# data_dir = os.path.expanduser('~/o/FYSIK/list-SurfCat/setups/sniffer/Data/pc Cu') # linux data_dir = r"C:\EC_data\scott\CO_and_lattice_O_project" # Windows # U:\FYSIK\list-SurfCat\setups\sniffer\Data\single_crystal_Cu\19J08_Ruben MSset = {"comment": "20A30%"} #'time':'2020-01-26%', folder = "20A30_16O" if not os.path.isdir("pickles"): os.mkdir("pickles") # to put the synchronized data, as pickle files if not os.path.isdir("overviews"): os.mkdir("overviews") # to put the overview plots # -------- first, we get all the MS data from the folder and combine it -------- # if True: # it's a bit slow... MS_data = download_cinfdata_set(**MSset) # now, as a sanity check, and to find our way around the experiment, we plot all of the MS data! ax = plot_signal(MS_data) ax.legend() plt.savefig("./overviews/" + folder + "_MS_data.png") # and save it as an overview plot. # also, save the combined MS data as a pickle! with open("./pickles/" + folder + "_MS_data.pkl", "wb") as pkl: # defines the file, 'wb' means 'write binary'. pickle.dump(MS_data, pkl) # save MS_data into the file # -------- Then, we load each EC experiment and combining it with MS data -------- # # figure out which files correspond to EC data:
""" Created on Thu Jun 6 14:01:33 2019 @author: scott """ import numpy as np from matplotlib import pyplot as plt from EC_MS import download_cinfdata_set, plot_signal, plot_signal_vs_temperature, compare_signal_to_temperature from EC_MS import load_calibration_results from EC_MS import plot_flux plt.close('all') data = download_cinfdata_set(setup='microreactorNG', time='2019-06-25 09:52:30') #plot_signal(data, leg=True, meta_data=['TC temperature'], rh_label='Temperature [C]') #plot_signal_vs_temperature(data, leg=True, reciprocal=True) compare_signal_to_temperature(MS_data=data) plt.show() exit() mdict = load_calibration_results('19F04_calibration.pkl') O2, CO2, CO, Ar = mdict['O2'], mdict['CO2'], mdict['CO'], mdict['Ar'] if True: # take background from CO2 cracking into account when calculating CO flux # NOTE below on why cal_mat is used exactly this way. CO.cal_mat = {'M28': 1 / CO.F_cal} CO.cal_mat[
""" from matplotlib import pyplot as plt from EC_MS import download_cinfdata_set, plot_signal from EC_MS import chip_calibration, point_calibration, recalibrate from EC_MS import load_calibration_results, save_calibration_results plt.close('all') mdict = load_calibration_results('19B22_calibration.pkl') O2 = mdict['O2'] data = download_cinfdata_set(setup='microreactorNG', time='2019-06-04 17:29:26') plot_signal(data, leg=True) chip = chip_calibration(data, mol=O2, gas='O2', composition=1, chip='microreactor', tspan=[8200, 8350]) chip.save('MR12') print('\nAir flux through the chip in mol/s: ' + str(chip.capillary_flow(gas='air') / 6.02e23)) Ar = point_calibration(data, mol='Ar', mass='M40', cal_type='external', tspan=[10000, 10200], carrier='Ar', chip=chip) CO = point_calibration(data, mol='CO', mass='M28', cal_type='external', tspan=[15400, 15600], carrier='CO', chip=chip) H2 = point_calibration(data, mol='H2', mass='M2', cal_type='external', tspan=[20000, 20200], carrier='H2', chip=chip)
Created on Thu Jun 6 14:01:33 2019 @author: scott """ import numpy as np from matplotlib import pyplot as plt from EC_MS import download_cinfdata_set, plot_signal from EC_MS import load_calibration_results from EC_MS import plot_flux #plt.close('all') data = download_cinfdata_set(setup='microreactorNG', time='2019-06-05 13:11:18') plot_signal(data, leg=True) mdict = load_calibration_results('19F04_calibration.pkl') O2, CO2, CO, Ar = mdict['O2'], mdict['CO2'], mdict['CO'], mdict['Ar'] if True: # take background from CO2 cracking into account when calculating CO flux # NOTE below on why cal_mat is used exactly this way. CO.cal_mat = {'M28':1/CO.F_cal} CO.cal_mat['M44'] = - CO.cal_mat['M28'] * CO2.spectrum['M28']/CO2.spectrum['M44']
from matplotlib import pyplot as plt from EC_MS import download_cinfdata_set, plot_signal, plot_flux from EC_MS import Chip, point_calibration, recalibrate from EC_MS import save_calibration_results plt.close('all') chip = Chip('SI-3iv1-14-B4') print('\nAir flux through the chip in mol/s: ' + str(chip.capillary_flow(gas='air') / 6.02e23)) data = download_cinfdata_set(setup='microreactorNG', time='2019-02-22 14:05:27', use_caching=True) ax = plot_signal(data, unit='A') ax.legend() O2 = point_calibration(data, mol='O2', mass='M32', cal_type='external', tspan=[2000, 3000], carrier='air', chip=chip) Ar = point_calibration(data, mol='Ar', mass='M40', cal_type='external', tspan=[2000, 3000], carrier='air', chip=chip) N2 = point_calibration(data, mol='N2', mass='M28', cal_type='external', tspan=[2000, 3000], carrier='air', chip=chip) quantify = {'CH4':'M15', 'CO2':'M44', 'CO':'M28', #'CH3OH':'M31' } def T(M):