def test_to_dataframe():
cwb_files, event = read_data_dir('geonet', 'nz2018p115908')
st = read_data(cwb_files[0])[0]
df1 = streams_to_dataframe([st, st], event=event)
np.testing.assert_array_equal(df1.STATION.tolist(), ['WPWS', 'WPWS'])
np.testing.assert_array_equal(df1.NAME.tolist(),
['Waipawa_District_Council', 'Waipawa_District_Council'])
target_levels = ['ELEVATION', 'EPICENTRAL_DISTANCE',
'GREATER_OF_TWO_HORIZONTALS', 'H1', 'H2', 'Z',
'HYPOCENTRAL_DISTANCE', 'LAT', 'LON', 'NAME', 'NETID', 'SOURCE',
'STATION', '', 'PGA', 'PGV', 'SA(0.3)', 'SA(1.0)', 'SA(3.0)']
# let's use sets to make sure all the columns are present in whatever order
cmp1 = set(['ELEVATION', 'EPICENTRAL_DISTANCE',
'GREATER_OF_TWO_HORIZONTALS', 'H1', 'H2',
'HYPOCENTRAL_DISTANCE', 'LAT', 'LON',
'NAME', 'NETID', 'SOURCE', 'STATION', 'Z'])
cmp2 = set(['', 'PGA', 'PGV', 'SA(0.3)', 'SA(1.0)', 'SA(3.0)'])
header1 = set(df1.columns.levels[0])
header2 = set(df1.columns.levels[1])
assert header1 == cmp1
assert header2 == cmp2
# idx = 0
# for s in df1.columns.levels:
# for col in s:
# try:
# assert col == target_levels[idx]
# except Exception as e:
# x = 1
# idx += 1
# This was previously not being tested
"""imts = ['PGA', 'PGV', 'SA(0.3)', 'SA(1.0)', 'SA(3.0)']
def test_to_dataframe():
cwb_files, event = read_data_dir('geonet', 'nz2018p115908')
st = read_data(cwb_files[0])[0]
df1 = streams_to_dataframe([st, st], event=event)
np.testing.assert_array_equal(df1.STATION.tolist(), ['WPWS', 'WPWS'])
np.testing.assert_array_equal(df1.NAME.tolist(),
['Waipawa_District_Council', 'Waipawa_District_Council'])
target_levels = ['ELEVATION', 'EPICENTRAL_DISTANCE',
'GREATER_OF_TWO_HORIZONTALS', 'HN1', 'HN2', 'HNZ',
'HYPOCENTRAL_DISTANCE', 'LAT', 'LON', 'NAME', 'NETID', 'SOURCE',
'STATION', '', 'PGA', 'PGV', 'SA(0.3)', 'SA(1.0)', 'SA(3.0)']
idx = 0
for s in df1.columns.levels:
for col in s:
assert col == target_levels[idx]
idx += 1
# This was previously not being tested
"""imts = ['PGA', 'PGV', 'SA(0.3)', 'SA(1.0)', 'SA(3.0)']
def save_shakemap_amps(processed, event, event_dir):
"""Write ShakeMap peak amplitudes to an Excel spreadsheet.
Args:
processed (StreamCollection):
Processed waveforms.
event (ScalarEvent):
Event object.
event_dir (str):
Directory where peak amps should be written.
Returns:
str: Path to output amps spreadsheet.
"""
ampfile_name = None
if processed.n_passed:
dataframe = streams_to_dataframe(processed,
event=event)
ampfile_name = os.path.join(event_dir, 'shakemap.xlsx')
dataframe.to_excel(ampfile_name)
wb = load_workbook(ampfile_name)
ws = wb.active
# TODO: This ws.append() fails sometimes. Going back to using pandas.
# for r in dataframe_to_rows(dataframe, index=True, header=True):
# try:
# ws.append(r)
# except Exception as e:
# x = 1
# we don't need the index column, so we'll delete it here
ws.delete_cols(1)
ws.insert_rows(1)
ws['A1'] = 'REFERENCE'
ws['B1'] = dataframe['SOURCE'].iloc[0]
wb.save(ampfile_name)
return ampfile_name