s_db, csv_fn = s_cfg.combine_run_cfg(station_save_dir)
# make xml file
s_xml = archive.XMLMetadata()
s_xml.read_config_file(survey_cfg)
s_xml.supplement_info = s_xml.supplement_info.replace(
"\\n", "\n\t\t\t")
# location
s_xml.survey.east = s_db.lon.median()
s_xml.survey.west = s_db.lon.median()
s_xml.survey.north = s_db.lat.median()
s_xml.survey.south = s_db.lat.median()
# get elevation from national map
s_elev = archive.get_nm_elev(s_db.lat.median(), s_db.lon.median())
s_xml.survey.elev_min = s_elev
s_xml.survey.elev_max = s_elev
# start and end time
s_xml.survey.begin_date = s_db.start_date.min()
s_xml.survey.end_date = s_db.stop_date.max()
# add list of files
s_xml.supplement_info += "\n\t\t\tFile List:\n\t\t\t" + "\n\t\t\t".join(
asc_fn_list)
# write station xml
s_xml.write_xml_file(
os.path.join(station_save_dir, "{0}_meta.xml".format(station)))
zc = archive.Z3DCollection()
fn_list = zc.get_time_blocks(z3d_path)
h5_fn = r"d:\Peacock\MTData\GabbsValley\gv01\h5_test.hdf5"
if os.path.exists(h5_fn):
os.remove(h5_fn)
h5_obj = h5py.File(h5_fn, 'w')
for ii, fn_block in enumerate(fn_list, 1):
ts_db, meta_arr = zc.merge_ts(fn_list[0])
# fill attributes
h5_obj.attrs['datum'] = 'WGS84'
h5_obj.attrs['latitude'] = meta_arr['lat'].mean()
h5_obj.attrs['longitude'] = meta_arr['lon'].mean()
h5_obj.attrs['elevation'] = archive.get_nm_elev(meta_arr['lat'].mean(),
meta_arr['lon'].mean())
h5_obj.attrs['station'] = 'gv01'
# fill channel attributes
for m_arr in meta_arr:
for c_attr, h_attr in zip(['ch_num', 'ch_length', 'ch_azm'],
['sensor', 'length', 'azimuth']):
h5_obj.attrs['{0}_{1}'.format(m_arr['comp'].lower(),
h_attr)] = m_arr[c_attr]
# create group for schedule action
schedule = h5_obj.create_group('schedule_{0:02}'.format(ii))
# add metadata
schedule.attrs['start_time'] = meta_arr['start'].max()
schedule.attrs['stop_time'] = meta_arr['stop'].min()
schedule.attrs['n_samples'] = meta_arr['n_samples'].min()
schedule.attrs['n_channels'] = meta_arr.size
# ab_list = [chr(i) for i in range(ord('A'),ord('Z')+1)]
# char_dict = dict([(index, alpha) for index, alpha in enumerate(ab_list, 1)])
# =============================================================================
# Rename EDI files and rename station
# =============================================================================
edi_list = [
os.path.join(edi_path, edi) for edi in os.listdir(edi_path)
if edi.endswith(".edi")
]
lines = ["station,lat,lon,nm_elev"]
for edi_fn in edi_list:
mt_obj = mt.MT(edi_fn)
nm_elev = archive.get_nm_elev(mt_obj.lat, mt_obj.lon)
lines.append("{0},{1:.5f},{2:.5f},{3:.2f}".format(mt_obj.station,
mt_obj.lat, mt_obj.lon,
nm_elev))
with open(os.path.join(edi_path, "imush_station_locations_nm.csv"),
"w") as fid:
fid.write("\n".join(lines))
# print(mt_obj.station)
# new_station = '{0}{1:03}'.format(char_dict[int(mt_obj.station[0:2])],
# int(mt_obj.station[2:]))
# mt_obj.station = new_station
# print(mt_obj.station)
# mt_obj.write_mt_file(save_dir=sv_path)
zc = archive.Z3DCollection()
fn_list = zc.get_time_blocks(z3d_path)
h5_fn = r"d:\Peacock\MTData\GabbsValley\gv01\h5_test.hdf5"
if os.path.exists(h5_fn):
os.remove(h5_fn)
h5_obj = h5py.File(h5_fn, "w")
for ii, fn_block in enumerate(fn_list, 1):
ts_db, meta_arr = zc.merge_ts(fn_list[0])
# fill attributes
h5_obj.attrs["datum"] = "WGS84"
h5_obj.attrs["latitude"] = meta_arr["lat"].mean()
h5_obj.attrs["longitude"] = meta_arr["lon"].mean()
h5_obj.attrs["elevation"] = archive.get_nm_elev(meta_arr["lat"].mean(),
meta_arr["lon"].mean())
h5_obj.attrs["station"] = "gv01"
# fill channel attributes
for m_arr in meta_arr:
for c_attr, h_attr in zip(["ch_num", "ch_length", "ch_azm"],
["sensor", "length", "azimuth"]):
h5_obj.attrs["{0}_{1}".format(m_arr["comp"].lower(),
h_attr)] = m_arr[c_attr]
# create group for schedule action
schedule = h5_obj.create_group("schedule_{0:02}".format(ii))
# add metadata
schedule.attrs["start_time"] = meta_arr["start"].max()
schedule.attrs["stop_time"] = meta_arr["stop"].min()
schedule.attrs["n_samples"] = meta_arr["n_samples"].min()
schedule.attrs["n_channels"] = meta_arr.size
