def plot_chgload_dt(data,
time_scale=1.,
loadv_scale=1.,
chgv_scale=1.,
alpha=0.8,
colors=cs.clist(),
center=False,
figsize=(5, 4)):
# """ Returns a lineplot figure of osrs in the order of the dataset provided.
# requres time/chgv/loadv dataset. Note time does not currently work but
# time scale can be used to adjust the time bins"""
fig, ax1 = plt.subplots(figsize=figsize)
time = data['time'] * time_scale
maxt = max(time)
chgv = data['chgv'] * chgv_scale
loadv = data['loadv'] * loadv_scale
#time = np.linspace(0,maxt,len(time),endpoint=True)
if center:
time = time - np.median(time)
ax1.plot(time, loadv, color=colors[0], label='Load', alpha=alpha)
ax2 = ax1.twinx()
ax2.plot(time, chgv, color=colors[1], label='Charge', alpha=alpha)
ax1.set_title('Charge/Load Pulses')
fig.tight_layout()
return fig
def plot_mTrace(dataset,
time_scale=1.,
channel='loadv',
channel_scale=1.,
alpha=0.8,
colors=cs.clist(),
labels=None,
center=False):
""" Returns a figure, axes, and lines for a single channel from a dataset of multiple traces """
fig, ax = plt.subplots(sharex=True)
mykeys = sorted(dataset.keys())
lines = []
for i, data in enumerate(mykeys):
time = dataset[data]['time'] * time_scale
maxt = max(time)
chanv = dataset[data][channel] * channel_scale
if center:
time = time - np.median(time)
if labels is None:
lbl = None
else:
lbl = labels[i]
#print len(time), len(chanv)
line, = ax.plot(time, chanv, color=colors[i], label=lbl, alpha=alpha)
lines.append(line)
ax.set_title('Channel Voltage')
fig.tight_layout()
return fig, ax, lines
def plot_mCH_dt(dataset,
time_scale=1.,
channel='loadv',
channel_scale=1.,
alpha=0.8,
colors=cs.clist(),
labels=None,
center=False):
# """ Returns a lineplot figure of osrs in the order of the dataset provided.
# requres time/chgv/loadv dataset. Note time does not currently work but
# time scale can be used to adjust the time bins"""
fig = plt.figure(figsize=(5, 4))
Plot = fig.add_subplot(111)
mykeys = sorted(dataset.keys())
for i, data in enumerate(mykeys):
time = dataset[data]['time'] * time_scale
maxt = max(time)
chanv = dataset[data][channel] * channel_scale
#time = np.linspace(0,maxt,len(time),endpoint=True)
if center:
time = time - np.median(time)
if labels is None:
lbl = data
else:
lbl = labels[i]
Plot.plot(time, chanv, color=colors[i], label=lbl, alpha=alpha)
Plot.set_title('Channel Voltage')
fig.tight_layout()
return fig
def plot_osrs_scatter(dataset,
loadR=3.9,
time_scale=1.,
alt_x=None,
chgv_scale=1.,
loadv_scale=.1,
color=cs.clist()[0]):
""" Returns a scatterplot figure of osrs in the order of the dataset provided.
requres time/chgv/loadv dataset """
fig = plt.figure(figsize=(5, 4))
Plot = fig.add_subplot(111)
mykeys = sorted(dataset.keys())
for i, data in enumerate(mykeys):
minosr = []
chgv = dataset[data]['chgv'] * chgv_scale
loadv = dataset[data]['loadv'] * loadv_scale
minosr = (max(chgv) / 2 - max(loadv)) * loadR / max(loadv)
if alt_x is None:
Plot.scatter(i, minosrs[i], color=color)
else:
Plot.scatter(alt_x[i], minosr, color=color)
del chgv, loadv
Plot.set_title('On-state Resistance')
fig.tight_layout()
return fig
def plot_osrs_dt(dataset,
time_scale=1.,
chgv_scale=1.,
loadv_scale=.1,
alpha=0.8,
colors=cs.clist(),
loadR=3.9,
labels=None,
center=False):
""" Returns a lineplot figure of osrs in the order of the dataset provided.
