def load_test_data_file(filename):
"""helper function to open test file regardless of invocation"""
try:
return load(filename)
except IOError:
return load('tests/{}'.format(filename))
def load_test_data_file(filename):
"""helper function to open test file regardless of invocation"""
try:
return load(filename)
except IOError:
return load('tests/{}'.format(filename))
allFiles = sorted(glob.glob(path + "*06*testwoudc.csv"))
# /home/poyraden/Analysis/Homogenization_Analysis/Files/Nilu/Sodankyl/version2/DQA/20050406_testwoudc.csv
list_data = []
list_udata = []
dfm = pd.DataFrame()
fi = 0
for filename in allFiles:
print(filename)
# try except is applied for the cases when there is formatting error: WOUDCExtCSVReaderError
extcsv_to = load(filename)
try:
extcsv_to = load(filename)
# access all tables
tables = extcsv_to.sections.keys()
## first copy the profile data and delete this from the keys to save the metadata. For Praha data it is 'PORFILE',
# watch out that this naming may change from station to station
profile_keys = extcsv_to.sections['PROFILE'].keys()
Profile = extcsv_to.sections['PROFILE']['_raw']
del extcsv_to.sections['PROFILE']
# profile_uncertainity = extcsv_to.sections['PROFILE_UNCERTAINTY']['_raw']
# del extcsv_to.sections['PROFILE_UNCERTAINTY']
except WOUDCExtCSVReaderError:
print('error')
def test_load_file(self):
"""Test file loading"""
with self.assertRaises(TypeError):
load()
def test_load_file(self):
"""Test file loading"""
with self.assertRaises(TypeError):
load()
2006-12-30,0,0,260,,,,,25,,05
2006-12-31,0,0,270,,,,,35,,04
* MEAN 235 ::S=8 CLOUDY SKY/HAZE:XXX=OZONE 1 2 153
#TIMESTAMP
UTCOffset,Date,Time
+00:00:00,2006-12-31,
#MONTHLY
Date,ColumnO3,StdDevO3,Npts
2006-12-01,235,21.4,23
'''
# load file into memory from local path
extcsv_to = load('../tests/data/20061201.brewer.mkiv.153.imd.csv')
# access all tables
# multiple occurance of tables are indexed as per order of occurance
tables = extcsv_to.sections.keys()
print('All tables:')
print(tables)
print('')
# get fields for a talbe
CONTENT = extcsv_to.sections['CONTENT'].keys()
print('CONTENT fields:')
print(CONTENT)
print('')
# get field value
CONTENT_Category = extcsv_to.sections['CONTENT']['Category']
print('CONTENT.Category value:')
def load(filename):
"""stub to woudc_extcsv.load"""
return woudc_extcsv.load(filename)
2006-12-30,0,0,260,,,,,25,,05
2006-12-31,0,0,270,,,,,35,,04
* MEAN 235 ::S=8 CLOUDY SKY/HAZE:XXX=OZONE 1 2 153
#TIMESTAMP
UTCOffset,Date,Time
+00:00:00,2006-12-31,
#MONTHLY
Date,ColumnO3,StdDevO3,Npts
2006-12-01,235,21.4,23
'''
# load file into memory from local path
extcsv_to = load('../tests/data/20061201.brewer.mkiv.153.imd.csv')
# access all tables
# multiple occurance of tables are indexed as per order of occurance
tables = extcsv_to.sections.keys()
print('All tables:')
print(tables)
print('')
# get fields for a talbe
CONTENT = extcsv_to.sections['CONTENT'].keys()
print('CONTENT fields:')
print(CONTENT)
print('')
# get field value
CONTENT_Category = extcsv_to.sections['CONTENT']['Category']
print('CONTENT.Category value:')
def load(filename):
"""stub to woudc_extcsv.load"""
return woudc_extcsv.load(filename)