# 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):