def load_virtual_gate_matrix_from_ds(ds_id, hardware_name): ''' load virtual gate matrix from a existing dataset. Args: ds_id (int) : id of the dataset to load hardware_name (str) : name of hardware in the snapshot present in the dataset ''' load_virtual_gate_matrix_from_snapshot(load_by_id(ds_id).snapshot, hardware_name)
def load_AWG_to_dac_conversion_from_ds(ds_id, hardware_name): ''' load AWG to dac conversion from a exisisting dataset. Args: ds_id (int) : id of the dataset to load harware_name (str) : name of the hardware in the dataset its snapshow ''' load_AWG_to_dac_conversion_from_snapshot(load_by_id(ds_id).snapshot, hardware_name)
# update plot every 300 ms for a smooth plotting experience self.plot_layout.parentWidget().setUpdatesEnabled(True) self.timer.timeout.connect(self.update_plots) self.timer.start(300) def update_plots(self): if self.ds.completed == True: self.timer.stop() self.ds.sync() for plot in self.plot_widgets: try: plot.update() except: logging.error(f'Plot update failed', exc_info=True) if __name__ == '__main__': from core_tools.data.SQL.connect import SQL_conn_info_local, SQL_conn_info_remote, sample_info, set_up_local_storage, set_up_remote_storage from core_tools.data.ds.data_set import load_by_uuid, load_by_id import sys import datetime # set_up_local_storage('stephan', 'magicc', 'test', 'Intel Project', 'F006', 'SQ38328342') set_up_remote_storage('131.180.205.81', 5432, 'xld_measurement_pc', 'XLDspin001', 'spin_data', "6dot", "XLD", "6D3S - SQ20-20-5-18-4") ds = load_by_id(307) p = data_plotter(ds)
# 'remote_usernam', 'remote_passwd', 'remote_dbname', # 'project_name', 'set_up_name', 'sample_name') # in case you are using both a local and remote server. # set_up_local_and_remote_storage('ipaddr_rem_server', 5432, # 'local_usernam', 'local_passwd', 'local_dbname', # 'remote_usernam', 'remote_passwd', 'remote_dbname', # 'project_name', 'set_up_name', 'sample_name') # when you want to do sweeps from core_tools.sweeps.sweeps import do0D, do1D, do2D ds = do2D(param, start, stop, n_points, delay).run() # see what is in the dataset print(ds) # inspecting data (extract arrays, labels, units): x_data, y_data, z_data = ds.m1.x(), ds.m1.y(), ds.m1() x_label, y_label, z_label = ds.m1.x.label, ds.m1.y.label, ds.m1.label x_unit, y_unit, z_unit = ds.m1.x.unit, ds.m1.y.unit, ds.m1.unit # when you want to plot a dataset from core_tools.data.gui.plot_mgr import data_plotter plot = data_plotter(ds) # load a dataset by id or uuid from core_tools.data.ds.data_set import load_by_id, load_by_uuid ds = load_by_id(101)
from good_morning.fittings.fit_symmetry import fit_symmetry if __name__ == '__main__': from core_tools.data.SQL.connect import set_up_local_storage set_up_local_storage("xld_user", "XLDspin001", "vandersypen_data", "6dot", "XLD", "6D2S - SQ21-XX-X-XX-X") from core_tools.data.ds.data_set import load_by_id ds = load_by_id(16789) x_axis = ds('read1').x() y_axis = ds('read1').y() probabilities = ds('read1').z() fit_symmetry(x_axis, y_axis, probabilities, True)
