修改python模块引用方式
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import numpy as np
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from scipy.interpolate import Akima1DInterpolator
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from scipy.optimize import curve_fit
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from netCDF4 import Dataset
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from ProfileDataType import Profile
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'''
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************************************************************
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该模块用于从数据库中, 获取剖面信息
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************************************************************
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'''
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# 时间段标识
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timeDict = {
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# 全年平均
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'Annual': '00',
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# 1-12月
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'January': '01',
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'February': '02',
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'March': '03',
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'April': '04',
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'May': '05',
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'June': '06',
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'July': '07',
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'August': '08',
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'September': '09',
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'October': '10',
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'November': '11',
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'December': '12',
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# 北半球四季
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'Winter': '13',
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'Spring': '14',
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'Summer': '15',
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'Autumn': '16'
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}
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# def MunkFormula(z, v1, epsilon, z1):
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# eta = 2*(z-z1)/z1
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# return v1*(1+epsilon*(np.exp(-eta)+eta-1))
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def soundSpeed(tem, sal, dep):
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'''
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声速计算公式
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'''
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# C = 1449.2 + 4.6*T - 0.055*T^2 + 0.00029*T^3 + (1.34 - 0.01*T)(S-35) + 0.017*D
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# 式中：T为海⽔测点的温度，单位为℃；S为海⽔测点的盐度，单位为‰；D为海⽔测点的深度，单位为m。
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vel = 1449.2 + 4.6*tem - 0.055*tem*tem + 0.00029 * \
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tem*tem*tem + (1.34 - 0.01*tem) * \
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(sal-35.0) + 0.017*dep
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return vel
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class DataBase():
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"""
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获取数据库中的剖面信息
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"""
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def __init__(self,ETOPO1Path,STpath):
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print(ETOPO1Path)
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# 打开ETOPO1数据
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fileETOPO1 = ETOPO1Path + '/ETOPO1_Bed_g_gmt4.nc'
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dataETOPO1 = Dataset(fileETOPO1)
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# 获取ETOPO1网格
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self.latGrid1 = dataETOPO1.variables['y'][:]
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self.lonGrid1 = dataETOPO1.variables['x'][:]
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# 获取海深数据
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self.botGrid = -dataETOPO1.variables['z'][:]
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self.STPath=STpath
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return
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def clearVar(self):
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"""
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清空变量
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"""
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self.botDep = None
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self.salRawPf = None
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self.temRawPf = None
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self.velRawPf = None
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self.velInterpPf = None
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self.velExtPf = None
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self.velFullPf = None
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self.isValid = True
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return
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def set_timePeriod(self, timeIndex):
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"""
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设置时间段
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"""
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timeIndex = '01'
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self.timeIndex = timeIndex
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# 打开WOA18数据
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fileWOA18sal = self.STPath + '/woa18_A5B7_s' + timeIndex + '_04.nc'
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fileWOA18tem = self.STPath + '/woa18_A5B7_t' + timeIndex + '_04.nc'
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dataWOA18Sal = Dataset(fileWOA18sal)
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dataWOA18Tem = Dataset(fileWOA18tem)
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# 获取WOA18网格
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self.latGrid2 = dataWOA18Sal.variables['lat'][:]
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self.lonGrid2 = dataWOA18Sal.variables['lon'][:]
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# 获取深度数据
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self.depthGrid = dataWOA18Sal.variables['depth'][:]
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# 获取盐度数据
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self.salGrid = np.squeeze(dataWOA18Sal.variables['s_an'][:])
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# 获取温度数据
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self.temGrid = np.squeeze(
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dataWOA18Tem.variables['t_an'][:])
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self.clearVar()
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return
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def set_coord(self, lat, lon):
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"""
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设置坐标
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"""
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self.lat = lat
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self.lon = lon
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self.clearVar()
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return
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def interpBilinear(self, latId, lonId, dataGrid, dataTpye):
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"""
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双线性插值
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"""
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latId0 = int(np.ceil(latId))
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lonId0 = int(np.ceil(lonId))
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a = latId - latId0
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b = lonId - lonId0
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if (dataTpye == 1):
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data0 = dataGrid[latId0, lonId0]
