412 lines
13 KiB
Python
412 lines
13 KiB
Python
# -*- coding: UTF-8 -*-
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"""
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@Project:SalinityMain.py
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@File:AuxData.py
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@Function: 读取指标物候辅助数据
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@Contact:
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@Author:SHJ
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@Date:2021/10/21 19:25
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@Version:1.0.0
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"""
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import csv
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import numpy as np
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import mahotas
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import logging
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import random
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from tool.algorithm.algtools.CoordinateTransformation import lonlat2geo, geo2imagexy
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from tool.algorithm.image.ImageHandle import ImageHandler
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logger = logging.getLogger("mylog")
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class PhenologyMeasCsv:
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def __init__(self, csv_path, preprocessed_paras):
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self.__csv_path = csv_path
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self.__preprocessed_paras = preprocessed_paras
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def api_read_phenology_measure(self):
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csv_data = self.__readcsv(self.__csv_path)
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return self.__trans_measuredata(csv_data)
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def class_list(self):
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"""
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输出csv表中的前三列
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"""
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reader = csv.reader(open(self.__csv_path, newline=''))
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class_list=[]
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type_id_name = {}
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for line_data in reader:
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class_list.append(line_data) # class_list含有四列
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for data in class_list[1:]:
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type_id = data[2]
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type_name = data[3]
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if type_id not in type_id_name.keys():
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if type_id.strip() != "":
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type_id_name.update({type_id: type_name})
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return type_id_name
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pass
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@staticmethod
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def __readcsv(csv_path):
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"""
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读取csv表格数据
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:para csv_path: csv文件路径
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"""
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reader = csv.reader(open(csv_path, newline=''))
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csv_list = []
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for line_data in reader:
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csv_list.append(line_data)
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return csv_list[1:]
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@staticmethod
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def readcsv_dic(csv_path):
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"""
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读取csv表格数据
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:para csv_path: csv文件路径
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"""
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reader = csv.reader(open(csv_path, newline=''))
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csv_list = []
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for line_data in reader:
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csv_list.append(line_data)
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keys = csv_list[0]
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datas = csv_list[1:]
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data_dic = {}
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for key ,n in zip(keys,range(len(keys))):
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values = [data for data in datas[n]]
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data_dic.update({key: values})
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return data_dic
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def __trans_measuredata(self, meas_data):
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"""
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获取多边形区域内所有的点，分为训练集数据和测试集数据
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:para meas_data: csv读取的实测数据
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"""
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train_data = []
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test_data = []
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type_data = {}
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for data in meas_data:
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point_list = []
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data_use_type = data[0]
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sar_img_name = data[1]
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name = sar_img_name.rstrip('.tar.gz')
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dataset, rows, cols = self.__get_para_tif_inf(name)
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if data_use_type == 'train':
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phenology_id = int(data[2])
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phenology_name = data[3]
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if phenology_id not in type_data.keys():
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type_data.update({phenology_id: phenology_name})
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else:
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phenology_id = -1
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pointList = self.__roiPolygonAnalysis(data[4])
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for points in pointList:
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poly = []
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for point in points:
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lon = float(point[0])
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lat = float(point[1])
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projs = lonlat2geo(dataset, lon, lat)
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coord = geo2imagexy(dataset, projs[1], projs[0])
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row = round(coord[1])
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col = round(coord[0])
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if 0 <= row < rows and 0 <= col < cols:
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poly.append([row, col])
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else:
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logger.warning("measure data: %s is beyond tif scope !", data)
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point_list = point_list + self.__render(poly)
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if data_use_type == 'train':
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train_data.append([name, phenology_id, point_list])
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elif data_use_type == 'test':
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test_data.append([name, phenology_id, point_list])
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type_map = []
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for n, id in zip(range(len(type_data)), type_data):
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type_map.append([n + 1, id, type_data[id]])
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return train_data, test_data, type_map
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@staticmethod
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def __render(poly):
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# https://www.cnpython.com/qa/51516
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"""Return polygon as grid of points inside polygon.
