def process_data(cur):
stars = get_stars_with_no_amplitudes(cur)
def process_curves(cur2):
for s in stars:
i = s[0]
survey = s[1]
cluster = s[2]
period = s[3]
print(i, cluster, survey, period)
for band in ["I", "V"]:
print(band)
curve = get_light_curve(cur2, i, survey, cluster, band)
for c in curve:
lc = database.unpack_curve(c)
results = process((lc, period))
save_results(cur, s, band, results)
print("")
database.with_database(database_file, process_curves)
def main():
"""
python3 add.py ../../rrab.sqlite RRab.csv curves.csv
"""
database_file = sys.argv[1]
survey = "Ferro_2012"
cluster = "M53"
catalog_file = sys.argv[2]
curves_file = sys.argv[3]
oost = "II"
survey_info = pd.read_csv(catalog_file)
ID = "VName"
PERIOD = "Per"
lc_ids = np.array([i.strip() for i in survey_info[ID]])
periods = np.array(survey_info[PERIOD])
data = np.column_stack((lc_ids, periods))
def process_data(cur):
database.add_survey(cur, survey, cluster, oost)
for row in data:
i = row[0]
period = row[1]
database.add_star(cur, i, survey, cluster, period)
curves = pd.read_csv(curves_file)
for band in ["I", "V"]:
curve = get_light_curve(curves, band, i)
print(i, band)
database.add_light_curve(cur, i, survey, cluster, band,
curve)
database.with_database(database_file, process_data)
def main():
"""
light_curve = numpy vector where dim 1 are the observations and in dim 2
there are time mag magerr
python3 calculate_amplitude.py rrab.sqlite
"""
database_file = sys.argv[1]
def process_data(cur):
stars = get_stars_with_no_amplitudes(cur)
def process_curves(cur2):
for s in stars:
i = s[0]
survey = s[1]
cluster = s[2]
period = s[3]
print(i, cluster, survey, period)
for band in ["I", "V"]:
print(band)
curve = get_light_curve(cur2, i, survey, cluster, band)
for c in curve:
lc = database.unpack_curve(c)
results = process((lc, period))
save_results(cur, s, band, results)
print("")
database.with_database(database_file, process_curves)
database.with_database(database_file, process_data)