MeteoInfoLab脚本示例：CALIPSO Backscatter data

MeteoInfo · 发表于 2016-2-19 12:42:42

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本帖最后由 MeteoInfo 于 2016-2-19 14:12 编辑

读取和绘制CALIPSO卫星遥感数据中的Total Attenuated Backscatter变量。

# Add file
fn = 'D:/Temp/hdf/CAL_LID_L1-ValStage1-V3-01.2007-06-12T03-42-18ZN.hdf'
f = addfile(fn)
# Read data
vname = 'Total_Attenuated_Backscatter_532'
var = f[vname]
data = var[:1000,:]
data = rot90(data)
lats = f['latitude'][:1000,0]
latstrs = []
for lat in lats:
latstrs.append('%.1f' % lat)
height = f['metadata'][None]
m = height.findMember('Lidar_Data_Altitudes')
h = array(height.getArray(0, m))
h = h[::-1]
hstrs = []
for hh in h:
hstrs.append('%.1f' % hh)
# Plot
levs = [0.0001,0.0002,0.0003,0.0004,0.0005,0.0006,0.0007,0.0008,0.0009,\
0.001,0.0015,0.002,0.0025,0.003,0.0035,0.004,0.0045,0.005,0.0055,0.006,\
0.0065,0.007,0.0075,0.008,0.01,0.02,0.03,0.04,0.05,0.06,0.07,0.08,0.09,01]
layer = imshow(data, levs, cmap='MPL_terrain')
xticks(data.dimvalue(1), latstrs)
yticks(data.dimvalue(0), hstrs)
xlabel('Latitude')
ylabel('Altitude (km)')
colorbar(layer, label=r'$\rm{km}^{-1}$ \rm{sr}$^{-1}')
basename = os.path.basename(fn)
title('{0}\n{1}'.format(basename, vname))

# Add file 
fn = 'D:/Temp/hdf/CAL_LID_L1-ValStage1-V3-01.2007-06-12T03-42-18ZN.hdf' 
f = addfile(fn) 
 
# Read data 
vname = 'Total_Attenuated_Backscatter_532' 
var = f[vname] 
data = var[:1000,:] 
data = rot90(data) 
lats = f['latitude'][:1000,0] 
latstrs = [] 
for lat in lats: 
    latstrs.append('%.1f' % lat) 
height = f['metadata'][None] 
m = height.findMember('Lidar_Data_Altitudes') 
h = array(height.getArray(0, m)) 
h = h[::-1] 
hstrs = [] 
for hh in h: 
    hstrs.append('%.1f' % hh) 
 
# Plot 
levs = [0.0001,0.0002,0.0003,0.0004,0.0005,0.0006,0.0007,0.0008,0.0009,\ 
    0.001,0.0015,0.002,0.0025,0.003,0.0035,0.004,0.0045,0.005,0.0055,0.006,\ 
    0.0065,0.007,0.0075,0.008,0.01,0.02,0.03,0.04,0.05,0.06,0.07,0.08,0.09,01] 
layer = imshow(data, levs, cmap='MPL_terrain') 
xticks(data.dimvalue(1), latstrs) 
yticks(data.dimvalue(0), hstrs) 
xlabel('Latitude') 
ylabel('Altitude (km)') 
colorbar(layer, label=r'$\rm{km}^{-1}$ \rm{sr}$^{-1}') 
basename = os.path.basename(fn) 
title('{0}\n{1}'.format(basename, vname))

MeteoInfo · 发表于 2016-2-19 15:46:38

本帖最后由 MeteoInfo 于 2019-10-30 15:47 编辑

基于CAPLISO官网上MatLab例子中的kathys_lidar_colors.m程序，写了一个生成和官网色标一致的色标生成脚本。本例中使用的数据文件来自此网页：http://ccplot.org/api/ ，利用新色标生成的图形如下：

脚本程序文件：

CALIPSO_L1.py (1.46 KB, 下载次数: 33)