line = QtWidgets.QFrame(self.geom_parent) line.setFrameShape(QtWidgets.QFrame.HLine) line.setFrameShadow(QtWidgets.QFrame.Sunken) line.setObjectName(name) return line if __name__ == '__main__': from core_tools.data.SQL.connector import SQL_conn_info_local, SQL_conn_info_remote, sample_info, set_up_local_storage from core_tools.data.SQL.SQL_measurment_queries import query_for_measurement_results from core_tools.data.ds.data_set import load_by_id import sys import datetime set_up_local_storage('stephan', 'magicc', 'test', 'Intel Project', 'F006', 'SQ38328342') ds = load_by_id(45782) class test_window(QtWidgets.QMainWindow): def __init__(self, MainWindow, ds): super().__init__() self.centralwidget = QtWidgets.QWidget(MainWindow) self.gridLayout_2 = QtWidgets.QGridLayout(self.centralwidget) self.gridLayout_2.setObjectName("gridLayout_2") self.scrollArea = QtWidgets.QScrollArea(self.centralwidget) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Fixed, QtWidgets.QSizePolicy.Expanding) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.scrollArea.sizePolicy().hasHeightForWidth()) self.scrollArea.setSizePolicy(sizePolicy) self.scrollArea.setMaximumSize(QtCore.QSize(800, 16777215))
Args: frequency (np.ndarray) : GHz probability (np.ndarray) : spin prob ''' fit_result, confidence_interval = fit_resonance_raw(frequency, probability) print(f'res freq = {round(fit_result.params["f_res"].value*1e-9, 6)} GHz') if plot==True: plt.figure() plt.plot(frequency, probability, label='original data') plt.plot(frequency, gauss_peak_function(fit_result.params, frequency), label='fitted data') plt.xlabel('frequency (GHz)') plt.ylabel(('spin probability (%)')) plt.legend() plt.show() return fit_result.params['f_res'].value if __name__ == '__main__': from core_tools.data.SQL.connect import set_up_local_storage set_up_local_storage("xld_user", "XLDspin001", "vandersypen_data", "6dot", "XLD", "6D2S - SQ21-XX-X-XX-X") from core_tools.data.ds.data_set import load_by_id ds = load_by_id(16728) data = ds('read12') print(data) x = data.x() y = data.y() print(x, y) fit_resonance(x, y, True)
intermedediate_result = mini.minimize(method='Nelder') result = mini.minimize(method='leastsq', params=intermedediate_result.params) best_fit = data + result.residual if plot==True: plt.figure() plt.plot(data, 'bo') plt.plot(best_fit, 'r--', label='best fit') plt.xlabel('nth gate') plt.ylabel('spin prob (%)') plt.legend(loc='best') plt.show() # approximate errors. print(f'Change pi time by {round(-result.params["rotation_error"].value/np.pi*100,2)} %') print(f'Off resonant by {round(result.params["detuning_error"].value/time_pi_pulse*1e-6, 3)} MHz') return -result.params["rotation_error"].value/np.pi, result.params["detuning_error"].value/time_pi_pulse/2 if __name__ == '__main__': import numpy as np from core_tools.data.SQL.connect import set_up_local_storage set_up_local_storage("xld_user", "XLDspin001", "vandersypen_data", "6dot", "XLD", "6D2S - SQ21-XX-X-XX-X") from core_tools.data.ds.data_set import load_by_id ds = load_by_id(15996) data = np.average(np.reshape(ds('read4').y(), (5, 21)), axis= 0) a,b = fit_allXY(data, 300e-9, True) print(a, b)
"6D3S - SQ20-20-5-18-4") # ds = load_by_id(16949) # data = ds('read5') # fit_phase(data.x(), data.y(), False, True) # ds = load_by_id(16947) # data = ds('read1') # fit_phase(data.x(), data.y(), False, True) # ds = load_by_id(16948) # data = ds('read2') # fit_phase(data.x(), data.y(), True, True) # ds = load_by_id(16950) # data = ds('read4') # fit_phase(data.x(), data.y(), True, True) # ds = load_by_id(16949) # data = ds('read5') # fit_phase(data.x(), data.y(), False, True) # ds = load_by_id(17046) # data = ds('read4') # fit_phase(data.x(), data.y(), True, True) ds = load_by_id(17063) data = ds('read2') fit_phase(data.x(), data.y(), False, True) # plt.show()