requres time/chgv/loadv dataset. Note time does not currently work but
time scale can be used to adjust the time bins"""
fig = plt.figure(figsize=(5, 4))
Plot = fig.add_subplot(111)
mykeys = sorted(dataset.keys())
for i, data in enumerate(mykeys):
osr = []
time = dataset[data]['time'] * time_scale
maxt = max(time)
chgv = dataset[data]['chgv'] * chgv_scale
loadv = dataset[data]['loadv'] * loadv_scale
#osr = (max(chgv)/2-max(loadv))*loadR/loadv
osr = (max(chgv) / 2 - (loadv)) * loadR / loadv
#time = np.linspace(0,maxt,len(time))
time = time - np.mean(time)
print len(osr), len(time)
time = time[[osr > 0] and [osr < 50]]
osr = osr[[osr > 0] and [osr < 50]]
#time = time - np.median(time)
if labels is None:
lbl = data
else:
lbl = labels[i]
Plot.plot(time, osr, color=colors[i], label=lbl, alpha=alpha)
Plot.set_title('On-state Resistance')
fig.tight_layout()
return fig
import numpy as np
import matplotlib.pyplot as plt
import colors as cs
import pandas as pd
colors = cs.clist()
def del_nonfloat(filename, delim=',', header=None):
""" reads file and removes all lines after header which do not contain
float-like strings then overwrites the file after adding the header back in"""
filein = open(filename, 'r')
lines = ''
deleted = 0
if header is None:
rlines = filein.readlines()
else:
rlines = filein.readlines()[header:]
filein.close()
for l in rlines:
words = l.rstrip('/n').split(delim)
try:
[float(w) for w in words]
lines += l
except:
deleted += 1
fileout = open(filename, 'w')
fileout.write(lines)
fileout.close()
return deleted
Min = np.min(dataset[key][channel])
Max = np.max(dataset[key][channel])
Avg = np.average(dataset[key][channel])
print '%s\t%.2e\t%.2e\t%.2e' % (Name, Min, Max, Avg)
sys.stdout.close()
os.system('unix2dos %s' % (folder + calc_filename))
sys.stdout = temp
# Plot the data
fig, ax, lines = scplt.plot_mTrace(dataset,
channel='chgv',
time_scale=t_scale,
channel_scale=chgv_scale,
labels=labels,
center=False,
colors=cs.clist(len(dataset) / ch_skip))
# LEGEND PARAMS
if legends:
legend = ax.legend(fontsize=11, bbox_to_anchor=(1, 1), ncol=2)
legend.get_frame().set_alpha(.5)
# PLOT LAYOUT
for line in lines:
line.set_linewidth(0.8)
line.set_alpha(.6)
for line in lines[-4:]:
line.set_linewidth(2)
line.set_alpha(0.8)
ax.set_title('EHT RCC Hipot Test')
ax.set_xlabel('Time (ns)')
#sys.exit()
Plaser = Plaser * E_laser / NRJ #normalize laser power function for energy per pulse
#check1_Elaser=np.max(integ.cumtrapz(t,Plaser)) # check elaser is correct
#print check1_Elaser
t_recomb_logarray = np.linspace(
-4, -7, 10) # array of 10^-4 to 10^-7 recombination times, arraysize=10
fig, ax1 = plt.subplots()
for i, logt_recomb in enumerate(
t_recomb_logarray): #loop through recombination times in seconds
t_recomb = 10**logt_recomb #calculate carrier concnetration as a function of time based on Nunally (eq8)
K = (1 - R) / (w * l * d) / (h * c / lmbda) * (
1 - np.exp(-Abs * d)
) #constant factor to include switch volume and light efficiency
n = n0 + K * np.exp(-t / t_recomb) * integ.cumtrapz(
np.exp(t / t_recomb) * Plaser, x=t,
initial=0) #carrier concetration in m^-3
lab = '%.2f-us' % (t_recomb * 1e6)
logt = np.log10(t)
ax1.plot(logt, n, label=lab, color=cs.clist()[i])
#ax2 = ax1.twinx()
#ax2.plot(t, Plaser, linestyle='--')
plt.xlabel('Log10(Time) (s)')
ax1.set_ylabel('Carrier Density (#/cm3)')
#ax2.set_ylabel('Laser Intensity')
legend = ax1.legend()
#legend.get_frame().set_facecolor('none')
legend.get_frame().set_alpha(0.6)
[i.set_lw(2.) for i in legend.get_lines()]
plt.show()
rf = recovery_factor
cols = [(1, 0, 0), (0, 1, 0), (0, 0, 1)]
lines = ['--', '-', ':']
#plot heat
plt.figure(figsize=(5, 4))
plt.subplots_adjust(right=.6)
heat_v = []
for i, s in enumerate([5, 34]):
sarea = 2.
