i2_ua = np.array(i2_ua)
# First, close any open plots
plt.close('all')
#
# Now, it's time to tell the story
# These plots are organized by the topic being investigated
#
#===============================#
# Generic IV characteristics #
#===============================#
ax1 = init_fig('Voltage (V)','Current ($\mu$A)')
this = lconfig.dfile(data_dir + filename[22])
i = this.data[:,1]*25.242500 - .15605
v = this.data[:,0]
ax1.plot(v,i,marker='d',markersize=4,mec='k',mew=.5,mfc='w',ls='none',label='5.8mm, .55')
this = lconfig.dfile(data_dir + filename[27])
i = this.data[:,1]*25.242500 - .15605
v = this.data[:,0]
ax1.plot(v,i,marker='o',markersize=4,mec='k',mew=.5,mfc='w',ls='none', label='5.8mm, .80')
this = lconfig.dfile(data_dir + filename[39])
i = this.data[:,1]*25.242500 - .15605
v = this.data[:,0]
ax1.plot(v,i,marker='s',markersize=4,mec='k',mew=.5,mfc='k',ls='none', label='11.7mm, .55')
ax1.legend(loc=0)
ax1.set_xlim([-10,10])
export_file = 'ivchar'
plt.savefig(os.path.join(export_dir,export_file + std_type), dpi=std_dpi)
# look for the positive 0 crossing in voltage
if I[index]<0. and I[index+1]>=0.:
Vsample.append(\
V[index] - (V[index+1] - V[index])/(I[index+1] - I[index]) * I[index])
Is = I[index:index+100].tolist()
Is.sort(reverse=True)
tsample.append(t[index+50])
Isample.append(Is[4]) # Reject the 4 largest points
Tsample.append(np.mean(out['T'][index:index+100]))
index+=120
else:
index += 1
out['Tsample'] = Tsample
out['Isample'] = Isample
out['tsample'] = tsample
out['Vsample'] = Vsample
return out
datafile = 'data/a4_1.dat'
#datafile = 'data/b1_1.dat'
data = lconfig.dfile(datafile, afun=fsanalysis, afile=None)
plt.close('all')
lplot.set_defaults(screen_dpi=112)
ax = lplot.init_fig('Voltage (V)', 'Current ($\mu$A)', figure_size=(6., 4.5))
index = data.t()>15.
ax.plot(data.analysis['V'][index], data.analysis['I'][index], '.')
def fsanalysis(fileobj):
# First, copy the meta parameters using the default function
out = lconfig.default_afun(fileobj)
# Create calibrated data
V = fileobj.data[:, 0]
I = fileobj.data[:, 1] * 25.242500 - .15605
ts = 1. / fileobj.config[0].samplehz
t = fileobj.t()
out['V'] = V
out['I'] = I
return out
steelfile = 'data/a3_1.dat'
#steelfile = 'data/b2_3.dat'
steel = lconfig.dfile(steelfile, afun=fsanalysis, afile=None)
C = lconfig.collection(afun=fsanalysis, asave=False)
C.add_dir('../experiment2/data/150_1')
cufile = '../experiment2/data/150_1/ivchar20170412170728.dat'
#cufile = '../experiment2/data/150_1/ivchar20170412175533.dat'
cu1 = lconfig.dfile(cufile, afun=fsanalysis, afile=None)
cufile = '../experiment2/data/150_1/ivchar20170412175136.dat'
#cufile = '../experiment2/data/150_1/ivchar20170412171254.dat'
cu2 = lconfig.dfile(cufile, afun=fsanalysis, afile=None)
plt.close('all')
lplot.set_defaults(screen_dpi=112)
ax0 = lplot.init_fig('Voltage (V)', 'Current ($\mu$A)', figure_size=(6., 4.5))
ax0.plot(steel.analysis['V'][17700:349700],
steel.analysis['I'][17700:349700],
out['Vsample'] = Vsample
return out
files = ['data/b1_1.dat', 'data/b2_3.dat']
tstart = [24., 24.]
tstop = [344., 600.]
