169 行
4.0 KiB
Python
169 行
4.0 KiB
Python
import unicodedata
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import numpy as np
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from ProfileDataType import Profile
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from scipy.interpolate import interp1d
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from scipy.signal import butter, filtfilt
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from DataBase import DataBase
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'''
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************************************************************
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该模块用读取实测的声速剖面
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************************************************************
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'''
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def is_number(s):
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'''
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判断是否为数字
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'''
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try:
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float(s)
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return True
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except ValueError:
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pass
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try:
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unicodedata.numeric(s)
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return True
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except (TypeError, ValueError):
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pass
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return False
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def readRawProfile(fname):
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# 读取经纬度, 海深等信息
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f = open(fname)
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line = f.readline()
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line = line.split(',')
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if is_number(line[1]):
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lat = float(line[1])
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else:
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lat = None
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if is_number(line[3]):
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lon = float(line[3])
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else:
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lon = None
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if is_number(line[5]):
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botDep = float(line[5])
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else:
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botDep = None
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f.close()
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# 读取数据
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data = np.loadtxt(fname, skiprows=2,delimiter=',')
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# 剖面赋值
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velPf = Profile()
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velPf.set_data(data[:, 0], data[:, 1])
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velPf.set_coord(lat, lon)
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velPf.set_bottomDepth(botDep)
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return velPf
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def removeHead(velPf):
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'''
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去掉剖面头部异常数据, 刚入水的
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'''
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lat = velPf.lat
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lon = velPf.lon
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botDep = velPf.botDep
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dep = velPf.x
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vel = velPf.y
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# 梯度阈值
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gradc = 1.0
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# 去掉前面一段（刚入水）变化计较剧烈的区域
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for i in range(dep.size-1):
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grad = np.abs((vel[i+1]-vel[i])/(dep[i+1]-dep[i]))
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if grad < gradc:
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break
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dep = dep[i+1:]
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vel = vel[i+1:]
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# 剖面赋值
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velPf = Profile()
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velPf.set_data(dep, vel)
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velPf.set_coord(lat, lon)
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velPf.set_bottomDepth(botDep)
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return velPf
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def removeTail(velPf, ETOPO1Path, STPath):
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'''
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去掉剖面尾部异常数据, 触底后的
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'''
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lat = velPf.lat
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lon = velPf.lon
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botDep = velPf.botDep
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dep = velPf.x
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vel = velPf.y
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# 如果没有给定深度，则直接从数据库中提取
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if botDep == None:
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data = DataBase(ETOPO1Path, STPath)
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data.set_coord(lat, lon)
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botDep = data.get_bottomDepth()
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# 过滤掉触底后的曲线
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temp = dep < botDep
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dep = dep[temp]
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vel = vel[temp]
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# 剖面赋值
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velPf = Profile()
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velPf.set_data(dep, vel)
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velPf.set_coord(lat, lon)
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velPf.set_bottomDepth(botDep)
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return velPf
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def resampleProfile(velPf):
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'''
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重采样剖面, 间隔1m采样
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'''
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lat = velPf.lat
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lon = velPf.lon
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botDep = velPf.botDep
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dep = velPf.x
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vel = velPf.y
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# 得到等间距的采样曲线
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depInterp = np.arange(0, dep[-1])
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f = interp1d(dep, vel, fill_value='extrapolate')
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velInterp = f(depInterp)
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# 剖面赋值
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velPf = Profile()
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velPf.set_data(depInterp, velInterp)
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velPf.set_coord(lat, lon)
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velPf.set_bottomDepth(botDep)
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return velPf
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def lowPassFilter(velPf):
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'''
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低通滤波器, 使曲线平滑
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'''
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lat = velPf.lat
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lon = velPf.lon
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botDep = velPf.botDep
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dep = velPf.x
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vel = velPf.y
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# 设计数字滤波器
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freqc = 0.05
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order = 2
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b, a = butter(order, freqc)
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# 对曲线进行滤波
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vel = filtfilt(b, a, vel)
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# 剖面赋值
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velPf = Profile()
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velPf.set_data(dep, vel)
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velPf.set_coord(lat, lon)
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velPf.set_bottomDepth(botDep)
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return velPf
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def processProfile(velRawPf, ETOPO1Path, STPath):
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'''
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对原始剖面数据进行处理, 得到处理后的剖面
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'''
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# 去掉刚入水，剧烈变化部分
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velPf = removeHead(velRawPf)
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# 去掉触底后，无效部分
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velPf = removeTail(velPf, ETOPO1Path, STPath)
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# 等间距重采样
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velPf = resampleProfile(velPf)
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# 低通滤波
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velPf = lowPassFilter(velPf)
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return velPf
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