2018-8-10 15:09 上传

点击文件名下载附件

生成色标的脚本程序（CAPLIPSO_colors.py）：

import mipylib.numeric as np
def makecolors(gray=True):
"""
Return colors for CAPLIPSO backscatter data plot.
:param gray: Using gray scale colors or not.
:returns: Colors.
Acknowledgements: This is mostly copied from Kathy Powells IDL routine(s) to generate a
color map and colorbar for plotting CALIPSO lidar data. Thank you Kathy!
"""
red_c=[0.0,0.0,42.5,85.0,127.5,170.0,212.5,255.0,0.0,42.5,85.0,127.5,170.0,212.5,255.0,\
0.0,42.5,85.0,127.5,170.0,212.5,255.0,0.0,42.5,85.0,127.5,170.0,212.5,255.0,\
0.0,42.5,85.0,127.5,170.0,212.5,255.0,0.0,42.5,85.0,127.5,170.0,212.5,255.0,\
0.0,42.5,85.0,127.5,170.0,212.5,255.0,0.0,42.5,85.0,127.5,170.0,212.5,255.0,\
0.0,42.5,85.0,127.5,170.0,212.5,255.0,0.0,42.5,85.0,127.5,170.0,212.5,255.0,\
0.0,42.5,85.0,127.5,170.0,212.5,255.0,0.0,42.5,85.0,127.5,170.0,212.5,255.0,\
0.0,42.5,85.0,127.5,170.0,212.5,255.0,\
0.0,0.0,0.0,0.0,0.0,0.0,42.5,85.0,127.5,170.0,212.5,255.0,255.0,255.0,255.0,255.0,255.0,\
0.0,0.0,0.0,0.0,0.0,0.0,42.5,85.0,127.5,170.0,212.5,255.0,255.0,255.0,255.0,255.0,255.0,\
0.0,0.0,0.0,0.0,0.0,0.0,42.5,85.0,127.5,170.0,212.5,255.0,255.0,255.0,255.0,255.0,255.0,\
0.0,0.0,0.0,0.0,0.0,0.0,42.5,85.0,127.5,170.0,212.5,255.0,255.0,255.0,255.0,255.0,255.0,\
0.0,0.0,0.0,0.0,0.0,0.0,42.5,85.0,127.5,170.0,212.5,255.0,255.0,255.0,255.0,255.0,255.0,\
0.0,0.0,0.0,0.0,0.0,0.0,42.5,85.0,127.5,170.0,212.5,255.0,255.0,255.0,255.0,255.0,255.0,\
42.5,85.0,127.5,170.0,212.5,42.5,85.0,127.5,170.0,212.5,\
42.5,85.0,127.5,170.0,212.5,42.5,85.0,127.5,170.0,212.5,42.5,85.0,127.5,170.0,212.5]
green_c=[0.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,\
255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,\
255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,\
255.0,255.0,255.0,255.0,255.0,255.0,255.0,212.5,212.5,212.5,212.5,212.5,212.5,212.5,\
170.0,170.0,170.0,170.0,170.0,170.0,170.0,127.5,127.5,127.5,127.5,127.5,127.5,127.5,\
85.0,85.0,85.0,85.0,85.0,85.0,85.0,42.5,42.5,42.5,42.5,42.5,42.5,42.5,\
0.0,0.0,0.0,0.0,0.0,0.0,0.0,\
212.5,170.0,127.5,85.0,42.5,0.0,0.0,0.0,0.0,0.0,0.0,0.0,42.5,85.0,127.5,170.0,212.5,\
212.5,170.0,127.5,85.0,42.5,0.0,0.0,0.0,0.0,0.0,0.0,0.0,42.5,85.0,127.5,170.0,212.5,\
