read_nc.py

from netCDF4 import Dataset
import numpy as npfile = 'file.nc'nc_obj=Dataset(file)#查看nc文件信息
print(nc_obj)
print(nc_obj.dimensions)
print('---------------------------------------')#查看每个变量的信息
for var_name in nc_obj.variables.keys():print(f'var name: {var_name}')var = nc_obj.variables[var_name]for arrt_name in var.ncattrs():print(f'arrt name: {arrt_name}, arrt value: {var.__dict__[arrt_name]}')print('')
print('---------------------------------------')#读取数据值
for var_name in nc_obj.variables.keys():var = nc_obj.variables[var_name]data = var[:]data = np.array(data)if '_FillValue' in var.__dict__:fillvalue = var.__dict__['_FillValue']data = np.where(data==fillvalue, data, np.nan)#data[data==fillValue] = np.nanif 'missing_value' in var.__dict__:missing_value = var.__dict__['missing_value']data = np.where(data==missing_value, data, np.nan)if 'valid_min' in var.__dict__:valid_min = var.__dict__['valid_min']data = np.where(data<valid_min, data, np.nan)#data[data<valid_min] = np.nanif 'valid_max' in var.__dict__:valid_max = var.__dict__['valid_max']data = np.where(data>valid_max, data, np.nan)if 'valid_range' in var.__dict__:valid_range = var.__dict__['valid_range']data = np.where(data<valid_range[0], data, np.nan)data = np.where(data>valid_range[1], data, np.nan)scale_factor = var.__dict__.get('scale_factor', 1.0) add_offset = var.__dict__.get('add_offset', 0.0)data =  data * scale_factor + add_offset#print(np.nanmax(data))#print(np.nanmin(data))print(data)print('')
print('---------------------------------------')

change_nc.py

from netCDF4 import DatasetncFile = 'test.nc'
dataset = Dataset(ncFile, 'r+')dataset.variables['lon'][0]=99.9
dataset.variables['chlor_a'][0, 0] =  99.9for key in dataset.variables.keys():print(dataset.variables[key])dataset.close()

nc2rgb.py

from netCDF4 import Dataset
from time import time
from PIL import Image, ImageDraw
import numpy as np
import mathdef getInd( sample, value ):number=len(sample)if value<=sample[0]:ind=0elif value>=sample[number-1]:ind=sample[number-1]else:i=1while value>sample[i]:i+=1ind=i-1 + (value-sample[i-1])/(sample[i]-sample[i-1])   return inddef getColor( color, ind ):number=len(color)if ind<=0:r, g, b = color[0]elif ind>=number-1:r, g, b = color[number-1]else:ind1 = math.floor(ind)ind2 = ind1+1r = round( color[ind1][0] * (ind2-ind) + color[ind2][0] * (ind-ind1) )g = round( color[ind1][1] * (ind2-ind) + color[ind2][1] * (ind-ind1) )b = round( color[ind1][2] * (ind2-ind) + color[ind2][2] * (ind-ind1) )return r, g, bstart = time()
print("Start: " + str(start))color =((147,0,108),(111,0,144 ),(72,0,183  ),(33,0,222  ),(0,10,255  ),(0,74,255  ),(0,144,255 ),(0,213,255 ),(0,255,215 ),(0,255,119 ),(0,255,15  ),(96,255,0  ),(200,255,0 ),(255,235,0 ),(255,183,0 ),(255,131,0 ),(255,79,0  ),(255,31,0  ),(230,0,0   ),(165,0,0   ),(105,0,0   ))sample=(0.0000,0.0471,0.0980,0.1490,0.2000,0.2471,0.2980,0.3490,0.4000,0.4471,0.4980,0.5490,0.6000,0.6471,0.6980,0.7490,0.8000,0.8471,0.8980,0.9490,1.0000)file = 'V2020214.L3m_DAY_JPSS1_CHL_chlor_a_9km.nc'dataSet=Dataset(file)chl=dataSet.variables['chlor_a']fillValue=chl._FillValue
validMin=chl.valid_min
validMax=chl.valid_maxdisplayMin=chl.display_min
displayMax=chl.display_maxdisplayScale=chl.display_scalechlValue=np.array(chl)tmp = chlValue.flatten()tmp[tmp==fillValue]=np.nan
tmp[tmp<validMin]=np.nan
tmp[tmp>validMax]=np.nannanInd = np.isnan(tmp)tmp[tmp<displayMin]=displayMin
tmp[tmp>displayMax]=displayMaxtmp[nanInd]=displayMinif displayScale=='log':tmp = (np.log(tmp)-np.log(displayMin))/(np.log(displayMax)-np.log(displayMin))
else:tmp = (tmp-displayMin)/(displayMax-displayMin)backColor=(0, 0, 0)
nanColor=(255, 255, 255)
width = 4320
height = 2160
image = Image.new('RGB', (width, height), backColor)draw = ImageDraw.Draw(image)for y in range(height):for x in range(width):value = x + width * yind = getInd( sample, tmp[value] )r, g, b = getColor( color, ind )if nanInd[value]:draw.point((x, y), fill=nanColor)else:draw.point((x, y), fill=(r, g, b))image.save('chl.png', 'png')stop = time()
print("Stop: " + str(stop))
print(str(stop-start) + "秒")

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Python netCDF4

Python netCDF4

read_nc.py

change_nc.py

nc2rgb.py

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