如何正确编写用于执行和绘制for循环操作的语法？

import matplotlib.pylab as plt import numpy as np from astropy import units as u import scipy.constants %matplotlib inline #Importing constants to use. h = scipy.constants.h c = scipy.constants.c k = scipy.constants.k wavelengths= np.arange(1000,30000)\*.e-10 temperature=[3000,4000,5000,6000] for lam in wavelengths: for T in temperature: B_lambda = ((2\*\*\*2)/(lam\*5))\*(1)/(np.exp((h\*)/(lam\*\*))-1)) plt.figure() plt.plot(wavelengths,B_lambda) --------------------------------------------------------------------------- ValueError Traceback (most recent call last) <ipython-input-6-73b866241c49> in <module> 17 B_lambda = ((2\*\*\*2)/(lam\*5))\*(1)/(np.exp((h\*)/(lam\*\*))-1)) 18 plt.figure() ---> 19 plt.plot(wavelengths,B_lambda) 20 21 /usr/local/lib/python3.6/dist-packages/matplotlib/pyplot.py in plot(scalex, scaley, data, \*rgs, \*kwargs) 2787 return gca().plot( 2788 \*rgs, scalex=scalex, scaley=scaley, \*({"data": data} if data -> 2789 is not None else {}), \*kwargs) 2790 2791 /usr/local/lib/python3.6/dist-packages/matplotlib/axes/_axes.py in plot(self, scalex, scaley, data, \*rgs, \*kwargs) 1663 """ 1664 kwargs = cbook.normalize_kwargs(kwargs, mlines.Line2D._alias_map) -> 1665 lines = [\*elf._get_lines(\*rgs, data=data, \*kwargs)] 1666 for line in lines: 1667 self.add_line(line) /usr/local/lib/python3.6/dist-packages/matplotlib/axes/_base.py in __call__(self, \*rgs, \*kwargs) 223 this += args[0], 224 args = args[1:] --> 225 yield from self._plot_args(this, kwargs) 226 227 def get_next_color(self): /usr/local/lib/python3.6/dist-packages/matplotlib/axes/_base.py in _plot_args(self, tup, kwargs) 389 x, y = index_of(tup[-1]) 390 --> 391 x, y = self._xy_from_xy(x, y) 392 393 if self.command == 'plot': /usr/local/lib/python3.6/dist-packages/matplotlib/axes/_base.py in _xy_from_xy(self, x, y) 268 if x.shape[0] != y.shape[0]: 269 raise ValueError("x and y must have same first dimension, but " --> 270 "have shapes {} and {}".format(x.shape, y.shape)) 271 if x.ndim > 2 or y.ndim > 2: 272 raise ValueError("x and y can be no greater than 2-D, but have " ValueError: x and y must have same first dimension, but have shapes (29000,) and (1,) \` \` \`

要注意的第一件事（这是次要的）是运行代码不需要astropy。因此，您可以简化导入语句。

import matplotlib.pylab as plt
import numpy as np
import scipy.constants
%matplotlib inline

#Importing constants to use.
h = scipy.constants.h
c = scipy.constants.c
k = scipy.constants.k


wavelengths= np.arange(1000,30000,100)\*.e-10 # here, I chose steps of 100, because plotting 29000 datapoints takes a while
temperature=[3000,4000,5000,6000]

其次，要整理一下循环，可以编写一个辅助函数，您可以在循环内部调用该函数：

def f(lam, T):
    return ((2\*\*\*2)/(lam\*5))\*(1)/(np.exp((h\*)/(lam\*\*))-1))

现在您可以收集函数的输出以及输入参数，例如在元组列表中：

outputs = []

for lam in wavelengths:
    for T in temperature:
        outputs.append((lam, T, f(lam, T)))

由于您同时改变波长和温度，因此3d图很有意义：

from mpl_toolkits.mplot3d import Axes3D

fig = plt.figure(figsize=(10,10))
ax = fig.add_subplot(111, projection='3d')

ax.plot(\*ip(\*utputs))

另一种选择是将数据显示为图像，使用颜色指示功能输出。

我还将在此方法中包括另一种生成数据的方法。由于函数“ f”可以将数组作为输入，因此您可以一次输入一个温度，并同时输入所有波长。

# initialise output as array with proper shape
outputs = np.zeros((len(wavelengths), len(temperature)))

for i, T in enumerate(temperature):
    outputs[:,i] = f(wavelengths, T)

现在的输出是一个大矩阵，您可以将其可视化为图像：

fig = plt.figure()
ax = fig.add_subplot(111)
ax.imshow(outputs, aspect=10e8, interpolation='none', 
          extent=[
              np.min(temperature),
              np.max(temperature),
              np.max(wavelengths),
              np.min(wavelengths)]
         )

回答来源：stackoverflow

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如何正确编写用于执行和绘制for循环操作的语法？

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