def LoadData(self, data_item_number, filename):
"""LoadData(self, data_item_number, filename) --> none
Loads the data from filename into the data_item_number.
"""
try:
datafile = Data(str(filename),
debug=True) # does all the hard work here
except Exception as e:
ShowWarningDialog(
self.parent,
"Could not load the file: " + filename +
" \nPlease check the format.\n\n Stoner.Data" +
" gave the following error:\n" + str(e),
)
else:
# For the freak case of only one data point
try:
if datafile.setas.cols["axes"] == 0:
self.x_col = datafile.find_col(self.x_col)
self.y_col = datafile.find_col(self.y_col)
self.e_col = datafile.find_col(self.e_col)
datafile.etsas(x=self.x_col, y=self.y_col, e=self.e_col)
else:
self.x_col = datafile.setas.cols["xcol"]
self.y_col = datafile.setas.cols["ycol"][0]
if len(datafile.setas.cols["yerr"]) > 0:
self.e_col = datafile.setas.cols["yerr"][0]
else:
datafile.add_column(np.ones(len(datafile)))
datafile.setas[-1] = "e"
except Exception as e:
ShowWarningDialog(
self.parent,
"The data file does not contain" +
"all the columns specified in the opions\n" + e.message,
)
# Okay now we have showed a dialog lets bail out ...
return
# The data is set by the default Template.__init__ function, neat hu
# Know the loaded data goes into *_raw so that they are not
# changed by the transforms
datafile.y = np.where(datafile.y == 0.0, 1e-8, datafile.y)
self.data[data_item_number].x_raw = datafile.x
self.data[data_item_number].y_raw = datafile.y
self.data[data_item_number].error_raw = datafile.e
# Run the commands on the data - this also sets the x,y, error memebers
# of that data item.
self.data[data_item_number].run_command()
# Send an update that new data has been loaded
self.SendUpdateDataEvent()
def collate(grp,trail,**kargs):
"""Gather all the data up again."""
grp.sort()
final=Data()
final.add_column(grp[0].column('Energy'),'Energy')
for g in grp:
final.add_column(g.column('Asym'),g.title)
if "group_key" in kargs:
final[kargs["group_key"]]=grp.key
final["path"]=trail
if "save" in kargs and kargs["save"]:
final.save(kargs["filename"])
return final
def collate(grp, trail, **kargs):
"""Gather all the data up again."""
grp.sort()
final = Data()
final.add_column(grp[0].column("Energy"), "Energy")
for g in grp:
final.add_column(g.column("Asym"), g.title)
if "group_key" in kargs:
final[kargs["group_key"]] = grp.key
final["path"] = trail
if "save" in kargs and kargs["save"]:
final.save(kargs["filename"])
return final
def LoadData(self, data_item_number, filename):
"""LoadData(self, data_item_number, filename) --> none
Loads the data from filename into the data_item_number.
"""
try:
datafile=Data(str(filename),debug=True) # does all the hard work here
except Exception as e:
ShowWarningDialog(self.parent, 'Could not load the file: ' +\
filename + ' \nPlease check the format.\n\n Stoner.Data'\
+ ' gave the following error:\n' + str(e))
else:
# For the freak case of only one data point
try:
if datafile.setas.cols["axes"]==0:
self.x_col=datafile.find_col(self.x_col)
self.y_col=datafile.find_col(self.y_col)
self.e_col=datafile.find_col(self.e_col)
datafile.etsas(x=self.x_col,y=self.y_col,e=self.e_col)
else:
self.x_col=datafile.setas.cols["xcol"]
self.y_col=datafile.setas.cols["ycol"][0]
if len(datafile.setas.cols["yerr"])>0:
self.e_col=datafile.setas.cols["yerr"][0]
else:
datafile.add_column(np.ones(len(datafile)))
datafile.setas[-1]="e"
except Exception as e:
ShowWarningDialog(self.parent, 'The data file does not contain'\
+ 'all the columns specified in the opions\n'+e.message)
