def createHDF(allvars):
varinfo = {
0:
'nametimestamp',
1:
'calipso fname',
2:
'mod21km fname',
3:
'mod03 fname',
4:
'myd35 fnames',
5: ['Latitude', {
'units': 'deg',
'valid_range': '-90.0...90.0'
}],
6: ['Longitude', {
'units': 'deg',
'valid_range': '-90.0...90.0'
}],
7:
['IGBP_Surface_Type', {
'units': 'no units',
'valid_range': '1... 18'
}],
8: ['DEM_Surface_Elevation', {
'units': 'km'
}],
9: ['Layer_Top_Altitude', {
'units': 'km',
'fill_value': '-9999'
}],
10: ['Feature_Classification_Flags', {}],
11: [
'SCM_classification', {
'valid_range': '0,1',
'description': '1:Layered\n0:clear'
}
],
12: [
'Clear_Layered_Mask', {
'valid_range':
'0...4',
'description':
'4:Invalid\n3:Cloud+Aerosol\n2:Aerosol\n1:Cloud\n0:Clear'
}
],
13: ['Cloud_Mask', {}],
14: [
'Confusion_Matrix_SCM', {
'valid_range':
'-2,-1,1,2',
'description':
'2:True Layered\n1:True Clear\n-1:False Clear\n-2:False Layered'
}
],
15: [
'Confusion_Matrix_CM', {
'valid_range':
'-2,-1,1,2',
'description':
'2:True Layered\n1:True Clear\n-1:False Clear\n-2:False Layered'
}
],
16: ['Number_Layers_Found', {}],
17: ['SensorZenith', {
'units': 'deg',
'valid_range': '0.0...180.0'
}],
18: ['SensorAzimuth', {
'units': 'deg',
'valid_range': '0.0...180.0'
}],
19:
['Solar_Zenith_Angle', {
'units': 'deg',
'valid_range': '0.0...180.0'
}],
20: [
'Solar_Azimuth_Angle', {
'units': 'deg',
'valid_range': '0.0...180.0'
}
],
21: ['Layer_Base_Altitude', {
'units': 'km'
}],
22: ['Layer_Top_Pressure', {}],
23: ['Midlayer_Pressure', {}],
24: ['Layer_Base_Pressure', {}],
25: ['Layer_Top_Temperature', {}],
26: ['Layer_Centroid_Temperature', {}],
27: ['Midlayer_Temperature', {}],
28: ['Layer_Base_Temperature', {}],
29: ['CAD_Score', {
'fill_value': '-127'
}],
30: ['Initial_CAD_Score', {
'fill_value': '-127'
}],
31: [
'Profile_UTC_Time', {
'units': 'no units',
'valid_range': '60,426.0...261,231.0'
}
],
32: [
'Snow_Ice_Surface_Type', {
'units': 'no units',
'valid_range': '0.0...255.0'
}
],
33:
['Scattering_Angle', {
'units': 'deg',
'valid_range': '0.0...180.0'
}],
34: ['Skill_Score', {}],
35: ['Hit_Rate', {}]
}
data_types = {
'float64': SDC.FLOAT64,
'float32': SDC.FLOAT32,
'int32': SDC.INT32,
'uint32': SDC.UINT32,
'int16': SDC.INT16,
'uint16': SDC.UINT16,
'int8': SDC.INT8,
'uint8': SDC.UINT8,
'<U11': SDC.UCHAR
}
filename = 'CALTRACK-333m_SCM_V1-1_' + allvars[
0] + '.hdf' # Create HDF file.
print(filename)
path = 'E:\\Custom_HDFs\\'
hdfFile = SD(path + filename, SDC.WRITE | SDC.CREATE)
# Assign a few attributes at the file level
hdfFile.File_Name = filename
hdfFile.Timestamp = allvars[0]
hdfFile.Fill_Value = -9999
hdfFile.Description = 'SCM, VFM, MYD35 cloud classifications coincident with the CALIOP 333m track'
fused = f'{allvars[1]}\n{allvars[2]}\n{allvars[3]}\n' + '\n'.join(
str(s) for s in allvars[4])
hdfFile.Files_Used = fused
#Parametirize this
print('SKILL SCORES:', allvars[34])
hdfFile.Skill_Scores = f'MYD35:{allvars[34][0]}\nSCM:{allvars[34][1]}'
hdfFile.Hit_Rates = f'MYD35:{allvars[35][0]}\nSCM:{allvars[35][1]}'
hdfFile.Processing_Time = datetime.datetime.now().strftime(
"%Y-%m-%d %H:%M:%S")
for i in range(5, len(allvars) - 2):
#Check if array is 2D
try:
allvars[i].shape
arr = allvars[i]
except:
arr = np.array(allvars[i])
#Get data type from data_types dictionary
data_type = data_types.get(str(arr.dtype))
#Different x value for 2D arrays
x = 1
if arr.ndim > 1: x = arr.shape[1]
v1 = hdfFile.create(varinfo.get(i)[0], data_type, (len(arr), x))
#GZIP compression
v1.setcompress(SDC.COMP_DEFLATE, value=1)
# Set some attributts on 'd1'
for key in varinfo.get(i)[1]:
setattr(v1, key, varinfo.get(i)[1][key])
v1[0:] = arr
v1.endaccess() # Close file
hdfFile.end()
