def Plot_fancy(self, *args, **kwargs):
"""
Just like Plot_all but with a fancy layout that is more suited to
ipython notebooks
"""
remove = ["T_av", "T0", "Tp", "Tm", "I_fit", "T0_fit"]
measures = [i for i in self.measures if i not in remove]
ref_meas = ["kxx", "kxx/T", "kxy", "kxy/kxx", "dTx",
"dTx/T", "dTy", "dTy/dTx", "Resistance", "Tp_Tm"]
measures = [i for i in ref_meas if i in measures]
n = len(measures)
fig, ax = V.create_grid(n)
try:
show = kwargs["show"]
kwargs.pop("show")
except KeyError:
show = None
try:
filename = kwargs["filename"]
kwargs.pop("filename")
except KeyError:
filename = None
try:
overwrite = kwargs["overwrite"]
kwargs.pop("overwrite")
except KeyError:
overwrite = "ask"
for i in range(n):
self.Plot(measures[i], *args, show=None,
fig=fig, ax=ax[i], **kwargs)
if hasattr(self, "__sample") is True:
plt.suptitle(self["sample"], y=0.95, fontsize=22)
else:
pass
fig.tight_layout(rect=[0.01, 0.01, 1, 0.96])
if filename is not None:
filename = os.path.abspath(filename)
U.save_to_pdf(filename, fig, overwrite=overwrite)
else:
pass
if show is True:
plt.show()
elif show is False:
plt.close()
else:
pass
return fig, ax
def Plot_all(self, *args, **kwargs):
"""
Plots all non trivial measures, all the same kwargs as Conductivity.Plot
with the addition of filename to save the file.
"""
remove = ["T_av", "T0", "Tp", "Tm", "T0_fit", "I_fit"]
measures = [i for i in self.measures if i not in remove]
figures = []
try:
filename = kwargs["filename"]
kwargs.pop("filename")
except KeyError:
filename = None
try:
overwrite = kwargs["overwrite"]
kwargs.pop("overwrite")
except KeyError:
overwrite = "ask"
for key in measures:
figures.append(self.Plot(key, *args, **kwargs)[0])
if filename is not None:
filename = os.path.abspath(filename)
U.save_to_pdf(filename, figures, overwrite=overwrite)
else:
pass
return
def Plot_fancy(self, *args, **kwargs):
"""
Just like Plot_all but with a fancy layout that is more suited to
ipython notebooks
"""
remove = ["T_av", "T0", "Tp", "Tm"]
if len(self.measurements) > 1:
remove.append("Tp_Tm")
else:
pass
measures = [i for i in self.measures if i not in remove]
ref_meas = [
"kxx", "kxx/T", "kxy", "kxy/T", "dTx", "dTx/T", "dTy", "dTy/dTx",
"Resistance"
]
measures = [i for i in ref_meas if i in measures]
n = len(measures)
fig, ax = V.create_grid(n)
try:
show = kwargs["show"]
kwargs.pop("show")
except KeyError:
show = True
# Tries to find sample name
if "sample" in self.parameters:
sample = self.measurements[0]["sample"]
for m in self.measurements:
if sample == m["sample"]:
pass
else:
sample = None
break
try:
filename = kwargs["filename"]
kwargs.pop("filename")
except KeyError:
filename = None
try:
overwrite = kwargs["overwrite"]
kwargs.pop("overwrite")
except KeyError:
overwrite = "ask"
for i in range(n):
self.Plot(measures[i],
*args,
show=None,
fig=fig,
ax=ax[i],
**kwargs)
if sample is not None:
plt.suptitle(sample, y=0.95, fontsize=22)
else:
pass
fig.tight_layout(rect=[0.01, 0.01, 1, 0.95])
if filename is not None:
filename = os.path.abspath(filename)
U.save_to_pdf(filename, fig, overwrite=overwrite)
else:
pass
if show is True:
plt.show()
elif show is False:
plt.close()
else:
pass
return fig, ax
def Current(self, _min, _max, deg=5, T_max=100, N=100, *args, **kwargs):
"""
Used to compute the optimal current function for the sample.
Parameters:
------------------------------------------------------------------------
_min, _max: int or float
The min/max of dT/T in percentages
deg: int
The degree of the polynomial fit
T_max: int or float
T0 max for the plot
N: int
Number of points in the plot
"""
directory = os.path.split(self["filename"])[0]
rnge = "%1.0f%s_to_%1.0f%s.dat" % (_min, "%", _max, "%")
name = "_".join([self["sample"].replace(" ", "_"), "dTovT", rnge])
datafile = os.path.join(directory, name)
n = self["T_av"].shape[0]
dT_T = np.linspace(_min/100, _max/100, n)
alpha = self["w"]*self["t"]/self["L"]
I = np.sqrt(self["kxx"]*alpha*self["T_av"]*dT_T/5000)
coeff_I = np.polyfit(self["T0"], I, deg)
poly_func = np.poly1d(coeff_I)
T0 = np.linspace(0, T_max, N)
I_fit = poly_func(T0)
self["T0_fit"] = T0
self["I_fit"] = I_fit*1000
self["coeff_I"] = coeff_I
self.measures += ["T0_fit", "I_fit"]
# Looks for show as kwarg
try:
show = kwargs["show"]
if type(show) is not bool:
if show is not None:
raise TypeError("show must be of type bool or None")
else:
kwargs.pop("show")
else:
kwargs.pop("show")
except KeyError:
show = True
try:
filename = kwargs["filename"]
kwargs.pop("filename")
except KeyError:
filename = None
label = r"$\Delta$ T / T from %1.2f%s to %1.2f%s" % (
_min, "%", _max, "%")
fig, ax = self.Plot("I_fit", x_axis="T0_fit", show=None, parameters=[])
plt.figtext(1-0.005, 0.005, label, fontsize=14,
va="baseline", ha="right")
if show is True:
plt.show()
elif show is False:
plt.close()
else:
pass
if filename is not None:
filename = os.path.abspath(filename)
U.save_to_pdf(filename, fig)
else:
pass
try:
write = kwargs["write"]
kwargs.pop("write")
except KeyError:
write = True
if write is True:
degrees = np.array([i for i in range(coeff_I.shape[0])])
data = np.array([degrees, coeff_I[::-1]]).T
header = "Current function coefficients\norder\tcoeff"
U.write_to_file(datafile, data, header, fmt=["%i", "%,18e"])
else:
pass
return