# Okay now we have showed a dialog lets bail out ...
return
# The data is set by the default Template.__init__ function, neat hu
# Know the loaded data goes into *_raw so that they are not
# changed by the transforms
datafile.y=np.where(datafile.y==0.0,1E-8,datafile.y)
self.data[data_item_number].x_raw = datafile.x
self.data[data_item_number].y_raw = datafile.y
self.data[data_item_number].error_raw = datafile.e
# Run the commands on the data - this also sets the x,y, error memebers
# of that data item.
self.data[data_item_number].run_command()
# Send an update that new data has been loaded
self.SendUpdateDataEvent()
def norm_group(pos, _, **kargs):
"""Takes the drain current for each file in group and builds an analysis file and works out the mean drain"""
if "signal" in kargs:
signal = kargs["signal"]
else:
signal = "fluo"
lfit = kargs["lfit"]
rfit = kargs["rfit"]
posfile = Data()
posfile.metadata = pos[0].metadata
posfile = posfile & pos[0].column(0)
posfile.column_headers = ["Energy"]
for f in pos:
print(str(f["run"]) + str(f.find_col(signal)))
posfile = posfile & f.column(signal)
posfile.add_column(lambda r: np.mean(r[1:]), "mean drain")
ec = posfile.find_col("Energy")
md = posfile.find_col("mean drain")
linearfit = scipy.poly1d(
posfile.polyfit(ec, md, 1, lambda x, y: lfit[0] <= x <= lfit[1]))
posfile.add_column(lambda r: r[md] - linearfit(r[ec]), "minus linear")
highend = posfile.mean("minus", lambda r: rfit[0] <= r[ec] <= rfit[1])
ml = posfile.find_col("minus linear")
posfile.add_column(lambda r: r[ml] / highend, "normalised")
if "group_key" in kargs:
posfile[kargs["group_key"]] = pos.key
return posfile
def norm_group(pos,_,**kargs):
"""Takes the drain current for each file in group and builds an analysis file and works out the mean drain"""
if "signal" in kargs:
signal=kargs["signal"]
else:
signal="fluo"
lfit=kargs["lfit"]
rfit=kargs["rfit"]
posfile=Data()
posfile.metadata=pos[0].metadata
posfile=posfile&pos[0].column(0)
posfile.column_headers=['Energy']
for f in pos:
print(str(f["run"])+str(f.find_col(signal)))
posfile=posfile&f.column(signal)
posfile.add_column(lambda r:np.mean(r[1:]),"mean drain")
ec=posfile.find_col('Energy')
md=posfile.find_col('mean drain')
linearfit=scipy.poly1d(posfile.polyfit(ec,md,1,lambda x,y:lfit[0]<=x<=lfit[1]))
posfile.add_column(lambda r:r[md]-linearfit(r[ec]),'minus linear')
highend=posfile.mean('minus',lambda r:rfit[0]<=r[ec]<=rfit[1])
ml=posfile.find_col('minus linear')
posfile.add_column(lambda r:r[ml]/highend,"normalised")
if "group_key" in kargs:
posfile[kargs["group_key"]]=pos.key
return posfile
d.setas="xy"
d.labels[d.find_col('Angle')]=r"Reflection Angle $\theta$"
t.del_rows(0, lambda x,y: x<critical_edge)
t.setas="xy"
t.template.fig_width=7.0
t.template.fig_height=5.0
t.plot(fmt='go', plotter=pyplot.semilogy)
main_fig=d.plot(figure=t.fig, plotter=pyplot.semilogy)
d.show()
#Now convert the angle to sin^2
t.apply(lambda x: np.sin(np.radians(x[0]/2.0))**2, 0,header=r"$sin^2\theta$")
# Now create the m^2 order
m=np.arange(len(t))+fringe_offset
m=m**2
#And add it to t
t.add_column(m, column_header='$m^2$')
