我想将netCDF文件中的值转换为大于零的名为LandMask_NaN的NaN。但是，LandMask和numpy将转换为NaN之间似乎存在类型不匹配。任何帮助非常感谢，代码和信息如下：
import netCDF4 as nc
import numpy as np
import matplotlib.pyplot as plt
import csv as cs
import pandas as pd
ncfile = nc.Dataset('C:\Users\mmso2\Google Drive\ENVI_I-PAC_2007_10_21_21_22_47.nc')#office machine
SARwind = ncfile.variables['sar_wind']
ModelWind = ncfile.variables['model_speed']
LON = ncfile.variables['longitude']
LAT = ncfile.variables['latitude']
LandMask = ncfile.variables['mask']
#clean the data of values = 70
SARwind_nan = SARwind[:].copy()
SARwind_nan[SARwind_nan == 0.0] = np.nan
SARwind_nan[SARwind_nan == 70.0] = np.nan
#clear the data of values where there is land
# % pos = land; neg = water
LandMask_NaN = LandMask[:].copy()
#LandMask_NaN[int(float(LandMask_NaN))]### will not convert
LandMask_NaN[LandMask_NaN >0.0] = np.nan #error here
我得到的错误是
#error
line 37, in <module>
LandMask_NaN[LandMask_NaN >= 0.0] = np.nan
ValueError: cannot convert float NaN to integer
尝试时
LandMask_NaN[int(float(LandMask_NaN))]
或
LandMask_NaN[float(int(LandMask_NaN))]
在尝试转换为NaN之前，我得到了
TypeError: only length-1 arrays can be converted to Python scalars
检查LandMask的类型时我得到了
<type 'netCDF4._netCDF4.Variable'>
我不知道如何找出变量类型？
更新：nc变量的详细信息
NetCDF dimension information:
Name: x
size: 848
type: WARNING: x does not contain variable attributes
Name: y
size: 972
type: WARNING: y does not contain variable attributes
Name: xfit
size: 6
type: WARNING: xfit does not contain variable attributes
NetCDF variable information:
Name: acquisition_time
dimensions: ()
size: 1.0
type: dtype('float64')
units: u'seconds since 2000-01-01 00:00:00'
long_name: u'Acqusition time in Julian seconds since 2000-01-01T00:00:00Z'
standard_name: u'time'
calendar: u'gregorian'
Name: nx
dimensions: ()
size: 1.0
type: dtype('int32')
units: u'1'
long_name: u'Number of elements in this file'
Name: ny
dimensions: ()
size: 1.0
type: dtype('int32')
units: u'1'
long_name: u'Number of lines in this file'
Name: nx0
dimensions: ()
size: 1.0
type: dtype('int32')
units: u'1'
long_name: u'Number of elements in SIO file'
Name: ny0
dimensions: ()
size: 1.0
type: dtype('int32')
units: u'1'
long_name: u'Number of lines in SIO file'
Name: nx00
dimensions: ()
size: 1.0
type: dtype('int32')
units: u'1'
long_name: u'Number of elements in original SAR file'
Name: ny00
dimensions: ()
size: 1.0
type: dtype('int32')
units: u'1'
long_name: u'Number of lines in original SAR file'
Name: xn
dimensions: ()
size: 1.0
type: dtype('float32')
units: u'1'
long_name: u'1'
Name: yn
dimensions: ()
size: 1.0
type: dtype('float32')
units: u'1'
long_name: u'1'
Name: line_size
dimensions: ()
size: 1.0
type: dtype('float32')
units: u'm'
long_name: u'Line size'
Name: pixel_size
dimensions: ()
size: 1.0
type: dtype('float32')
units: u'm'
long_name: u'Pixel size'
Name: model_time_js
dimensions: ()
size: 1.0
type: dtype('float64')
units: u'seconds since 2000-01-01 00:00:00'
long_name: u'Model time julian seconds since 2000-01-01T00:00:00Z'
Name: model_time_js_tau
dimensions: ()
size: 1.0
type: dtype('float64')
units: u'seconds since 2000-01-01 00:00:00'
long_name: u'Model time plus tau julian seconds since 2000-01-01T00:00:00Z'
Name: upper_left_longitude
dimensions: ()
size: 1.0
type: dtype('float32')
units: u'degrees_east'
long_name: u'degrees'
Name: upper_right_longitude
dimensions: ()
size: 1.0
type: dtype('float32')
units: u'degrees_east'
long_name: u'degrees'
Name: upper_left_latitude
dimensions: ()
size: 1.0
type: dtype('float32')
units: u'degrees_north'
long_name: u'degrees'
