From 18177b83a0af9b5196cdfb0955da13c9fa0d7698 Mon Sep 17 00:00:00 2001 From: Badal Mondal <56228126+bmondal94@users.noreply.github.com> Date: Thu, 27 Jun 2024 15:27:07 +0100 Subject: [PATCH] Banduppy new updates (#27) * Bug fix for PC band path Cartesian coordinate conversion * Improved band structures plotting * Implemented plotting band centers at each SCF cycles * Implemented save band structure data independently * Implemented effective mass modules * Added version track file * Added bibliography file (.bib) for referencing * Added tips and tricks in README * Documentation improved * Bug fix in tutorial scipts * Fix some printing mistakes --------- Co-authored-by: Badal Mondal --- README.md | 190 +- REFERENCES.md | 46 + RELEASE.md | 35 + banduppy/BasicFunctions/__init__.py | 4 +- banduppy/BasicFunctions/general_functions.py | 24 +- .../BasicFunctions/general_plot_functions.py | 12 +- banduppy/Utilities/EBS_plot.py | 483 +- banduppy/Utilities/EBS_properties.py | 466 +- banduppy/Utilities/__init__.py | 8 +- banduppy/Utilities/folding_degree_plot.py | 12 +- banduppy/__init__.py | 6 +- banduppy/src/__init__.py | 8 +- banduppy/src/folding.py | 52 +- banduppy/src/folding_properties.py | 16 +- banduppy/src/unfolding.py | 266 +- banduppy/unfolding.py | 734 +- tutorials/BandCenters_broadening.py | 44 +- tutorials/CompareOldNewBandupPyVersion.py | 96 - tutorials/GeneralBandUPpyTutorial.py | 33 +- .../Ge_supercell/bandstructure_unfolded.dat | 7102 +++++----- .../Ge_supercell/kpoints_unfolded.dat | 128 +- .../bandstructure_unfolded.dat | 11094 ++++++++-------- .../Si_Ge_supercell/kpoints_unfolded.dat | 128 +- .../Si_supercell/bandstructure_unfolded.dat | 7164 +++++----- .../Si_supercell/kpoints_unfolded.dat | 128 +- tutorials/SiGe_OverlayBandStructurePlot.py | 10 +- tutorials/Vasp/input/KPOINTS_PC | 2 +- tutorials/Vasp/input/KPOINTS_SC | 2 +- .../Vasp/results/bandstructure_unfolded.dat | 8944 ++++++------- tutorials/Vasp/results/kpoints_unfolded.dat | 178 +- tutorials/Vasp/results/results.out | 155 +- tutorials/Vasp/run_banduppy_vasp.py | 36 +- tutorials/sample_output_from_banduppy.out | 155 +- 33 files changed, 19378 insertions(+), 18383 deletions(-) create mode 100644 REFERENCES.md create mode 100644 RELEASE.md delete mode 100644 tutorials/CompareOldNewBandupPyVersion.py diff --git a/README.md b/README.md index dcbcc28..2c8aedd 100644 --- a/README.md +++ b/README.md @@ -19,7 +19,7 @@ Unfolded band structure - flatband mode (Si0.5Ge0.5) | Unfolded band structure __Developer of BandUPpy :__ -* [Stepan S. Tsirkin](https://github.com/stepan-tsirkin), University of Zurich, [stepan.tsirkin@uzh.ch](mailto:stepan.tsirkin@uzh.ch) +* [Stepan S. Tsirkin](https://github.com/stepan-tsirkin) __BandUPpy Package is Restructured by (maintainer):__ @@ -37,9 +37,9 @@ __BandUPpy Contributors:__ [Contributors](https://github.com/band-unfolding/ban * We sincerely thank each and every contributor for their valuable input and support. -__Contact us:__ [Email developer/maintainer team](mailto:stepan.tsirkin@uzh.ch,badalmondal.chembgc@gmail.com) +__Contact us:__ [Email developer/maintainer team](mailto:stepan.tsirkin@ehu.eus,badalmondal.chembgc@gmail.com) -* If you would like to contribute to the development of `BandUPpy` or request new functionality, please get in touch with [us](mailto:stepan.tsirkin@uzh.ch,badalmondal.chembgc@gmail.com) or open a pull request. We will be happy to support your request ASAP. +* If you would like to contribute to the development of `BandUPpy` or request new functionality, please get in touch with [us](mailto:stepan.tsirkin@ehu.eus,badalmondal.chembgc@gmail.com) or open a pull request. We will be happy to support your request ASAP. @@ -70,6 +70,10 @@ __Contact us:__ [Email developer/maintainer team](mailto:stepan.tsirkin@uzh.ch,b cd banduppy pip install . ``` +Or, without cloning +``` + pip install git+https://github.com/band-unfolding/banduppy.git #@specific_branch +``` ### 4. Installation using `setup.py` [deprecated] Alternatively you can clone the repository and run `setup.py` in the usual manner: @@ -109,9 +113,17 @@ banduppy package: 2. BandStructure class 2.1 BandStructure() 3. Properties class - 3.1 band_centers_broadening_bandstr() - 4. Plotting class - 4.1 plot_ebs() + 3.1 collect_bandstr_data_only_in_energy_window() + 3.2 band_centers_broadening_bandstr() + 3.3 calculate_effecfive_mass() + 3.4 fit_functions() + 4. SaveBandStructuredata class + 4.1 save_unfolded_pc_kpts() + 4.2 save_unfolded_bandstucture() + 4.3 save_unfolded_bandcenter() + 5. Plotting class + 5.1 plot_ebs() + 5.2 plot_scf() ``` #### 1. Lat's start @@ -223,18 +235,19 @@ __Option 2:__ If this part is used independently from the above instances re-ini 'fname': 'bandstructure_unfolded', 'fname_suffix': ''}) ``` -#### 5. Determine band centers and band width -``` -# This uses SCF algorithm of automatic band center determination from -# PRB 89, 041407(R) (2014) paper. -# -------------------- Initiate Properties method ----------------------------- +#### 4. Determine band centers and band width +Band ceneters are determined using the SCF algorithm of automatic band center determination from [Paulo V. C. Medeiros, Sven Stafström, and Jonas Björk, Phys. Rev. B **89**, 041407(R) (2014)](http://doi.org/10.1103/PhysRevB.89.041407) paper. +```. + # -------------------- Initiate Properties method ----------------------------- unfolded_band_properties = banduppy.Properties(print_log='high') - min_sum_dNs_for_a_band = 0.05 - threshold_dN_2b_trial_band_center = 0.05 - prec_pos_band_centers = 1e-5 # in eV - err_tolerance = 1e-8 - min_dN = 1e-5 - + #=================================== + min_dN = 1e-5 # get rid of small weights bands + threshold_dN_2b_trial_band_center = 0.05 # initial guess of the band centers based on the threshold wights. + min_sum_dNs_for_a_band = 0.05 # Cut off criteria for minimum weights that a band center should have. + #=================================== + err_tolerance = 1e-8 # The tolerance to group the bands set per unique kpoints value. + prec_pos_band_centers = 1e-5 # in eV # Precision when compared band centers from previous and current SCF + #=================================== unfolded_bandstructure_properties, all_scf_data = \ unfolded_band_properties.band_centers_broadening_bandstr(unfolded_bandstructure_, min_dN_pre_screening=min_dN, @@ -242,11 +255,37 @@ __Option 2:__ If this part is used independently from the above instances re-ini threshold_dN_2b_trial_band_center, min_sum_dNs_for_a_band=min_sum_dNs_for_a_band, precision_pos_band_centers=prec_pos_band_centers, - err_tolerance_compare_kpts=err_tolerance, + err_tolerance_compare_kpts_val=err_tolerance, collect_scf_data=False) ``` -#### 4. Plot unfolded band structure (scatter plot/density plot/band_centers plot) -##### --------------------- Plot band structure --------------------------------- +#### 5. Determine effective mass (parabolic and non-parabolic) from part of the band structure or band center data +``` + m_star, optimized_parameters, convergence_measure = \ + unfolded_band_properties.calculate_effecfive_mass(kpath, band_energy, + initial_guess_params=None, + params_bounds = (-np.inf, np.inf), + fit_weights=None, absolute_weights=False, + parabolic_dispersion=True, + hyperbolic_dispersion_positive=False, + hyperbolic_dispersion_negative=False, + params_name = ['alpha', 'kshift', 'cbm', 'gamma']) + #=================================== + band_energy_fit = unfolded_band_properties.fit_functions(kpath, optimized_parameters, + parabolic_dispersion=True, + hyperbolic_dispersion_positive=False, + hyperbolic_dispersion_negative=False) +``` +#### 6. Determine alloy-scattering potential from part of the band structure or band center data +This is based on the ... paper. +``` + TBA +``` +#### 7. Save unfolded band structure and band center data +One can save the generated data within the function call for unfolding and band ceneter determination routines as shown above. [recommened] + +__However,__ you may want save the generated data (from the above function calls) after some post processing, for e.g., you want to save part of the data only. __In such cases,__ you can use functions from `SaveBandStructuredata` class to save those data. Note that the data format should be compatible with the required data format for each functions. + +#### 8. Plot unfolded band structure (scatter plot/density plot/band_centers plot) ``` # Fermi energy Efermi = 5.9740 @@ -258,6 +297,7 @@ __Option 2:__ If this part is used independently from the above instances re-ini save_file_name = 'unfolded_bandstructure.png' ``` __Option 1:__ Continue with previous instance. +##### --------------------- Plot band structure --------------------------------- ``` fig, ax, CountFig \ = band_unfold.plot_ebs(save_figure_dir=save_to_dir, save_file_name=save_file_name, CountFig=None, @@ -277,7 +317,10 @@ __Option 2:__ Using BandUPpy Plotting module. kpline = np.loadtxt(f'{save_to_dir}/kpoints_unfolded.dat')[:,1] with open(f'{save_to_dir}/KPOINTS_SpecialKpoints.pkl', 'rb') as handle: special_kpoints_pos_labels = pickle.load(handle) - +``` +##### --------------------- Plot band structure ---------------------------------- +``` + fig, ax, CountFig \ = plot_unfold.plot_ebs(kpath_in_angs=kpline, unfolded_bandstructure=unfolded_bandstructure_, save_file_name=save_file_name, CountFig=None, @@ -287,23 +330,7 @@ __Option 2:__ Using BandUPpy Plotting module. threshold_weight=0.01, show_legend=True, color='gray', color_map='viridis') ``` -##### ----------------- Plot the band centers ----------------------------------- -``` - # --------------------- Initiate Plotting method ---------------------------- - plot_unfold = banduppy.Plotting(save_figure_dir=save_to_dir) - - # --------------------- Plot band centers and band width -------------------- - fig, ax, CountFig \ - = plot_unfold.plot_ebs(kpath_in_angs=kpline, - unfolded_bandstructure=unfolded_bandstructure_properties, - save_file_name=save_file_name, CountFig=None, - Ef=Efermi, Emin=Emin, Emax=Emax, pad_energy_scale=0.5, - mode="band_centers", special_kpoints=special_kpoints_pos_labels, - marker='x', smear=0.2, plot_colormap_bandcenter=True, - color='black', color_map='viridis') -``` - -##### ------------ Plot and overlay multiple band structures -------------------- +##### --------- Plot and overlay multiple band structures ------------ ``` fig, ax, CountFig \ = plot_unfold.plot_ebs(kpath_in_angs=kpline1, @@ -312,53 +339,87 @@ __Option 2:__ Using