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helper_functions.py
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def get_datafiles(data_dir, data, row_num, col_num):
die = 'Die_01/'
try:
filename=glob.glob(data_dir+die+ '*' + str(row_num) + '_col_' + str(col_num) + '_VW_sweep.pkl')
data.append(pickle.load( open(filename[0],"rb")))
except:
print('Die_01 Not Found')
data.append({})
die = 'Die_07/'
try:
filename=glob.glob(data_dir+die+ '*' + str(row_num) + '_col_' + str(col_num) + '_VW_sweep.pkl')
data.append(pickle.load( open(filename[0],"rb")))
except:
print('Die_07 Not Found')
data.append({})
die = 'Die_13/'
try:
filename=glob.glob(data_dir+die+ '*' + str(row_num) + '_col_' + str(col_num) + '_VW_sweep.pkl')
data.append(pickle.load( open(filename[0],"rb")))
except:
print('Die_13 Not Found')
data.append({})
die = 'Die_15/'
try:
filename=glob.glob(data_dir+die+ '*' + str(row_num) + '_col_' + str(col_num) + '_VW_sweep.pkl')
data.append(pickle.load( open(filename[0],"rb")))
except:
print('Die_15 Not Found')
data.append({})
die = 'Die_17/'
try:
filename=glob.glob(data_dir+die+ '*' + str(row_num) + '_col_' + str(col_num) + '_VW_sweep.pkl')
data.append(pickle.load( open(filename[0],"rb")))
except:
print('Die_17 Not Found')
data.append({})
die = 'Die_25/'
try:
filename=glob.glob(data_dir+die+ '*' + str(row_num) + '_col_' + str(col_num) + '_VW_sweep.pkl')
data.append(pickle.load( open(filename[0],"rb")))
except:
print('Die_25 Not Found')
data.append({})
die = 'Die_39/'
try:
filename=glob.glob(data_dir+die+ '*' + str(row_num) + '*_col_' + str(col_num) + '_VW_sweep.pkl')
data.append(pickle.load( open(filename[0],"rb")))
except:
print('Die_39 Not Found')
data.append({})
die = 'Die_19/'
try:
filename=glob.glob(data_dir+die+ '*' + str(row_num) + '*_col_' + str(col_num) + '_VW_sweep.pkl')
data.append(pickle.load( open(filename[0],"rb")))
except:
print('Die_19 Not Found')
data.append({})
die = 'Die_49/'
try:
filename=glob.glob(data_dir+die+ '*' + str(row_num) + '*_col_' + str(col_num) + '_VW_sweep.pkl')
data.append(pickle.load( open(filename[0],"rb")))
except:
print('Die_49 Not Found')
data.append({})
def plot_VW(data,
chan = 1,
zoom_span = 5,
prominence = 4.5,
fit_order = 8,
fsr = 15,
ideal_peak_wl = 1550,
index = 0,
save = False):
try:
fig = plt.figure( figsize = (9,7), dpi = 500 )
widths = [1, 1, 0.1]
heights = [1, 1]
spec = fig.add_gridspec(ncols=3,
nrows=2,
width_ratios=widths,
height_ratios=heights)
colors = plt.cm.viridis(np.linspace(0,1,len(data['voltages'])))
a0 = fig.add_subplot(spec[0,:-1]) #raw spectra
a01 = fig.add_subplot(spec[:,2]) #voltage applied
a1 = fig.add_subplot(spec[1,0]) #IV curve
a2 = fig.add_subplot(spec[1,1]) #zoom window
wl = np.array(data['wavelengths'][index])
pw = np.array(data['powers'][index][chan - 1])
ridx = np.isfinite(wl) & np.isfinite(pw)
baseline = np.poly1d(np.polyfit(wl[ridx],pw[ridx],fit_order))
pw_bs = pw - baseline(wl) + max(baseline(wl)) - max(pw)
wl_per_args = wl[1] - wl[0]
peaks ,_ = find_peaks(-pw_bs, prominence = prominence, distance = int(fsr/wl_per_args))