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Input : poly (list of lists)
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Output : output (list of lists)
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"""
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xs, ys = zip(*poly)
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minx, maxx = min(xs), max(xs)
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miny, maxy = min(ys), max(ys)
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newPoly = [(int(x - minx), int(y - miny)) for (x, y) in poly]
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X = maxx - minx + 1
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Y = maxy - miny + 1
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grid = np.zeros((X, Y), dtype=np.int8)
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mahotas.polygon.fill_polygon(newPoly, grid)
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return [(x + minx, y + miny) for (x, y) in zip(*np.nonzero(grid))]
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def __get_para_tif_inf(self, tif_name):
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"""
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获取影像的信息
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:para tif_name: 影像名称
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"""
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tif_path = self.__preprocessed_paras[tif_name + '_HH']
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ih = ImageHandler()
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dataset = ih.get_dataset(tif_path)
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rows = ih.get_img_height(tif_path)
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cols = ih.get_img_width(tif_path)
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return dataset, rows, cols
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@staticmethod
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def __roiPolygonAnalysis(roiStr):
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"""
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将csv的POLY数据转为数组
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:para roiStr: poly数据
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:return pointList: 保存多边形的list
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"""
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pointList = []
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strContent = roiStr.replace("POLYGON", "")
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# 解析轮廓字符串为二维数组
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bracketsList = []
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strTemp = ''
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strList = []
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for c in strContent:
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if c == '(':
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bracketsList.append(c)
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continue
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elif c == ')':
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if len(bracketsList) > 0:
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bracketsList.pop(0)
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if len(strTemp) > 0:
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strList.append(strTemp)
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strTemp = ''
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else:
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strTemp += c
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for item in strList:
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if len(item) == 0:
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continue
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pTempList = item.split(',')
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pList = []
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for row in pTempList:
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cells = row.split(' ')
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if len(cells) != 2:
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continue
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point = []
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point.append(float(cells[0]))
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point.append(float(cells[1]))
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pList.append(point)
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pointList.append(pList)
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return pointList
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class PhenoloyMeasCsv_geo:
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def __init__(self, csv_path, preprocessed_paras, max_tran__num_per_class=100000):
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self.__csv_path = csv_path
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self.__preprocessed_paras = preprocessed_paras
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self.__max_tran__num_per_class = max_tran__num_per_class
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def api_read_measure(self):
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"""
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读取csv表格数据api函数
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"""
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csv_data = self.__readcsv(self.__csv_path)
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return self.__trans_measuredata(csv_data)
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def api_read_measure_by_name(self, name):
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"""
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读取csv表格数据api函数
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"""
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csv_data = self.__readcsv_by_name(self.__csv_path, name)
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return self.__trans_measuredata(csv_data)
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def class_list(self):
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"""
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输出csv表中的前三列
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"""
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reader = csv.reader(open(self.__csv_path, newline=''))
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class_list=[]
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type_id_name = {}
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type_id_parent = {}
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for line_data in reader:
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class_list.append(line_data) # class_list含有四列
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for data in class_list[1:]:
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type_parent= data[0]
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type_id = int(data[1])
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type_name = data[2]
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if type_id not in type_id_name.keys():
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type_id_name.update({type_id: type_name})
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type_id_parent.update({type_id: type_parent})
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return type_id_name, type_id_parent
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pass
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@staticmethod
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def __readcsv(csv_path):
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"""
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读取csv表格数据
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:para csv_path: csv文件路径
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"""
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reader = csv.reader(open(csv_path, newline=''))
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csv_list = []
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for line_data in reader:
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csv_list.append(line_data)
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return csv_list[1:]
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@staticmethod
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def __readcsv_by_name(csv_path, name):
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"""
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读取csv表格数据
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:para csv_path: csv文件路径
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"""
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reader = csv.reader(open(csv_path, newline=''))
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csv_list = []
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for line_data in reader:
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if name in line_data[0]:
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csv_list.append(line_data)
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return csv_list
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def __trans_measuredata(self, meas_data):
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"""
