如何快速讀取兩個Q3D Matrix CSV並計算及輸出偏差值圖及CSV表

 

"""
Created on Thu Apr  8 11:16:35 2021
Output deviation of 2 Q3D matrix
@author: mlin
"""
# -------------------------------User Input-------------------------------------
path = 'd:/demo'
f_pair = [('case1.csv', 'case2.csv'), ]

# ---------------------------Don't Revise Code Below----------------------------
import os, math
import matplotlib.pyplot as plt

matrix_type = ['Capacitance Matrix',
               'Conductance Matrix',
               'DC Inductance Matrix',
               'DC Resistance Matrix',
               'AC Inductance Matrix',
               'AC Resistance Matrix', ]


def getDiagonal(x):
    N = int(math.sqrt(len(x)))
    result = [x[i * N + i] for i in range(N)]
    return result


def readQ3Dcsv(csv_path):
    data = {i: [] for i in matrix_type}
    name = {i: [] for i in matrix_type}

    with open(csv_path) as f:
        for line in f:
            if line.strip() in matrix_type:
                mtype = line.strip()
                continue
            else:
                for i in line.strip().split(','):
                    try:
                        data[mtype].append(float(i))
                        continue
                    except:
                        ...

                    try:
                        if i.strip() != '':
                            name[mtype].append(i)
                    except:
                        ...

    result = {i: getDiagonal(data[i]) for i in data}
    return result, name


for f1, f2 in f_pair:
    label = '{} - {}'.format(f1.split('.')[0], f2.split('.')[0])

    f1 = os.path.join(path, f1)
    f2 = os.path.join(path, f2)
    data1, name1 = readQ3Dcsv(f1)
    data2, name2 = readQ3Dcsv(f2)

    with open(os.path.join(path, label + '.csv'), 'w') as f:
        for mtype in data1:
            result = []
            f.writelines(f'\n[{mtype}]\n')
            png_name = f'{label} [{mtype}]'
            title = f'{label}\n[{mtype}]'
            try:
                for name, v1, v2 in zip(name1[mtype], data1[mtype], data2[mtype]):
                    deviation = (v2 - v1) * 100 / v1
                    result.append(deviation)
                    f.writelines(f'{name:36}{v2:12}{v1:12}{deviation:12.3f}%\n')
                plt.plot(result, linewidth=1, color='b')
                plt.title(title)
                plt.ylim(-2, 2)
                plt.grid()
                plt.ylabel('deviation(%)')
                plt.savefig(os.path.join(path, png_name + '.png'))
                plt.show()
            except:
                print(f'Failed: {label}, {mtype}')

(圖一)差異圖

(圖二)差異表