idx = np.abs(wl[peaks] - ideal_peak_wl).argmin()
center_peak = peaks[idx]
span = int(0.5*zoom_span/wl_per_args)
start_zoom, stop_zoom = center_peak - span, center_peak + span
for i in range(len(data['wavelengths'])):
wl = np.array(data['wavelengths'][i])
pw = np.array(data['powers'][i][chan - 1])
a0.plot(wl, pw,
lw = 0.5,
color = colors[i])
a2.plot(wl[start_zoom:stop_zoom],
pw[start_zoom:stop_zoom],
color = colors[i])
norm = mpl.colors.Normalize(vmin=np.min(data['voltages']),
vmax=np.max(data['voltages']))
cbar = a01.figure.colorbar(plt.cm.ScalarMappable(norm=norm, cmap='viridis'),
ax=a01,
fraction=1, pad=0.04,
extend='both',
label = 'Voltage Applied')
a01.axis('off')
a0.set_title('Raw Spectra for Dev: ' + data['name'] + ' Measured: ' + data['datetime'].strftime('%b %d, %Y at %H:%M') )
a0.set_xlabel('Wavelength (nm)')
a0.set_ylabel('Power (dBm)')
a0.xaxis.set_major_locator(MaxNLocator(18))
a2.set_title('Zoom Window to Peak Nearest {:} nm'.format(ideal_peak_wl))
a2.set_xlabel('\nWavelength (nm)')
a2.set_ylabel('Power (dBm)')
a1.plot(data['voltages'], data['currents']*1e3, '-o', color = 'purple')
a1.set_title('IV Curve')
a1.set_xlabel('Voltage (V)')
a1.set_ylabel('Current (mA)')
fig.tight_layout()
if save:
fig.savefig(directory + data['name'] + '_VWSweep.png',
dpi = 500)
plt.close()
else:
plt.show()
except:
print('Empty data')
def extract_peaks(data,
chan = 1,
zoom_span = 0.75,
prominence = 4.5,
fit_order = 8,
fsr = 15,
ideal_peak_wl = 1550,
exclude = False):
try:
peak_wl = np.array([])
peak_pw = np.array([])
peak_width = np.array([])
peak_depth = np.array([])
for i in range(len(data['wavelengths'])):
wl = np.array(data['wavelengths'][i])
pw = np.array(data['powers'][i][chan - 1])
ridx = np.isfinite(wl) & np.isfinite(pw)
baseline = np.poly1d(np.polyfit(wl[ridx],pw[ridx],fit_order))
pw_bs = pw - baseline(wl) + max(baseline(wl)) - max(pw)
wl_per_args = wl[1] - wl[0]
peaks ,_ = find_peaks(-pw_bs, prominence = prominence, distance = int(fsr/wl_per_args))
idx = np.abs(wl[peaks] - ideal_peak_wl).argmin()
center_peak = peaks[idx]
span = int(0.5*zoom_span/wl_per_args)
start_zoom, stop_zoom = center_peak - span, center_peak + span
wl_left = wl[start_zoom:center_peak]
wl_right = wl[center_peak:stop_zoom]
pw_left = pw[start_zoom:center_peak]
pw_right = pw[center_peak:stop_zoom]
peak_wl = np.append(peak_wl, wl[center_peak])
peak_pw = np.append(peak_pw, pw[center_peak])
peak_depth = np.append(peak_depth, peak_prominences(-pw_bs, center_peak.flatten(), wlen=span*2)[0])
peak_half = (peak_pw[i] + (peak_depth[i]/2))
peak_left = wl_left[np.abs(pw_left - peak_half).argmin()]
peak_right = wl_right[np.abs(pw_right - peak_half).argmin()]
peak_width = np.append(peak_width, peak_right - peak_left)
if(exclude == False):
return peak_wl, peak_pw, peak_depth, peak_width
else:
return np.zeros(11), np.full(11, np.inf), np.zeros(11), np.zeros(11)
except:
print('Empty data')
return np.zeros(11), np.full(11, np.inf), np.zeros(11), np.zeros(11)
def plot_resonances(data, peak, ave_res, row_num, col_num):
