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historical_data_processing_helpers.py
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historical_data_processing_helpers.py
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import numpy as np
import matplotlib.pyplot as plt
from math import floor
import qiskit
from qiskit import Aer, IBMQ
from qiskit import QuantumRegister, ClassicalRegister, QuantumCircuit, execute, transpile, visualization
from qiskit.quantum_info import Operator
from qiskit.quantum_info import Kraus, SuperOp, Operator, average_gate_fidelity
from qiskit.providers.aer import QasmSimulator
from qiskit.providers.ibmq.job import job_monitor
from qiskit.quantum_info.analysis import hellinger_fidelity
from qiskit.converters import circuit_to_dagdependency
from qiskit.converters import circuit_to_dag
sim = Aer.get_backend('qasm_simulator')
sim_statevect = Aer.get_backend('statevector_simulator')
from qiskit import IBMQ
IBMQ.load_account()
provider=IBMQ.get_provider(hub='ibm-q-ornl', group='ornl', project='phy147')
import datetime
import pickle
from copy import deepcopy
def load_historical_data(processors,gather_date):
for item in processors:
file_name = "./" + gather_date + "_machine_props/" + item + "_" + gather_date + "_to_release_properties"
file = open(file_name, "rb")
processors[item] = pickle.load(file)
return processors
def remove_duplicate_records(processor_dict):
found_records = []
filtered_processor_dict = {}
for i in processor_dict:
if processor_dict[i]['last_update_date'] not in found_records:
found_records.append(processor_dict[i]['last_update_date'])
filtered_processor_dict[i] = processor_dict[i]
return filtered_processor_dict
def find_longest_measurement_gate_pair(record_in):
'''
in ns but convert to us
'''
qubit_tracker = {}
for i in range(len(record_in['qubits'])):
qubit_tracker[i] = {}
for j in record_in['qubits'][i]:
if j['name'] == 'readout_length':
qubit_tracker[i]['readout_length'] = j['value']
for i in qubit_tracker:
longest_gate = 0
for j in record_in['gates']:
if i in j['qubits']:
for k in j['parameters']:
if k['name'] == 'gate_length':
if k['value'] > longest_gate:
longest_gate = k['value']
qubit_tracker[i]['longest_gate'] = longest_gate
longest_measurement_gate = 0
for i in qubit_tracker:
if qubit_tracker[i]['longest_gate'] + qubit_tracker[i]['readout_length'] > longest_measurement_gate:
longest_measurement_gate = qubit_tracker[i]['longest_gate'] + qubit_tracker[i]['readout_length']
return longest_measurement_gate/1000
def isolate_1q_property(n_qubits,processors,what_to_analyze,verbose = True):
'''
returns dictionary q_prop, q_prop_mean, and unit
look for 'T1', 'T2', 'frequency', 'anharmonicity', 'readout_error', 'prob_meas0_prep1', 'prob_meas1_prep0' , 'readout_length'
NOTE: not all records contain all these features (earlier records don't include as much....)
duplicate and incomplete records are removed from returned set
'''
#n_qubits = 27
q_prop = {}
q_prop_mean = {}
unit = None
labels = {}
for i in processors:
new_processor = remove_duplicate_records(processors[i][i])
q_prop[i] = {}
q_prop_mean[i] = []
labels[i] = []
for j in range(n_qubits):
q_prop[i][j] = []
for j in new_processor.keys():
#print(f'hello {j} {i}')
#try:
if len(new_processor[j]['qubits']) != n_qubits:
q_w_data = len(new_processor[j]['qubits'])
if verbose == True:
print(f'Only {q_w_data} qubits have {what_to_analyze} on {i} on {j}.')
continue
#only record property if every qubit has it
temp_prop = []
incomplete_record = False
for k in range(len(new_processor[j]['qubits'])):
prop_index = None
for m in range(len(new_processor[j]['qubits'][k])):
if what_to_analyze == new_processor[j]['qubits'][k][m]['name']:
prop_index = m
if prop_index == None:
if verbose == True:
print(f'{what_to_analyze} unknown on {i} qubit {k} on {j}.')
incomplete_record = True
break
#q_prop[i][k].append(new_processor[j]['qubits'][k][prop_index]['value'])
temp_prop.append(new_processor[j]['qubits'][k][prop_index]['value'])
if unit == None:
unit = new_processor[j]['qubits'][k][prop_index]['unit']
if incomplete_record == False:
for k in range(len(temp_prop)):
q_prop[i][k].append(temp_prop[k])
labels[i].append(j)
#except:
#continue
for j in q_prop[i]:
q_prop_mean[i].append(np.mean(np.array(q_prop[i][j])))
return q_prop, q_prop_mean, unit, labels
def isolate_cx_error(processors, coupling_map, threshold=1, verbose=True):
'''
returns dictionary cx_error, cx_error_mean
duplicate, at/above threshold, and incomplete records are removed from returned set
'''
cx_error = {}
cx_error_mean = {}
labels = {}
for i in processors:
new_processor = remove_duplicate_records(processors[i][i])
cx_error[i] = {}
cx_error_mean[i] = {}
labels[i] = []
for j in coupling_map:
cx_error[i][str(j)] = []
for j in new_processor.keys():
#remove all incomplete samples!!
