In [17]:

    

from lib import transient
from lib import genericfunctions as gfs
from imp import reload
reload(transient)

import os
import numpy as np

import matplotlib.pyplot as plt
import matplotlib.colors as colors
import matplotlib.colorbar as colorbar
import matplotlib.cm as cmx
from mpl_toolkits.axes_grid1 import make_axes_locatable
%matplotlib inline

import pandas as pd


    

In [63]:

    

tr = transient.Transient()

filepath = 'E:\data\RuCl3\kerr_rotation'
pump_spot = 80
probe_spot = 50
cutFreq = 0.01 # THz
t0 = 80
key_parameter = 'pump_energy'
description = ''

###########################
# init lsits:
scanList = []
k_parameters = []

for i in range(len(files)):
    tr = transient.Transient()
    tr.import_file(filepath + files[i],cleanData=False, key_parameter = key_parameter, description=description)
    tr.pump_spot = pump_spot
    tr.probe_spot = probe_spot
    tr.calc_energy_densities()
    tr.crop_time_scale()
    tr.shift_time(t0)
    tr.filter_low_pass(cutFreq)
#     tr.flip_trace()
    tr.remove_DC_offset()
    tr.flip_time()
    tr.trace = (tr.trace - norm_file.trace) * 120
    k_parameters.append(float(getattr(tr,key_parameter)))
#     tr.trace = np.divide(tr.trace,max(tr.trace))
    scanList.append(tr)    
    
print('Imported {0} scan(s) as {1} dependence'.format(len(scanList),scanList[0].key_parameter))


fig = plt.figure(figsize=(8,5))
ax = fig.add_subplot(111)
jet = cm = plt.get_cmap('jet') 
cNormLog = colors.LogNorm(vmin=min(k_parameters), vmax=max(k_parameters))
cNorm  = colors.Normalize(vmin=min(k_parameters), vmax=max(k_parameters))
scalarMap = cmx.ScalarMappable(norm=cNormLog, cmap=jet)
lines = []
for idx in range(len(scanList)):
    colorVal = scalarMap.to_rgba(getattr(scanList[idx],key_parameter))
    retLine, = ax.plot(scanList[idx].time, scanList[idx].trace, color=colorVal)
    lines.append(retLine)
# make labels
    labels = []
for i in range(len(lines)):
    labels.append((lines[i],k_parameters[i]))
labels = sorted(labels, key=lambda kpar: float(kpar[1]))
lbLines=[]
lbVals=[]
for i in range(len(labels)):
    lbLines.append(labels[i][0])
    lbVals.append('{} µJ/cm^2'.format(labels[i][1]*1000))
ax.legend(lbLines, lbVals, loc='upper right')
# plt.xlim((-5,5))
# plt.ylim((-0.0002,0.0008))
plt.ylabel('Kerr rotation angle [deg]')
plt.xlabel('Time [ps] ')
ax.grid()
plt.savefig('e:/Steinn/Data/RuCl3/kerr rotation fluence dependence at 3,8K.png')
/


    

    




0.001
0.072
0.001
0.072
0.003
0.072
0.006
0.072
0.011
0.072
0.022
0.072
0.045
0.072
0.09
0.072
0.169
0.072
0.337
0.072
0.675
0.072
Imported 11 scan(s) as pump_energy dependence






    
Out[63]:





()






    

In [36]:

    

norm_file = transient.Transient()
norm_file.import_file('E:/data/RuCl3/2017-12-18/Ru3Cl-Pu-0.1-pr-0.2-1kAVG-T-3.8K-kerr.mat',cleanData=True, key_parameter='pump_power',description='none')
norm_file.filter_low_pass(0.004)
plt.plot(norm_file.trace)


    

    
Out[36]:





[<matplotlib.lines.Line2D at 0x251a9c74710>]






    

In [30]:

    

plt.plot(norm_file.trace)


    

    
Out[30]:





[<matplotlib.lines.Line2D at 0x251a81e6748>]






    

In [49]:

    

csvDir = 'e:/Steinn/Data/RuCl3/'
if not os.path.isdir(csvDir):
    os.makedirs(csvDir)
for scan in scanList:
    scan.export_file_csv(csvDir)


    

    




Exporting Ru3Cl__0.005_mW
Exporting Ru3Cl__0.01_mW
Exporting Ru3Cl__0.02_mW
Exporting Ru3Cl__0.04_mW
Exporting Ru3Cl__0.08_mW
Exporting Ru3Cl__0.16_mW
Exporting Ru3Cl__0.32_mW
Exporting Ru3Cl__0.64_mW
Exporting Ru3Cl__1.2_mW
Exporting Ru3Cl__2.4_mW
Exporting Ru3Cl__4.8_mW

In [2]:

    

os.getcwd()


    

    
Out[2]:





'E:\\py_code\\RegAscope2017'

In [27]:

    

tr = transient.Transient()

filepath = 'E:/data/RuCl3/kerr_rotation/temperature_160uW/'
pump_spot = 80
probe_spot = 50
cutFreq = 0.01 # THz
t0 = 80
key_parameter = 'temperature'
description = ''

###########################
# init lsits:
scanList = []
k_parameters = []
files = os.listdir(filepath)

for i in range(len(files)):
    print(gfs.get_metadata_from_name(filepath + files[i]))

    if files[i] == 'background.mat':
        norm_file = transient.Transient()
        norm_file.import_file(filepath + files[i],cleanData=True, key_parameter='pump_power',description='none')
        norm_file.filter_low_pass(0.004)
# plt.plot(norm_file.trace)
    else:
                
        tr = transient.Transient()
        tr.import_file(filepath + files[i],cleanData=False, key_parameter = key_parameter, description=description)
        tr.pump_spot = pump_spot
        tr.probe_spot = probe_spot
        tr.calc_energy_densities()
        tr.crop_time_scale()
        tr.shift_time(t0)
        tr.filter_low_pass(cutFreq)
    #     tr.flip_trace()
        tr.remove_DC_offset()
        tr.flip_time()
        tr.trace = (tr.trace - norm_file.trace) * 120
        k_parameters.append(float(getattr(tr,key_parameter)))
    #     tr.trace = np.divide(tr.trace,max(tr.trace))
        scanList.append(tr)    
    
print('Imported {0} scan(s) as {1} dependence'.format(len(scanList),scanList[0].key_parameter))


fig = plt.figure(figsize=(8,5))
ax = fig.add_subplot(111)
jet = cm = plt.get_cmap('jet') 
cNormLog = colors.LogNorm(vmin=min(k_parameters), vmax=max(k_parameters))
cNorm  = colors.Normalize(vmin=min(k_parameters), vmax=max(k_parameters))
scalarMap = cmx.ScalarMappable(norm=cNormLog, cmap=jet)
lines = []
for idx in range(len(scanList)):
    colorVal = scalarMap.to_rgba(getattr(scanList[idx],key_parameter))
    retLine, = ax.plot(scanList[idx].time, scanList[idx].trace, color=colorVal)
    lines.append(retLine)
# make labels
    labels = []
for i in range(len(lines)):
    labels.append((lines[i],k_parameters[i]))
labels = sorted(labels, key=lambda kpar: float(kpar[1]))
lbLines=[]
lbVals=[]
for i in range(len(labels)):
    lbLines.append(labels[i][0])
    lbVals.append('{} K'.format(labels[i][1]))
ax.legend(lbLines, lbVals, loc='upper right')
# plt.xlim((-5,5))
# plt.ylim((-0.0002,0.0008))
plt.ylabel('Kerr rotation angle [deg]')
plt.xlabel('Time [ps] ')
ax.grid()
plt.savefig('e:/Data/RuCl3/kerr rotation temperature.png')


    

    




{'date': '2016-12-06-20.25.46', 'material': 'backgroun'}
{'date': '2016-12-06-20.04.18', 'pump_power': 0.16, 'probe_power': 0.2, 'temperature': 3.9, 'material': 'Ru3Cl', 'other': ['1kavg', 'kerr']}
0.022
0.072
{'date': '2016-12-06-20.12.18', 'pump_power': 0.16, 'probe_power': 0.2, 'temperature': 5.0, 'material': 'Ru3Cl', 'other': ['1kavg', 'kerr']}
0.022
0.072
{'date': '2016-12-06-20.16.14', 'pump_power': 0.16, 'probe_power': 0.2, 'temperature': 6.0, 'material': 'Ru3Cl', 'other': ['1kavg', 'kerr']}
0.022
0.072
{'date': '2016-12-06-20.20.28', 'pump_power': 0.16, 'probe_power': 0.2, 'temperature': 7.0, 'material': 'Ru3Cl', 'other': ['1kavg', 'kerr']}
0.022
0.072
Imported 4 scan(s) as temperature dependence






    

In [44]:

    

tr = transient.Transient()

filepath = 'E:/data/RuCl3/kerr_rotation/fluence_12K/'
pump_spot = 80
probe_spot = 50
cutFreq = 0.01 # THz
t0 = 80
key_parameter = 'pump_energy'
description = ''