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获取多边形区域内所有的点，分为训练集数据和测试集数据
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:para meas_data: csv读取的实测数据
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"""
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type_data = {}
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n = 1
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train_data_list = []
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for data in meas_data:
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for d in data:
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if d == '':
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raise Exception('there are empty data!', data)
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point_list = []
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dataset, rows, cols = self.__get_para_tif_inf()
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type_id = int(data[1])
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type_name = data[2]
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if type_id not in type_data.keys():
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train_data_list.append([n, type_id, type_name, []])
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type_data.update({type_id: type_name})
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n += 1
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pointList = self.__roiPolygonAnalysis(data[3])
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for points in pointList:
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poly = []
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for point in points:
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lon = float(point[0])
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lat = float(point[1])
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# projs = lonlat2geo(dataset, lon, lat)
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coord = geo2imagexy(dataset, lon, lat)
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row = round(coord[1])
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col = round(coord[0])
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if 0 <= row < rows and 0 <= col < cols:
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poly.append([row, col])
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else:
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logger.warning("point %s is beyond tif scope, in measure data: %s !", point, data)
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if poly != []:
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point_list.append(self.__render(poly))
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for train_data in train_data_list:
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if train_data[1] == type_id:
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train_data[3] = train_data[3] + self.__render(poly)
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if train_data[3] == [] :
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raise Exception('there are empty data!', train_data)
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if len(train_data_list) <= 1:
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raise Exception('there is only one label type!', train_data_list)
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num_list = []
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for train_data in train_data_list:
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if not len(train_data[3]) == 0:
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num_list.append(len(train_data[3]))
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max_num = np.min(num_list)
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for train_data in train_data_list:
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logger.info(str(train_data[0]) + "," + str(train_data[2]) +"," + "num:" + str(len(train_data[3])))
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# max_num = self.__max_tran__num_per_class
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logger.info("max number =" + str(max_num) +", random select"+str(max_num)+" point as train data!")
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if(len(train_data[3]) > max_num):
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train_data[3] = random.sample(train_data[3], max_num)
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return train_data_list
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@staticmethod
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def __render(poly):
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# https://www.cnpython.com/qa/51516
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"""Return polygon as grid of points inside polygon.
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Input : poly (list of lists)
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Output : output (list of lists)
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"""
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xs, ys = zip(*poly)
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minx, maxx = min(xs), max(xs)
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miny, maxy = min(ys), max(ys)
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newPoly = [(int(x - minx), int(y - miny)) for (x, y) in poly]
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X = maxx - minx + 1
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Y = maxy - miny + 1
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grid = np.zeros((X, Y), dtype=np.int8)
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mahotas.polygon.fill_polygon(newPoly, grid)
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return [(x + minx, y + miny) for (x, y) in zip(*np.nonzero(grid))]
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def __get_para_tif_inf(self):
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"""
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获取影像的信息
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:para tif_name: 影像名称
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"""
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tif_path = self.__preprocessed_paras
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ih = ImageHandler()
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dataset = ih.get_dataset(tif_path)
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rows = ih.get_img_height(tif_path)
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cols = ih.get_img_width(tif_path)
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return dataset, rows, cols
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@staticmethod
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def __roiPolygonAnalysis(roiStr):
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"""
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将csv的POLY数据转为数组
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:para roiStr: poly数据
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:return pointList: 保存多边形的list
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"""
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pointList = []
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strContent = roiStr.replace("POLYGON", "")
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# 解析轮廓字符串为二维数组
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bracketsList = []
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strTemp = ''
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strList = []
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for c in strContent:
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if c == '(':
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bracketsList.append(c)
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continue
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elif c == ')':
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if len(bracketsList) > 0:
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bracketsList.pop(0)
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if len(strTemp) > 0:
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strList.append(strTemp)
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strTemp = ''
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else:
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strTemp += c
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for item in strList:
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if len(item) == 0:
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continue
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pTempList = item.split(',')
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pList = []
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for row in pTempList:
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cells = row.split(' ')
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if len(cells) != 2:
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continue
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point = [float(cells[0]), float(cells[1])]
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pList.append(point)
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pointList.append(pList)
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return pointList |