def create_psurf_apriori_file(self, spectrum_filename,
psurf_output_filename):
base_spec_name = os.path.basename(spectrum_filename)
# Use grep because its faster than doing it outself
grep_cmd = "grep -E " + base_spec_name + " " + self.runlog_filename
matched_line = os.popen(grep_cmd).readline()
if matched_line == None or len(matched_line) == 0:
raise IOError('Could not find spectrum name: %s in run log file: %s' % (base_spec_name, self.runlog_filename))
try:
matched_columns = matched_line.split()
psurf_val = float(matched_columns[self.pout_col_idx]) * self.convert_factor
except:
raise ValueError('Failed to parse psurf value from: "%s" from runlog line: %s' % (matched_columns[self.pout_col_idx], matched_line))
out_obj = OcoMatrix()
out_obj.data = numpy.zeros((1,1), dtype=float)
out_obj.data[0,0] = psurf_val
out_obj.file_id = 'psurf value extracted for spectrum named: %s from runlog file: %s' % (base_spec_name, self.runlog_filename)
out_obj.labels = ['PSURF']
out_obj.write(psurf_output_filename)
def write_oco_ascii(self, filename=None):
if not self.model:
self.create_model()
fn_date_str = self.model_dt.strftime("%Y%m%d%H%M")
id_date_str = self.model_dt.strftime("%Y-%m-%dT%H:%M:%S")
if not filename:
filename = "model_%s.dat" % (fn_date_str)
nlev = self.model.pressure.data.shape[0]
# Convert pressure from mbar to Pascals
press_mbar = self.model.pressure
press_pa = press_mbar._replace(data=press_mbar.data * 100.0)
data_in_order = (press_pa, self.model.height, self.model.temperature,
self.model.h2o_vmr)
data_arr = zeros((nlev, len(data_in_order)), dtype=float)
for idx in range(len(data_in_order)):
# Reverse data to be increasing pressure order
data_arr[:, idx] = data_in_order[idx].data[::-1]
# Put import here to not make this code rely on this module
from full_physics.oco_matrix import OcoMatrix
out_mat = OcoMatrix()
out_mat.file_id = "Atmosphere Model Created from NCEP data interpolated to latitude: %f, longitude: %f on %s" % (
self.site_lat, self.site_lon, id_date_str)
out_mat.units = []
out_mat.labels = []
for val in data_in_order:
out_mat.units.append(val.units)
if val.name == "Temperature":
out_mat.labels.append("T")
else:
out_mat.labels.append(val.name)
out_mat.header["Surface_Pressure"] = self.model.surface_pressure.data
out_mat.header[
"Surface_Pressure_Units"] = self.model.surface_pressure.units
out_mat.data = data_arr
logger.debug("Writing to ASCII file: %s" % filename)
out_mat.write(filename)
def write_oco_ascii(self, filename=None):
if not self.model:
self.create_model()
fn_date_str = self.model_dt.strftime("%Y%m%d%H%M")
id_date_str = self.model_dt.strftime("%Y-%m-%dT%H:%M:%S")
if not filename:
filename = "model_%s.dat" % (fn_date_str)
nlev = self.model.pressure.data.shape[0]
# Convert pressure from mbar to Pascals
press_mbar = self.model.pressure
press_pa = press_mbar._replace(data=press_mbar.data * 100.0)
data_in_order = (press_pa, self.model.height, self.model.temperature, self.model.h2o_vmr)
data_arr = zeros((nlev, len(data_in_order)), dtype=float)
for idx in range(len(data_in_order)):
# Reverse data to be increasing pressure order
data_arr[:, idx] = data_in_order[idx].data[::-1]
# Put import here to not make this code rely on this module
from full_physics.oco_matrix import OcoMatrix
out_mat = OcoMatrix()
out_mat.file_id = "Atmosphere Model Created from NCEP data interpolated to latitude: %f, longitude: %f on %s" % (self.site_lat, self.site_lon, id_date_str)
out_mat.units = [ v.units for v in data_in_order ]
out_mat.labels = [ v.name for v in data_in_order ]
out_mat.header["Surface_Pressure"] = self.model.surface_pressure.data
out_mat.header["Surface_Pressure_Units"] = self.model.surface_pressure.units
out_mat.data = data_arr
logger.debug("Writing to ASCII file: %s" % filename)
out_mat.write(filename)
def reformat_gfit_atmosphere(mav_file, out_file, next_spec_srch=None):
print('Reading mav data from %s' % mav_file)
spec_line_start = 1
mav_data = []
mav_fobj = open(mav_file, "r")
file_line_idx = 0
