グラフが表示されない理由がわかりません。

Question

pythonで実行すると文字が出てきてグラフとして表示されません。なぜでしょうか。

Mu1= [0. 0.]
Sigma1= [[2. 0. ]
[0. 0.5]]
Mu2= [5. 0.]
Sigma2= [[ 2.5 -1.5]
[-1.5 2.5]]
Traceback (most recent call last):
File "report7.py", line 181, in <module>
plt.show()
File "/home/g2021048/.local/lib/python3.8/site-packages/matplotlib/pyplot.py", line 378, in show
return _backend_mod.show(*args, **kwargs)
File "/home/g2021048/.local/lib/python3.8/site-packages/matplotlib/backend_bases.py", line 3575, in show
manager.show() # Emits a warning for non-interactive backend.
File "/home/g2021048/.local/lib/python3.8/site-packages/matplotlib/backends/backend_gtk3.py", line 393, in show
self.canvas.draw()
File "/home/g2021048/.local/lib/python3.8/site-packages/matplotlib/backends/backend_gtk3agg.py", line 70, in draw
backend_agg.FigureCanvasAgg.draw(self)
File "/home/g2021048/.local/lib/python3.8/site-packages/matplotlib/backends/backend_agg.py", line 406, in draw
self.figure.draw(self.renderer)
File "/home/g2021048/.local/lib/python3.8/site-packages/matplotlib/artist.py", line 74, in draw_wrapper
result = draw(artist, renderer, *args, **kwargs)
File "/home/g2021048/.local/lib/python3.8/site-packages/matplotlib/artist.py", line 51, in draw_wrapper
return draw(artist, renderer, *args, **kwargs)
File "/home/g2021048/.local/lib/python3.8/site-packages/matplotlib/figure.py", line 2780, in draw
mimage._draw_list_compositing_images(
File "/home/g2021048/.local/lib/python3.8/site-packages/matplotlib/image.py", line 132, in _draw_list_compositing_images
a.draw(renderer)
File "/home/g2021048/.local/lib/python3.8/site-packages/matplotlib/artist.py", line 51, in draw_wrapper
return draw(artist, renderer, *args, **kwargs)
File "/home/g2021048/.local/lib/python3.8/site-packages/matplotlib/_api/deprecation.py", line 431, in wrapper
return func(*inner_args, **inner_kwargs)
File "/home/g2021048/.local/lib/python3.8/site-packages/matplotlib/axes/_base.py", line 2921, in draw
mimage._draw_list_compositing_images(renderer, self, artists)
File "/home/g2021048/.local/lib/python3.8/site-packages/matplotlib/image.py", line 132, in _draw_list_compositing_images
a.draw(renderer)
File "/home/g2021048/.local/lib/python3.8/site-packages/matplotlib/artist.py", line 51, in draw_wrapper
return draw(artist, renderer, *args, **kwargs)
File "/home/g2021048/.local/lib/python3.8/site-packages/matplotlib/collections.py", line 1012, in draw
super().draw(renderer)
File "/home/g2021048/.local/lib/python3.8/site-packages/matplotlib/artist.py", line 51, in draw_wrapper
return draw(artist, renderer, *args, **kwargs)
File "/home/g2021048/.local/lib/python3.8/site-packages/matplotlib/collections.py", line 406, in draw
renderer.draw_markers(
TypeError: must be real number, not str

---

#!/usr/bin/env python3
#coding:utf-8
#
# パターンが2次元連続変数で
# 多変量正規分布(Multivariate Normal Distribution) でモデル化した場合の
# 識別境界面
#
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.tri as tri
import matplotlib.cm as cm
import functools
import scipy.stats as st
import scipy.special as sp
import math
import sys
from mpl_toolkits.axes_grid1 import make_axes_locatable


class Norm2D:
    """
    2変量正規分布 (2 dimensional normal distribution)
    """
    def __init__(self, X):
        self.__X     = np.copy(X)
        self.__Mu    = np.mean(self.__X, axis=0)
        self.__Sigma = np.cov(self.__X, rowvar=False, bias=True)
        self.__dim   = len(self.__Mu)
        self.__N     = len(self.__X)

    def get_N(self):
        """ 学習データ数の取得 """
        return self.__N

    def get_X(self):
        """ 学習データの取得 """
        return self.__X

    def get_param(self):
        """ 正規分布パラメタの取得 """
        return self.__Mu, self.__Sigma

    def pdf(self, x):
        """ 与えられた分布の(x)における確率密度値を求める"""
        return st.multivariate_normal.pdf(x, mean=self.__Mu, cov=self.__Sigma)

    def sampling(self, N):
        """ 与えられた分布に従ってN点サンプリングする"""
        return st.multivariate_normal.rvs(mean=self.__Mu, cov=self.__Sigma, size=N)

    def this_likelihood(self, x):
        """ パターンxが与えられた時の与えられた分布での尤度を求める """
        L = 1.0
        for n in range(len(x)):
            L *= self.pdf(x[n])
        return L

    def this_log_likelihood(self, x):
        """ パターンxが与えられた時の与えられた分布での対数尤度を求める """
        logL = 0.0
        for n in range(len(x)):
            logL += log(self.pdf(x[n]))
        return logL