212.5,170.0,127.5,85.0,42.5,0.0,0.0,0.0,0.0,0.0,0.0,0.0,42.5,85.0,127.5,170.0,212.5,\
212.5,170.0,127.5,85.0,42.5,0.0,0.0,0.0,0.0,0.0,0.0,0.0,42.5,85.0,127.5,170.0,212.5,\
212.5,170.0,127.5,85.0,42.5,0.0,0.0,0.0,0.0,0.0,0.0,0.0,42.5,85.0,127.5,170.0,212.5,\
212.5,170.0,127.5,85.0,42.5,0.0,0.0,0.0,0.0,0.0,0.0,0.0,42.5,85.0,127.5,170.0,212.5,\
42.5,42.5,42.5,42.5,42.5,85.0,85.0,85.0,85.0,85.0,\
127.5,127.5,127.5,127.5,127.5,170.0,170.0,170.0,170.0,170.0,212.5,212.5,212.5,212.5,212.5]
blue_c=[0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,42.5,42.5,42.5,42.5,42.5,42.5,42.5,\
85.0,85.0,85.0,85.0,85.0,85.0,85.0,127.5,127.5,127.5,127.5,127.5,127.5,127.5,\
170.0,170.0,170.0,170.0,170.0,170.0,170.0,212.5,212.5,212.5,212.5,212.5,212.5,212.5,\
255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,\
255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,\
255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,\
255.0,255.0,255.0,255.0,255.0,255.0,255.0,\
212.5,212.5,212.5,212.5,212.5,212.5,212.5,212.5,212.5,212.5,212.5,212.5,212.5,212.5,212.5,212.5,212.5,\
170.0,170.0,170.0,170.0,170.0,170.0,170.0,170.0,170.0,170.0,170.0,170.0,170.0,170.0,170.0,170.0,170.0,\
127.5,127.5,127.5,127.5,127.5,127.5,127.5,127.5,127.5,127.5,127.5,127.5,127.5,127.5,127.5,127.5,127.5,\
85.0,85.0,85.0,85.0,85.0,85.0,85.0,85.0,85.0,85.0,85.0,85.0,85.0,85.0,85.0,85.0,85.0,\
42.5,42.5,42.5,42.5,42.5,42.5,42.5,42.5,42.5,42.5,42.5,42.5,42.5,42.5,42.5,42.5,42.5,\
0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,\
0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,\
0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0]
if gray:
g_scale = [70,100,130,155,180,200,225,235,240,242,245,249,253]
ix1 = 10
ix2 = 23
red_c[ix1:ix2] = g_scale[0:13];
green_c[ix1:ix2] = g_scale[0:13];
blue_c[ix1:ix2] = g_scale[0:13];
red_c[0] = red_c[49]
green_c[0] = green_c[49]
blue_c[0] = blue_c[49]
color_bar = np.array([130,113,113, 64, 57, 50, 43, 36, 29,128,144, 7, 7,193,192,191,190,188,155,139,123, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 49])
#color_bar = color_bar + 1
colors = []
for j in color_bar:
r = red_c[j]
g = green_c[j]
b = blue_c[j]
colors.append([int(r),int(g),int(b)])
return colors