###########################
# init lsits:
scanList = []
k_parameters = []
files = os.listdir(filepath)

for i in range(len(files)):
    print(gfs.get_metadata_from_name(filepath + files[i]))

    if files[i] == 'background.mat':
        norm_file = transient.Transient()
        norm_file.import_file(filepath + files[i],cleanData=True, key_parameter='pump_power',description='none')
        norm_file.filter_low_pass(0.004)
# plt.plot(norm_file.trace)
    else:
                
        tr = transient.Transient()
        tr.import_file(filepath + files[i],cleanData=False, key_parameter = key_parameter, description=description)
        tr.pump_spot = pump_spot
        tr.probe_spot = probe_spot
        tr.calc_energy_densities()
        tr.crop_time_scale()
        tr.shift_time(t0)
        tr.filter_low_pass(cutFreq)
    #     tr.flip_trace()
        tr.remove_DC_offset()
        tr.flip_time()
        if i <8:
            tr.trace = (tr.trace - norm_file.trace) * 120
        else:
            tr.trace = (tr.trace) * 120

        k_parameters.append(float(getattr(tr,key_parameter)))
#         tr.trace = np.divide(tr.trace,max(tr.trace))
#         tr.trace = np.divide(tr.trace,max(tr.trace))

        scanList.append(tr)    
    
print('Imported {0} scan(s) as {1} dependence'.format(len(scanList),scanList[0].key_parameter))


fig = plt.figure(figsize=(8,5))
ax = fig.add_subplot(111)
jet = cm = plt.get_cmap('jet') 
cNormLog = colors.LogNorm(vmin=min(k_parameters), vmax=max(k_parameters))
cNorm  = colors.Normalize(vmin=min(k_parameters), vmax=max(k_parameters))
scalarMap = cmx.ScalarMappable(norm=cNormLog, cmap=jet)
lines = []
for idx in range(len(scanList)):
    colorVal = scalarMap.to_rgba(getattr(scanList[idx],key_parameter))
    retLine, = ax.plot(scanList[idx].time, scanList[idx].trace, color=colorVal)
    lines.append(retLine)
# make labels
    labels = []
for i in range(len(lines)):
    labels.append((lines[i],k_parameters[i]))
labels = sorted(labels, key=lambda kpar: float(kpar[1]))
lbLines=[]
lbVals=[]
for i in range(len(labels)):
    lbLines.append(labels[i][0])
    lbVals.append('{} µJ/cm^2'.format(labels[i][1]*1000))
ax.legend(lbLines, lbVals, loc='upper right')
# plt.xlim((-5,5))
# plt.ylim((-0.0002,0.0008))
plt.ylabel('Kerr rotation angle [deg]')
plt.xlabel('Time [ps] ')
ax.grid()
plt.savefig('e:/Data/RuCl3/kerr rotation power - 12K norm.png')


    

    




{'date': '2016-12-06-19.29.52', 'pump_power': 0.005, 'probe_power': 0.2, 'material': 'Ru3Cl', 'other': ['1kavg', 't', '12k', 'kerr']}
0.001
0.072
{'date': '2016-12-06-19.32.42', 'pump_power': 0.01, 'probe_power': 0.2, 'material': 'Ru3Cl', 'other': ['1kavg', 't', '12k', 'kerr']}
0.001
0.072
{'date': '2016-12-06-19.35.04', 'pump_power': 0.02, 'probe_power': 0.2, 'material': 'Ru3Cl', 'other': ['1kavg', 't', '12k', 'kerr']}
0.003
0.072
{'date': '2016-12-06-19.37.34', 'pump_power': 0.04, 'probe_power': 0.2, 'material': 'Ru3Cl', 'other': ['1kavg', 't', '12k', 'kerr']}
0.006
0.072
{'date': '2016-12-06-19.40.20', 'pump_power': 0.08, 'probe_power': 0.2, 'material': 'Ru3Cl', 'other': ['1kavg', 't', '12k', 'kerr']}
0.011
0.072
{'date': '2016-12-06-19.42.56', 'pump_power': 0.16, 'probe_power': 0.2, 'material': 'Ru3Cl', 'other': ['1kavg', 't', '12k', 'kerr']}
0.022
0.072
{'date': '2016-12-06-19.45.32', 'pump_power': 0.32, 'probe_power': 0.2, 'material': 'Ru3Cl', 'other': ['1kavg', 't', '12k', 'kerr']}
0.045
0.072
{'date': '2016-12-06-19.48.18', 'pump_power': 0.64, 'probe_power': 0.2, 'material': 'Ru3Cl', 'other': ['1kavg', 't', '12k', 'kerr']}
0.09
0.072
{'date': '2016-12-06-19.54.16', 'pump_power': 1.2, 'probe_power': 0.2, 'material': 'Ru3Cl', 'other': ['1kavg', 't', '12k', 'kerr']}
0.169
0.072
{'date': '2016-12-06-19.56.48', 'pump_power': 2.4, 'probe_power': 0.2, 'material': 'Ru3Cl', 'other': ['1kavg', 't', '12k', 'kerr']}
0.337
0.072
Imported 10 scan(s) as pump_energy dependence






    

In [ ]: