BandU
BandU OVERVIEW
A package that performs a principal component inspired analysis on the Bloch wavefunctions of periodic material to provide a real space visualization of the states that significantly contribute to the Fermi surface.
These real space functions can then be projected onto the Fermi surface to provide a clear visual for where a nesting vector may combine two points in reciprocal space.
This package is designed to be very straightforward in its use, offering Fermi surface and BandU function visualizations in as little as 5 lines of Python script. This package can also be used to just visual the Fermi surface, without BandU projections, if provided with the necessary k-point and eigenvalue data.
INSTALLATION INSTRUCTIONS
THROUGH GITHUB
-
Inside that directory type on the command line
"git clone https://github.com/pcross0405/BandU.git" -
Type "cd BandU"
-
Make sure you have python's build tool up to date with
"python3 -m pip install --upgrade build" -
Once up to date type
"python3 -m build" -
This should create a "dist" directory with a .whl file inside
-
On the command line type
"pip install dist/*.whl"
THROUGH PIP
pip install bandu
DEPENDENCIES
REQUIRED FOR VISUALIZING FERMI SURFACE
REQUIRED FOR CUSTOM COLORS
WAVEFUNCTIONS THAT CAN BE READ DIRECTLY
Currently only reading directly from ABINIT 7 and 10 wavefunctions is supported. Reading eigenvalues from other DFT packages will come in future updates.
REPORTING ISSUES
Please report any issues here
TUTORIAL
An example script that can run the different functions of the BandU program is given below.
from bandu.bandu import BandU
from bandu.abinit_reader import AbinitWFK
from bandu.isosurface_class import Isosurface
from bandu.plotter import Plotter
from bandu.colors import Colors
root_name = 'your file root name here' # root_name of WFK files and of XSF files
xsf_number = 1 # XSF file number to be read in
energy_level = 0.000 # Energy relative to the Fermi energy to be sampled
width = 0.0005 # Search half the the width above and below the specified energy level
wfk_path = f'path\to\WFK\file\{root_name}_o_WFK'
xsf_path = f'path\to\XSF\file\{root_name}_bandu_{xsf_number}'
bandu_name = f'{root_name}_bandu'
def main(
principal_orbital_components:bool,
fermi_surface:bool,
fermi_surface_projection:bool,
load_fermi_surface:bool
)->None:
# this option will generate the principal orbital components 1 through 10
# to generate more or less, adjust the range of the "nums" keyword in the ToXSF() function
# the energy sampled can be set, relative to the Fermi energy, by changing the the "energy_level" global variable
# states are included in the analysis if they are within +/- 1/2*width of the set energy_level
# to get fewer or more states, decrease or increase, respectively, the "width" global variable
# by default, the prinicipal orbital components are generated from an irreducible wedge of the Brillouin Zone
# to generate from the full BZ, change the "sym" attribute in the BandU class from "False" to "True"
if principal_orbital_components:
wfk_gen = AbinitWFK(wfk_path).ReadWFK(
energy_level = energy_level,
width=width
)
wfk = BandU(
wfks = wfk_gen,
energy_level = energy_level,
width = width,
sym = False
)
wfk.ToXSF(
xsf_name = bandu_name,
nums = [1,10]
)
# this option will only generate an energy isosurface and will not project principal component overlap onto the surface
# the "energy_level" global variable is the energy at which the isosurface will be be generated, relative to the Fermi energy
# so energy_level = 0.0 will generate the Fermi surface
# the "width" global variable determines how many states are included in the generation of the isosurface
# a small width (~10 meV or ~0.5 mHa) is best here as larger widths may introduce bands that do not cross the Fermi energy
# the color of the surface can be changed to any string compatible with the matplotlib colors
# see named colors here: https://matplotlib.org/stable/gallery/color/named_colors.html
# the Plot function has many other keywords to customize the visuals to the users liking, see the docstring for more
elif fermi_surface:
contours = Isosurface(
wfk_name = wfk_path,
energy_level = energy_level,
width = width
)
contours.Contour() # make contours
plot = Plotter(
isosurface = contours,
save_file=f'{root_name}_bandu_{xsf_number}_fermi_surf.pkl'
) # create plotter object
plot.Plot(
color = 'silver',
) # plot contours
# this option will generate an energy isosurface as well as project the overlap of a principal orbital component onto the surface
# everything remains the same as the previous option, except now the principal orbtial component XSF file is needed
# also the color of the surface is done with the Colors module by default
# other colors can be made with the Colors module, also any matplotlib colormap works
elif fermi_surface_projection:
contours = Isosurface(
wfk_name = wfk_path,
energy_level = energy_level,
width = width
)
contours.Contour() # make contours
plot = Plotter(
isosurface = contours,
save_file=f'{root_name}_bandu_{xsf_number}_fermi_surf.pkl'
) # create plotter object
overlap_vals = plot.SurfaceColor(
wfk_path=wfk_path,
xsf_path=xsf_path,
) # compute overlap between principal orbital component and states in Brillouin Zone
plot.Plot(
surface_vals = overlap_vals,
colormap = Colors().blues,
) # plot contours
# this option will load a previously generated and saved fermi surface file
# update the "save_path" keyword to match the path and name of your save file
elif load_fermi_surface:
Plotter().Load(
save_path='{root_name}_bandu_{xsf_number}_fermi_surf.pkl',
)
# to run any of the options above, make sure to set that option to "True"
# also be sure that the other options (or at least all options that come before) are set to "False"
# the main function will only run which ever option is the first found to be "True" in top to bottom order
# in other words, the priority follows as most to least in the order:
# principal_orbital_components -> fermi_surface -> fermi_surface_projection -> load_fermi_surface
if __name__ == '__main__':
main(
principal_orbital_components=True,
fermi_surface=True,
fermi_surface_projection=True,
load_fermi_surface=True
)
Metadata
Release files for bandu 1.3.11
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| bandu-1.3.11.tar.gz | 33.7 kB | With provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| bandu-1.3.11-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 68.7 kB
Release files / bandu-1.3.11.tar.gz
| Download URL | bandu-1.3.11.tar.gz |
|---|---|
| Size | 33.7 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
0c227311f66554fabecf19a8763f0df37f7c990759287bbe512590ed5c26762e
|
|
BLAKE2b-256 checksum How to use checksums |
726aa55cf6b6260afbf416c8d3c76ab4a4bf9b833df8709feab8698b1b780ee6
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.12
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on May 27, 2026.
Transparency logRelease files / bandu-1.3.11-py3-none-any.whl
| Download URL | bandu-1.3.11-py3-none-any.whl |
|---|---|
| Size | 35.0 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
a8fb50f24899935873f36764c77d4bb954ad118cbb21838accfb03e8246d1716
|
|
BLAKE2b-256 checksum How to use checksums |
3d0a035bd58579ed7ca8680e27d40c9d63eca6314a11f8850dfb324eab2364ad
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.12
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on May 27, 2026.
Transparency logSecurity for bandu 1.3.11
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
Full provenance
All 2 files in this release have been uploaded with provenance metadata.
Attestation for bandu-1.3.11.tar.gz
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on May 27, 2026.
Transparency logA note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.