# 例題2
# x(ω1) = {(0, 4√2), (4, 4√2), (2, 4√2-1), (2, 4√2+1)}
# x(ω2) = {(0, 0), (4, 0), (2, -1), (2, 1), (2(1-√3), 0), (2(1+√3), 0), (2, -√3), (2, √3)}
"""
x1 = np.array([[0.0, 4.0*np.sqrt(2.0)],
               [4.0, 4.0*np.sqrt(2.0)],
               [2.0, 4.0*np.sqrt(2.0)-1.0],
               [2.0, 4.0*np.sqrt(2.0)+1.0]])
x2 = np.array([[0.0, 0.0],
               [4.0, 0.0],
               [2.0,-1.0],
               [2.0, 1.0],
               [2.0*(1.0-np.sqrt(3.0)), 0],
               [2.0*(1.0+np.sqrt(3.0)), 0],
               [2.0,-np.sqrt(3.0)],
               [2.0, np.sqrt(3.0)]])
# Set the drow range
x = y = np.arange(-2, 18, 0.1)
"""

#
# 例題3
# x(ω1) = {(-2, 0), (0, 1), (0, -1), (2, 0)}
# x(ω2) = {(3, 2), (4, -1), (6, 1), (7, -2)}
x1 = np.array([[-2.0, 0.0],
               [0.0, 1.0],
               [0.0,-1.0],
               [2.0, 0.0]])
x2 = np.array([[3.0, 2.0],
               [4.0,-1.0],
               [6.0, 1.0],
               [7.0,-2.0]])
# Set the drow range
x = y = np.arange(-5, 10, 0.1)

#
# Create Distributions
#
dist1 = Norm2D(x1)
dist2 = Norm2D(x2)

#
# Show Mu and Sigma
#
Mu1, Sigma1 = dist1.get_param()
print('Mu1=', Mu1);
print('Sigma1=', Sigma1)

Mu2, Sigma2 = dist2.get_param()
print('Mu2=', Mu2)
print('Sigma2=', Sigma2)


#
# Create the drawing mesh
#
X, Y = np.meshgrid(x, y)
pos = np.dstack((X,Y))

#
# Calc. pdf
#
Z1 = dist1.pdf(pos)
Z2 = dist2.pdf(pos)

Z = np.log(np.fmax(Z1, Z2))    # Logarithmic expression
Zdiff = Z1 - Z2

maxZ = np.max(Z)
minZ = np.min(Z)
#print('max Z=', maxZ)
#print('min Z=', minZ)

minZ = -20    # Clip the lowest Z value


#
# Init. a graph
#
fig = plt.figure(figsize=(7,5))

ax = fig.add_subplot(111, aspect='equal')
ax.grid()
plt.xlabel('x')
plt.ylabel('y')


#
# draw the contour
#
levels = np.linspace(minZ, maxZ, 50)
cs = ax.contourf(X, Y, Z, levels=levels, cmap=cm.inferno, extend='both')

#
# draw the boundary
#
ax.contour(X, Y, Zdiff, levels=[-1.0e-300, 1.0e-300], colors='r', linestyles='-')

#
# data
#
ax.scatter(dist1.get_X()[:,0], dist1.get_X()[:,1], s=40, c='red',  marker='o', alpha=0.5, linewidths='2')
ax.scatter(dist2.get_X()[:,0], dist2.get_X()[:,1], s=40, c='blue', marker='o', alpha=0.5, linewidths='2')

#
# draw a colorbar
#
divider = make_axes_locatable(ax)                       # create the same size divider as the contour graph
cax = divider.append_axes('right', size='5%', pad=0.1)  # append 5% space to the right-end
fig.colorbar(cs, cax=cax, format='%.1f')                # show a colorbar

#
# Draw
#
plt.show()

Comments

[ppaul]

report7.pyにバグがあるからです。原因を質問したいならreport7.pyのコードを質問に追加しましょう。

[valley]

ソースコード追加しました。よろしくおねがいします。

[jbpb0]

pythonのコードの一番最初の行のすぐ上に
```python
だけの行を追加してください
また、pythonのコードの一番最後の行のすぐ下に
```
だけの行を追加してください

現状、コードがとても読み辛いです
質問にコードを載せる際に上記をやってくれたら、他人がコードを読みやすくなり、コードの実行による現象確認もやりやすくなるので、回答されやすくなります

[valley]

すみません、、ありがとうございます。改善しました。

[can110]

以下を参考に修正ください。
https://teratail.storage.googleapis.com/uploads/contributed_images/56957fe805d9d7befa7dba6a98676d2b.gif

Answer 1

TypeError: must be real number, not str

ax.scatter(...linewidths='2')

↓ 修正 (二ヶ所)

ax.scatter(...linewidths=2)