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data1 = dataGrid[latId0+1, lonId0]
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data2 = dataGrid[latId0+1, lonId0+1]
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data3 = dataGrid[latId0, lonId0+1]
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else:
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data0 = dataGrid[:, latId0, lonId0]
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data1 = dataGrid[:, latId0+1, lonId0]
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data2 = dataGrid[:, latId0+1, lonId0+1]
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data3 = dataGrid[:, latId0, lonId0+1]
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data01 = (1-a)*data0+a*data1
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data32 = (1-a)*data3+a*data2
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data = (1-b)*data01+b*data32
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return data
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def normCoord(self, latGrid, lonGrid):
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"""
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坐标单位化
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"""
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lat0 = latGrid[0]
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lon0 = lonGrid[0]
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dlat = latGrid[1]-latGrid[0]
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dlon = lonGrid[1]-lonGrid[0]
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latId = (self.lat - lat0)/dlat
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lonId = (self.lon - lon0)/dlon
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return (latId, lonId)
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def get_bottomDepth(self):
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"""
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获得海底深度
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"""
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if (self.botDep == None):
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# 单位化经纬度
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(latId, lonId) = self.normCoord(self.latGrid1, self.lonGrid1)
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# 获取网格点海深
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self.botDep = self.interpBilinear(latId, lonId, self.botGrid, 1)
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return self.botDep
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def get_salRawProfile(self):
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"""
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获得原始盐度剖面
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"""
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if (self.salRawPf == None):
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botDep = self.get_bottomDepth()
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# 单位化经纬度
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(latId, lonId) = self.normCoord(self.latGrid2, self.lonGrid2)
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# 获取盐度剖面信息
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sal = self.interpBilinear(latId, lonId, self.salGrid, 2)
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# 获取有效数据段
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dep = self.depthGrid[sal.mask == False]
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sal = sal[sal.mask == False]
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dep = dep.flatten()
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sal = sal.flatten()
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# 若为空，则为无效数据
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if sal.size <= 1:
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self.isValid = False
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# 剖面赋值
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salRawPf = Profile()
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salRawPf.set_data(dep, sal)
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salRawPf.set_coord(self.lat, self.lon)
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salRawPf.set_bottomDepth(botDep)
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self.salRawPf = salRawPf
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return self.salRawPf
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def get_temRawProfile(self):
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"""
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获得原始温度剖面
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"""
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if (self.temRawPf == None):
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botDep = self.get_bottomDepth()
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# 单位化经纬度
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(latId, lonId) = self.normCoord(self.latGrid2, self.lonGrid2)
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# 获取温度剖面信息
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tem = self.interpBilinear(latId, lonId, self.temGrid, 2)
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# 获取有效数据段
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dep = self.depthGrid[tem.mask == False]
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tem = tem[tem.mask == False]
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dep = dep.flatten()
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tem = tem.flatten()
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# 若为空，则为无效数据
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if tem.size <= 1:
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self.isValid = False
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# 剖面赋值
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temRawPf = Profile()
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temRawPf.set_data(dep, tem)
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temRawPf.set_coord(self.lat, self.lon)
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temRawPf.set_bottomDepth(botDep)
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self.temRawPf = temRawPf
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return self.temRawPf
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def get_velRawProfile(self):
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"""
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获得原始声速剖面
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"""
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if (self.velRawPf == None):
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botDep = self.get_bottomDepth()
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# 获取温盐深数据
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dep = self.get_salRawProfile().x
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sal = self.get_salRawProfile().y
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tem = self.get_temRawProfile().y
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# 计算声速
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if self.isValid == True:
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vel = soundSpeed(tem, sal, dep)
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else:
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dep = np.array([0])
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vel = np.array([0])
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# 剖面赋值
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velRawPf = Profile()
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velRawPf.set_data(dep, vel)
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velRawPf.set_coord(self.lat, self.lon)
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velRawPf.set_bottomDepth(botDep)
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self.velRawPf = velRawPf
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return self.velRawPf
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def get_velInterpProfile(self):
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"""
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获得插值后的声速剖面
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将非等距离采样填充为深度间隔为1m的序列, 并应用Akima插值算法, 对数据进行插值
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"""
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if (self.velInterpPf == None):
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botDep = self.get_bottomDepth()