# plot resonances, peak widths, and peak depths
for i in range(0, len(peak), 6):
fig = plt.figure( figsize = (20,14), dpi = 100 )
fig.suptitle('row_' + str(row_num) + '_col_' + str(col_num) + ': ' + str(ave_res[int(i/6)]) + ' nm resonance')
ax = fig.add_subplot(211)
ax.set_title('Resonance and peak width as voltage is swept from -2.0V to 0.5V')
ax.set_ylabel('Wavelength (nm)')
ax.set_xlabel('Voltage (V)')
ax2 = fig.add_subplot(212)
ax2.set_title('Peak depth as voltage is swept from -2.0V to 0.5V')
ax2.set_ylim(0,40)
ax2.set_ylabel('Power (dBm)')
ax2.set_xlabel('Voltage (V)')
colors = ['r', 'g', 'b', 'orange', 'purple', 'grey', 'gold']
dice = ['Die_01', 'Die_07', 'Die_13', 'Die_15', 'Die_17', 'Die_25', 'Die_37']
v, r, w, d = [], [], [], []
for j in range(6):
try:
voltages = data[j]['voltages']
v.append(voltages[np.abs(peak[i+j,1]) != np.inf])
r.append(peak[i+j,0][np.abs(peak[i+j,1]) != np.inf])
w.append(peak[i+j,3][np.abs(peak[i+j,1]) != np.inf])
d.append(peak[i+j,2][np.abs(peak[i+j,1]) != np.inf])
ax.plot(v[j], r[j], color=colors[j], label=dice[j] + ' resonance')
ax.plot(v[j], w[j], '--', color=colors[j], label=dice[j] + ' peak width')
ax.legend(loc='upper right');
ax2.plot(v[j], d[j], color=colors[j], label=dice[j] +' peak depth')
ax2.legend(loc='upper right');
except:
voltages = np.zeros(len(peak[i+j,0]))
v.append(voltages[np.abs(peak[i+j,1]) != np.inf])
r.append(peak[i+j,0][np.abs(peak[i+j,1]) != np.inf])
w.append(peak[i+j,3][np.abs(peak[i+j,1]) != np.inf])
d.append(peak[i+j,2][np.abs(peak[i+j,1]) != np.inf])
ax.plot(v[j], r[j], color=colors[j], label=dice[j] + ' resonance')
ax.plot(v[j], w[j], '--', color=colors[j], label=dice[j] + ' peak width')
ax.legend(loc='upper right');
ax2.plot(v[j], d[j], color=colors[j], label=dice[j] +' peak depth')
ax2.legend(loc='upper right');
fig.savefig('figures/r' + str(row_num) + '_c' + str(col_num) + '_' + str(ave_res[int(i/6)]) + 'nm.png')
def plot_average_resonances(data, peak, ave_res, row_num, col_num):
# plot resonances, peak widths, and peak depths
for i in range(0, len(peak), 6):
fig = plt.figure( figsize = (20,14), dpi = 100 )
fig.suptitle('row_' + str(row_num) + '_col_' + str(col_num) + ': ' + str(ave_res[int(i/6)]) + ' nm resonance')
ax = fig.add_subplot(211)
ax.set_title('Average resonance and peak width')
ax.set_ylabel('Wavelength (nm)')
ax.set_xlabel('Voltage (V)')
ax2 = fig.add_subplot(212)
ax2.set_title('Average peak depth')
ax2.set_ylim(0,40)
ax2.set_ylabel('Power (dBm)')
ax2.set_xlabel('Voltage (V)')
v, r, w, d = [], [], [], []
for j in range(6):
try:
voltages = data[j]['voltages']
voltages[np.abs(peak[i+j,1]) == np.inf] = np.nan
v.append(voltages)
resonances = peak[i+j,0]
resonances[np.abs(peak[i+j,1]) == np.inf] = np.nan
r.append(resonances)
widths = peak[i+j,3]
widths[np.abs(peak[i+j,1]) == np.inf] = np.nan
w.append(widths)
depths = peak[i+j,2]
depths[np.abs(peak[i+j,1]) == np.inf] = np.nan
d.append(depths)
except:
voltages = np.zeros(len(peak[i+j,0]))
voltages[np.abs(peak[i+j,1]) == np.inf] = np.nan
