Hi,
I use this command to calculate an array of 3x3 matrices
sigma = data[indices, 3:12].reshape((-1, 3, 3))
to return
# Plot the xx, yy and zz components as a function of the first column
plt.figure()
labels = ("xx", "yy", "zz")
for i, label in enumerate(labels):
plt.plot(Ef, sigma[:, i, i], label=label)
plt.legend(loc="best")
plt.xlabel(r"Energy [eV]")
plt.ylabel(r"$\sigma$ [1/$\Omega$ m s]")
plt.tight_layout()
plt.show()
Without an small example of the arrays *data* and *indices* (as well as
possibly *Ef*) or a more precise description of their shape and
dimensions, I have to admit that it is a bit difficult (at least for me)
to understand precisely what you are trying to plot and to invert.
For what I understood, I wonder if you are not just looking for
something like ``sigma[:, i, i][::-1]`` (more information on slicing
here: Indexing — NumPy v1.13 Manual),
I may just have missed the point. Beware that you may also have to flip
the *labels*.
Best regards,
Adrien
···
On 04/16/2018 07:25 AM, alberto wrote:
Hi,
I use this command to calculate an array of 3x3 matrices
sigma = data[indices, 3:12].reshape((-1, 3, 3))
to return
# Plot the xx, yy and zz components as a function of the first column
plt.figure()
labels = ("xx", "yy", "zz")
for i, label in enumerate(labels):
??? plt.plot(Ef, sigma[:, i, i], label=label)
plt.legend(loc="best")
plt.xlabel(r"Energy [eV]")
plt.ylabel(r"\\sigma [1/\\Omega m s]")
plt.tight_layout()
plt.show()
How could invert the results xx to zz?
something as data[indices, 12:3]?
regards
Alberto
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