BandUPpy Plotting module. Ef=Efermi, Emin=Emin, Emax=Emax, pad_energy_scale=0.5, mode="fatband", special_kpoints=special_kpoints_pos_labels1, plotSC=True, fatfactor=20, nE=100, smear=0.2, - color='red', color_map='viridis') + color='red', color_map='viridis', show_plot=False) fig, ax, CountFig \ = plot_unfold.plot_ebs(ax=ax, kpath_in_angs=kpline1, - unfolded_bandstructure=unfolded_bandstructure_properties, + unfolded_bandstructure=unfolded_bandstructure_2, save_file_name=save_file_name, CountFig=None, Ef=Efermi, Emin=Emin, Emax=Emax, pad_energy_scale=0.5, - mode="band_centers", special_kpoints=None, - marker='x', smear=0.2, - color='black', color_map='viridis') + mode="fatband", special_kpoints=None, marker='x', + smear=0.2, color='black', color_map='viridis') +``` + +##### ----------------- Plot the band centers ----------------------------------- +``` + fig, ax, CountFig \ + = plot_unfold.plot_ebs(kpath_in_angs=kpline, + unfolded_bandstructure=unfolded_bandstructure_properties, + save_file_name=save_file_name, CountFig=None, threshold_weight=min_dN, + Ef=Efermi, Emin=Emin, Emax=Emax, pad_energy_scale=0.5, + mode="band_centers", special_kpoints=special_kpoints_pos_labels, + marker='x', smear=0.2, plot_colormap_bandcenter=True, + color='black', color_map='viridis') +``` +##### -------------- Plot the band centers SCF cycles --------------------- +``` + plot_unfold.plot_scf(kpath_in_angs=kpline, unfolded_bandstructure=unfolded_bandstructure_, + al_scf_data=all_scf_data, plot_max_scf_steps=3, save_file_name=save_file_name, + Ef=Efermi, Emin=Emin, Emax=Emax, pad_energy_scale=0.5, threshold_weight=min_dN, + special_kpoints=special_kpoints_pos_labels, plot_sc_unfold=True, marker='o', + fatfactor=20, smear=0.05, color=None, color_map='viridis', show_legend=False, + plot_colormap_bandcenter=True, show_colorbar=True, colorbar_label=None, + vmin=None, vmax=None, dpi=72) ``` -## Citations and references: +## Tips and tricks: -If you use `BandUPpy` in your work, you should: +__Problem:__ I am getting `RuntimeError` in one of my calculations using VASP. How can I resolve this? - * **State EXPLICITLY that you've used the BandUP code** - (or a modified version of it, if this is the case). - * **Read and cite the following papers** (and the appropriate - references therein): - ->> Paulo V. C. Medeiros, Sven Stafström, and Jonas Björk, - [Phys. Rev. B **89**, 041407(R) (2014)](http://dx.doi.org/10.1103/PhysRevB.89.041407) ->> Paulo V. C. Medeiros, Stepan S. Tsirkin, Sven Stafström, and Jonas Björk, - [Phys. Rev. B **91**, 041116(R) (2015)](http://dx.doi.org/10.1103/PhysRevB.91.041116) +`RuntimeError: *** error - computed ncnt=18134 != input nplane=18133` + +**Answer**: VASP does not write which plane waves it uses to the `WAVECAR` file. Therefore, when `banduppy` (specifically `IrRep`) reads the band structure, it tries to mimic `VASP`'s selection and ordering of plane waves that fall within the cut-off sphere. Occasionally, due to numerical errors, one code might consider a plane wave within the sphere while the other does not. This discrepancy can result in an extra vector, as seen in the above case. To address this, use a small correction coefficient (`_correct_Ecut0`) value. This slightly adjusts the `Ecut` to either exclude or include plane waves near the boundary of the cut-off sphere. In the example case, use small negative correction to exclude plane waves near the boundary of the cut-off sphere. Use small positive correction when `computed ncnt < input nplane`. + +`bands = banduppy.BandStructure(code="vasp", spinor=spinorbit, fPOS = "POSCAR", fWAV = "WAVECAR", _correct_Ecut0=-1e-7)` + + + +## Citations and references: -If you use `BandUPpy`, please also cite +If you use `BandUPpy` in your work, please: ->> Mikel Iraola, Juan L. Mañes, Barry Bradlyn, Titus Neupert, Maia G. Vergniory, Stepan S. Tsirkin - "IrRep: symmetry eigenvalues and irreducible representations of ab initio band structures", [arXiv:2009.01764](https://arxiv.org/abs/2009.01764) + * **State EXPLICITLY that you have used the BandUP code** (or a modified version of it, if this is the case), for instance, adding a sentence like: -An appropriate way of acknowledging the use of BandUP in your -publications would be, for instance, adding a sentence like: + "The unfolding has been performed using the BandUP(py) code" - "The unfolding has been performed using the BandUP code" + * **Read and cite the following papers** (and the appropriate references therein): + +>> 1. Paulo V. C. Medeiros, Sven Stafström, and Jonas Björk, + [Phys. Rev. B **89**, 041407(R) (2014)](http://doi.org/10.1103/PhysRevB.89.041407) +>> 2. Paulo V. C. Medeiros, Stepan S. Tsirkin, Sven Stafström, and Jonas Björk, + [Phys. Rev. B **91**, 041116(R) (2015)](http://doi.org/10.1103/PhysRevB.91.041116) +>> 3. Mikel Iraola, Juan L. Mañes, Barry Bradlyn, Titus Neupert, Maia G. Vergniory, Stepan S. Tsirkin, + "IrRep: Symmetry eigenvalues and irreducible representations of ab initio band structures", [Comput. Phys. Commun. **272**, 108226 (2022)](https://doi.org/10.1016/j.cpc.2021.108226) -followed by the citation to our papers. +__Bibliography file:__ Here is the [bibliography (.bib) file](REFERENCES.md) for your convenience. -### Refer to for further details +## Further details ##### ##### + +## Version release +__Latest release: v0.3.2__ + +Chekout out [version release history here](RELEASE.md) for the full list of updates and upgrades. + + + ## License @@ -378,8 +439,7 @@ along with BandUP. If not, see . ## Upcoming (TBD) -1. Effective mass implementation -2. Scattering potential implementation -3. Orbital contribution projection implementation +1. Orbital contribution projection implementation +2. Improve band center determination algorithm diff --git a/REFERENCES.md b/REFERENCES.md new file mode 100644 index 0000000..34918bc --- /dev/null +++ b/REFERENCES.md @@ -0,0 +1,46 @@ + +``` +@article{EffectsMedeirosPRB2014, + title = {Effects of extrinsic and intrinsic perturbations on the electronic structure of graphene: Retaining an effective primitive cell band structure by band unfolding}, + author = {Medeiros, Paulo V. C. and Stafstr\"om, Sven and Bj\"ork, Jonas}, + journal = {Phys. Rev. B}, + volume = {89}, + issue = {4}, + pages = {041407}, + numpages = {4}, + year = {2014}, + month = {Jan}, + publisher = {American Physical Society}, + doi = {10.1103/PhysRevB.89.041407}, + url = {https://link.aps.org/doi/10.1103/PhysRevB.89.041407} +} + + +@article{UnfoldingMedeirosPRB2015, + title = {Unfolding spinor wave functions and expectation values of general operators: Introducing the unfolding-density operator}, + author = {Medeiros, Paulo V. C. and Tsirkin, Stepan S. and Stafstr\"om, Sven and Bj\"ork, Jonas}, + journal = {Phys. Rev. B}, + volume = {91}, + issue = {4}, + pages = {041116}, + numpages = {5}, + year = {2015}, + month = {Jan}, + publisher = {American Physical Society}, + doi = {10.1103/PhysRevB.91.041116}, + url = {https://link.aps.org/doi/10.1103/PhysRevB.91.041116} +} + +@article{IrRepIraolaCPC2022, + title = {IrRep: Symmetry eigenvalues and irreducible representations of ab initio band structures}, + author = {Iraola, Mikel and Mañes, Juan L. and Bradlyn, Barry and Horton, Matthew K. and Neupert, Titus and Vergniory, Maia G. and Tsirkin, Stepan S.}, + journal = {Comput. Phys. Commun.}, + volume = {272}, + pages = {108226}, + year = {2022}, + issn = {0010-4655}, + doi = {10.1016/j.cpc.2021.108226}, + url = {https://www.sciencedirect.com/science/article/pii/S0010465521003386} +} + +``` diff --git a/RELEASE.md b/RELEASE.md new file mode 100644 index 0000000..301a02c --- /dev/null +++ b/RELEASE.md @@ -0,0 +1,35 @@ +__Latest release: v0.3.2__ + +__v0.3.2__ + +* Bug fix for PC band path cartesian coordinate conversion +* Improved band structures plotting +* Implemented plotting band centers at each SCF cycles +* Implemened save band structure data independently +* Implemented effective mass modules +* Added version track file +* Added bibliograpy file (.bib) for referencing +* Added tips and tricks in README +* Documentation improved + +__v0.3.1__ + +* Package release in PyPi repository + +__v0.2.1__ + +* Package restructuring with significant code reimplementation +* Documentation improved +* Implemented folding degree module +* Band centers determination algorithm implemented +* Unfolded band structures plotting module improved + +__v0.2.0__ + +* Band unfolding implemented +* Plot unfolded band structures implemented + + + + + diff --git a/banduppy/BasicFunctions/__init__.py b/banduppy/BasicFunctions/__init__.py index 1a7caba..6f08ac9 100644 --- a/banduppy/BasicFunctions/__init__.py +++ b/banduppy/BasicFunctions/__init__.py @@ -1,4 +1,4 @@ -from .general_functions import SaveData2File, _BasicFunctionsModule +from .general_functions import _SaveData2File, _BasicFunctionsModule -__all__ = ['SaveData2File','_BasicFunctionsModule'] \ No newline at end of file +__all__ = ['_SaveData2File','_BasicFunctionsModule'] diff --git a/banduppy/BasicFunctions/general_functions.py b/banduppy/BasicFunctions/general_functions.py index adbf79f..836859d 100644 --- a/banduppy/BasicFunctions/general_functions.py +++ b/banduppy/BasicFunctions/general_functions.py @@ -67,12 +67,12 @@ def _return_mod(input_array, round_decimals:bool=True): return input_array%1 ## ============================================================================ -class SaveData2File: +class _SaveData2File: def __init__(self): pass @staticmethod - def default_save_settings(save_data): + def _default_save_settings(save_data): tmp_save = {'save2file': False, 'fdir': '.', 'fname': 'test', 'fname_suffix': ''} for ll in tmp_save: if ll in save_data: @@ -80,9 +80,9 @@ def default_save_settings(save_data): return tmp_save @staticmethod - def save_2_file(data=None, save_dir='.', file_name:str='', file_name_suffix:str='', - header_txt:str='', footer_txt:str='',comments_symbol='! ', - np_data_fmt='%12.8f', print_log:bool=True): + def _save_2_file(data=None, save_dir='.', file_name:str='', file_name_suffix:str='', + header_txt:str='', footer_txt:str='',comments_symbol='! ', + np_data_fmt='%12.8f', print_log:bool=True): """ Save the generated SC kpoints to a file. @@ -129,10 +129,10 @@ def save_2_file(data=None, save_dir='.', file_name:str='', file_name_suffix:str= return fname_save_file @staticmethod - def save_sc_kpts_2_file(data=None, save_dir='.', file_name:str='', - file_name_suffix:str='', file_format:str='vasp', - header_txt:str='', footer_txt:str='',comments_symbol='! ', - print_log:bool=False, print_msg:str='Saving