import mipylib.numeric as np 
def makecolors(gray=True): 
    """ 
    Return colors for CAPLIPSO backscatter data plot. 
 
    :param gray: Using gray scale colors or not. 
 
    :returns: Colors. 
 
    Acknowledgements: This is mostly copied from Kathy Powells IDL routine(s) to generate a 
        color map and colorbar for plotting CALIPSO lidar data. Thank you Kathy! 
    """ 
    red_c=[0.0,0.0,42.5,85.0,127.5,170.0,212.5,255.0,0.0,42.5,85.0,127.5,170.0,212.5,255.0,\ 
        0.0,42.5,85.0,127.5,170.0,212.5,255.0,0.0,42.5,85.0,127.5,170.0,212.5,255.0,\ 
        0.0,42.5,85.0,127.5,170.0,212.5,255.0,0.0,42.5,85.0,127.5,170.0,212.5,255.0,\ 
        0.0,42.5,85.0,127.5,170.0,212.5,255.0,0.0,42.5,85.0,127.5,170.0,212.5,255.0,\ 
        0.0,42.5,85.0,127.5,170.0,212.5,255.0,0.0,42.5,85.0,127.5,170.0,212.5,255.0,\ 
        0.0,42.5,85.0,127.5,170.0,212.5,255.0,0.0,42.5,85.0,127.5,170.0,212.5,255.0,\ 
        0.0,42.5,85.0,127.5,170.0,212.5,255.0,\ 
        0.0,0.0,0.0,0.0,0.0,0.0,42.5,85.0,127.5,170.0,212.5,255.0,255.0,255.0,255.0,255.0,255.0,\ 
        0.0,0.0,0.0,0.0,0.0,0.0,42.5,85.0,127.5,170.0,212.5,255.0,255.0,255.0,255.0,255.0,255.0,\ 
        0.0,0.0,0.0,0.0,0.0,0.0,42.5,85.0,127.5,170.0,212.5,255.0,255.0,255.0,255.0,255.0,255.0,\ 
        0.0,0.0,0.0,0.0,0.0,0.0,42.5,85.0,127.5,170.0,212.5,255.0,255.0,255.0,255.0,255.0,255.0,\ 
        0.0,0.0,0.0,0.0,0.0,0.0,42.5,85.0,127.5,170.0,212.5,255.0,255.0,255.0,255.0,255.0,255.0,\ 
        0.0,0.0,0.0,0.0,0.0,0.0,42.5,85.0,127.5,170.0,212.5,255.0,255.0,255.0,255.0,255.0,255.0,\ 
        42.5,85.0,127.5,170.0,212.5,42.5,85.0,127.5,170.0,212.5,\ 
        42.5,85.0,127.5,170.0,212.5,42.5,85.0,127.5,170.0,212.5,42.5,85.0,127.5,170.0,212.5] 
 
    green_c=[0.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,\ 
        255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,\ 
        255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,\ 
        255.0,255.0,255.0,255.0,255.0,255.0,255.0,212.5,212.5,212.5,212.5,212.5,212.5,212.5,\ 
        170.0,170.0,170.0,170.0,170.0,170.0,170.0,127.5,127.5,127.5,127.5,127.5,127.5,127.5,\ 
        85.0,85.0,85.0,85.0,85.0,85.0,85.0,42.5,42.5,42.5,42.5,42.5,42.5,42.5,\ 
        0.0,0.0,0.0,0.0,0.0,0.0,0.0,\ 
        212.5,170.0,127.5,85.0,42.5,0.0,0.0,0.0,0.0,0.0,0.0,0.0,42.5,85.0,127.5,170.0,212.5,\ 
        212.5,170.0,127.5,85.0,42.5,0.0,0.0,0.0,0.0,0.0,0.0,0.0,42.5,85.0,127.5,170.0,212.5,\ 
        212.5,170.0,127.5,85.0,42.5,0.0,0.0,0.0,0.0,0.0,0.0,0.0,42.5,85.0,127.5,170.0,212.5,\ 
        212.5,170.0,127.5,85.0,42.5,0.0,0.0,0.0,0.0,0.0,0.0,0.0,42.5,85.0,127.5,170.0,212.5,\ 
        212.5,170.0,127.5,85.0,42.5,0.0,0.0,0.0,0.0,0.0,0.0,0.0,42.5,85.0,127.5,170.0,212.5,\ 
        212.5,170.0,127.5,85.0,42.5,0.0,0.0,0.0,0.0,0.0,0.0,0.0,42.5,85.0,127.5,170.0,212.5,\ 
        42.5,42.5,42.5,42.5,42.5,85.0,85.0,85.0,85.0,85.0,\ 
        127.5,127.5,127.5,127.5,127.5,170.0,170.0,170.0,170.0,170.0,212.5,212.5,212.5,212.5,212.5] 
 
