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numpy - 如何从我正在处理的 numpy 数据集中在 Matplotlib 中绘制多个图形？

问题描述

我是编程新手，在绘制多个图表时遇到了困难。我想要得到的是一个包含沿 Y 轴的 K 值相对于 Dk 值绘制的图表。我需要这张图包含每个温度 Tcwin 在 (10,40,1) 范围内的所有 K=f(Dk) 虽然代码似乎运行良好并且我已经获得了我试图计算的数据，但我可以' t 似乎在绘制它们。任何帮助，将不胜感激。

import numpy as np
import pandas as pd
A=3000
d_in=20
CF=0.85
w=2.26
Tcwin=12
Dk=np.arange(27.418,301.598,27.418)
dk=(Dk*1000/(A*3.600))
cp=4.19
Gw=13000
e=2.718281828
f_velocity=w*1.1/(20**0.25)
for Tcwin in range(10,40,1):
    while Tcwin<35:
        print(Tcwin)
        f_w=0.12*CF*(1+0.15*Tcwin)
        Ф_в=f_velocity**f_w
        K=CF*4070*((1.1*w/(d_in**0.25))**(0.12*CF*(1+0.15*Tcwin)))*(1-(((35-Tcwin)**2)*(0.52-0.0072*dk)*(CF**0.5))/1000)
        n=(K*A)/(cp*Gw*1000)
        Tcwout_theor=Tcwin+(Dk*2225/(cp*Gw))
        Subcooling_theor=(Tcwout_theor-Tcwin)/(e**(K*A/(cp*(Gw*1000/3600)*1000)))
        TR_theor=Tcwout_theor-Tcwin
        Tsat_theor=Tcwout_theor+Subcooling_theor
        print(K)
        print(Tcwout_theor)
        print(Subcooling_theor)
        print(Tsat_theor)
        Tcwin+=1
    else:
        print('Loop done')

标签： numpymatplotlibarray-broadcasting

解决方案

这是你想要的？每次运行后绘制：

import numpy as np
import pandas as pd
A=3000
d_in=20
CF=0.85
w=2.26
Tcwin=12
Dk=np.arange(27.418,301.598,27.418)
dk=(Dk*1000/(A*3.600))
cp=4.19
Gw=13000
e=2.718281828
f_velocity=w*1.1/(20**0.25)
for Tcwin in range(10,40,1):
    while Tcwin<35:
        print(Tcwin)
        f_w=0.12*CF*(1+0.15*Tcwin)
        Ф_в=f_velocity**f_w
        K=CF*4070*((1.1*w/(d_in**0.25))**(0.12*CF*(1+0.15*Tcwin)))*(1-(((35-Tcwin)**2)*(0.52-0.0072*dk)*(CF**0.5))/1000)
        n=(K*A)/(cp*Gw*1000)
        Tcwout_theor=Tcwin+(Dk*2225/(cp*Gw))
        Subcooling_theor=(Tcwout_theor-Tcwin)/(e**(K*A/(cp*(Gw*1000/3600)*1000)))
        TR_theor=Tcwout_theor-Tcwin
        Tsat_theor=Tcwout_theor+Subcooling_theor
        print(K)
        print(Tcwout_theor)
        print(Subcooling_theor)
        print(Tsat_theor)
        Tcwin+=1
        plt.plot(K,dk) #---------------> this is the code for plotting 
        
    else:
        print('Loop done')

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