我可以把换色器放在一个循环吗？ [英] Can i put a color changer in a loop?

问题描述

所以基本上我想知道，在我的代码的底部，当我绘制我的试验的图形，有没有办法运行一个颜色生成器通过那里？或者更明确地说，我可以列出温暖的颜色，并把它放入我的绘图函数，其中它遍历列表中的每个颜色，当循环通过，因此我的情节只由温暖的颜色？

 来自numpy import * 
来自pylab import show，plot 
来自scipy.special import erfinv 
n = 366＃天数
 ntrials = 5000 
u = random.rand（ntrials）
v = sqrt（2。）* erfinv（2. * u-1。）
 mu = 0 
 sigma = .05 
 investment = 1000. 
 data = empty（（ntrials，n））
 data [：，0] = investment 
 for t在范围（n-1）中：
u = random.rand（ntrials）
v = sqrt（2。）* erfinv（2. * u-1。）
 epsilon = v 
 data [：，t + 1] =（1. + mu + sigma * epsilon）* data [：，t] 
 
 data2 = data.sum（axis = 0）
 = data2 [-1] / ntrials 
 data3 = data2 [-1] 
x = linspace（0，n，n）
 for t in range（n）：
 plot解决方案
 
  div> 
听起来你只是想要这样的东西？
  import matplotlib.pyplot as plt 
 import matplotlib as mpl 
 import numpy as np 
 
＃生成数据... 
 nx，nsteps = 100，20 
x = np.linspace（0，1，nx ）
 data = np.random.random（（nx，nsteps）） -  0.5 
 data = data.cumsum（axis = 0）
 data = data.cumsum（axis = 1）
 
＃plot 
 cmap = mpl.cm.autumn 
 for i，y in enumerate（data.T）：
 plt.plot（x，y，color = cmap（i / float（nsteps）））
 
 plt.show（）
  
  
 
 
 
键调用具有0和1之间的值的matplotlib颜色图实例将返回一种颜色（其中0是颜色图中最低的颜色，1是最高颜色）。
 
 
 
可用色彩图表列表，请参阅此处。您可以使用 name_r （例如， mpl.cm.autumn 的反转版本 mpl.cm.autumn_r ）。
 
So basically what i'm wondering, is at the bottom of my code when i plot the graph of my trials, is there a way to run a color generator through there? Or more explicitly put, could i make a list of warm colors, and put that into my plot function, where it runs through each color in a list as the loop runs through, and therefore my plot would only consist of warm colors?
from numpy import *
from pylab import show,plot
from scipy.special import erfinv    
n = 366 #number of days     
ntrials = 5000
u = random.rand(ntrials)
v = sqrt(2.)*erfinv(2.*u-1.)
mu = 0                                          
sigma = .05                             
investment = 1000.              
data = empty((ntrials,n))
data[:,0] = investment        
for t in range(n-1):
    u = random.rand(ntrials)
    v = sqrt(2.)*erfinv(2.*u-1.)
    epsilon = v
    data[:,t+1] = (1. + mu +sigma*epsilon)*data[:,t]

data2 = data.sum(axis=0)
woo = data2[-1]/ntrials                 
data3 = data2[-1]
x = linspace(0,n,n)
for t in range(n):
    plot(x,data[t,:])    
show()

解决方案
It sounds like you just want something like this?
import matplotlib.pyplot as plt
import matplotlib as mpl
import numpy as np

# Generate data...
nx, nsteps = 100, 20
x = np.linspace(0, 1, nx)
data = np.random.random((nx, nsteps)) - 0.5
data = data.cumsum(axis=0)
data = data.cumsum(axis=1)

# Plot
cmap = mpl.cm.autumn
for i, y in enumerate(data.T):
    plt.plot(x, y, color=cmap(i / float(nsteps)))

plt.show()


The key is that calling a matplotlib colormap instance with a value between 0 and 1 will return a color (where 0 is the lowest color in the colormap and 1 is the highest).

For a list of available colormaps, see here. You can access the reversed version of any of these with name_r (e.g. the reversed version of mpl.cm.autumn is mpl.cm.autumn_r).

                        
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