temp = []
for k in new_processor[j]['gates']:
#determine if CX gate
if len(k['qubits'])==2:
temp.append(k['qubits'])
str_c_map = set(str(k) for k in coupling_map)
str_temp = set(str(k) for k in temp)
if str_c_map == str_temp:
#remove all records that contain a 1
temp_error_vals = {}
threshold_found = False
for k in new_processor[j]['gates']:
if len(k['qubits'])==2:
for m in k['parameters']:
if m['name'] == 'gate_error':
temp_error_vals[str(k['qubits'])] = m['value']
if m['value'] >= threshold:
threshold_found = True
if verbose == True:
print(f'Threshold exceeded {i} on {j} for '+str(k['qubits'])+' : '+str(m['value']))
if threshold_found == False:
for k in temp_error_vals.keys():
cx_error[i][k].append(temp_error_vals[k])
labels[i].append(j)
else:
if verbose==True:
print(f'Record mismatch with coupling map for {i} on {j}. {len(coupling_map)} items in map, {len(temp)} found.')
unique_temp = str_temp-str_c_map
unique_map = str_c_map-str_temp
print(f' not connection: {unique_temp}')
print(f' missing: {unique_map}')
for j in cx_error[i]:
cx_error_mean[i][j] = np.mean(np.array(cx_error[i][j]))
return cx_error, cx_error_mean, labels
def clean_data(processors,prop_setting='cx',coupling_map = None , threshold = 1, one_q_prop = None, n_qubits=None, verbose = True):
'''
Returns dict that is the same as what's input (how the historical data is initially loaded).
All duplicates, incorrect, and partial records are removed.
for T1/T2, records with coherence times too short for real use are removed
Call EACH TIME you want to include a feature.
If prop_setting == "1q_prop", one_q_prop must be a str in the set of:
{'T1', 'T2', 'frequency', 'anharmonicity', 'readout_error',
'prob_meas0_prep1', 'prob_meas1_prep0' , 'readout_length'}
coupling_map and threshold are used for 2q gate properties
n_qubits used for 1q properties
'''
if prop_setting == 'cx' and coupling_map != None :
#do the cx filtering
new_data_dict = {}
for i in processors:
new_processor = remove_duplicate_records(processors[i][i])
new_data_dict[i] = {i:{}}
for j in new_processor.keys():
temp = []
for k in new_processor[j]['gates']:
#determine if cx gate
if len(k['qubits']) == 2:
temp.append(k['qubits'])
str_c_map = set(str(k) for k in coupling_map)
str_temp = set(str(k) for k in temp)
if str_c_map == str_temp:
#remove all records that contain a 1
#temp_error_vals = {}
threshold_found = False
for k in new_processor[j]['gates']:
if len(k['qubits'])==2:
for m in k['parameters']:
if m['name'] == 'gate_error':
#temp_error_vals[str(k['qubits'])] = m['value']
if m['value'] >= threshold:
threshold_found = True
if verbose == True:
print(f'Threshold exceeded {i} on {j} for '+str(k['qubits'])+' : '+str(m['value']))
if threshold_found == False:
new_data_dict[i][i][j] = deepcopy(new_processor[j])
else:
if verbose==True:
print(f'Record mismatch with coupling map for {i} on {j}. {len(coupling_map)} items in map, {len(temp)} found.')
unique_temp = str_temp-str_c_map
unique_map = str_c_map-str_temp
print(f' not connection: {unique_temp}')
print(f' missing: {unique_map}')
return new_data_dict
elif prop_setting == '1q_prop' and one_q_prop != None and n_qubits!= None:
#do the 1q properties filtering
new_data_dict = {}
for i in processors:
new_processor = remove_duplicate_records(processors[i][i])
new_data_dict[i] = {i:{}}
for j in new_processor.keys():
if len(new_processor[j]['qubits']) != n_qubits:
q_w_data = len(new_processor[j]['qubits'])
if verbose == True:
print(f'Only {q_w_data} qubits have {one_q_prop} on {i} on {j}.')
continue
#only record property if every qubit has it
if one_q_prop == 'T1' or one_q_prop == 'T2':
longest_measurement_gate = find_longest_measurement_gate_pair(new_processor[j])
incomplete_record = False
for k in range(len(new_processor[j]['qubits'])):
prop_index = None
for m in range(len(new_processor[j]['qubits'][k])):
if one_q_prop == new_processor[j]['qubits'][k][m]['name']:
prop_index = m
if prop_index == None:
if verbose == True:
print(f'{one_q_prop} unknown on {i} qubit {k} on {j}.')
incomplete_record = True
break
# only include T1/T2 records if they are greater than longest operation+measurement
if one_q_prop == 'T1' or one_q_prop == 'T2':
if new_processor[j]['qubits'][k][prop_index]['value'] < longest_measurement_gate:
if verbose == True:
print(f'{one_q_prop} smaller than longest gate/measurement pair on {i} qubit {k} on {j}.')
incomplete_record = True
break
if incomplete_record == False:
new_data_dict[i][i][j] = deepcopy(new_processor[j])
return new_data_dict
else:
print('ERROR: Cannot filter data. Check your input parameters.')
return {}