    blue_c=[0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,42.5,42.5,42.5,42.5,42.5,42.5,42.5,\ 
        85.0,85.0,85.0,85.0,85.0,85.0,85.0,127.5,127.5,127.5,127.5,127.5,127.5,127.5,\ 
        170.0,170.0,170.0,170.0,170.0,170.0,170.0,212.5,212.5,212.5,212.5,212.5,212.5,212.5,\ 
        255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,\ 
        255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,\ 
        255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,255.0,\ 
        255.0,255.0,255.0,255.0,255.0,255.0,255.0,\ 
        212.5,212.5,212.5,212.5,212.5,212.5,212.5,212.5,212.5,212.5,212.5,212.5,212.5,212.5,212.5,212.5,212.5,\ 
        170.0,170.0,170.0,170.0,170.0,170.0,170.0,170.0,170.0,170.0,170.0,170.0,170.0,170.0,170.0,170.0,170.0,\ 
        127.5,127.5,127.5,127.5,127.5,127.5,127.5,127.5,127.5,127.5,127.5,127.5,127.5,127.5,127.5,127.5,127.5,\ 
        85.0,85.0,85.0,85.0,85.0,85.0,85.0,85.0,85.0,85.0,85.0,85.0,85.0,85.0,85.0,85.0,85.0,\ 
        42.5,42.5,42.5,42.5,42.5,42.5,42.5,42.5,42.5,42.5,42.5,42.5,42.5,42.5,42.5,42.5,42.5,\ 
        0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,\ 
        0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,\ 
        0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0] 
 
    if gray: 
        g_scale = [70,100,130,155,180,200,225,235,240,242,245,249,253] 
        ix1 = 10 
        ix2 = 23 
        red_c[ix1:ix2] = g_scale[0:13]; 
        green_c[ix1:ix2] = g_scale[0:13]; 
        blue_c[ix1:ix2] = g_scale[0:13]; 
 
    red_c[0] = red_c[49] 
    green_c[0] = green_c[49] 
    blue_c[0] = blue_c[49] 
 
    color_bar = np.array([130,113,113, 64, 57, 50, 43, 36, 29,128,144,  7,  7,193,192,191,190,188,155,139,123, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 49]) 
    #color_bar = color_bar + 1 
    colors = [] 
    for j in color_bar: 
        r = red_c[j] 
        g = green_c[j] 
        b = blue_c[j] 
        colors.append([int(r),int(g),int(b)]) 
    return colors

读取数据并绘图的脚本：

sys.path.append('D:/Working/MIScript/Jython/mis/hdf')
import CALIPSO_colors
# Add file
fn = 'D:/Temp/hdf/CAL_LID_L1-ValStage1-V3-01.2007-06-12T03-42-18ZN.hdf'
f = addfile(fn)
# Read data
x1 = 0
x2 = 1001
nx = x2 - x1
h1 = 0 # km
h2 = 20 # km
nz = 500 # Number of pixels in the vertical
vname = 'Total_Attenuated_Backscatter_532'
var = f[vname]
data = var[x1:x2,:]
data = rot90(data)
lats = f['Latitude'][x1:x2,0]
lons = f['Longitude'][x1:x2,0]
height = f['metadata']['Lidar_Data_Altitudes']
height = height[::-1]
data.setdimvalue(0, height)
# Interpolate data on a regular grid
x = arange(x1, x2)
h = linspace(h1, h2, nz)
data = np.linint2(data, x, h)
# X axis ticks
xvals = []
xstrs = []
for j in range(0, nx, 200):
xvals.append(j + x1)
if j == 0:
xstrs.append('Lat: %.2f\nLon: %.2f' % (lats[j],lons[j]))
else:
xstrs.append('%.2f\n%.2f' % (lats[j],lons[j]))
# Plot
levs = [0.0001,0.0002,0.0003,0.0004,0.0005,0.0006,0.0007,0.0008,0.0009,\
0.001,0.0015,0.002,0.0025,0.003,0.0035,0.004,0.0045,0.005,0.0055,0.006,\
0.0065,0.007,0.0075,0.008,0.01,0.02,0.03,0.04,0.05,0.06,0.07,0.08,0.09,0.1]
colors = CALIPSO_colors.makecolors()
layer = imshow(x, h, data, levs, colors=colors)
xaxis(tickin=False)
yaxis(tickin=False)
xticks(xvals, xstrs)
ylabel('Altitude (km)')
colorbar(layer, extendrect=False, label=r'$\rm{km}^{-1}$ \rm{sr}$^{-1}$')
basename = os.path.basename(fn)
title('{0}\n{1}'.format(basename, vname))

