def get_jobids_from_file(direct,
circuit_name=None,
run_type=None,
timestamp=None):
'''
The jobids are loaded from the last saved file if direct=True.
If not,they are loaded from the file specified by circuit name and run type and timestamp
returns a 2-length list of the jobids and the data corresponding to the jobid stored in the pickle file.
See Functions.Data_storage.save_jobdata() for more info of the data
'''
if direct == True:
loaded_jobiddata = store.load_last()
elif direct == False:
if circuit_name == None:
circuit_name = input('Circuit name: ')
if run_type == None:
run_type = input('Run Type: ')
if timestamp == None:
date = input('Date of experiment (mm_dd):')
time = input('Time of experiment (hh_mm_ss):')
loaded_jobiddata = store.load_jobdata(circuit_name, run_type,
date + '-' + time)
else:
loaded_jobiddata = store.load_jobdata(circuit_name, run_type,
timestamp)
nr_batches = loaded_jobiddata['Batchnumber']
jobids = [''] * nr_batches
for job in loaded_jobiddata['Data']:
jobids[job['batchno']] = job['Jobid']
return [jobids, loaded_jobiddata]
def get_tomoset_from_file(direct,
circuit_name=None,
run_type=None,
timestamp=None):
if direct == True:
loaded_jobiddata = store.load_last()
elif direct == False:
if circuit_name == None:
circuit_name = input('Circuit name: ')
if run_type == None:
run_type = input('Run Type: ')
if timestamp == None:
date = input('Date of experiment (mm_dd):')
time = input('Time of experiment (hh_mm_ss):')
loaded_jobiddata = store.load_jobdata(circuit_name, run_type,
date + '-' + time)
else:
loaded_jobiddata = store.load_jobdata(circuit_name, run_type,
timestamp)
return loaded_jobiddata['tomoset']
def get_jobids_from_file(direct,
circuit_name=None,
run_type=None,
timestamp=None):
if direct == True:
loaded_jobiddata = store.load_last()
elif direct == False:
if circuit_name == None:
circuit_name = input('Circuit name: ')
if run_type == None:
run_type = input('Run Type: ')
if timestamp == None:
date = input('Date of experiment (mm_dd):')
time = input('Time of experiment (hh_mm_ss):')
loaded_jobiddata = store.load_jobdata(circuit_name, run_type,
date + '-' + time)
else:
loaded_jobiddata = store.load_jobdata(circuit_name, run_type,
timestamp)
nr_batches = loaded_jobiddata['Batchnumber']
jobids = [''] * nr_batches
for job in loaded_jobiddata['Data']:
jobids[job['batchno']] = job['Jobid']
return [jobids, loaded_jobiddata]
import Functions.Data_storage as store
import Analysis.Analysefunc as an
import Analysis.tomography_functions as tomoself
import Functions.Plotting as pt
import numpy as np
fit_method = 'own'
n = 2
direct = False
#%% Gather the results from file
if direct == True:
timestamp = store.load_last()['Experiment time']
run_type = store.load_last()['Type']
circuit_name = store.load_last()['Circuit name']
else:
run_type = input('Run Type is (enter as string): ')
circuit_name = input('Circuit name is(enter as string): ')
timestamp = None
results_loaded = store.load_results(circuit_name, run_type, timestamp)
#%% Gather the tomo set and its outcomes from the results
tomo_set = results_loaded['Tomoset']
results = results_loaded['Results']
tomo_data = an.tomo.tomography_data(results, circuit_name, tomo_set)
#%% Tomography;