to file...'): + def _save_sc_kpts_2_file(data=None, save_dir='.', file_name:str='', + file_name_suffix:str='', file_format:str='vasp', + header_txt:str='', footer_txt:str='',comments_symbol='! ', + print_log:bool=False, print_msg:str='Saving to file...'): """ Save the generated SC kpoints to a file. @@ -175,8 +175,8 @@ def save_sc_kpts_2_file(data=None, save_dir='.', file_name:str='', if print_log: print(f"{'='*_draw_line_length}\n- {print_msg}.") fname_save_file = \ - SaveData2File.save_2_file(data=data, save_dir=save_dir, file_name=file_name, - file_name_suffix=file_name_suffix, header_txt=header_txt, - footer_txt=footer_txt,comments_symbol=comments_symbol) + _SaveData2File._save_2_file(data=data, save_dir=save_dir, file_name=file_name, + file_name_suffix=file_name_suffix, header_txt=header_txt, + footer_txt=footer_txt,comments_symbol=comments_symbol) if print_log: print(f'-- Filepath: {fname_save_file}\n- Done') return fname_save_file \ No newline at end of file diff --git a/banduppy/BasicFunctions/general_plot_functions.py b/banduppy/BasicFunctions/general_plot_functions.py index 2dc8fba..934b153 100644 --- a/banduppy/BasicFunctions/general_plot_functions.py +++ b/banduppy/BasicFunctions/general_plot_functions.py @@ -2,7 +2,7 @@ ### =========================================================================== -class GeneratePlots: +class _GeneratePlots: def __init__(self, save_figure_dir='.'): """ Initialize the plotting class. @@ -32,8 +32,12 @@ def __init__(self, save_figure_dir='.'): plt.rcParams.update(params) plt.rc('font', size=24) - def save_figure(self, fig_name, CountFig=None, fig_dpi=300): - plt.savefig(f'{self.save_figure_folder}/{fig_name}', - bbox_inches='tight', dpi=fig_dpi) + def _save_figure(self,fig_name, fig=None, CountFig=None, **kwargs_savefig): + if fig is not None: + fig.savefig(f'{self.save_figure_folder}/{fig_name}', + bbox_inches='tight', **kwargs_savefig) + else: + plt.savefig(f'{self.save_figure_folder}/{fig_name}', + bbox_inches='tight', **kwargs_savefig) if CountFig is not None: CountFig += 1 return CountFig \ No newline at end of file diff --git a/banduppy/Utilities/EBS_plot.py b/banduppy/Utilities/EBS_plot.py index 9ef4e8e..55fc862 100644 --- a/banduppy/Utilities/EBS_plot.py +++ b/banduppy/Utilities/EBS_plot.py @@ -1,11 +1,10 @@ import numpy as np import matplotlib.pyplot as plt -from ..BasicFunctions.general_plot_functions import GeneratePlots -from .EBS_properties import _FormatSpecialKpts +from ..BasicFunctions.general_plot_functions import _GeneratePlots +from .EBS_properties import _GeneralFunctionsDefs, _FormatSpecialKpts ### =========================================================================== - -class EBSplot(GeneratePlots, _FormatSpecialKpts): +class _EBSplot(_GeneratePlots, _GeneralFunctionsDefs, _FormatSpecialKpts): """ Plotting (effective) band structures and related. @@ -20,192 +19,60 @@ def __init__(self, kpath_in_angs=None, unfolded_bandstructure=None, kpath_in_angs : array, optional k on path (in A^-1) coordinate. The default is None. unfolded_bandstructure : ndarray, optional - Unfolded effective band structure data. - Format: k on path (A^-1), energy, weight, "Sx, Sy, Sz" if is_spinor. + Unfolded effective band structure/band center data. + Format: [k index, k on path (A^-1), energy, weight, "Sx, Sy, Sz" if spinor.] or + Format: [kpoint coordinate, Band center, Band width, Sum of dN] for band centers The default is None. save_figure_dir : str/path, optional Directory where to save the figure. The default is current directory. + + Returns + ------- + kpath_in_angs : array + k on path (in A^-1) coordinate. + unfolded_bandstructure : ndarray + Unfolded effective band structure/band center data. + Format: [k index, k on path (A^-1), energy, weight] or + Format: [kpoint coordinate, Band center, Band width, Sum of dN] for band centers + efermi : float + Default Fermi energy. Set to 0.0. """ - GeneratePlots.__init__(self, save_figure_dir=save_figure_dir) + _GeneratePlots.__init__(self, save_figure_dir=save_figure_dir) self.efermi = 0.0 if kpath_in_angs is None: try: self.kpath_in_angs_ = self.kpline.copy() except: - raise ValueError('No bandstructure data file is found') + raise ValueError('Provide k-path data (kpath_in_angs).') else: self.kpath_in_angs_ = kpath_in_angs.copy() if unfolded_bandstructure is None: try: - self.plot_result = self.unfolded_bandstructure.copy() + plt_result = self.unfolded_bandstructure.copy() except: raise ValueError('No bandstructure data file is found') else: - self.plot_result = unfolded_bandstructure.copy() - - - # def plot(self, ax=None, save_file_name=None, CountFig=None, Ef=None, Emin=None, - # Emax=None, pad_energy_scale:float=0.5, threshold_weight:float=None, - # mode:str="fatband", yaxis_label:str='E (eV)', special_kpoints:dict=None, - # plotSC:bool=True, marker='o', fatfactor=20, nE:int=100, smear:float=0.05, - # scatter_color='gray', color_map='viridis', show_legend:bool=True): - # """ - # Scatter/density plot of the band structure. - - # Parameters - # ---------- - # ax : matplotlib.pyplot axis, optional - # Figure axis to plot on. If None, new figure will be created. - # The default is None. - # save_file_name : str, optional - # Name of the figure file. If None, figure will be not saved. - # The default is None. - # CountFig: int, optional - # Figure count. The default is None. - # Ef : float, optional - # Fermi energy. If None, set to 0.0. The default is None. - # Emin : float, optional - # Minimum in energy. The default is None. - # Emax : float, optional - # Maximum in energy. The default is None. - # pad_energy_scale: float, optional - # Add padding of pad_energy_scale to minimum and maximum energy if Emin - # and Emax are None. The default is 0.5. - # threshold_weight : float, optional - # The band centers with band weights lower than the threshhold weights - # are discarded. The default is None. If None, this is ignored. - # mode : ['fatband','density'], optional - # Mode of plot. The default is "fatband". - # yaxis_label : str, optional - # Y-axis label text. The default is 'E (eV)'. - # special_kpoints : dictionary, optional - # Dictionary of special kpoints position and labels. If None, ignore - # special kpoints. The default is None. - # plotSC : bool, optional - # Plot supercell bandstructure. The default is True. - # marker : matplotlib.pyplot markerMarkerStyle, optional - # The marker style. Marker can be either an instance of the class or - # the text shorthand for a particular marker. - # The default is 'o'. - # fatfactor : int, optional - # Scatter plot marker size. The default is 20. - # nE : int, optional - # Number of pixels in Energy scale when used 'density' mode. - # The default is 100. - # smear : float, optional - # Gaussian smearing. The default is 0.05. - # scatter_color : str/color, optional - # Color of scatter plot of unfolded band structure. The color of supercell - # band structures is gray. The default is 'gray'. - # color_map: str/ matplotlib colormap - # Colormap for density plot. The default is viridis. - # show_legend : bool - # If show legend or not. The default is True. - - # Raises - # ------ - # ValueError - # If plot mode is unknown. - - # Returns - # ------- - # fig : matplotlib.pyplot.figure - # Figure instance. If ax is not None previously generated fig instance - # will be used. - # ax : Axis instance - # Figure axis instance. - # CountFig: int or None - # Figure count. - - # """ - - # print('- Plotting band structures...') - # if ax is None: - # self.fig, ax = plt.subplots() - - # if Ef == 'auto' or Ef is None: - # Ef = self.efermi - # # Shift the energy scale to 0 fermi energy level - # if Ef is not None: - # self.plot_result[:,2] -= Ef - # ax.axhline(y=0, color='k', ls='--', lw=1) - # yaxis_label = r"E$-$E$_\mathrm{F}$ (eV)" - # print(f"-- Efermi was set to {Ef} eV") - - # if Emin is None: Emin = self.plot_result[:,2].min() - pad_energy_scale - # if Emax is None: Emax = self.plot_result[:,2].max() + pad_energy_scale - - # result_ = self.plot_result[(self.plot_result[:,2] >= Emin - max(smear*10, 0.1)) * - # (self.plot_result[:,2] <= Emax + max(smear*10, 0.1))] - # result = result_[:, 1:] - # # Set weights to 0 which are below threshold_weight - # if threshold_weight is not None: - # result[result[:, 2] < threshold_weight, 2] = 0 - - # # Plot as fat band - # if mode == "fatband": - # if plotSC: - # ax.scatter(result[:, 0], result[:, 1], s=fatfactor, color='gray', label="supercell") - # ax.scatter(result[:, 0], result[:, 1], s=result[:, 2]*fatfactor, - # marker=marker, color=scatter_color, label="unfolded") - # if show_legend: ax.legend(loc=1) - # elif mode == "density": - # energy = np.linspace(Emin, Emax, nE) - # density = np.zeros((len(self.kpath_in_angs_),nE), dtype=float) - # for k, E, w in result[:, :3]: - # ik = np.argmin(abs(k - self.kpath_in_angs_)) - # # Gaussian smearing - # density[ik, :] += w*np.exp(-(energy-E)**2/(2*smear**2)) - # # density=np.log(density) - # # density[density<1e-3]=0 - # k1 = np.hstack(([self.kpath_in_angs_[0]], - # (self.kpath_in_angs_[1:]+self.kpath_in_angs_[:-1])/2, - # [self.kpath_in_angs_[-1]])) - # E1 = np.hstack(([energy[0]],(energy[1:]+energy[:-1])/2,[energy[-1]])) - # # print(k1,E1) - # # density=np.pad(density,((0,1),(0,1))) - # # print("before",k1.shape,E1.shape,density.shape) - # k1, E1 = np.meshgrid(k1,E1) - # # print("after",k1.shape,E1.shape,density.shape) - # plt.pcolormesh(k1, E1, density.T, cmap=color_map) - # plt.colorbar() - # else: - # raise ValueError("Unknownplot mode: '{}'".format(mode)) + plt_result = unfolded_bandstructure.copy() - # if special_kpoints is not None: - # x_tiks_labels, x_tiks_positions = \ - # _FormatSpecialKpts._extract_special_kpts_info(special_kpoints, - # self.kpath_in_angs_) - # plt.xticks(x_tiks_positions, x_tiks_labels) - # # Draw vertical lines - # for line_pos in x_tiks_positions: - # plt.axvline(x=line_pos, color='k', ls='--', lw=2) - - # ax.set_ylabel(yaxis_label) - # ax.set_ylim([Emin, Emax]) - # ax.set_xlim([self.kpath_in_angs_.min(), self.kpath_in_angs_.max()]) - - # if save_file_name is None: - # plt.show() - # else: - # CountFig = self.save_figure(save_file_name, CountFig=CountFig) - # plt.close() - # return self.fig, ax, CountFig + self.plot_result = _GeneralFunctionsDefs._reformat_columns_full_bandstr_data(plt_result) - def