def test_readDirect_sites_nonexistant_list(self):
with assert_raises(WSFileError):
IO.read_sites('this_is_not_a_file.lst')
def test_readDirect_raw_data_nonexistant_data(self):
sites = IO.read_sites(badlist)
with assert_raises(WSFileError):
IO.read_raw_data(site_names=sites)
def main_data(args):
defaults = {
'azimuth': 0.0,
'flag_outliers': 'y',
'outlier_errmap': 10,
'lowTol': 2.0,
'highTol': 10.0,
'use_TF': 'y',
'period_choice': 'n',
'cTol': 0.5,
'hfreq_errmap': 20,
'XXYY_errmap': 10,
'no_period_errmap': 50
}
if set(('dbg', 'debug', '-dbg',
'-debug')).intersection(set([x.lower() for x in args])):
DEBUG = True
WSDS.DEBUG = True
if set(('i', '-i')).intersection(set([x.lower() for x in args])):
interactive = True
else:
interactive = False
# Get list file
list_file = WSIO.verify_input('Enter list file name:', expected='read')
try:
site_names = WSIO.read_sites(list_file)
except WSFileError as e: # Error is raised if something is wrong with the file.
print(e.message)
print('Exiting...')
return
dataset = WSDS.Dataset(listfile=list_file)
# Get desired azimuth
azimuth = WSIO.verify_input('Desired azimuth (deg. from True North)',
expected=float,
default=defaults['azimuth'])
flag_outliers = WSIO.verify_input('Adjust error map for outliers?',
default=defaults['flag_outliers'],
expected='yn')
if flag_outliers == 'y':
dataset.data.OUTLIER_MAP = WSIO.verify_input(
'Set outlier error map',
default=defaults['outlier_errmap'],
expected=int)
else:
dataset.data.OUTLIER_MAP = 1
dataset.data.HIGHFREQ_MAP = WSIO.verify_input(
'Error map on high frequencies (>1000Hz)',
default=defaults['hfreq_errmap'],
expected=int)
dataset.data.XXYY_MAP = WSIO.verify_input('XXYY error map',
default=defaults['XXYY_errmap'],
expected=int)
dataset.data.NO_PERIOD_MAP = WSIO.verify_input(
'Missing period error map',
default=defaults['no_period_errmap'],
expected=int)
lowTol = WSIO.verify_input(
'High frequency (>1Hz) matching tolerance %-age',
default=defaults['lowTol'],
expected=float)
lowTol /= 100
highTol = WSIO.verify_input(
'High frequency (>=10s) matching tolerance %-age',
default=defaults['highTol'],
expected=float)
highTol /= 100
raw_data = dataset.raw_data
num_TF = 0
for site in raw_data.sites.values():
if 'TZXR' in site.components:
num_TF += 1
print('{} sites out of {} have tipper data'.format(num_TF,
len(site_names)))
use_TF = WSIO.verify_input('Would you like to include TF data?',
default=defaults['use_TF'],
expected='yn')
if use_TF:
defaults.update({'inv_type': 5})
else:
defaults.update({'inv_type': 1})
dType = WSIO.verify_input(
'Which periods would you like to choose from?\n'
'Options are MTU-5, MTU-A, both, freqset, all, or program selected '
'(5/A/b/o/m/n)',
default=defaults['period_choice'],
expected='5aboamn')
# if dType == 'n':
cTol = WSIO.verify_input(
'Required fraction of sites containing each period?',
default=defaults['cTol'],
expected=float)
if cTol > 1:
cTol /= 100
period_set = raw_data.narrow_period_list(periods=MTU_data_types(
data=raw_data, dType=dType),
high_tol=highTol,
low_tol=lowTol,
count_tol=cTol)
sorted_periods = sorted(period_set.keys())
# Can set this up later to only run if -i is set (or set that as the default)
# Want user to be able to decide between interactive (plotting) mode, and just
# straight command line input.
chosen = pick_periods(sorted_periods, period_set, interactive)
for ii, p in enumerate(chosen):
if p < 0:
chosen[ii] = -1 / p
else:
chosen[ii] = p
inv_type = int(
WSIO.verify_input('Inversion Type?',
default=defaults['inv_type'],
expected='12345'))
# Still have to make sure this method also applies the error map properly.
dataset.get_data_from_raw(
lTol=lowTol,
hTol=highTol,
periods=chosen,
components=WSIO.get_components(invType=inv_type)[0])
dataset.data.set_error_map()
if azimuth != 0:
dataset.rotate_sites(azimuth)
while True:
outdata = WSIO.verify_input('Output file name?',
default='.data',
expected='write')
if outdata:
if outdata[-5:] != '.data':
outdata = ''.join([outdata, '.data'])
dataset.write_data(outfile=outdata, overwrite=True)
break
return dataset