How to use handle_csv method in autotest

Best Python code snippet using autotest_python

welcome.py

Source:welcome.py Github

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1import sys2import os3from PyQt5.QtCore import pyqtSignal4from PyQt5.QtGui import QFont5from PyQt5.QtWidgets import (6 QApplication,7 QWidget,8 QPushButton,9 QLabel,10 QComboBox,11 QTableWidget,12 QAbstractItemView,13 QTableWidgetItem,14 QHeaderView)15import csv16import pandas as pd17import numpy as np18from enger_charge_project.interface.standard_tech import Ui_Form as Std_Tech_Form19class Handle_CSV(object):20 def __init__(self, table):21 self.table = table22 def read_from_file(self):23 """读取csv文件的内容到QTableWidget对象中"""24 i = 0 # 初始化一个计数器25 with open('energy_charge_info.csv', encoding="gbk") as f:26 reader = csv.reader(f)27 for row in reader:28 for content in row:29 if content == '时间':30 break # 这里虽然用的break，但是和通常的用法不一样31 new_item = QTableWidgetItem(content)32 self.table.setItem(i - 1, row.index(content), new_item) # 列， 行， 内容33 # 增加一个计数34 i += 135 def write_to_file(self):36 # TODO 明天写37 pass38class StandardTechTnterface():39 pass40class WelocomeInterface(QWidget):41 def __init__(self):42 super().__init__()43 self.title = '欢迎使用行知聚能电力大数据系统！'44 self.left = 1045 self.top = 1046 self.width = 84047 self.height = 68048 self.initUI()49 def initUI(self):50 self.setWindowTitle(self.title)51 self.setGeometry(self.left, self.top, self.width, self.height)52 # 查看按钮53 self.button_watch = QPushButton('查看', self)54 self.button_watch.setToolTip('可以点击查看具体的电费结构')55 self.button_watch.move(200, 100)56 self.button_watch.clicked.connect(self.watch_energy_charge_table)57 # 修改按钮58 self.button_update = QPushButton("修改", self)59 self.button_update.setToolTip("可以点击修改具体的电费结构")60 self.button_update.move(400, 100)61 self.button_update.clicked.connect(self.update_energy_charge_table)62 # 返回按钮63 self.button_back = QPushButton('返回', self)64 # self.label_back = QLabel("返回", self.table_energy_charge)65 self.button_back.move(600, 100)66 self.button_back.clicked.connect(self.go_back_welcome)67 # 欢迎标语68 font = QFont()69 font.setFamily("Algerian")70 font.setPointSize(16)71 self.label_welcome = QLabel("欢迎使用行知聚能电力大数据系统！", self)72 self.label_welcome.move(140, 50)73 self.label_welcome.setFont(font)74 # 电费结构标签75 self.label_energy_charge_structure = QLabel("电费结构", self)76 self.label_energy_charge_structure.move(100, 100)77 # 设备选择标签78 self.label_equipment = QLabel("设备选择", self)79 self.label_equipment.move(100, 150)80 # 下拉文本框81 self.ComboBox_equipment_options = QComboBox(self)82 self.ComboBox_equipment_options.move(200, 150)83 items = ['%d号中频炉' % item for item in range(1, 11)]84 items += ["%d号还原炉" % item