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# 获得原始声速剖面数据
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dep = self.get_velRawProfile().x
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vel = self.get_velRawProfile().y
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if self.isValid == True:
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# 对剖面进行垂向插值处理，将非等距离采样填充为深度间隔为1m的序列
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depInterp = np.arange(0, dep[-1]+1, 1)
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# 应用Akima插值算法，对数据进行插值
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func = Akima1DInterpolator(dep, vel)
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velInterp = func(depInterp)
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else:
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depInterp = np.array([0])
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velInterp = np.array([0])
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# 剖面赋值
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velInterpPf = Profile()
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velInterpPf.set_data(depInterp, velInterp)
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velInterpPf.set_coord(self.lat, self.lon)
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velInterpPf.set_bottomDepth(botDep)
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self.velInterpPf = velInterpPf
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return self.velInterpPf
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def get_velExtProfile(self):
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"""
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获得延拓后的声速剖面
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"""
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if (self.velExtPf == None):
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botDep = self.get_bottomDepth()
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if self.isValid == True:
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# 获得原始声速剖面数据
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dep = self.get_velRawProfile().x
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vel = self.get_velRawProfile().y
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# 获得剖面最低处温盐值
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tem = self.get_temRawProfile().y[-1]
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sal = self.get_salRawProfile().y[-1]
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# 延拓部分深度序列
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depExt = np.arange(dep[-1]+1, botDep+1)
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# 按照声速公式延拓，假设温盐不变，仅深度变化
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velExt = soundSpeed(tem, sal, depExt)
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else:
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depExt = np.array([0])
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velExt = np.array([0])
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# 剖面赋值
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velExtPf = Profile()
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velExtPf.set_data(depExt, velExt)
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velExtPf.set_coord(self.lat, self.lon)
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velExtPf.set_bottomDepth(botDep)
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self.velExtPf = velExtPf
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return self.velExtPf
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def get_velFullProfile(self):
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'''
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获得全海深声速剖面
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'''
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if (self.velFullPf == None):
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botDep = self.get_bottomDepth()
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if self.isValid == True:
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# 插值后的速度剖面
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depInterp = self.get_velInterpProfile().x
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velInterp = self.get_velInterpProfile().y
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# 延拓后的速度剖面
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depExt = self.get_velExtProfile().x
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velExt = self.get_velExtProfile().y
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# 全海深声速剖面
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depFull = np.concatenate((depInterp, depExt))
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velFull = np.concatenate((velInterp, velExt))
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else:
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depFull = np.array([0])
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velFull = np.array([0])
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# 剖面赋值
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velFullPf = Profile()
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velFullPf.set_data(depFull, velFull)
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velFullPf.set_coord(self.lat, self.lon)
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velFullPf.set_bottomDepth(botDep)
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self.velFullPf = velFullPf
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return self.velFullPf
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def export_velFullProfile_txt(self, filePath):
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'''
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速度剖面导出txt文件
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'''
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velPf = self.get_velFullProfile()
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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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# 导出文本
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line1 = 'lat[degree north], {0:>7.4f}, lon[degree east], {1:>7.4f}, BottomDepth[m], {2:>5.0f}\n'.format(
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lat, lon, botDep)
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line2 = 'depth[m], velocity[m/s]'
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np.savetxt(filePath, np.stack((dep, vel), -1),
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fmt='%.5e', delimiter=',', comments='', header=line1+line2)
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def export_velFullProfile_nc(self, filePath):
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'''
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速度剖面导出nc文件
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'''
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velPf = self.get_velFullProfile()
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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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data = Dataset(filePath, 'w', format='NETCDF4')
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data.createDimension('lon', 1)
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data.createDimension('lat', 1)
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data.createDimension('botDep', 1)
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data.createDimension('dep', dep.size)
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data.createDimension('vel', vel.size)
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data.createVariable('lon', 'f', ('lon'))
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data.createVariable('lat', 'f', ('lat'))
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data.createVariable('botDep', 'f', ('botDep'))
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data.createVariable('dep', 'f', ('dep'))
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data.createVariable('vel', 'f', ('vel'))
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data.variables['lat'][:] = lat
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data.variables['lon'][:] = lon
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data.variables['botDep'][:] = botDep
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data.variables['dep'][:] = dep
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data.variables['vel'][:] = vel
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data.close()
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在新工单中引用
屏蔽一个用户