plot(self, ax=None, save_file_name=None, CountFig=None, Ef=None, Emin=None, - Emax=None, pad_energy_scale:float=0.5, threshold_weight:float=None, - mode:str="fatband", yaxis_label:str='E (eV)', special_kpoints:dict=None, - plotSC:bool=True, marker='o', fatfactor=20, nE:int=100, smear:float=0.05, - color='gray', color_map='viridis', plot_colormap_bandcenter:bool=True, - show_legend:bool=True): + def _plot(self, fig=None, ax=None, save_file_name=None, CountFig=None, Ef=None, Emin=None, + Emax=None, pad_energy_scale:float=0.5, threshold_weight:float=None, + mode:str="fatband", yaxis_label:str='E (eV)', special_kpoints:dict=None, + plotSC:bool=True, marker='o', fatfactor=20, nE:int=100, smear:float=0.05, + color='gray', color_map='viridis', plot_colormap_bandcenter:bool=True, + show_legend:bool=True, show_colorbar:bool=False, colorbar_label:str=None, + vmin=None, vmax=None, show_plot:bool=True, **kwargs_savefig): """ - Scatter/density plot of the band structure. + Scatter/density/band_centers plot of the band structure. Parameters ---------- + fig : matplotlib.pyplot figure instance, optional + Figure instance to plot on. The default is None. ax : matplotlib.pyplot axis, optional Figure axis to plot on. If None, new figure will be created. The default is None. @@ -255,6 +122,18 @@ def plot(self, ax=None, save_file_name=None, CountFig=None, Ef=None, Emin=None, If plotting the band ceneters by colormap. The default is True. show_legend : bool, optional If show legend or not. The default is True. + show_colorbar : bool, optional + Plot the colorbar in the figure or not. If fig=None, this is ignored. + The default is False. + colorbar_label : str, optional + Colorbar label. The default is None. If None, ignored. + vmin, vmax : float, optional + vmin and vmax define the data range that the colormap covers. + By default, the colormap covers the complete value range of the supplied data. + show_plot : bool, optional + To show the plot when not saved. The default is True. + **kwargs_savefig : dict + The matplotlib keywords for savefig function. Raises ------ @@ -264,72 +143,76 @@ def plot(self, ax=None, save_file_name=None, CountFig=None, Ef=None, Emin=None, Returns ------- fig : matplotlib.pyplot.figure - Figure instance. If ax is not None previously generated fig instance - will be used. + Figure instance. If ax is not None previously generated/passed fig instance + will be returned. Return None, if no fig instance is inputed along with ax. ax : Axis instance Figure axis instance. CountFig: int or None Figure count. """ - - print('- Plotting band structures...') if ax is None: self.fig, ax = plt.subplots() + else: + self.fig = fig + + if yaxis_label is None: yaxis_label='' if mode != "band_centers" and len(self.plot_result[0]) > 3: self.plot_result = self.plot_result[:, 1:] - if Ef == 'auto' or Ef is None: - Ef = self.efermi + if Ef == 'auto' or Ef is None: Ef = self.efermi + + Emin, Emax, result = \ + _GeneralFunctionsDefs._get_data_in_energy_window(self.plot_result, + Ef, Emin=Emin, Emax=Emax, + pad_energy_scale=pad_energy_scale, + threshold_weight=threshold_weight) # Shift the energy scale to 0 fermi energy level if Ef is not None: - self.plot_result[:, 1] -= Ef ax.axhline(y=0, color='k', ls='--', lw=1) - yaxis_label = r"E$-$E$_\mathrm{F}$ (eV)" - print(f"-- Efermi was set to {Ef} eV") - - if Emin is None: Emin = self.plot_result[:, 1].min() - pad_energy_scale - if Emax is None: Emax = self.plot_result[:, 1].max() + pad_energy_scale - - result = self.plot_result[(self.plot_result[:, 1] >= Emin - max(smear*10, 0.1)) * - (self.plot_result[:, 1] <= Emax + max(smear*10, 0.1))] - - # Set weights to 0 which are below threshold_weight - if threshold_weight is not None: - result[result[:, -1] < threshold_weight, -1] = 0 + if yaxis_label == 'E (eV)': yaxis_label = r"E$-$E$_\mathrm{F}$ (eV)" # Plot as fat band if mode == "fatband": - ax = self._plot_fatband(result, ax, marker=marker, fatfactor=fatfactor, - scatter_color=color, show_legend=show_legend, - plotSC=plotSC) + ax, return_plot = self._plot_fatband(result, ax, marker=marker, fatfactor=fatfactor, + scatter_color=color, show_legend=show_legend, + plotSC=plotSC) elif mode == "density": - ax = self._plot_density(result, ax, Emin, Emax, nE, self.kpath_in_angs_, - smear, cmap=color_map) + + ax, return_plot = self._plot_density(result, ax, Emin, Emax, nE, self.kpath_in_angs_, + smear, cmap=color_map, vmin=vmin, vmax=vmax) elif mode == 'band_centers': - ax = self._plot_band_centers(result, ax, color=color, color_map=color_map, - plot_colormap=plot_colormap_bandcenter) + ax, return_plot = self._plot_band_centers(result, ax, color=color, color_map=color_map, + plot_colormap=plot_colormap_bandcenter, + min_weight=vmin, max_weight=vmax) + elif mode == 'only_for_all_scf': # This mode is hidden. Used for all_scf plots later. + pass # This plots the skeleton of the plots without raising error. else: raise ValueError("Unknownplot mode: '{}'".format(mode)) + if show_colorbar and (self.fig is not None): + cbar = self.fig.colorbar(return_plot, ax=ax) + if colorbar_label is not None: + cbar.set_label(colorbar_label) + if special_kpoints is not None: x_tiks_labels, x_tiks_positions = \ _FormatSpecialKpts._extract_special_kpts_info(special_kpoints, self.kpath_in_angs_) - plt.xticks(x_tiks_positions, x_tiks_labels) + ax.set_xticks(x_tiks_positions, x_tiks_labels) # Draw vertical lines for line_pos in x_tiks_positions: - plt.axvline(x=line_pos, color='k', ls='--', lw=2) + ax.axvline(x=line_pos, color='k', ls='--', lw=2) ax.set_ylabel(yaxis_label) ax.set_ylim([Emin, Emax]) ax.set_xlim([self.kpath_in_angs_.min(), self.kpath_in_angs_.max()]) if save_file_name is None: - plt.show() + if show_plot: plt.show() else: - CountFig = self.save_figure(save_file_name, CountFig=CountFig) + CountFig = self._save_figure(save_file_name, fig=self.fig, CountFig=CountFig, **kwargs_savefig) plt.close() return self.fig, ax, CountFig @@ -370,20 +253,21 @@ def _plot_fatband(cls, data_4_plot, ax, marker='o', fatfactor=20, scatter_color= ------- ax : matplotlib.pyplot axis Figure axis to plot on. + sc : figure instance """ if plotSC: - ax.scatter(data_4_plot[:, 0], data_4_plot[:, 1], s=fatfactor, - color='gray', label="supercell") - ax.scatter(data_4_plot[:, 0], data_4_plot[:, 1], s=data_4_plot[:, 2]*fatfactor, - marker=marker, color=scatter_color, label=legend_label) + sc = ax.scatter(data_4_plot[:, 0], data_4_plot[:, 1], s=fatfactor, + color='gray', label="supercell") + sc = ax.scatter(data_4_plot[:, 0], data_4_plot[:, 1], s=data_4_plot[:, 2]*fatfactor, + marker=marker, color=scatter_color, label=legend_label) if show_legend: ax.legend(loc=legend_pos) - return ax + return ax, sc @classmethod def _plot_density(cls, data_4_plot, ax, Emin, Emax, nE, kpath_in_angs_, - smear, cmap='viridis'): + smear, cmap='viridis', vmin=None, vmax=None): """ Plot density plot of band structure. @@ -405,11 +289,16 @@ def _plot_density(cls, data_4_plot, ax, Emin, Emax, nE, kpath_in_angs_, Gaussian smearing. cmap : str/ matplotlib colormap Colormap for density plot.The default is 'viridis'. + vmin, vmax : float, optional + vmin and vmax define the data range that the colormap covers. + By default, the colormap covers the complete value range of the supplied data. Returns ------- ax : matplotlib.pyplot axis Figure axis to plot on. + pcm : matplotlib pcolormesh plot instance + Plot instance. """ energy = np.linspace(Emin, Emax, nE) @@ -428,13 +317,13 @@ def _plot_density(cls, data_4_plot, ax, Emin, Emax, nE, kpath_in_angs_, # print("before",k1.shape,E1.shape,density.shape) k1, E1 = np.meshgrid(k1,E1) # print("after",k1.shape,E1.shape,density.shape) - plt.pcolormesh(k1, E1, density.T, cmap=cmap) - plt.colorbar() - return ax + pcm = ax.pcolormesh(k1, E1, density.T, cmap=cmap, vmin=vmin, vmax=vmax) + return ax, pcm @classmethod def _plot_band_centers(cls, data_4_plot, ax, color='k', plot_colormap:bool=True, - err_bar_fmt='x', color_map='viridis'): + err_bar_fmt='x', color_map='viridis', min_weight:float=None, + max_weight:float=None): """ Plot the band centers and band width. @@ -442,6 +331,7 @@ def _plot_band_centers(cls, data_4_plot, ax, color='k', plot_colormap:bool=True, ---------- data_4_plot : numpy 2d array Data to plot. + Format: [kpoint coordinate, Band center, Band width, Sum of dN] ax : matplotlib.pyplot axis, optional Figure axis to plot on. color : matplotlib color/str, optional @@ -452,16 +342,27 @@ def _plot_band_centers(cls, data_4_plot, ax, color='k', plot_colormap:bool=True, matplotlib errorbar fmt. The default is 'x'. color_map : str/ matplotlib colormap Colormap for density plot.The default is 'viridis'. + min_weight : float, optional + Minimum in the color scale for the band centers. + The default is None. If None, determined from the data array supplied. + max_weight : float, optional + Maximum in the color scale for the band centers. + The default is None. If None, determined from the data array supplied. Returns ------- ax : matplotlib.pyplot axis Figure axis to plot on. + cmap_mappable : + Figure instance or colormap instance for colorbar. """ if plot_colormap: # This is super slow - max_weight, min_weight = data_4_plot[:, -1].max(), data_4_plot[:, -1].min() + if min_weight is None: + min_weight = data_4_plot[:, -1].min() + if max_weight is None: + max_weight = data_4_plot[:, -1].max() cmap = plt.get_cmap(color_map) norm = plt.Normalize(min_weight, max_weight) # Normalize the float values @@ -470,9 +371,169 @@ def _plot_band_centers(cls, data_4_plot, ax, color='k', plot_colormap:bool=True, for ii, JJ in enumerate(data_4_plot): ax.errorbar(JJ[0], JJ[1], yerr=JJ[2], fmt=err_bar_fmt, ecolor=error_colors[ii], color=error_colors[ii]) - cbar = plt.colorbar(plt.cm.ScalarMappable(norm=norm, cmap=cmap), ax=ax) - cbar.set_label('Weight') + cmap_mappable = plt.cm.ScalarMappable(norm=norm, cmap=cmap) + else: + cmap_mappable = ax.errorbar(data_4_plot[:,0], data_4_plot[:,1], yerr=data_4_plot[:, 2], + fmt=err_bar_fmt, color=color, linestyle='') + return ax, cmap_mappable + + def _plot_scf(self, al_scf_data, plot_max_scf_steps:int=None, + save_file_name=None, Ef=None, Emin=None, + Emax=None, pad_energy_scale:float=0.5, threshold_weight:float=None, + yaxis_label:str='E (eV)', special_kpoints:dict=None, + plot_sc_unfold:bool=True, marker='o', fatfactor=20, smear:float=0.05, + color='gray', color_map='viridis', plot_colormap_bandcenter:bool=True, + show_legend:bool=True, show_colorbar:bool=True, colorbar_label:str=None, + vmin=None, vmax=None, show_plot:bool=True, **kwargs_savefig): + """ + Band centers all scf steps plot. + + Parameters + ---------- + al_scf_data : dictionary + All SCF data. + Each array contains the final details of band centers in a particular + kpoint. The dictionary then contains the details for each SCF cycles with + keys are the SCF cycle number. The highest level dictionary then contains + details for each kpoints with keys are the kpoint indices. Returns None + if collect_data_scf is false. + Format: {kpoint_index: {SCF_cycle_index: [Band center, Band width, Sum of dN]}} + plot_max_scf_steps : int, optional + How many maximum scf cycle to plot? + The default is maximum SCF steps found in the dictionary of all k-points. + If scf cycle not found for a particular kpoint previous SCF cycle will be plotted. + save_file_name : str, optional + Name of the figure file. If None, figure will be not saved. + The default is None. + Ef : float, optional + Fermi energy. If None, set to 0.0. The default is None. + Emin : float, optional + Minimum in energy. The default is None. + Emax : float, optional + Maximum in energy. The default is None. + pad_energy_scale: float, optional + Add padding of pad_energy_scale to minimum and maximum energy if Emin + and Emax are None. The default is 0.5. + threshold_weight : float, optional + The band centers with band weights lower than the threshhold weights + are discarded. The default is None. If None, this is ignored. + yaxis_label : str, optional + Y-axis label text. The default is 'E (eV)'. + special_kpoints : dictionary, optional + Dictionary of special kpoints position and labels. If None, ignore + special kpoints. The default is None. + plot_sc_unfold : bool, optional + Plot supercell unfolded bandstructure. The default is True. + marker : matplotlib.pyplot markerMarkerStyle, optional + The marker style. Marker can be either an instance of the class or + the text shorthand for a particular marker. + The default is 'o'. + fatfactor : int, optional + Scatter plot marker size. The default is 20. + smear : float, optional + Gaussian smearing. The default is 0.05. + color : str/color, optional + Color for band centers plot when color_map is not used. + The default is 'gray'. The color of supercell + band structures is gray always. + color_map: str/ matplotlib colormap + Colormap for band centers plot. The default is viridis. + plot_colormap_bandcenter : bool, optional + If plotting the band ceneters by colormap. The default is True. + show_legend : bool, optional + If show legend or not. The default is True. + show_colorbar : bool, optional + Plot the colorbar in the figure or not. If fig=None, this is ignored. + The default is True. + colorbar_label : str, optional + Colorbar label. The default is None. If None, ignored. + vmin, vmax : float, optional + vmin and vmax define the data range that the colormap covers. + By default, the colormap covers the complete value range of the supplied data. + show_plot : bool, optional + To show the plot when not saved. The default is True. + **kwargs_savefig : dict + The matplotlib keywords for savefig function. + + Raises + ------ + ValueError + If plot mode is unknown. + + """ + # If scf cycle not found for a particular kpoint previous SCF cycle will be plotted. + if plot_max_scf_steps is None: + plot_max_scf_steps = max([max(al_scf_data[JJ].keys()) for JJ in al_scf_data.keys()]) + elif plot_max_scf_steps <1 : + print('Warning: scf steps indices starts with 1.') + plot_max_scf_steps = 1 else: - ax.errorbar(data_4_plot[:,0], data_4_plot[:,1], yerr=data_4_plot[:, 2], - fmt=err_bar_fmt, color=color) - return ax \ No newline at end of file + max_scf_steps_f = max([max(al_scf_data[JJ].keys()) for JJ in al_scf_data.keys()]) + if plot_max_scf_steps > max_scf_steps_f: + _rtx__ = f'Requested {plot_max_scf_steps} maximum SCF steps plot. Found {max_scf_steps_f} maximum SCF steps in dictionary.' + print(f'Warning: {_rtx__}. Will plot {max_scf_steps_f} SCF steps.') + plot_max_scf_steps = max_scf_steps_f + + # Find the maximum and minimum in color scale + if plot_colormap_bandcenter: + minN_weight, maxX_weight = 0, 0 + for which_kp in al_scf_data.values(): + for ZZ_tmp in which_kp.values(): + ZZ= ZZ_tmp[:, -1] + max_weight, min_weight = ZZ.max(), ZZ.min() + if max_weight > maxX_weight: + maxX_weight = max_weight + if min_weight < minN_weight: + minN_weight = min_weight + if vmin is None: + vmin = minN_weight + if vmax is None: + vmax = maxX_weight + + plot_mode = 'fatband' if plot_sc_unfold else 'only_for_all_scf' + if Ef == 'auto' or Ef is None: Ef = self.efermi + count_fig_pec = len(str(plot_max_scf_steps+1)) + + for scf_step in range(1, plot_max_scf_steps+1): # loop over scf cycle + print(f'-- Plotting SCF step: {scf_step}') + fig, ax = plt.subplots() + fig, ax, _ \ + = self._plot(fig=fig, ax=ax, save_file_name=None, Ef=Ef, + Emin=Emin, Emax=Emax, pad_energy_scale=pad_energy_scale, + threshold_weight=threshold_weight, mode=plot_mode, + yaxis_label=yaxis_label, special_kpoints=special_kpoints, + plotSC=False, marker=marker, fatfactor=fatfactor, + smear=smear, color='gray', show_legend=show_legend, + show_colorbar=False, show_plot=False) + save_file_name_ = f'{scf_step:0{count_fig_pec}}_{save_file_name}' + for which_kp in al_scf_data: # loop over k-points + while True: + if al_scf_data[which_kp].get(scf_step) is None: + scf_step -= 1 + #print(f'-- Going back to previous SCF step for this kpoint: {scf_step}') + else: + break + + XX = [self.kpath_in_angs_[which_kp]]*len(al_scf_data[which_kp][scf_step]) + YY = al_scf_data[which_kp][scf_step][:, 0] - Ef + result_tmp = np.column_stack( (XX, YY, al_scf_data[which_kp][scf_step][:, 1:]) ) + + ax, return_plot = self._plot_band_centers(result_tmp, ax, color=color, + color_map=color_map, + plot_colormap=plot_colormap_bandcenter, + min_weight=vmin, + max_weight=vmax) + + if plot_colormap_bandcenter and show_colorbar: + cbar = fig.colorbar(return_plot, ax=ax) + if colorbar_label is not None: + cbar.set_label(colorbar_label) + + # ax.set_ylim([Emin, Emax]) + # ax.set_xlim([self.kpath_in_angs_.min(), self.kpath_in_angs_.max()]) + + if save_file_name is None: + if show_plot: plt.show() + else: + _ = self._save_figure(save_file_name_, fig=fig, CountFig=None, **kwargs_savefig) + plt.close() \ No newline at end of file diff --git a/banduppy/Utilities/EBS_properties.py b/banduppy/Utilities/EBS_properties.py index 6cd95db..7dfa8e4 100644 --- a/banduppy/Utilities/EBS_properties.py +++ b/banduppy/Utilities/EBS_properties.py @@ -1,7 +1,177 @@ import numpy as np -from ..BasicFunctions.general_functions import SaveData2File, _draw_line_length +from scipy.optimize import curve_fit +from ..BasicFunctions.general_functions import _SaveData2File, _draw_line_length ### =========================================================================== +class _GeneralFunctionsDefs: + @staticmethod + def _reformat_columns_full_bandstr_data(full_data): + """ + Gather first 4 columns of data. Discard S_x,y,z data in spinor. + + Parameters + ---------- + kpath_in_angs : array, optional + k on path (in A^-1) coordinate. The default is None. + full_data : ndarray + Unfolded effective band structure/band center data. + Format: [k index, k on path (A^-1), energy, weight, "Sx, Sy, Sz" if spinor.] or + Format: [kpoint coordinate, Band center, Band width, Sum of dN] for band centers + + Returns + ------- + ndarray + Unfolded effective band structure/band center data within the range. + Format: [k index, k on path (A^-1), energy, weight] or + Format: [kpoint coordinate, Band center, Band width, Sum of dN] for band centers + + """ + return full_data[:, :4] # column upto weight/Sum of dN + + @classmethod + def _get_data_in_energy_window(cls, full_data, Ef, Emin=None, Emax=None, + pad_energy_scale:float=0.5, + threshold_weight:float=None): + """ + Collect data within the condition and range specified. + + Parameters + ---------- + full_data : ndarray, optional + Unfolded effective band structure/band center data. + Ef : float + Fermi energy. Set to 0.0 if None or 'auto'. + Emin : float, optional + Minimum in energy. The default is None. + Emax : float, optional + Maximum in energy. The default is None. + pad_energy_scale: float, optional + Add padding of pad_energy_scale to minimum and maximum energy if Emin + and Emax are None. The default is 0.5. + threshold_weight : float, optional + The band centers with band weights lower than the threshhold weights + are put to zero. The default is None. If None, this is ignored. + + Returns + ------- + Emin : float + Minimum in energy. + Emax : float + Maximum in energy. + result: ndarray + Unfolded effective band structure/band center data within the range. + + """ + if Ef == 'auto' or Ef is None: Ef = 0.0 + # Shift the energy scale to 0 fermi energy level + if Ef is not None: + YYY = full_data[:, 1] - Ef + print(f"-- Efermi was set to {Ef} eV") + + if Emin is None: Emin = YYY.min() - pad_energy_scale + if Emax is None: Emax = YYY.max() + pad_energy_scale + + pos_right_energy_window = (YYY >= Emin) * (YYY <= Emax) + result = full_data[pos_right_energy_window] + result[:, 1] = YYY[pos_right_energy_window] + + # Set weights to 0 which are below threshold_weight + if threshold_weight is not None: + result[result[:, -1] < threshold_weight, -1] = 0 + + return Emin, Emax, result + + @classmethod + def _get_bandstr_data_only_in_energy_kpts_window(cls, complete_data, Ef:float=None, + Emin:float=None, Emax:float=None, + pad_energy_scale:float=0.5, + min_dN_screen:float=0.0): + """ + Collect data within the condition and range specified. + Note: Returns only 1st 4 columns. Removes the spinor data part for + spinor activated effective band structure data. + + Parameters + ---------- + complete_data : ndarray, optional + Unfolded effective band structure/band center data. + Ef : float + Fermi energy. Set to 0.0 if None or 'auto'. + Emin : float, optional + Minimum in energy. The default is None. + Emax : float, optional + Maximum in energy. The default is None. + pad_energy_scale: float, optional + Add padding of pad_energy_scale to minimum and maximum energy if Emin + and Emax are None. The default is 0.5. + min_dN_screen : float, optional + The band centers with band weights lower than the threshhold weights + are discarded. The default is 0. + + Returns + ------- + ndarray + Unfolded effective band structure/band center data within the range. + + """ + + # Returns only 1st 4 columns. Removes the spinor data part. + complete_data_ = cls._reformat_columns_full_bandstr_data(complete_data) + # Collect