for item in range(1, 7)]85 self.ComboBox_equipment_options.addItems(items)86 # 下拉文本框的信号机制87 self.ComboBox_equipment_options.currentIndexChanged[str].connect(self.get_value)88 # 电费价格表 实例化89 self.table_energy_charge = QTableWidget(self)90 self.table_energy_charge.resize(640, 400)91 self.table_energy_charge.move(60, 200)92 self.table_energy_charge.setToolTip("双击进行修改")93 # 设置表头的背景色为灰色94 self.table_energy_charge.horizontalHeader().setStyleSheet('QHeaderView::section{background:grey}')95 self.table_energy_charge.setRowCount(24) # 23行96 self.table_energy_charge.setColumnCount(3) # 3列97 # 设置随内容自动调整列宽98 self.table_energy_charge.horizontalHeader().setSectionResizeMode(QHeaderView.Stretch)99 self.table_energy_charge.horizontalHeader().setSectionResizeMode(0, QHeaderView.ResizeToContents)100 self.table_energy_charge.setHorizontalHeaderLabels(['时间', "峰值类型", "电价(元/度)"]) # 创建表头101 self.table_energy_charge.hide() # 必须，默认隐藏102 # 标准工艺库的界面103 self.std_tech_form = Std_Tech_Form()104 self.std_tech_form.setupUi(self.std_tech_form)105 self.show()106 def watch_energy_charge_table(self):107 """查看电费价格表"""108 # 注意： 读取的时候禁止编辑109 self.table_energy_charge.hide()110 self.table_energy_charge.setEditTriggers(QAbstractItemView.NoEditTriggers) # TODO 有问题111 # 从文件读取112 handle_csv = Handle_CSV(self.table_energy_charge)113 handle_csv.read_from_file()114 # 展示115 self.table_energy_charge.show()116 def update_energy_charge_table(self):117 # 从文件读取(这一步必须的， 当不进行查看直接修改的时候， 默认要有东西供修改)118 self.table_energy_charge.hide()119 self.table_energy_charge.setEditTriggers(QAbstractItemView.DoubleClicked) # 双击进入修改状态120 # 从文件读取121 handle_csv = Handle_CSV(self.table_energy_charge)122 handle_csv.read_from_file()123 self.table_energy_charge.show()124 # TODO 反向写入文件，以供下一次读取125 item = self.table_energy_charge.selectedItems()126 try:127 origin_item_content = item[0].text()128 except Exception as e:129 pass130 else:131 row = self.table_energy_charge.currentRow() # 行号， 从0开始计数132 col = self.table_energy_charge.currentColumn() # 列号，从0开始计数133 if len(item) == 0:134 pass135 else:136 print(item[0].text())137 print(col)138 print(row)139 def go_back_welcome(self):140 self.table_energy_charge.hide()141 def get_value(self, value):142 """获取下拉列表的内容， 并打印"""143 print(value)144 name = value145 # for k, v in name_dic.items():146 # if v == value:147 # print(k, v)148 # imei = imei_dic.get(k, None)149 #150 # data = check_exist_std_hub(name, imei)151 # TODO 跳转到对应的工艺中152 self.std_tech_form.show()153 self.std_tech_form.pushButton_2.clicked.connect(self.std_tech_form.get_time_data)154 # sys.exit(app.exec_())155if __name__ == '__main__':156 app = QApplication(sys.argv)157 welcome_interface = WelocomeInterface()...