if next_spec_srch == None:
found_spec = True
else:
found_spec = False
for mav_line in mav_fobj.readlines():
line_parts = mav_line.split()
mav_data.append(line_parts)
if mav_line.find('Next Spectrum:') >= 0 and next_spec_srch != None:
if re.search(next_spec_srch, mav_line):
spec_line_start = file_line_idx
found_spec = True
file_line_idx += 1
if not found_spec:
raise ValueError(
'Could not find next spectrum search string: %s in mav file: %s' %
(next_spec_srch, mav_file))
print('Processing for', ' '.join(mav_data[spec_line_start]))
mav_size_row = spec_line_start + 1
mav_header_row = mav_size_row + 2
try:
(num_skip, num_cols,
num_rows) = [int(val) for val in mav_data[mav_size_row]]
except:
mav_header_row = 0
num_skip = -2
num_cols = len(mav_data[0])
num_rows = len(mav_data)
print()
print("Skip: %d, Cols %d, Rows: %d" % (num_skip, num_cols, num_rows))
mav_beg_row = mav_size_row + num_skip + 2
mav_end_row = mav_beg_row + num_rows - 3
mav_all_cols = mav_data[mav_header_row]
print("Column names:", mav_all_cols)
out_col_idx = 0
output_data_matrix = numpy.zeros(
(mav_end_row - mav_beg_row + 1, len(all_col_names)), dtype=float)
for (curr_mav_col, scale) in mav_col_extract:
print('Processing column:', curr_mav_col)
mav_col_idx = mav_all_cols.index(curr_mav_col)
row_idx = mav_end_row - mav_beg_row
for mav_row_data in mav_data[mav_beg_row:mav_end_row + 1]:
new_col_data = float(mav_row_data[mav_col_idx]) * float(scale)
output_data_matrix[row_idx, out_col_idx] = output_data_matrix[
row_idx, out_col_idx] + new_col_data
row_idx -= 1
out_col_idx += 1
print('Writing output file %s' % out_file)
out_mat_obj = OcoMatrix()
out_mat_obj.file_id = 'GFIT Atmospheric State modified from: %s' % (
mav_file)
out_mat_obj.dims = [len(output_data_matrix), len(all_col_names)]
out_mat_obj.labels = all_col_names
out_mat_obj.units = all_unit_names
out_mat_obj.data = output_data_matrix
out_mat_obj.write(out_file)
def reformat_gfit_atmosphere(mav_file, out_file, next_spec_srch=None):
print 'Reading mav data from %s' % mav_file
spec_line_start = 1
mav_data = []
mav_fobj = open(mav_file, "r")
file_line_idx = 0
if next_spec_srch == None:
found_spec = True
else:
found_spec = False
for mav_line in mav_fobj.readlines():
line_parts = mav_line.split()
mav_data.append( line_parts )
if mav_line.find('Next Spectrum:') >= 0 and next_spec_srch != None:
if re.search(next_spec_srch, mav_line):
spec_line_start = file_line_idx
found_spec = True
file_line_idx += 1
if not found_spec:
raise ValueError('Could not find next spectrum search string: %s in mav file: %s' % (next_spec_srch, mav_file))
print 'Processing for', ' '.join(mav_data[spec_line_start])
mav_size_row = spec_line_start + 1
mav_header_row = mav_size_row + 2
try:
(num_skip, num_cols, num_rows) = [int(val) for val in mav_data[mav_size_row]]
except:
mav_header_row = 0
num_skip = -2
num_cols = len(mav_data[0])
num_rows = len(mav_data)
print
print "Skip: %d, Cols %d, Rows: %d" % (num_skip, num_cols, num_rows)
mav_beg_row = mav_size_row + num_skip + 2
mav_end_row = mav_beg_row + num_rows - 3
mav_all_cols = mav_data[mav_header_row]
print "Column names:", mav_all_cols
out_col_idx = 0
output_data_matrix = numpy.zeros((mav_end_row-mav_beg_row+1, len(all_col_names)), dtype=float)
for (curr_mav_col, scale) in mav_col_extract:
print 'Processing column:', curr_mav_col
mav_col_idx = mav_all_cols.index(curr_mav_col)
row_idx = mav_end_row-mav_beg_row
for mav_row_data in mav_data[mav_beg_row:mav_end_row+1]:
new_col_data = float(mav_row_data[mav_col_idx]) * float(scale)
output_data_matrix[row_idx, out_col_idx] = output_data_matrix[row_idx, out_col_idx] + new_col_data
row_idx -= 1
out_col_idx += 1
print 'Writing output file %s' % out_file
out_mat_obj = OcoMatrix()
out_mat_obj.file_id = 'GFIT Atmospheric State modified from: %s' % (mav_file)
out_mat_obj.dims = [len(output_data_matrix), len(all_col_names)]
out_mat_obj.labels = all_col_names
out_mat_obj.units = all_unit_names
out_mat_obj.data = output_data_matrix
out_mat_obj.write(out_file)