rf = s
print s
for j, x in enumerate([.5, 1, 1.5, 3, 5]):
freq = x * 1e5
heat_V = (Vlt / 2 / (osr + Z))**2 * osr * pulsewidth * freq
heat_I = (Cur)**2 * osr * pulsewidth * freq
trans_coef_ratio = np.log10((heat_V / heat_I) / dT / sarea * rf)
plt.plot(Vlt, trans_coef_ratio, label='%.0f-kHz' % (freq/1e3), \
color=colors.clist()[j], linestyle=lines[i+1], linewidth=2)
plt.xlabel('Charge Voltage/Current $(V)$', fontsize=12)
plt.ylabel('log(H) (W/cm$^2$K)', fontsize=12)
plt.xticks(fontsize=10)
plt.yticks(fontsize=10)
plt.ylim((-4, 3))
legend = plt.legend(loc='best', fontsize=10, ncol=2)
legend.get_frame().set_alpha(0.6)
plt.tight_layout()
plt.savefig('Heat_Flux_V_%s.png' % time.time(), transparent=True)
plt.close()
intensity = [1]
for i, k in enumerate(z):
intensity.append(intensity[-1] * np.exp(-Abs * d))
#constant factor to include switch volume and light efficiency
K = (1 - R) / (w * l * d) / (h * c / lmbda) * (intensity[-1])
R = 0
#carrier concetration in m^-3
n = n0 + K * np.exp(-t / t_recomb) * integ.cumtrapz(
np.exp(t / t_recomb) * Plaser, x=t, initial=0)
lab = '%.2f-us' % (t_recomb * 1e6)
logt = np.log10(t)
carrier_peak.append(np.max(n))
if i % (len(z) / 10) == 0:
print 'Intensity(x=%.2fmm) =\t%.2e' % (k * 1e3, intensity[-1])
fig, ax1 = plt.subplots()
ax1.plot(z * 1e3, carrier_peak, c=cs.clist()[1], lw=2)
ax2 = ax1.twinx()
ax2.plot(z * 1e3, intensity[:-1], c=cs.clist()[2], lw=2)
ax1.set_xlabel('Depth (mm)')
ax1.set_ylabel('Carrier Density (#/cm3)')
ax2.set_ylabel('Relative Intensity (AU)')
ax1.set_title('Peak Carrier Density Profile')
ax1col = cs.clist()[1]
ax2col = cs.clist()[2]
ax1.yaxis.label.set_color(ax1col)
ax1.spines['left'].set_color(ax1col)
ax2.spines['left'].set_color(ax1col)
ax1.tick_params(axis='y', colors=ax1col)
ax2.yaxis.label.set_color(ax2col)
ax1.spines['right'].set_color(ax2col)
ax2.spines['right'].set_color(ax2col)