我在Python3中使用numpy和matplotlib 以下代码导致错误:
import matplotlib
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
from matplotlib.figure import Figure
from matplotlib.axes import Subplot as plt
from matplotlib import pylab
a=[1,1]
b=[1,1]
fsam = 48000
w, h = freqz(b, a, worN=2000)
plt.plot(((fsam-8000) * 0.5 / np.pi) * w, abs(h), label=" ")
matplotlib 1.3.x的实际错误:
File "/usr/local/lib/python3.2/dist-packages/matplotlib-1.3.x-py3.2-linux-x86_64.egg/matplotlib/axes.py", line 4119, in plot
if not self._hold:
AttributeError: 'numpy.ndarray' object has no attribute '_hold'
matplotlib 1.2.0的实际错误:
Traceback (most recent call last):
File "/home/christoph/audio_measurement/AudioTools/AudioTools.py", line 222, in <module>
main()
File "/home/christoph/audio_measurement/AudioTools/AudioTools.py", line 216, in main
form = AppForm()
File "/home/christoph/audio_measurement/AudioTools/AudioTools.py", line 39, in __init__
self.on_draw()
File "/home/christoph/audio_measurement/AudioTools/AudioTools.py", line 80, in on_draw
self.transfer = Transfer(self.canvas)
File "/home/christoph/audio_measurement/AudioTools/Transfer.py", line 42, in __init__
plt.plot(((fsam-8000) * 0.5 / np.pi) * w, abs(h), label=" ")
File "/usr/local/lib/python3.2/dist-packages/matplotlib/axes.py", line 3995, in plot
if not self._hold: self.cla()
AttributeError: 'numpy.ndarray' object has no attribute '_hold'
转移是一个类,它绘制在画布上。
我查看了系数a和b的长度,但它们没有影响结果 我找不到任何东西。有谁知道什么是错的?
答案 0 :(得分:1)
通常我会将import matplotlib.pyplot as plt
与plt.plot
,plt.subplot
,plt.show
等一起使用 - 甚至只使用from pylab import *
。无论如何,这一行
from matplotlib.axes import Subplot as plt
是你有一个未绑定的plot
函数试图对ndarray
参数进行操作的原因。 Subplot
需要实例化。这应该有效:
import numpy as np
from scipy.signal import freqz
import matplotlib
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
from matplotlib.figure import Figure
from matplotlib.axes import Subplot
fig = Figure()
ax = Subplot(fig, 111)
fig.add_subplot(ax)
canvas = FigureCanvas(fig)
a=[1,1]
b=[1,1]
fsam = 48000
w, h = freqz(b, a, worN=2000)
ax.plot(((fsam-8000) * 0.5 / np.pi) * w, abs(h), label=" ")
canvas.show()