v.append(voltages)
resonances = peak[i+j,0]
resonances[np.abs(peak[i+j,1]) == np.inf] = np.nan
r.append(resonances)
widths = peak[i+j,3]
widths[np.abs(peak[i+j,1]) == np.inf] = np.nan
w.append(widths)
depths = peak[i+j,2]
depths[np.abs(peak[i+j,1]) == np.inf] = np.nan
d.append(depths)
v_ave = np.nanmean((v), axis=0)
r_ave = np.nanmean((r), axis=0)
w_ave = np.nanmean((w), axis=0)
d_ave = np.nanmean((d), axis=0)
ax.plot(v_ave, r_ave, color='orangered', lw=3, label='average resonance')
ax.plot(v_ave, w_ave, '--', color='orangered', lw=3, label='average peak width')
ax.legend(loc='upper right');
ax2.plot(v_ave, d_ave, color='orangered', lw=3, label='average peak depth')
ax2.legend(loc='upper right');
v_std = np.nanstd((v), axis=0)
r_std = np.nanstd((r), axis=0)
w_std = np.nanstd((w), axis=0)
d_std = np.nanstd((d), axis=0)
ax.fill_between(v_ave, r_ave-r_std,r_ave+r_std, color='orangered', alpha=.1)
ax.fill_between(v_ave, w_ave-w_std,w_ave+w_std, color='orangered', alpha=.1)
ax2.fill_between(v_ave, d_ave-d_std,d_ave+d_std, color='orangered', alpha=.1)
fig.savefig('figures/r' + str(row_num) + '_c' + str(col_num) + '_' + str(ave_res[int(i/6)]) + 'nm_ave.png')
def plot_res(
data,
peak,
ave_res,
row_num,
col_num,
num_die=6,
peak0=[],
num_die0=3,
colors = ['r', 'g', 'b', 'orange', 'purple', 'grey', 'black', 'blue', 'cyan'],
dice = ['Die_01', 'Die_07', 'Die_13', 'Die_15', 'Die_17', 'Die_25', 'Die-39 (from Q4 Condition #1 - 3.6E13 Doping)', 'Die-19 (from Q3 Condition #2 - 3.6E13 Doping)', 'Die-49 (from Q4 Condition #2 6.6E13)']):
# generate plots for each peak
for i in range(0, len(peak), num_die):
fig = plt.figure( figsize=(20,14), dpi=100 )
fig.suptitle('row_' + str(row_num) + '_col_' + str(col_num) + ': ' + str(ave_res[i//num_die]) + ' nm resonance')
ax1 = fig.add_subplot(211)
ax1.set_title('Resonance and peak width as voltage is swept from -2.0V to 0.5V')
ax1.set_ylabel('Wavelength (nm)')
ax1.set_xlabel('Voltage (V)')
ax2 = fig.add_subplot(212)
ax2.set_title('Peak depth as voltage is swept from -2.0V to 0.5V')
ax2.set_ylim(0,40)
ax2.set_ylabel('Power (dBm)')
ax2.set_xlabel('Voltage (V)')
v, r, w, d = [], [], [], []
# save average resonance, peak width, and peak depth data for each die
for j in range(num_die):
try:
voltages = data[j]['voltages']
voltages[np.abs(peak[i+j,1]) == np.inf] = np.nan
v.append(voltages)
resonances = peak[i+j,0]
resonances[np.abs(peak[i+j,1]) == np.inf] = np.nan
r.append(resonances)
widths = peak[i+j,3]
widths[np.abs(peak[i+j,1]) == np.inf] = np.nan
w.append(widths)
depths = peak[i+j,2]
depths[np.abs(peak[i+j,1]) == np.inf] = np.nan
d.append(depths)
except:
voltages = np.zeros(len(peak[i+j,0]))
voltages[np.abs(peak[i+j,1]) == np.inf] = np.nan
v.append(voltages)
resonances = peak[i+j,0]
resonances[np.abs(peak[i+j,1]) == np.inf] = np.nan
r.append(resonances)
widths = peak[i+j,3]
widths[np.abs(peak[i+j,1]) == np.inf] = np.nan
w.append(widths)
depths = peak[i+j,2]
depths[np.abs(peak[i+j,1]) == np.inf] = np.nan
d.append(depths)
# plot data for each die except comparison
v_ave = np.nanmean((v), axis=0)