sys.path.append('D:/Working/MIScript/Jython/mis/hdf') 
import CALIPSO_colors 
 
# Add file 
fn = 'D:/Temp/hdf/CAL_LID_L1-ValStage1-V3-01.2007-06-12T03-42-18ZN.hdf' 
f = addfile(fn) 
 
# Read data 
x1 = 0 
x2 = 1001 
nx = x2 - x1 
h1 = 0  # km 
h2 = 20  # km 
nz = 500  # Number of pixels in the vertical 
vname = 'Total_Attenuated_Backscatter_532' 
var = f[vname] 
data = var[x1:x2,:] 
data = rot90(data) 
lats = f['Latitude'][x1:x2,0] 
lons = f['Longitude'][x1:x2,0] 
height = f['metadata']['Lidar_Data_Altitudes'] 
height = height[::-1] 
data.setdimvalue(0, height) 
 
# Interpolate data on a regular grid 
x = arange(x1, x2) 
h = linspace(h1, h2, nz) 
data = np.linint2(data, x, h) 
 
# X axis ticks 
xvals = [] 
xstrs = [] 
for j in range(0, nx, 200): 
    xvals.append(j + x1) 
    if j == 0: 
        xstrs.append('Lat: %.2f\nLon: %.2f' % (lats[j],lons[j])) 
    else: 
        xstrs.append('%.2f\n%.2f' % (lats[j],lons[j])) 
 
# Plot 
levs = [0.0001,0.0002,0.0003,0.0004,0.0005,0.0006,0.0007,0.0008,0.0009,\ 
    0.001,0.0015,0.002,0.0025,0.003,0.0035,0.004,0.0045,0.005,0.0055,0.006,\ 
    0.0065,0.007,0.0075,0.008,0.01,0.02,0.03,0.04,0.05,0.06,0.07,0.08,0.09,0.1] 
colors = CALIPSO_colors.makecolors() 
layer = imshow(x, h, data, levs, colors=colors) 
xaxis(tickin=False) 
yaxis(tickin=False) 
xticks(xvals, xstrs) 
ylabel('Altitude (km)') 
colorbar(layer, extendrect=False, label=r'$\rm{km}^{-1}$ \rm{sr}$^{-1}$') 
basename = os.path.basename(fn) 
title('{0}\n{1}'.format(basename, vname))

rjys1219 · 发表于 2016-3-15 08:01:36

谢谢王老师分享，漂亮哈

2020Doraemon · 发表于 2016-4-17 16:42:47

请问楼主这句代码“from mipylib.midata import array”如何实现啊，我运行出来总是提示 ImportError: No module named midata

MeteoInfo · 发表于 2016-4-17 18:17:48

2020Doraemon 发表于 2016-4-17 16:42
请问楼主这句代码“from mipylib.midata import array”如何实现啊，我运行出来总是提示 ImportError: No m ...

midata改为minum

直来直往 · 发表于 2016-4-18 10:24:37

请问楼主，L1的后向散射数据，质量控制参数如何设置呀？

我才开始学，还请老师不吝赐教，谢谢谢谢~~

MeteoInfo · 发表于 2016-4-18 13:47:49

直来直往发表于 2016-4-18 10:24
请问楼主，L1的后向散射数据，质量控制参数如何设置呀？我才开始学，还请老师不吝赐教，谢谢谢谢~ ...

我也没有真正用过此类数据，帮不了你

2020Doraemon · 发表于 2016-4-18 20:44:16

MeteoInfo 发表于 2016-4-17 18:17
midata改为minum

谢谢楼主！

直来直往 · 发表于 2016-4-21 16:09:56

MeteoInfo 发表于 2016-4-18 13:47
我也没有真正用过此类数据，帮不了你

好吧

，还是谢谢啦~

aa22556688 · 发表于 2016-4-28 10:53:24

老师，这个可以用于2级数据吗？

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