styles = ['o', 's']
LAB = ['20scfh', '25scfh']
plt.close('all')
lplot.set_defaults(screen_dpi=112)
ax0 = lplot.init_fig('Floating Potential (V)',
'Saturation Current ($\mu$A)',
figure_size=(6., 4.5))
for index in range(len(files)):
data = lconfig.dfile(files[index], afun=fsanalysis, afile=None)
t = np.array(data.analysis['tsample'])
V = np.array(data.analysis['Vsample'])
I = np.array(data.analysis['Isample'])
ii = (t > tstart[index]) * (t < tstop[index])
ax0.plot(V[ii], I[ii], styles[index], mec='k', mfc='w', label=LAB[index])
ax0.legend(loc=0)
ax0.get_figure().savefig('float_sat.png')
# Create calibrated data
V = fileobj.data[:,0]
I = fileobj.data[:,1]*25.242500 - .15605
Vtc1 = smooth(fileobj.data[:,2],200)
Vtc2 = smooth(fileobj.data[:,3],200)
Vcj = tc.KmV(21.)
ts = 1./fileobj.config[0].samplehz
t = np.arange(0,len(I)*ts,ts)
out['V'] = V
out['I'] = I
out['T1'] = tc.K(Vtc1*1000.+Vcj)
out['T2'] = tc.K(Vtc2*1000.+Vcj)
out['t'] = t
return out
dfile = lconfig.dfile('data/drun2055_2.dat', afun=fsanalysis)
f = plt.figure(1)
f.clf()
ax1 = f.add_subplot(211)
ax2 = f.add_subplot(212)
f = plt.figure(2)
f.clf()
ax3 = f.add_subplot(111)
vtest = 0.0
vtol = .02
index = (dfile.analysis['V']<(vtest+vtol)) * (dfile.analysis['V']>(vtest-vtol))
V = dfile.analysis['V'][index]
def loadall(WORKING_DIR='/home/chris/experiment/data'):
"""Load all *.dat files containing lconfig data
records, DATA_RECORD = loadall()
records = number of files loaded
DATA_RECORD = dictionary containing the results
"""
DATA_RECORD = {
'data': [],
'path': [],
'filename': [],
'fileprefix': [],
'date': [],
'points': [],
'excite': [],
'V': [],
'I': [],
'analysis': []
}
meta_params = [
'standoff_in', 'plate_tpeak_c', 'fuel_scfh', 'oxygen_scfh',
'flow_scfh', 'ratio_fto'
]
# Add the meta params to the initial data record
for thismeta in meta_params:
DATA_RECORD[thismeta] = []
contents = os.listdir(WORKING_DIR)
contents.sort()
records = 0
for filename in contents:
thisfile = os.path.join(WORKING_DIR, filename)
thisfile = os.path.abspath(thisfile)
# Only analyze *.dat files
fileprefix, _, temp = filename.partition('.')
if temp == 'dat':
records += 1
DATA_RECORD['analysis'].append({})
DATA_RECORD['filename'].append(filename)
DATA_RECORD['path'].append(thisfile)
# load
data = lconfig.dfile(thisfile)
DATA_RECORD['data'].append(data)
# Strip the date from the file prefix
# Isolate only characters that are alpha
temp = ''
for thischar in fileprefix:
if thischar.isalpha():
temp += thischar
else:
break
DATA_RECORD['fileprefix'].append(temp)
# Test starting time
DATA_RECORD['date'].append(data.start)
# Pull the aosignal parameter
DATA_RECORD['excite'].append(data.config[0].aoch[0].signal)
# Get the calibrated data
DATA_RECORD['V'].append(data.data[:, 0])
DATA_RECORD['I'].append(data.data[:, 1] * 25.242500 - .15605)
# Now read the meta parameters
for thismeta in meta_params:
if thismeta in data.config[0].meta:
DATA_RECORD[thismeta].append(data.config[0].meta[thismeta])
else:
DATA_RECORD[thismeta].append(None)
# How many data points were collected?
DATA_RECORD['points'].append(data.data.shape)
return DATA_RECORD