r_ave = np.nanmean((r), axis=0)
w_ave = np.nanmean((w), axis=0)
d_ave = np.nanmean((d), axis=0)
ax1.plot(v_ave, r_ave, color='orangered', lw=3, label='Average resonance from Q2 Cond #1 - 2.4E13 Doping')
ax1.plot(v_ave, w_ave, '--', color='orangered', lw=3, label='Average peak from Q2 Cond #1 - 2.4E13 Doping')
ax2.plot(v_ave, d_ave, color='orangered', lw=3, label='Average peak depth from Q2 Cond #1 - 2.4E13 Doping')
# show standard deviations
v_std = np.nanstd((v), axis=0)
r_std = np.nanstd((r), axis=0)
w_std = np.nanstd((w), axis=0)
d_std = np.nanstd((d), axis=0)
ax1.fill_between(v_ave, r_ave-r_std,r_ave+r_std, color='orangered', alpha=.1)
ax1.fill_between(v_ave, w_ave-w_std,w_ave+w_std, color='orangered', alpha=.1)
ax2.fill_between(v_ave, d_ave-d_std,d_ave+d_std, color='orangered', alpha=.1)
# plot data for comparison die
# voltages0 = data[num_die]['voltages']
# v0 = voltages0[np.abs(peak0[i//num_die,1]) != np.inf]
# r0 = peak0[i//num_die,0][np.abs(peak0[i//num_die,1]) != np.inf]
# w0 = peak0[i//num_die,3][np.abs(peak0[i//num_die,1]) != np.inf]
# d0 = peak0[i//num_die,2][np.abs(peak0[i//num_die,1]) != np.inf]
# ax1.plot(v0, r0, color=colors[num_die], label=dice[num_die] + ' resonance')
# ax1.plot(v0, w0, '--', color=colors[num_die], label=dice[num_die] + ' peak width')
# ax2.plot(v0, d0, color=colors[num_die], label=dice[num_die] +' peak depth')
# ax1.legend(loc='upper right');
# ax2.legend(loc='upper right');
v0, r0, w0, d0 = [], [], [], []
for j in range(num_die0):
try:
voltages0 = data[num_die+j]['voltages']
v0.append(voltages0[np.abs(peak0[i//num_die*num_die0+j,1]) != np.inf])
r0.append(peak0[i//num_die*num_die0+j,0][np.abs(peak0[i//num_die*num_die0+j,1]) != np.inf])
w0.append(peak0[i//num_die*num_die0+j,3][np.abs(peak0[i//num_die*num_die0+j,1]) != np.inf])
d0.append(peak0[i//num_die*num_die0+j,2][np.abs(peak0[i//num_die*num_die0+j,1]) != np.inf])
ax1.plot(v0[j], r0[j], color=colors[num_die+j], label=dice[num_die+j] + ' resonance')
ax1.plot(v0[j], w0[j], '--', color=colors[num_die+j], label=dice[num_die+j] + ' peak width')
ax2.plot(v0[j], d0[j], color=colors[num_die+j], label=dice[num_die+j] +' peak depth')
except:
voltages0 = np.zeros(len(peak0[i//num_die*num_die0+j,0]))
v0.append(voltages0[np.abs(peak0[i//num_die*num_die0+j,1]) != np.inf])
r0.append(peak0[i//num_die*num_die0+j,0][np.abs(peak0[i//num_die*num_die0+j,1]) != np.inf])
w0.append(peak0[i//num_die*num_die0+j,3][np.abs(peak0[i//num_die*num_die0+j,1]) != np.inf])
d0.append(peak0[i//num_die*num_die0+j,2][np.abs(peak0[i//num_die*num_die0+j,1]) != np.inf])
ax1.plot(v0[j], r0[j], color=colors[num_die+j], label=dice[num_die+j] + ' resonance')
ax1.plot(v0[j], w0[j], '--', color=colors[num_die+j], label=dice[num_die+j] + ' peak width');
ax2.plot(v0[j], d0[j], color=colors[num_die+j], label=dice[num_die+j] +' peak depth')
ax1.legend(loc='upper right');
ax2.legend(loc='upper right');
fig.savefig('figures/r' + str(row_num) + '_c' + str(col_num) + '_' + str(ave_res[i//num_die]) + 'nm_ave.png')