Name: upper_right_latitude
dimensions: ()
size: 1.0
type: dtype('float32')
units: u'degrees_north'
long_name: u'degrees'
Name: start_center_longitude
dimensions: ()
size: 1.0
type: dtype('float32')
units: u'degrees_east'
long_name: u'degrees'
Name: start_center_latitude
dimensions: ()
size: 1.0
type: dtype('float32')
units: u'degrees_north'
long_name: u'degrees'
Name: scene_center_longitude
dimensions: ()
size: 1.0
type: dtype('float32')
units: u'degrees_east'
long_name: u'degrees'
Name: scene_center_latitude
dimensions: ()
size: 1.0
type: dtype('float32')
units: u'degrees_north'
long_name: u'degrees'
Name: lower_left_longitude
dimensions: ()
size: 1.0
type: dtype('float32')
units: u'degrees_east'
long_name: u'degrees'
Name: lower_right_longitude
dimensions: ()
size: 1.0
type: dtype('float32')
units: u'degrees_east'
long_name: u'degrees'
Name: lower_left_latitude
dimensions: ()
size: 1.0
type: dtype('float32')
units: u'degrees_north'
long_name: u'degrees'
Name: lower_right_latitude
dimensions: ()
size: 1.0
type: dtype('float32')
units: u'degrees_north'
long_name: u'degrees'
Name: end_center_longitude
dimensions: ()
size: 1.0
type: dtype('float32')
units: u'degrees_east'
long_name: u'degrees'
Name: end_center_latitude
dimensions: ()
size: 1.0
type: dtype('float32')
units: u'degrees_north'
long_name: u'degrees'
Name: northernmost_latitude
dimensions: ()
size: 1.0
type: dtype('float32')
units: u'degrees_north'
long_name: u'degrees'
Name: southernmost_latitude
dimensions: ()
size: 1.0
type: dtype('float32')
units: u'degrees_north'
long_name: u'degrees'
Name: easternmost_longitude
dimensions: ()
size: 1.0
type: dtype('float32')
units: u'degrees_east'
long_name: u'degrees'
Name: westernmost_longitude
dimensions: ()
size: 1.0
type: dtype('float32')
units: u'degrees_east'
long_name: u'degrees'
Name: nrcs_slope
dimensions: ()
size: 1.0
type: dtype('float32')
Name: nrcs_bias
dimensions: ()
size: 1.0
type: dtype('float32')
Name: sigma
dimensions: (u'y', u'x')
size: 824256
type: dtype('float32')
units: u'1'
long_name: u'Normalized Radar Cross Section.'
coordinates: u'longitude latitude'
Name: sar_wind
dimensions: (u'y', u'x')
size: 824256
type: dtype('float32')
units: u'm s-1'
long_name: u'SAR-derived wind speed at 10-m height neutral stability'
standard_name: u'wind_speed'
coordinates: u'longitude latitude'
Name: input_dir
dimensions: (u'y', u'x')
size: 824256
type: dtype('float32')
units: u'degrees'
long_name: u'Interpolated directions used for wind inversion'
coordinates: u'longitude latitude'
Name: model_speed
dimensions: (u'y', u'x')
size: 824256
type: dtype('float32')
units: u'm s-1'
long_name: u'Interpolated model wind speed (=1 for non model directions)'
standard_name: u'wind_speed'
coordinates: u'longitude latitude'
Name: mask
dimensions: (u'y', u'x')
size: 824256
type: dtype('int16')
units: u'1'
long_name: u'Interpolated land mask distance from shore line. Positive values land / Negative value water'
flag_values: array([-1, 0, 1], dtype=int16)
flag_meanings: u'water shore land'
coordinates: u'longitude latitude'
Name: longitude
dimensions: (u'y', u'x')
size: 824256
type: dtype('float32')
units: u'degrees_east'
long_name: u'Longitude array in decimal degrees'
standard_name: u'longitude'
Name: latitude
dimensions: (u'y', u'x')
size: 824256
type: dtype('float32')
units: u'degrees_north'
long_name: u'Latitude array in decimal degrees'
standard_name: u'latitude'
Name: rlook
dimensions: (u'y', u'x')
size: 824256
type: dtype('float32')
units: u'degrees'
