sgrA_dist = 7861.2597 * 3.086e+18 # Distance to Sgr A* from pc to cm
beam_size = 0.37 # Beam size in arcsec
x_pix, y_pix = [], []
mean_T, mean_n, mean_N_SIO, mean_N_SO = [], [], [], []
# Define the datafile
datafile = "{0}/data/tabula-sio_intratio.csv".format(DIREC)
# Read in the whole data file containing sources and source flux
with open(datafile, newline='') as f:
reader = csv.reader(f)
data = list(reader)
f.close()
# Read in the correct config file from the database
config_file = config.config_file(db_init_filename='database_archi.ini',
section='radex_fit_results')
bestfit_config_file = config.config_file(db_init_filename='database_archi.ini',
section='radex_bestfit_conditions')
db_pool = db.dbpool(config_file)
db_bestfit_pool = db.dbpool(bestfit_config_file)
# Parse the data to a dict list
observed_data = workerfunctions.parse_data(data, db_pool, db_bestfit_pool)
# Filter the observed data to contain only those species that we can use
# (normally limited by those with Radex data)
filtered_data = workerfunctions.filter_data(observed_data,
["SIO", "SO", "OCS", "H2CS"])
# Read the image data from Farhad
def main():
config.read_json_config(config.config_file())
twisted()
'g_u': 15.0,
'A_ul': 10**(-2.83461),
'E_u': 58.34783,
'Z': [72.3246, 2*480.8102]
}
so_data = {
'T': [100., 1000.],
'g_u': 17.0,
'A_ul': 10**(-1.94660),
'E_u': 62.14451,
'Z': [197.515, 2*850.217] # From Splatalogue (https://www.cv.nrao.edu/php/splat/species_metadata_displayer.php?species_id=20)
}
# Declare the database connections
config_file = config.config_file(db_init_filename='database.ini', section='postgresql')
bestfit_config_file = config.config_file(db_init_filename='database.ini', section='bestfit_conditions')
# Set up the connection pools
db_pool = db.dbpool(config_file)
db_bestfit_pool = db.dbpool(bestfit_config_file)
# Read in the whole data file containing sources and source flux
with open(datafile, newline='') as f:
reader = csv.reader(f)
data = list(reader)
f.close()
observed_data = workerfunctions.parse_data(data, db_pool, db_bestfit_pool)
'''
def test_check_config_file(self):
#check that the config_file returns the appropriate value
assert config.config_file()==os.path.join(config.config_folder(),"cnf.yml")
import requests
from config import config_file
texts = []
languages = ['de', 'es', 'fr']
text_files = ['directories/DE.txt', 'directories/ES.txt', 'directories/FR.txt']
for i in text_files:
with open(i, 'r') as file:
texts.append(file.read())
API_KEY = config_file() # API Key
URL = 'https://translate.yandex.net/api/v1.5/tr.json/translate'
def translate_it(text, to_lang):
params = {
'key': API_KEY,
'text': text,
'lang': f'ru-{to_lang}',
}
response = requests.get(URL, params=params)
return ''.join(response.json()['text'])
# print(translate_it('В настоящее время доступна единственная опция — признак включения в ответ автоматически определенного языка переводимого текста. Этому соответствует значение 1 этого параметра.', 'no'))
if __name__ == '__main__':
for j in languages:
for g in texts:
so_data = {
'T': [100., 1000.],
'g_u': 17.0,
'A_ul': 10**(-1.94660),
'E_u': 62.14451,
'Z': [
197.515, 2 * 850.217
] # From Splatalogue (https://www.cv.nrao.edu/php/splat/species_metadata_displayer.php?species_id=20)
}
# Declare the species that we're interested in
relevant_species = ["SIO", "SO", "OCS", "H2CS"]
# Declare the database connections
config_file = config.config_file(db_init_filename='database.ini',
section='static_fit_results')
bestfit_config_file = config.config_file(db_init_filename='database.ini',
section='bestfit_conditions')
# Set up the connection pools
db_pool = db.dbpool(config_file)
db_bestfit_pool = db.dbpool(bestfit_config_file)
# Read in the whole data file containing sources and source flux
with open(datafile, newline='') as f:
reader = csv.reader(f)
data = list(reader)
f.close()
# Parse the data to a dict list
observed_data = workerfunctions.parse_data(data, db_pool, db_bestfit_pool)
