def read_atl09_ancillary_data(atl09filepath):
# Iterate through keys for ancillary data
subgroup = '/ancillary_data/'
keys = getH5Keys(atl09filepath, subgroup)
key_info = get_H5_keys_info(atl09filepath, subgroup)
byte_encoded = ['control', 'data_start_utc', 'data_end_utc',
'granule_start_utc', 'granule_end_utc']
# Read each key, put it in pandas df
for idx, key in enumerate(keys):
data = readAtlH5(atl09filepath, subgroup + '/' + key + '/')
if np.isin(key, ['release', 'version']):
data = int(data)
if np.isin(key, byte_encoded):
data = data[0]
data = data.decode('utf-8')
if key_info[idx][1] != 'Group':
if len(key.split('/')) == 1:
if idx == 0:
df = pd.Series(data,
index=[key.split('/')[-1]],
dtype=object)
else:
df = pd.concat(
[df, pd.Series(data,
index=[key.split('/')[-1]],
dtype=object)])
return df
def read_atl03_heights_data(atl03filepath, gt):
# Iterate through keys for "Heights"
keys = getH5Keys(atl03filepath, gt + '/heights')
# Read each key, put it in pandas df
for idx, key in enumerate(keys):
data = readAtl03H5(atl03filepath, '/heights/' + key, gt)
if idx == 0:
df = pd.DataFrame(data, columns=[key])
else:
df = pd.concat([df, pd.DataFrame(data, columns=[key])], axis=1)
return df
def read_atl09_orbit_info(atl09filepath):
subgroup = '/orbit_info/'
keys = getH5Keys(atl09filepath, subgroup)
key_info = get_H5_keys_info(atl09filepath, subgroup)
# Read each key, put it in pandas df
for idx, key in enumerate(keys):
data = readAtlH5(atl09filepath, subgroup + '/' + key + '/')
if idx == 0:
df = pd.Series(data, index=[key], dtype=object)
else:
df_key = pd.Series(data, index=[key], dtype=object)
df = pd.concat([df, df_key])
return df
def read_atl08_land_segments(atl08filepath, gt):
# Iterate through keys for "Land Segments"
keys = getH5Keys(atl08filepath, gt + '/land_segments')
key_info = get_H5_keys_info(atl08filepath, gt + '/land_segments')
# Read each key, put it in pandas df
for idx, key in enumerate(keys):
data = readAtl03H5(atl08filepath, '/land_segments/' + key, gt)
if key_info[idx][1] != 'Group':
if idx == 0:
df = pd.DataFrame(data, columns=[key.split('/')[-1]])
else:
if len(data.shape) == 2:
cols = data.shape[1]
for idx2 in range(0, cols):
df = pd.concat([df,pd.DataFrame(data[:,idx2],columns=\
[key.split('/')[-1] +\
'_' + str(idx2)])],
axis=1)
else:
df = pd.concat([df,pd.DataFrame(data,columns=\
[key.split('/')[-1]])],
axis=1)
return df
def read_atl09_hr_profile(atl09filepath, gt):
# Iterate through keys for "Land Segments"
subgroup = 'profile_' + gt[2] + '/high_rate/'
keys = getH5Keys(atl09filepath, subgroup)
key_info = get_H5_keys_info(atl09filepath, subgroup)
# Read each key, put it in pandas df
for idx, key in enumerate(keys):
data = readAtlH5(atl09filepath, subgroup + '/' + key + '/')
if key == 'ds_layers':
ds_layers = np.array(data)
elif key == 'ds_va_bin_h':
ds_va_bin_h = np.array(data)
elif key == 'cab_prof':
cab_prof = np.array(data)
elif key == 'density_pass1':
density_pass1 = np.array(data)
elif key == 'density_pass2':
density_pass2 = np.array(data)
else:
if key_info[idx][1] != 'Group':
if idx == 0:
df = pd.DataFrame(data, columns=[key.split('/')[-1]])
else:
if len(data.shape) == 2:
cols = data.shape[1]
for idx2 in range(0, cols):
df = pd.concat(
[df,pd.DataFrame(data[:,idx2],columns=\
[key.split('/')[-1] +'_' +
str(idx2)])],axis=1)
else:
df = pd.concat(
[df,pd.DataFrame(data,columns=\
[key.split('/')[-1]])],axis=1)
return df, ds_layers, ds_va_bin_h, cab_prof, density_pass1, density_pass2
def get_H5_keys_info(atl08filepath, gt):
keys = getH5Keys(atl08filepath, gt)
h = h5py.File(atl08filepath, 'r')
key_name = []
key_type = []
key_len = []
for key in keys:
try:
data = h[gt + '/' + key]
kname = str(key)
ktype = str(data.dtype)
klen = int(len(data))
key_name.append(kname)
key_type.append(ktype)
key_len.append(klen)
except:
kname = str(key)
ktype = 'Group'
klen = 0
key_name.append(kname)
key_type.append(ktype)
key_len.append(klen)
key_info = [list(a) for a in zip(key_name, key_type, key_len)]
return key_info