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croped_and_predict.py

Source:croped_and_predict.py Github

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1import numpy as np2from PIL import Image3import os4from Model import *5import pandas as pd6def crop_image(filepath, box, width, height, nparray=False):7 res = []8 assert len(box) == 49 x1, y1, x2, y2 = box10 x1, y1, x2, y2 = round(x1), round(y1), round(x2), round(y2)11 res = Image.open(filepath).crop((x1,y1,x2,y2)).resize((width,height), Image.ANTIALIAS)12 if nparray:13 # res = np.array( list(map(lambda x:np.array(x),res)) )14 res = np.array(res)15 return res16def crop_image_generator(rootpath, filepaths, all_image_bboxes, width, height):17 i = 018 while i < len(filepaths):19 croped_images = crop_image(os.path.join(rootpath, filepaths[i]), all_image_bboxes[i], width, height, nparray=True)20 croped_images = np.expand_dims(croped_images,axis=0) / 255.021 i += 122 yield croped_images23def classify_main(rootpath, filepaths, all_image_bboxes):24 class_indices = {'0': 0, '1': 1, '10': 2, '11': 3, '12': 4, '13': 5, '14': 6, '15': 7, '16': 8, '17': 9, '18': 10, '19': 11, '2': 12, '20': 13, '21': 14, '22': 15, '23': 16, '24': 17, '25': 18, '26': 19, '27': 20, '28': 21, '29': 22, '3': 23, '30': 24, '31': 25, '32': 26, '33': 27, '34': 28, '35': 29, '36': 30, '37': 31, '38': 32, '39': 33, '4': 34, '40': 35, '41': 36, '42': 37, '43': 38, '44': 39, '45': 40, '46': 41, '47': 42, '48': 43, '49': 44, '5': 45, '50': 46, '51': 47, '52': 48, '53': 49, '54': 50, '55': 51, '56': 52, '57': 53, '58': 54, '59': 55, '6': 56, '60': 57, '7': 58, '8': 59, '9': 60}25 class_indices = dict((v,k) for k,v in class_indices.items())26 width = 22427 height = 11228 model = DenseNetTransfer((height,width,3), channel=4)29 model.load_weights("Transfer-densenet.h5", by_name=True)30 handle = open("temp.txt", "w+")31 # ret = []32 gen = crop_image_generator(rootpath, filepaths, all_image_bboxes, width,height)33 # 像素值归一化34 predict_res = model.predict_generator(gen, steps=len(filepaths), use_multiprocessing=True, max_queue_size=100)35 label = np.argmax(predict_res, axis=1)36 label = [ class_indices[l] for l in label ]37 score = np.max(predict_res, axis=1)38 for k,l in enumerate(label):39 # if l == "0":40 # continue41 handle.write("{} {} {}\n".format(filepaths[k], l, score[k]) )42 # return ret43if __name__ == '__main__':44 rootpath = "/home/Signboard/second/datasets/test/"45 temp_res_file = "merge.txt"46 handle_csv = pd.read_csv(temp_res_file, sep=' ', names=['filepath', "label", 'score', 'xmin', 'ymin', 'xmax', 'ymax'],47 dtype={"filepath":"str"})48 all_image_bboxes = handle_csv.loc[:,['xmin', 'ymin', 'xmax', 'ymax']].values49 classify_main(rootpath, handle_csv['filepath'].tolist(), all_image_bboxes)50 res_csv = pd.read_csv("temp.txt", sep=' ', names=['filepath', "label", 'score'], dtype={"filepath":"str", "label":"str", "score":"str"})51 handle_csv['label'] = res_csv['label']52 handle_csv['score'] = res_csv['score']53 handle_csv['xmin'] = handle_csv['xmin'].map(lambda x:str(int(round(x))) )54 handle_csv['ymin'] = handle_csv['ymin'].map(lambda x:str(int(round(x))) )55 handle_csv['xmax'] = handle_csv['xmax'].map(lambda x:str(int(round(x))) )56 handle_csv['ymax'] = handle_csv['ymax'].map(lambda x:str(int(round(x))) )57 handle_csv = handle_csv.loc[ handle_csv['label'] != '0', : ]...

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find_removeable.py

Source:find_removeable.py Github

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1import pandas as pd2import numpy as np3import os4import itertools5def MergeResult(Submission_path):6 fileLists = os.listdir(Submission_path)7 true_label = pd.read_csv("test_groundtruth.csv", sep=' ', names=['id', 'label_true'])8 for fileList in itertools.combinations(fileLists, 2):9 if fileList[0].split(".")[-1] != "csv" or fileList[1].split(".")[-1] != "csv":10 continue11 # 统计每一行次数出现最多的数字12 result_handle_1 = pd.read_csv(os.path.join(Submission_path,fileList[0]),sep=' ',names=['id','label_1'])13 result_handle_2 = pd.read_csv(os.path.join(Submission_path,fileList[1]),sep=' ',names=['id','label_2'])14 handle_csv = true_label.merge(result_handle_1, how='left', on='id').merge(result_handle_2, how="left", on="id")15 result_1_index = set(handle_csv[ handle_csv['label_1'] == handle_csv['label_true'] ].index)16 result_2_index = set(handle_csv[ handle_csv['label_2'] == handle_csv['label_true'] ].index)17 if result_1_index & result_2_index == result_2_index:18 print("Dropable:{}, compared to {}".format(fileList[1], fileList[0]))19 elif result_1_index & result_2_index == result_1_index:20 print("Dropable:{}, compared to {}".format(fileList[0], fileList[1]))21if __name__ == '__main__':22 Submission_path = "../Submission"23 test_truth = "test_groundtruth.csv"24 MergeResult(Submission_path)...

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