python--获取每张切片的不同PEF区间值的百分比

本文主要是介绍python--获取每张切片的不同PEF区间值的百分比，希望对大家解决编程问题提供一定的参考价值，需要的开发者们随着小编来一起学习吧！

在全直径数字岩心中，如何获取每张切片的不同PEF区间值的百分比？

import os
import datetime
from PIL import Image
import numpy as np
import csv
import easygui as gclass Table(object):def __init__(self, table_data_path):self.table_data_path = table_data_pathdef get_data(self):self.image = Image.open(self.table_data_path)self.array = np.array(self.image).flatten()self.table_data = [i for i in self.array if i > 0]if self.array.any() != 0:# Mode_value = round(stats.mode(self.table_data)[0][0], 2)# Mode_count = stats.mode(self.table_data)[1][0]# Count = np.size(self.table_data)Min = round(np.min(self.table_data), 5)min_list.append(Min)Max = round(np.max(self.table_data), 5)max_list.append(Max)Mean = round(np.mean(self.table_data), 5)mean_list.append(Mean)StdDev = round(np.std(self.table_data), 5)stdDev_list.append(StdDev)for a in range(len(data_range_use)):range_percent = round(len([j for j in self.table_data if(j > data_range_use[a][0]) and (j <= data_range_use[a][1])]) / len(self.table_data) * 100, 4)prepare_list['range_percent_list_%s' % a].append(range_percent)else:min_list.append(0)max_list.append(0)mean_list.append(0)stdDev_list.append(0)for m in range(len(data_range_use)):prepare_list['range_percent_list_%s' % m].append(0)if __name__ == '__main__':start = datetime.datetime.now()print(start)list_name = []min_list, mean_list, max_list, stdDev_list = [], [], [], []data_range = [[i / 10, (i + 2) / 10] for i in range(60)]data_range_use = [data_range[i] for i in range(len(data_range)) if (i % 2 == 0)]data_range_end = [[6, 100]]data_range_use.extend(data_range_end)prepare_list = {}  # 定义空字典def test_list_pre():prepare_list = locals()  # 返回prepare_list中当前位置每个字典里的全部局部变量（也就是键）for l in range(len(data_range_use)):prepare_list['range_percent_list_' + str(l)] = []slice_name = []rootpath = g.diropenbox()print(rootpath)for i in os.listdir(rootpath):print(os.path.join(rootpath, i))slice_name.append(i)t = Table(os.path.join(rootpath, i))t.get_data()data0 = {'slice_name': slice_name,'Min': min_list,'Max': max_list,'Mean': mean_list,'StdDev': stdDev_list,}data1 = {}for b in range(len(data_range_use)):k = '%s-%s' % (data_range_use[b][0], data_range_use[b][1])v = prepare_list['range_percent_list_%s' % b]data1.update({k: v})data = {}data.update(data0)data.update(data1)# print(data)csv_file = open('%s—2.csv' % rootpath.split("\\")[-1], 'w', newline='')writer = csv.writer(csv_file)table_head = ['slice_name', 'Min', 'Max', 'Mean', 'StdDev']table_head1 = [('%s-%s' % (data_range_use[i][0], data_range_use[i][1])) for i in range(len(data_range_use))]table_head.extend(table_head1)# print(table_head)writer.writerow(table_head)for ii in range(len(data['Min'])):writer.writerow([data[m][ii] for m in table_head])csv_file.close()print('the data has been saved!')stop = datetime.datetime.now()print(stop)time = (stop - start).secondsprint("Total time (min):%s" % round((time / 60), 2))

处理结果如下表：

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