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Clarification on Spin Texture Plotting: Components and Arrow Representation #163
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Hi @aktariitkgp,
Is this question regarding a 2D or 3D Fermi surface? For the 2D Fermi surface, we calculate the projections for For the 3D Fermi surface, the total spin magnitude is already plotted by default.
Just to clarify, are you asking for the color scale to represent the combination of spin components (e.g., Currently, we don't support this directly, but I can investigate how we might add this capability. Best, |
Hi @lllangWV My question is regarding a 2D fermi surface. I would like to know if it’s possible to plot the arrows as in-plane spin vectors (Sx + Sy) while using the color plot to represent the projection of Sz. All of this would be in a 2D Fermi surface. Thank you for your consideration, and I appreciate your help. Best regards, |
Hey,
Yes, that's correct. Currently, the available options for pyprocar.fermi2D(code='vasp',
dirname=data_dir,
# energy=0.60,
energy=-0.90,
fermi=-1.1904,
spin_texture=True,
no_arrow=False,
arrow_size=1,
arrow_density=8,
spin_projection='x',
clim=[-0.2, 0.2],
plot_color_bar=True)
Yes, this is possible. We assume Sz is always out-of-plane, while Sx and Sy are in-plane. The options mentioned above can be used to adjust accordingly. Best, |
Dear PyProcar Developers,
I am currently working with spin texture plots using PyProcar (QE-DFT data) and have a question regarding the interpretation of the arrows in these plots. Specifically:
1. Arrow Direction and Size:
◦ I understand that the direction of the arrows represents the spin vector direction, and the size indicates the magnitude of the spin. Is this magnitude representing the total spin ∣S∣ (i.e., the magnitude of the spin vector), or is it normalized in some way? If it is normalized, could you explain how this normalization is performed?
2. Plotting Custom Spin Component Combinations:
◦ I am interested in plotting specific combinations of spin components, such as Sx+Sy or Sx+Sy+Sz. How can I modify the plotting routine or configuration to visualize these custom combinations? Is there a specific option or parameter in PyProcar that allows for plotting such combinations, or do I need to preprocess the data to achieve this?
Thank you for your assistance!
Best regards,
Aktar
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