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1 | 1 | import pathlib |
2 | | -import numpy as np |
3 | | -import matplotlib.cm as cms |
4 | | -import cmocean.cm as cmo |
5 | | -from scipy.signal import savgol_filter as savgol |
6 | | -from scipy.signal import medfilt2d |
7 | | -from scipy.optimize import curve_fit |
8 | | -from scipy.stats import pearsonr, spearmanr, ttest_ind |
9 | | -import WrightTools as wt |
| 2 | +import matplotlib as mpl |
| 3 | +import makeitwright as mw |
10 | 4 |
|
11 | | -import makeitwright.process.andor as andor |
12 | | -import makeitwright.process.beckerhickl as becker |
13 | | -import makeitwright.process.spectralprofile |
14 | 5 |
|
15 | | -from makeitwright.process.helpers import show, roi, norm, set_label |
16 | | -from makeitwright.parsers import parse |
17 | | -from makeitwright.artists import setparams, setdpi |
18 | | -from makeitwright.spectra import plot_spectra as plot |
| 6 | +roi = mw.helpers.roi |
| 7 | +parse = mw.parsers.parse |
| 8 | +andor = mw.andor |
| 9 | +becker = mw.beckerhickl |
| 10 | +plot = mw.spectra.plot_spectra |
19 | 11 |
|
20 | | -setparams() |
21 | | -setdpi(150) |
| 12 | +fp = pathlib.Path().expanduser().resolve() / r"Desktop/Research Data/Wright Table/Original" |
22 | 13 |
|
23 | | -fp = pathlib.Path().expanduser().resolve() / r"Desktop/Research Data/Wright Table/Original" # filepath name to folder |
| 14 | +# set plotting parameters |
| 15 | +mpl.rcParams['font.sans-serif'] = "Arial" |
| 16 | +mpl.rcParams['font.family'] = "sans-serif" |
| 17 | +mpl.rcParams['font.size'] = 14 |
| 18 | +mpl.rcParams['figure.dpi'] = 300 |
| 19 | +mpl.rcParams['lines.linewidth'] = 4 |
| 20 | +mpl.rcParams['pcolor.shading'] = 'auto' |
| 21 | +mpl.rcParams['figure.dpi'] = 150 |
24 | 22 |
|
25 | | - |
26 | | -# |
27 | 23 | if True: # Plot PL |
28 | 24 | data = parse(fp, keywords='4 hr.asc') |
29 | | - #andor.correct_PL_background(data, ybkg=[0, 20]) |
30 | | - #y_profile = roi(data, {'wl': ([400, 800], 'sum')}) # If need to check object area |
31 | | - #plot(y_profile) |
32 | 25 | PL_ROI = roi(data, {'y': ([1021, 1047], 'average')}) |
33 | 26 | plot(PL_ROI, channel=0, xrange=[500, 850]) |
34 | | - PL_output = open('C:/Users/kmfor/Desktop/Research Data/Wright Table/Original/4hr.txt', 'w') |
| 27 | + PL_output = open(fp / '4hr.txt', 'w') |
35 | 28 | PL_dataTrace = zip(PL_ROI.axes[0], PL_ROI.channels[0]) |
36 | 29 | for x in PL_dataTrace: |
37 | 30 | PL_output.write(str(x[0])+'\t') |
38 | 31 | PL_output.write(str(x[1])+'\n') |
39 | 32 | PL_output.close() |
40 | 33 |
|
41 | | -# |
42 | 34 | if True: # Plot T/R/A |
43 | | - data = parse('C:/Users/kmfor/Desktop/Research Data/Wright Table/Original/For Chris/23_11_21/4ClPEASnI n1', keywords='Object 3') |
| 35 | + data = parse(fp / 'For Chris/23_11_21/4ClPEASnI n1', keywords='Object 3') |
44 | 36 | R = data[2] |
45 | 37 | R_back = data[1] |
46 | 38 | T = data[4] |
47 | 39 | T_back = data[3] |
48 | | - |
49 | 40 |
|
50 | 41 | andor.compute_reflectance(R, R_back, dark_wavelength_range=None) |
51 | 42 | y_profile = roi(R, {'wl': ([580, 750], 'sum')}) # If need to check object area |
52 | 43 | plot(y_profile) |
53 | 44 | plot(R, channel=1, ROI={'y': ([1020, 1070], 'average')}, xrange=[580, 750]) #Currently at 10 x mag |
54 | 45 | R_ROI = roi(R, {'y': ([1020, 1070], 'average')}) |
55 | | - R_output = open('C:/Users/kmfor/Desktop/Research Data/Wright Table/Original/For Chris/23_11_21/4ClPEASnI n1/Object 3 R processed.txt', 'w') |
| 46 | + R_output = open(fp / 'For Chris/23_11_21/4ClPEASnI n1/Object 3 R processed.txt', 'w') |
56 | 47 | R_dataTrace = zip(R_ROI.axes[0], R_ROI.channels[1]) |
57 | 48 | for x in R_dataTrace: |
58 | 49 | R_output.write(str(x[0])+'\t') |
|
64 | 55 | # plot(y_profile) |
65 | 56 | plot(T, channel=1, ROI={'y': ([1020, 1070], 'average')}, xrange=[580, 750]) # Current 10x mag, 100x mag 54-70 |
66 | 57 | T_ROI = roi(T, {'y': ([1020, 1070], 'average')}) |
67 | | - T_output = open('C:/Users/kmfor/Desktop/Research Data/Wright Table/Original/For Chris/23_11_21/4ClPEASnI n1/Object 3 T Processed.txt', 'w') |
| 58 | + T_output = open(fp / 'For Chris/23_11_21/4ClPEASnI n1/Object 3 T Processed.txt', 'w') |
68 | 59 | T_dataTrace = zip(T_ROI.axes[0], T_ROI.channels[1]) |
69 | 60 | for x in T_dataTrace: |
70 | 61 | T_output.write(str(x[0])+'\t') |
71 | 62 | T_output.write(str(x[1])+'\n') |
72 | 63 | T_output.close() |
73 | 64 | # |
74 | 65 | andor.compute_absorbance(R, T) |
75 | | - A_output = open('C:/Users/kmfor/Desktop/Research Data/Wright Table/Original/For Chris/23_11_21/4ClPEASnI n1/Object 3 A processed.txt', 'w') |
| 66 | + A_output = open(fp / 'For Chris/23_11_21/4ClPEASnI n1/Object 3 A processed.txt', 'w') |
76 | 67 | A_ROI = roi(T, {'y': ([1020, 1070], 'average')}) # A is channel 2 in both R and T data objects |
77 | 68 | plot(R, channel=2, ROI={'y': ([1020, 1070], 'average')}, xrange=[580, 750]) #Current 10x mag. can add vrange |
78 | 69 | A_dataTrace = zip(A_ROI.axes[0], A_ROI.channels[2]) |
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