long_name: u'Radar look direction array in decimal degrees from North'
coordinates: u'longitude latitude'
Name: incid
dimensions: (u'y', u'x')
size: 824256
type: dtype('float32')
units: u'degrees'
long_name: u'Incident angle array in degrees from nadir'
coordinates: u'longitude latitude'
Name: icemask
dimensions: (u'y', u'x')
size: 824256
type: dtype('int16')
units: u'1'
long_name: u'Ice mask 0=no_data 1=water 2=land 3=sea_ice 4=snow'
flag_values: array([0, 1, 2, 3, 4], dtype=int16)
flag_meanings: u'no_data water land sea_ice snow'
coordinates: u'longitude latitude'
Name: lon_coef
dimensions: (u'xfit',)
size: 6
type: dtype('float64')
units: u'1'
long_name: u'Coefficients to compute longitude in degs from pixel/lines'
Name: lon_xexp
dimensions: (u'xfit',)
size: 6
type: dtype('float32')
units: u'1'
long_name: u'Longitude pixel exponents'
Name: lon_yexp
dimensions: (u'xfit',)
size: 6
type: dtype('float32')
units: u'1'
long_name: u'Longitude line exponents'
Name: lat_coef
dimensions: (u'xfit',)
size: 6
type: dtype('float64')
units: u'1'
long_name: u'Coefficients to compute latitude in degs from pixel/lines'
Name: lat_xexp
dimensions: (u'xfit',)
size: 6
type: dtype('float32')
units: u'1'
long_name: u'Latitude pixel exponents'
Name: lat_yexp
dimensions: (u'xfit',)
size: 6
type: dtype('float32')
units: u'1'
long_name: u'Latitude line exponents'
Name: i_coef
dimensions: (u'xfit',)
size: 6
type: dtype('float64')
units: u'1'
long_name: u'Coefficients to compute pixel from longitue/latitude'
Name: i_xexp
dimensions: (u'xfit',)
size: 6
type: dtype('float32')
units: u'1'
long_name: u'Pixel longitude exponents'
Name: i_yexp
dimensions: (u'xfit',)
size: 6
type: dtype('float32')
units: u'1'
long_name: u'Pixel latitude exponents'
Name: j_coef
dimensions: (u'xfit',)
size: 6
type: dtype('float64')
units: u'1'
long_name: u'Coefficients to compute line from longitue/latitude'
Name: j_xexp
dimensions: (u'xfit',)
size: 6
type: dtype('float32')
units: u'1'
long_name: u'Line longitude exponents'
Name: j_yexp
dimensions: (u'xfit',)
size: 6
type: dtype('float32')
units: u'1'
long_name: u'Line latitude exponents'
Name: incid_coef
dimensions: (u'xfit',)
size: 6
type: dtype('float64')
units: u'1'
long_name: u'Coefficients to compute incid in degs from pixel/lines'
Name: incid_xexp
dimensions: (u'xfit',)
size: 6
type: dtype('float32')
units: u'1'
long_name: u'Incid pixel exponents'
Name: incid_yexp
dimensions: (u'xfit',)
size: 6
type: dtype('float32')
units: u'1'
long_name: u'Incid line exponents'
Name: rlook_coef
dimensions: (u'xfit',)
size: 6
type: dtype('float64')
units: u'1'
long_name: u'Coefficients to compute radar look direction in degs from pixel/lines'
Name: rlook_xexp
dimensions: (u'xfit',)
size: 6
type: dtype('float32')
units: u'1'
long_name: u'Radar look direction pixel exponents'
Name: rlook_yexp
dimensions: (u'xfit',)
size: 6
type: dtype('float32')
units: u'1'
long_name: u'Radar look direction line exponents'
答案 0 :(得分：1)
如果您分享netcdf文件，它会有所帮助，但这里有一些关于发生了什么的想法：
当前没有将变量作为numpy数组读入。您需要添加索引参数以将它们转换为数组。没有文件，我不确定它们是什么，但肯定有些是多维的。例如：
SARwind = ncfile.variables['sar_wind'][:,:]
ModelWind = ncfile.variables['model_speed'][:,:]
LON = ncfile.variables['longitude'][:]
LAT = ncfile.variables['latitude'][:]
LandMask = ncfile.variables['mask'][:,:]
然后，您只需将SARwind分配给新变量SARWind_nan并输入nan值，就像您一直在做的那样。
SARWind_nan = SARwind
SARwind_nan[SARwind_nan == 0.0] = np.nan
SARwind_nan[SARwind_nan == 70.0] = np.nan
LandMask正确读入（再次，我认为这很可能是2D，而不是1D），您可以类似地分配给新变量LandMask_nan并输入{{1} }值。仔细检查nan的类型，它可能是一个整数。 ncdump或ncks是检查netcdf内容的好工具。
LandMask