binedges)
bincenters = xmin + ((xmax-xmin)/nbins)*np.arange(nbins) + ((xmax-xmin)/(2*nbins))
ProfileFrame = DataFrame({'bincenters' : bincenters, 'N' : df['bin'].value_counts(sort=False)},index=range(1,nbins+1))
bins = ProfileFrame.index.values
for bin in bins:
ProfileFrame.ix[bin,'ymean'] = df.ix[df['bin']==bin,'y'].mean()
ProfileFrame.ix[bin,'yStandDev'] = df.ix[df['bin']==bin,'y'].std()
ProfileFrame.ix[bin,'yMeanError'] = ProfileFrame.ix[bin,'yStandDev'] / np.sqrt(ProfileFrame.ix[bin,'N'])
fig = plt.figure();
ax = ProfilePlot.add_subplot(1, 1, 1)
plt.errorbar(ProfileFrame['bincenters'], ProfileFrame['ymean'], yerr=ProfileFrame['yMeanError'], xerr=(xmax-xmin)/(2*nbins), fmt=None)
return ax
#or should I "return fig"
def Profile_Matrix(frame):
import pandas.core.common as com
import pandas.tools.plotting as plots
from pandas.compat import lrange
from matplotlib.artist import setp
range_padding=0.05
df = frame._get_numeric_data()
n = df.columns.size
fig, axes = plots._subplots(nrows=n, ncols=n, squeeze=False)
# no gaps between subplots
fig.subplots_adjust(wspace=0, hspace=0)
mask = com.notnull(df)
boundaries_list = []
for a in df.columns:
values = df[a].values[mask[a].values]
rmin_, rmax_ = np.min(values), np.max(values)
rdelta_ext = (rmax_ - rmin_) * range_padding / 2.
boundaries_list.append((rmin_ - rdelta_ext, rmax_+ rdelta_ext))
for i, a in zip(lrange(n), df.columns):
for j, b in zip(lrange(n), df.columns):
ax = axes[i, j]
common = (mask[a] & mask[b]).values
nbins = 100
(xmin,xmax) = boundaries_list[i]
ax=Profile(df[b][common],df[a][common],nbins,xmin,xmax)
#Profile(df[b][common].values,df[a][common].values,nbins,xmin,xmax)
ax.set_xlabel('')
ax.set_ylabel('')
plots._label_axis(ax, kind='x', label=b, position='bottom', rotate=True)
plots._label_axis(ax, kind='y', label=a, position='left')
if j!= 0:
ax.yaxis.set_visible(False)
if i != n-1:
ax.xaxis.set_visible(False)
for ax in axes.flat:
setp(ax.get_xticklabels(), fontsize=8)
setp(ax.get_yticklabels(), fontsize=8)
return axes
This will run with something like:
这将运行如下：
import pandas as pd
from pandas import Series, DataFrame
import numpy as np
import matplotlib.pyplot as plt
import ProfileModule as pm
x = np.random.uniform(0, 100, size=1000)
y = x *x + 50*x*np.random.randn(1000)
z = x *y + 50*y*np.random.randn(1000)
nbins = 25
xmax = 100
xmin = 0
ProfilePlot = pm.Profile(x,y,nbins,xmin,xmax)
plt.title("Look this works!")
#This does not work as expected
frame = DataFrame({'z' : z,'x' : x , 'y' : y})
ProfileMatrix = pm.Profile_Matrix(frame)
plt.show()
This would hopefully produce a simple profile plot and a 3x3 profile matrix but it does not. I have tried various different methods to get this to work but I imagine it is not worth explaining them all.
这有望产生一个简单的剖面图和一个 3x3 剖面矩阵，但它没有。我尝试了各种不同的方法来让它发挥作用，但我认为不值得一一解释。
I should mention I am using Enthought Canopy Express on Windows 7. Sorry for the long post and thanks again for any help with the code. This is my first week using Python.
我应该提到我在 Windows 7 上使用 Enthought Canopy Express。抱歉这篇长文章，再次感谢您对代码的任何帮助。这是我使用 Python 的第一周。
回答by tacaswell
You should pass around Axesobjects and break your functions up to operate on a single axes at a time. You are close, but just change
您应该传递Axes对象并将您的功能分解为一次在单个轴上操作。你很接近，但只是改变
import numpy as np
import matplotlib.pyplot as plt
def _profile(ax, x, y):
ln, = ax.plot(x, y)
# return the Artist created
return ln
def profile_matrix(n, m):
fig, ax_array = plt.subplots(n, m, sharex=True, sharey=True)
for ax in np.ravel(ax_array):
_profile(ax, np.arange(50), np.random.rand(50))
profile_matrix(3, 3)