#Now we can it a straight line
t.setas="x..y"
fit=t.lmfit(Linear,result=True,replace=False,header="Fit")
g=t["LinearModel:slope"]
gerr=t["LinearModel:slope err"]/g
g=np.sqrt(1.0/g)
gerr/=2.0
l=float(d['Lambda'])
th=l/(2*g)
therr=th*(gerr)
t.inset(loc="top right",width=0.5,height=0.4)
t.plot_xy(r"Fit",r"$sin^2\theta$", 'b-',label="Fit")
t.plot_xy(r"$m^2$",r"$sin^2\theta$", 'ro',label="Peak Position")
t.xlabel="Fringe $m^2$"
d.setas = "xy"
d.labels[d.find_col("Angle")] = r"Reflection Angle $\theta$"
t.del_rows(0, lambda x, y: x < critical_edge)
t.setas = "xy"
t.template.fig_width = 7.0
t.template.fig_height = 5.0
t.plot(fmt="go", plotter=pyplot.semilogy)
main_fig = d.plot(figure=t.fig, plotter=pyplot.semilogy)
d.show()
# Now convert the angle to sin^2
t.apply(lambda x: np.sin(np.radians(x[0] / 2.0)) ** 2, 0, header=r"$sin^2\theta$")
# Now create the m^2 order
m = np.arange(len(t)) + fringe_offset
m = m ** 2
# And add it to t
t.add_column(m, column_header="$m^2$")
# Now we can it a straight line
t.setas = "x..y"
fit = t.lmfit(Linear, result=True, replace=False, header="Fit")
g = t["LinearModel:slope"]
gerr = t["LinearModel:slope err"] / g
g = np.sqrt(1.0 / g)
gerr /= 2.0
l = float(d["Lambda"])
th = l / (2 * g)
therr = th * (gerr)
t.inset(loc="top right", width=0.5, height=0.4)
t.plot_xy(r"Fit", r"$sin^2\theta$", "b-", label="Fit")
t.plot_xy(r"$m^2$", r"$sin^2\theta$", "ro", label="Peak Position")
t.xlabel = "Fringe $m^2$"
t.del_rows(0, lambda x, y: x < critical_edge)
t.setas = "xy"
t.template.fig_width = 7.0
t.template.fig_height = 5.0
t.plot(fmt='go', plotter=pyplot.semilogy)
main_fig = d.plot(figure=t.fig, plotter=pyplot.semilogy)
d.show()
#Now convert the angle to sin^2
t.apply(lambda x: np.sin(np.radians(x[0] / 2.0))**2,
0,
header=r"$sin^2\theta$")
# Now create the m^2 order
m = np.arange(len(t)) + fringe_offset
m = m**2
#And add it to t
t.add_column(m, column_header='$m^2$')
#Now we can it a straight line
t.setas = "x..y"
fit = t.lmfit(Linear, result=True, replace=False, header="Fit")
g = t["LinearModel:slope"]
gerr = t["LinearModel:slope err"] / g
g = np.sqrt(1.0 / g)
gerr /= 2.0
l = float(d['Lambda'])
th = l / (2 * g)
therr = th * (gerr)
t.inset(loc="top right", width=0.5, height=0.4)
t.plot_xy(r"Fit", r"$sin^2\theta$", 'b-', label="Fit")
t.plot_xy(r"$m^2$", r"$sin^2\theta$", 'ro', label="Peak Position")
t.xlabel = "Fringe $m^2$"
d.del_rows(0, lambda x, r: np.any(np.isnan(r)))
popt, pcov = d.curve_fit(bg_wrapper,
xcol=t_col,
ycol=r_col,
p0=p0,
absolute_sigma=False)
perr = np.sqrt(np.diag(pcov))
labels = [r"\theta_D", r"\rho_0", r"A"]
units = ["K", r"\Omega m", r"\Omega m"]
annotation = [
"${}$: {}\n".format(l, format_error(v, e, latex=True, mode="eng", units=u))
for l, v, e, u in zip(labels, popt, perr, units)
]
annotation = "\n".join(annotation)
popt = np.append(popt, 5)
T = d.column(t_col)
d.add_column(blochGrueneisen(T, *popt), header=r"Bloch")
d.plot_xy(
t_col,
[r_col, "Bloch"],
["ro", "b-"],
label=["Data", r"$Bloch-Gr\"ueisen Fit$"],
)
d.xlabel = "Temperature (K)"
d.ylabel = "Resistance ($\Omega$)"
text(0.05, 0.65, annotation, transform=d.axes[0].transAxes)