data within energy window + Emin, Emax, complete_data_ = \ + cls._get_data_in_energy_window(complete_data_, Ef, Emin=Emin, Emax=Emax, + pad_energy_scale=pad_energy_scale) + # Pre-screen band structure data to minimize unnecessary small weights bands + return complete_data_[complete_data_[:, -1] >= min_dN_screen] + + @classmethod + def _save_band_centers(cls, data2save, print_log='low', + save_data_f_prop = {'save2file': False, 'fdir': '.', + 'fname': 'unfolded_bandcenters', + 'fname_suffix': ''}): + """ + Save unfolded band centers data. + Format: [kpoint coordinate, Band center, Band width, Sum of dN] + + Parameters + ---------- + data2save : 2d array + Data to save. + print_log : [None,'low','medium','high'], optional + Level of printing information. + The default is 'low'. If None, nothing is printed. + save_data : dictionary, optional + save2file :: Save data to file or not? + fir :: str or path + Directory path where to save the file. + fname :: str + Name of the file. + fname_suffix :: str + Suffix to add to the file name. + The default is {'save2file': False, 'fdir': '.', 'fname': 'unfolded_bandcenters', 'fname_suffix': ''}. + + Returns + ------- + None. + + """ + save_data = _SaveData2File._default_save_settings(save_data_f_prop) + if save_data['save2file']: + if print_log is not None: + print(f"{'='*_draw_line_length}\n- Saving unfolded band centers to file...") + header_msg = " Unfolded band centers data\n" + header_msg += " k on path (A^-1), Band center energy, Band width, Sum of dN\n" + # Save the sc-kpoints in file + save_f_name = _SaveData2File._save_2_file(data=data2save, + save_dir=save_data["fdir"], + file_name=save_data["fname"], + file_name_suffix=f'{save_data["fname_suffix"]}.dat', + header_txt=header_msg, comments_symbol='#', + print_log=bool(print_log)) + if print_log is not None: + print(f'-- Filepath: {save_f_name}\n- Done') + return + class _FormatSpecialKpts: """ Find position and format labels of the special k-points. @@ -31,13 +201,13 @@ def _extract_special_kpts_info(special_kpts, kpath_angs): kl = np.array([kpath_angs[ik] for ik in special_kpts.keys()]) ll = np.array([k for k in special_kpts.values()]) borders = [0] + list(np.where((kl[1:]-kl[:-1])>1e-4)[0]+1) + [len(kl)] - k_labels=[(kl[b1:b2].mean(),"/".join(set(ll[b1:b2]))) for b1,b2 in zip(borders,borders[1:])] + k_labels=[(kl[b1:b2].mean(),"/".join(list(dict.fromkeys(ll[b1:b2])))) for b1,b2 in zip(borders,borders[1:])] special_kpts_labels = [label[1] for label in k_labels] special_kpts_poss = [label[0] for label in k_labels] return special_kpts_labels, special_kpts_poss -class BandCentersBroadening: +class _BandCentersBroadening(_GeneralFunctionsDefs): """ Find band centers and broadening of the unfolded band structure. The implementation is based on the SCF algorithm of automatic band center @@ -51,7 +221,7 @@ def __init__(self, unfolded_bandstructure, min_dN_pre_screening:float=1e-4, threshold_dN_2b_trial_band_center:float=0.05, min_sum_dNs_for_a_band:float=0.05, precision_pos_band_centers:float=1e-5, - err_tolerance_compare_kpts:float=1e-8, + err_tolerance_compare_kpts_val:float=1e-8, print_log='low'): """ Intializing BandCentersBroadening class. Play with the different cut-offs @@ -61,40 +231,44 @@ def __init__(self, unfolded_bandstructure, min_dN_pre_screening:float=1e-4, ---------- unfolded_bandstructure : numpy array Unfolded effective band structure. - Format: k index, k on path (A^-1), energy, weight, "Sx, Sy, Sz" if is_spinor. + Format: [k index, k on path (A^-1), energy, weight, "Sx, Sy, Sz" if is_spinor] min_dN_pre_screening : float, optional - Discard the bands which has weights below min_dN_pre_screening. This - pre-screening step helps to minimize the data that will processed - now on. The default is 1e-4. + Discard the bands which has weights below min_dN_pre_screening to start with. + This pre-screening step helps to minimize the data that will processed + now on. The default is 1e-4. [* critical parameter] threshold_dN_2b_trial_band_center : float, optional Initial guess of the band centers based on the threshold wights. - The default is 0.05. + The default is 0.05. [* critical parameter] min_sum_dNs_for_a_band : float, optional - Cut off criteria for minimum weights that band center should have. + Cut off criteria for minimum weights that a band center should have. The band centers with lower weights than min_sum_dNs_for_a_band will be discarded during SCF refinements. If min_sum_dNs_for_a_band is smaller than threshold_dN_2b_trial_band_center, min_sum_dNs_for_a_band will be reset to threshold_dN_2b_trial_band_center value. - The default is 0.05. - precision_pos_band_centers : float, optional (in eV) - Precision when compared band centers from previous and latest SCF + The default is 0.05. [* critical parameter] + precision_pos_band_centers : float, optional + Precision when compared band centers from previous and current SCF iteration. SCF is considered converged if this precision is reached. - The default is 1e-5. - err_tolerance_compare_kpts : float, optional - The tolerance to group the bands set per unique kpoints. - The default is 1e-8. + The default is 1e-5. [not critical parameter] + err_tolerance_compare_kpts_val : float, optional + The tolerance to group the bands set per unique kpoints. This + determines if two flotting point numbers are the same or not. This is not + a critical parameter for band center determination algorithm. + The default is 1e-8. [not critical parameter] print_log : [None,'low','medium','high'], optional Print information of kpoints folding. Level of printing information. The default is 'low'. If None, nothing is printed. """ + # Returns only 1st 4 columns. Removes the spinor data part. # Pre-screen band structure data to minimize unnecessary small weights bands - self.unfolded_bandstructure_ = self._pre_screen_bandstr_data(unfolded_bandstructure, - min_dN_pre_screening) + self.unfolded_bandstructure_ = \ + self._pre_screen_bandstr_data(_GeneralFunctionsDefs._reformat_columns_full_bandstr_data(unfolded_bandstructure), + min_dN_pre_screening) # Setting parameters self.prec_pos_band_centers = precision_pos_band_centers - self.err_tolerance = err_tolerance_compare_kpts + self.err_tolerance = err_tolerance_compare_kpts_val self.print_output = print_log # Reset some parameters based on condition check @@ -102,11 +276,11 @@ def __init__(self, unfolded_bandstructure, min_dN_pre_screening:float=1e-4, self._check_min_sum_dNs_condition(min_sum_dNs_for_a_band, threshold_dN_2b_trial_band_center) - def scfs_band_centers_broadening(self, collect_data_scf:bool=False, - save_data = {'save2file': False, - 'fdir': '.', - 'fname': 'unfolded_bandcenters', - 'fname_suffix': ''}): + def _scfs_band_centers_broadening(self, collect_data_scf:bool=False, + save_data = {'save2file': False, + 'fdir': '.', + 'fname': 'unfolded_bandcenters', + 'fname_suffix': ''}): """ Find the band centers and broadening for a band structure. The implementation is based on the SCF algorithm of automatic band center @@ -121,7 +295,7 @@ def scfs_band_centers_broadening(self, collect_data_scf:bool=False, Whether to save the dtails of band centers in each SCF cycles. The default is False. save_data : dictionary, optional - save2file :: Save unfolded kpoints or not? + save2file :: Save unfolded band centers data to file or not? fir :: str or path Directory path where to save the file. fname :: str @@ -135,13 +309,14 @@ def scfs_band_centers_broadening(self, collect_data_scf:bool=False, return_grouped_unfolded_bandstructure_datails : 2d array Each array contains the final details of band centers at each kpoint. - Format: kpoint coordinate, Band center, Band width, Sum of dN. + Format: [kpoint coordinate, Band center, Band width, Sum of dN] gather_scf_data_ : dictionary of dictionary of array or None Each array contains the final details of band centers in a particular kpoint. The dictionary then contains the details for each SCF cycles with keys are the SCF cycle number. The highest level dictionary then contains details for each kpoints with keys are the kpoint indices. Returns None if collect_data_scf is false. + Format: {kpoint_index: {SCF_cycle_index: [Band center, Band width, Sum of dN]}} """ print(f"{'-'*72}\n- Finding band center and broadening for band structure...") @@ -160,13 +335,11 @@ def scfs_band_centers_broadening(self, collect_data_scf:bool=False, print('- Done') #return return_grouped_unfolded_bandstructure_datails, gather_scf_data_ final_results = np.concatenate(return_grouped_unfolded_bandstructure_datails, axis=0) + # Save the band ceneters data + _GeneralFunctionsDefs._save_band_centers(data2save=final_results, + print_log=self.print_output, + save_data_f_prop=save_data) - save_data = SaveData2File.default_save_settings(save_data) - if save_data['save2file']: - self._save_band_centers(data2save=final_results, - save_dir=save_data["fdir"], - file_name=save_data["fname"], - file_name_suffix=save_data["fname_suffix"]) return final_results, gather_scf_data_ def _scfs_band_centers_broadening_kpt(self, unfolded_bandstructure_current_kpt, @@ -178,7 +351,7 @@ def _scfs_band_centers_broadening_kpt(self, unfolded_bandstructure_current_kpt, ---------- unfolded_bandstructure_current_kpt : 2d numpy array Unfolded effective band structure. - Format: k index, k on path (A^-1), energy, weight, "Sx, Sy, Sz" if is_spinor. + Format: [k index, k on path (A^-1), energy, weight] collect_data_scf : bool, optional Whether to save the dtails of band centers in each SCF cycles. The default is False. @@ -189,16 +362,18 @@ def _scfs_band_centers_broadening_kpt(self, unfolded_bandstructure_current_kpt, Index of the kpoint. guess_band_details : 2d numpy array Band center details at the particular kpoint. - Format: kpoint coordinate, Band center, Band width, Sum of dN. + Format: [kpoint coordinate, Band center, Band width, Sum of dN] all_data_ : dict or None - Dictionary containing the band center details of all SCF cycles . + Dictionary containing the band center details of all SCF cycles. Return None if collect_data_scf is False. + Format: {SCF_cycle_index: [Band center, Band width, Sum of dN]} """ # Collect kpoint information kpoints_cord = unfolded_bandstructure_current_kpt[0, :2] k_index_ = int(kpoints_cord[0]) - print (f"{'-'*72}\n- Finding band center for kpoint: {k_index_}") + if self.print_output in ['low','medium','high']: + print (f"{'-'*72}\n- Finding band center for kpoint: {k_index_}") all_data_ = {} if collect_data_scf else None # Collect dNs and energies in array @@ -222,7 +397,7 @@ def _scfs_band_centers_broadening_kpt(self, unfolded_bandstructure_current_kpt, min_energy, max_energy, energies_for_current_kpt, dNs_for_current_kpt) - refined_band_centers = self._refine_band_centers(guess_band_details, min_energy, + refined_band_centers = self._refine_band_centers(guess_band_details, self.min_sum_dNs_for_each_band) converged = self._check_convergence(guess_band_centers, refined_band_centers, self.prec_pos_band_centers) @@ -244,7 +419,7 @@ def _scfs_band_centers_broadening_kpt(self, unfolded_bandstructure_current_kpt, else: guess_band_centers = refined_band_centers - if collect_data_scf: all_data_[count] = guess_band_details + if collect_data_scf: all_data_[count] = guess_band_details[:, -3:] # guess_band_details = (#kpoint coordinate #Band center #Band width #Sum of dN) return k_index_, guess_band_details, all_data_ @@ -292,7 +467,7 @@ def _pre_screen_bandstr_data(cls, unfolded_bandstructure, min_dN): ---------- unfolded_bandstructure : 2d numpy array Unfolded effective band structure before removing small weights centers. - Format: k index, k on path (A^-1), energy, weight, "Sx, Sy, Sz" if is_spinor. + Format: [k index, k on path (A^-1), energy, weight] min_dN : float Discard the bands which has weights below min_dN_pre_screening. This pre-screening step helps to minimize the data that will processed @@ -302,7 +477,7 @@ def _pre_screen_bandstr_data(cls, unfolded_bandstructure, min_dN): ------- 2d numpy array Unfolded effective band structure after removing small weights centers. - Format: k index, k on path (A^-1), energy, weight, "Sx, Sy, Sz" if is_spinor. + Format: [k index, k on path (A^-1), energy, weight] """ # Pre-screening: get rid of very small weights @@ -320,13 +495,13 @@ def _eliminate_duplicate_kpts_list(cls, unfolded_bandstructure): ---------- unfolded_bandstructure : 2d numpy array Unfolded effective band structure. - Format: k index, k on path (A^-1), energy, weight, "Sx, Sy, Sz" if is_spinor. + Format: [k index, k on path (A^-1), energy, weight] Returns ------- unfolded_bandstructure : 2d numpy array Unfolded effective band structure after removing duplicates. - Format: k index, k on path (A^-1), energy, weight, "Sx, Sy, Sz" if is_spinor. + Format: [k index, k on path (A^-1), energy, weight] """ # Eliminating duplicated points, e.g.: L-G,G-X -> get rid of two Gs @@ -343,7 +518,8 @@ def _eliminate_duplicate_kpts_list(cls, unfolded_bandstructure): unfolded_bandstructure[:, -1] = dNs return unfolded_bandstructure - + + @classmethod def _group_unique_kpts_data(cls, unfolded_bandstructure, err_tolerance:float=1e-8): """ Group bands at each unique k-points. @@ -352,7 +528,7 @@ def _group_unique_kpts_data(cls, unfolded_bandstructure, err_tolerance:float=1e- ---------- unfolded_bandstructure : 2d numpy array Unfolded effective band structure. - Format: k index, k on path (A^-1), energy, weight, "Sx, Sy, Sz" if is_spinor. + Format: [k index, k on path (A^-1), energy, weight] err_tolerance : float, optional The tolerance to group the bands set per unique kpoints. The default is 1e-8. @@ -361,7 +537,7 @@ def _group_unique_kpts_data(cls, unfolded_bandstructure, err_tolerance:float=1e- ------- list List of unfolded effective band structure group by kpoints. - Format: k index, k on path (A^-1), energy, weight, "Sx, Sy, Sz" if is_spinor.. + Format: [k index, k on path (A^-1), energy, weight] """ # Get unique kpoints coordinate @@ -441,7 +617,7 @@ def _calculate_guess_band_details(cls, guess_band_centers, min_energy, max_energ ------- 2d numpy array Band center details at the particular kpoint. - Format: kpoint coordinate, Band center, Band width, Sum of dN. + Format: [Band center, Band width, Sum of dN] """ guess_energy_width = cls._calculate_possible_energy_width(guess_band_centers, @@ -461,21 +637,21 @@ def _calculate_guess_band_details(cls, guess_band_centers, min_energy, max_energ return np.array(guess_band_details) @classmethod - def _refine_band_centers(cls, guess_band_details, min_energy, min_sum_dNs_for_a_band): + def _refine_band_centers(cls, guess_band_details, min_sum_dNs_for_a_band): """ Discard band centers which are too close in energy. Reducing the number of too close energy values. Discard band centers with - abs(e_n,current - e_(n-1),current) < 2*max[band_n_width, band_n-1_width] + band_weight_current_band < min_sum_dNs_for_a_band or + abs(band_center_n,current - band_center_(n-l),current) < 2*max[band_n_width, band_n-l_width] + for l>=0 scuh that band_center_(n-l),current is an accepted band ceneter. Parameters ---------- guess_band_details : 2d numpy array Band center details at the particular kpoint. - Format: kpoint coordinate, Band center, Band width, Sum of dN. - min_energy : TYPE - DESCRIPTION. + Format: [Band center, Band width, Sum of dN] min_sum_dNs_for_a_band : float Cut off criteria for minimum weights that a band center should have. The band centers with lower weights than min_sum_dNs_for_a_band will be @@ -485,19 +661,21 @@ def _refine_band_centers(cls, guess_band_details, min_energy, min_sum_dNs_for_a_ ------- 2d numpy array Band center details at the particular kpoint after refining. - Format: kpoint coordinate, Band center, Band width, Sum of dN. + Format: [Band center, Band width, Sum of dN] """ refined_band_centers = [] + iband_m_1 = -1 for iband in range(len(guess_band_details)): - bc, bwidth, b_weight = guess_band_details[iband] - previous_bc, previous_bwidth, previous_b_weight = guess_band_details[iband-1] - #print(iband, bc, bwidth, b_weight, previous_bc, previous_bwidth, previous_b_weight) + # band center, band width, band Bloch weight + bc_iband, bwidth_iband, bweight_iband = guess_band_details[iband] # current band + bc_iband_m_1, bwidth_iband_m_1, bweight_iband_m_1 = guess_band_details[iband_m_1] # iband_m_1 == current band minus 1 + #print(iband, bc, bwidth, b_weight, bc_cbm1, bwidth_cbm1, b_weight_cbm1) valid_bc = False - if(b_weight < min_sum_dNs_for_a_band or \ - abs(bc - previous_bc) < 2.0 * max([bwidth, previous_bwidth])): + if(bweight_iband < min_sum_dNs_for_a_band or \ + abs(bc_iband - bc_iband_m_1) < 2.0 * max([bwidth_iband, bwidth_iband_m_1])): try: - if(abs(b_weight / previous_b_weight) > 1.0): + if(abs(bweight_iband / bweight_iband_m_1) > 1.0): del refined_band_centers[-1] valid_bc = True except: @@ -506,7 +684,8 @@ def _refine_band_centers(cls, guess_band_details, min_energy, min_sum_dNs_for_a_ valid_bc = True if(valid_bc): - refined_band_centers.append(bc) + iband_m_1 = iband + refined_band_centers.append(bc_iband) return np.array(refined_band_centers) @staticmethod @@ -531,40 +710,149 @@ def _check_convergence(old_band_centers, new_band_centers, prec_pos_band_centers If two arrays are same or not. """ - return all(abs(old_band_centers[:len(new_band_centers)] - new_band_centers) - <= prec_pos_band_centers) + for ii, new_band_center_val in enumerate(new_band_centers): + if abs(old_band_centers[ii] - new_band_center_val) > prec_pos_band_centers: + return False + return True - def _save_band_centers(self, data2save, save_dir, file_name, file_name_suffix): +class _EffectiveMass: + """ + Class for calculating effective mass. + + E (1 + gamma*E) = hbar^2 k^2/(2m*) + => E (1 + gamma*E) = alpha k^2 + => Solving for E yields a quadratic equation when gamma != 0. + + General equation: + E (1 + gamma*E) = alpha*(k-kshift)^2 + cbm + + Fit bandstructure along k-path to alpha and gamma. + alpha = hbar^2/(2m*) + gamma = non-parabolicity ==> gamma = 0 for parabolic bands + Additional parameters: + kshift = horizontal kpath fit param + cbm = vertical energy fit param, conduction band minima + + For E in eV and k in A^-1; alpha has unit of eV.A^2 + + """ + def __init__(self, print_log='low'): """ - Save unfolded band centers data. - Format: kpoint coordinate, Band center, Band width, Sum of dN. - + Intializing EffectiveMass class. + + m_e = 9.1093837015e-31 kg + habr = 1.054571817e-34 J.s + 1 ang = 1e-10 m + 1 eV = 1.602176634e-19 J + + hbar^2/(2*m_e*alpha_in_eV_angsquare) + = (1.054571817e-34**2)/(2*9.1093837015e-31*1.602176634e-19*1e-10**2) + = 3.8099821114859607 + Parameters ---------- - data2save : 2d array - Data to save. - save_dir : str or path - Directory path where to save the file. - file_name : str - Name of the file. - file_name_suffix : str - Suffix to add to the file name. + + print_log : [None,'low','medium','high'], optional + Print information of kpoints folding. Level of printing information. + The default is 'low'. If None, nothing is printed. + """ + self.print_output = print_log + self.effective_mass_unit_conversion = 3.8099821114859607 + + @classmethod + def _fit_parabola(cls, k, alpha, kshift, cbm): + return alpha * np.power(k - kshift, 2) + cbm + + @classmethod + def _fit_hyperbola_positive(cls, k, alpha, kshift, cbm, gamma): + # Positive solution of E quadratic equation + return (-1 + np.sqrt(1 + 4*alpha*gamma*np.power(k-kshift,2)))/(2*gamma) + cbm + + @classmethod + def _fit_hyperbola_negative(cls, k, alpha, kshift, cbm, gamma): + # Negative solution of E quadratic equation + return (-1 - np.sqrt(1 + 4*alpha*gamma*np.power(k-kshift,2)))/(2*gamma) + cbm + + def _effective_mass_calculator(self, kpath, band_energy, p0=None, bounds = (-np.inf, np.inf), + sigma=None, absolute_sigma:bool=False, fit_parabola:bool=False, + fit_hyperbola_positive:bool=False, fit_hyperbola_negative:bool=False): + """ + kpath : numpy array + k on path (A^-1) of unfolded effective band structure/band centers that will + be fitted for calculating effective mass. + band_energy : numpy array + Energy (in eV) of unfolded effective band structure/band centers that will + be fitted for calculating effective mass. + p0 : array_like, optional + Initial guess for the parameters (length N). If None, then the + initial values will all be 1 (if the number of parameters for the + function can be determined using introspection, otherwise a + ValueError is raised). + bounds : 2-tuple of array_like or `Bounds`, optional + Lower and upper bounds on parameters. Defaults to no bounds. + There are two ways to specify the bounds: + - Instance of `Bounds` class. + - 2-tuple of array_like: Each element of the tuple must be either + an array with the length equal to the number of parameters, or a + scalar (in which case the bound is taken to be the same for all + parameters). Use ``np.inf`` with an appropriate sign to disable + bounds on all or some parameters. + sigma : None or scalar or M-length sequence or MxM array, optional + Determines the uncertainty in ydata. If we define residuals as + r = ydata - f(xdata, *popt), then the interpretation of sigma depends on + its number of dimensions: + A scalar or 1-D sigma should contain values of standard deviations of + errors in ydata. In this case, the optimized function is + chisq = sum((r / sigma) ** 2). + A 2-D sigma should contain the covariance matrix of errors in ydata. + In this case, the optimized function is + chisq = r.T @ inv(sigma) @ r. + The default is None. This is equivalent of 1-D sigma filled with ones. + absolute_sigma : bool, optional + If True, sigma is used in an absolute sense and the estimated parameter + covariance pcov reflects these absolute values. + If False, only the relative magnitudes of the sigma values matter. + The default is False. + fit_parabola : bool, optional + Fit parabolic Kane model of band dispersion. The default is False. + Order: fit_parabola > fit_hyperbola_positive > fit_hyperbola_negative + fit_hyperbola_positive : bool, optional + Fit hyperbolic model (upward hyperbola) of band dispersion. The default is False. + fit_hyperbola_negative : bool, optional + Fit hyperbolic model (downward hyperbola) of band dispersion. The default is False. Returns ------- - None. - + m_star : float + Calculated effective mass in m_0 unit. + popt : array + Optimal values for the parameters so that the sum of the squared + residuals of ``f(xdata, *popt) - ydata`` is minimized. + pcov : 2-D array + The estimated approximate covariance of popt. + + Raises + ------ + ValueError + if none of fit_* option is supplied. + ValueError + if either `ydata` or `xdata` contain NaNs, or if incompatible options + are used. + RuntimeError + if the least-squares minimization fails. + OptimizeWarning + if covariance of the parameters can not be estimated. """ - if self.print_output is not None: - print(f"{'='*_draw_line_length}\n- Saving unfolded band centers to file...") - header_msg = " Unfolded band centers data\n" - header_msg += " k on path (A^-1), Band center energy, Band width, Sum of dN\n" - # Save the sc-kpoints in file - save_f_name = \ - SaveData2File.save_2_file(data=data2save, - save_dir=save_dir, file_name=file_name, - file_name_suffix=f'{file_name_suffix}.dat', - header_txt=header_msg, comments_symbol='#', - print_log=bool(self.print_output)) - if self.print_output is not None: - print(f'-- Filepath: {save_f_name}\n- Done') \ No newline at end of file + if fit_parabola: + popt, pcov = curve_fit(self._fit_parabola, kpath, band_energy, p0=p0, + bounds=bounds, sigma=sigma, absolute_sigma=absolute_sigma) + elif fit_hyperbola_positive: + popt, pcov = curve_fit(self._fit_hyperbola_positive, kpath, band_energy, p0=p0, + bounds=bounds, sigma=sigma, absolute_sigma=absolute_sigma) + elif fit_hyperbola_negative: + popt, pcov = curve_fit(self._fit_hyperbola_negative, kpath, band_energy, p0=p0, + bounds=bounds, sigma=sigma, absolute_sigma=absolute_sigma) + else: + raise ValueError('No fitting option is supplied for fitting.') + m_star = self.effective_mass_unit_conversion/popt[0] + return m_star, popt, pcov \ No newline at end of file diff --git a/banduppy/Utilities/__init__.py b/banduppy/Utilities/__init__.py index f1b61a3..95a55a0 100644 --- a/banduppy/Utilities/__init__.py +++ b/banduppy/Utilities/__init__.py @@ -1,6 +1,6 @@ -from .EBS_plot import EBSplot -from .folding_degree_plot import FoldingDegreePlot -from .EBS_properties import BandCentersBroadening +from .EBS_plot import _EBSplot +from .folding_degree_plot import _FoldingDegreePlot +from .EBS_properties import _GeneralFunctionsDefs, _BandCentersBroadening, _EffectiveMass ### =========================================================================== -__all__ = ['EBSplot', 'FoldingDegreePlot', 'BandCentersBroadening'] +__all__ = ['_EBSplot', '_FoldingDegreePlot', '_GeneralFunctionsDefs', '_BandCentersBroadening', '_EffectiveMass'] diff --git a/banduppy/Utilities/folding_degree_plot.py b/banduppy/Utilities/folding_degree_plot.py index b8968ac..c624f78 100644 --- a/banduppy/Utilities/folding_degree_plot.py +++ b/banduppy/Utilities/folding_degree_plot.py @@ -1,10 +1,10 @@ import numpy as np import matplotlib.pyplot as plt -from ..BasicFunctions.general_plot_functions import GeneratePlots +from ..BasicFunctions.general_plot_functions import _GeneratePlots ### =========================================================================== -class FoldingDegreePlot(GeneratePlots): +class _FoldingDegreePlot(_GeneratePlots): """ Plotting number of kpoints in k-path vs degree of folding. @@ -23,11 +23,11 @@ def __init__(self, fold_results_dictionary, save_figure_dir='.'): Directory where to save the figure. The default is current directory. """ - GeneratePlots.__init__(self, save_figure_dir=save_figure_dir) + _GeneratePlots.__init__(self, save_figure_dir=save_figure_dir) self.proposed_folding_results_ = fold_results_dictionary.copy() - def plot_folding(self, save_file_name=None, CountFig=None, yaxis_label:str='Folding degree (%)', - xaxis_label:str='number of kpoints', line_color='k'): + def _plot_folding(self, save_file_name=None, CountFig=None, yaxis_label:str='Folding degree (%)', + xaxis_label:str='number of kpoints', line_color='k'): print('- Plotting folding degree...') for keys, vals in self.proposed_folding_results_.items(): @@ -45,6 +45,6 @@ def plot_folding(self, save_file_name=None, CountFig=None, yaxis_label:str='Fold if save_file_name is None: plt.show() else: - CountFig = self.save_figure(save_file_name, CountFig=CountFig) + CountFig = self._save_figure(save_file_name, CountFig=CountFig) plt.close() return fig, ax, CountFig \ No newline at end of file diff --git a/banduppy/__init__.py b/banduppy/__init__.py index 59085af..1faf261 100644 --- a/banduppy/__init__.py +++ b/banduppy/__init__.py @@ -1,10 +1,10 @@ -__version__ = "0.3.1" +__version__ = "0.3.2" import irrep if irrep.__version__ <"1.6.2" : raise ImportError("A critical bug was found in irrep-1.6.1, which caused incorrect results for unfolding with spin-orbit. Please ipdate irrep to 1.6.2 or newer (when available)") from irrep.bandstructure import BandStructure -from .unfolding import Unfolding, Properties, Plotting +from .unfolding import Unfolding, Properties, SaveBandStructuredata, Plotting -__all__ = ['Unfolding', 'BandStructure', 'Properties', 'Plotting'] +__all__ = ['Unfolding', 'BandStructure', 'Properties', 'SaveBandStructuredata', 'Plotting'] diff --git a/banduppy/src/__init__.py b/banduppy/src/__init__.py index 3b9f3ca..f30ac19 100644 --- a/banduppy/src/__init__.py +++ b/banduppy/src/__init__.py @@ -1,6 +1,6 @@ -from .folding import BandFolding -from .unfolding import BandUnfolding -from .folding_properties import FindProperties +from .folding import _BandFolding +from .unfolding import _GeneralFnsDefs, _BandUnfolding +from .folding_properties import _FindProperties ### =========================================================================== -__all__ = ['BandFolding','BandUnfolding', 'FindProperties'] +__all__ = ['_BandFolding','_GeneralFnsDefs', '_BandUnfolding', '_FindProperties'] diff --git a/banduppy/src/folding.py b/banduppy/src/folding.py index adf4eec..7f2b3df 100644 --- a/banduppy/src/folding.py +++ b/banduppy/src/folding.py @@ -1,6 +1,6 @@ import numpy as np -from ..BasicFunctions.general_functions import SaveData2File, _BasicFunctionsModule, _draw_line_length -from .folding_properties import FindProperties +from ..BasicFunctions.general_functions import _SaveData2File, _BasicFunctionsModule, _draw_line_length +from .folding_properties import _FindProperties from .. import __version__ try: @@ -205,9 +205,9 @@ def _propose_max_min_folding(cls, transformation_matrix, pathPBZ, # Search for max-min folding propose_folding_data_[i] = ((start, end), cls._serach_max_min_folding(transformation_matrix, start, end, - min_num_pts=min_num_pts, - max_num_pts=max_num_pts, - serach_mode=serach_mode)) + min_num_pts=min_num_pts, + max_num_pts=max_num_pts, + serach_mode=serach_mode)) return propose_folding_data_ @@ -496,7 +496,7 @@ def _generate_save_contents(self, footer_text=None, save_all_kpts:bool=False): return save_contents_data ## ============================================================================ -class BandFolding(_KpointsModule, FindProperties): +class _BandFolding(_KpointsModule, _FindProperties): """ Band folding from primitive to supercell. @@ -518,8 +518,8 @@ def __init__(self, supercell=None, print_info='low'): self.transformation_matrix = _BasicFunctionsModule._check_transformation_matrix(np.array(supercell)) self.print_information = print_info - def propose_best_least_folding(self, pathPBZ, min_num_pts:int=5, max_num_pts:int=20, - serach_mode:str='brute_force'): + def _propose_best_least_folding(self, pathPBZ, min_num_pts:int=5, max_num_pts:int=20, + serach_mode:str='brute_force'): """ Calculates SC Kpoints from PC kpoints and returns percent of folding. Maximum and Minimum degree of folding are reported. @@ -551,10 +551,10 @@ def propose_best_least_folding(self, pathPBZ, min_num_pts:int=5, max_num_pts:int max_num_pts=max_num_pts, serach_mode=serach_mode) - def generate_SC_K_from_pc_k_path(self, pathPBZ=None, nk=11, labels=None, kpts_weights=None, - save_all_kpts:bool=False, save_sc_kpts:bool=False, - save_dir='.', file_name:str='', - file_name_suffix:str='', file_format:str='vasp'): + def _generate_SC_K_from_pc_k_path(self, pathPBZ=None, nk=11, labels=None, kpts_weights=None, + save_all_kpts:bool=False, save_sc_kpts:bool=False, + save_dir='.', file_name:str='', + file_name_suffix:str='', file_format:str='vasp'): """ Generate supercell kpoints from reference primitive BZ k-path. @@ -621,18 +621,18 @@ def generate_SC_K_from_pc_k_path(self, pathPBZ=None, nk=11, labels=None, kpts_we footer_msg_path = self._generate_foot_text(pathPBZ, labels=labels, nk_list=nk) # Return SC kpoints from PC k-path k-points - return self.generate_K_from_k(kpointsPBZ=PBZ_kpts, kpts_weights=kpts_weights, + return self._generate_K_from_k(kpointsPBZ=PBZ_kpts, kpts_weights=kpts_weights, save_all_kpts=save_all_kpts, save_sc_kpts=save_sc_kpts, save_dir=save_dir, file_name=file_name, file_name_suffix=file_name_suffix, file_format=file_format, footer_msg=footer_msg_path, special_kpoints_pos_labels=special_kpoints_pos_labels) - def generate_K_from_k(self, kpointsPBZ=None, kpts_weights=None, - save_all_kpts:bool=False, save_sc_kpts:bool=False, - save_dir='.', file_name:str='', - file_name_suffix:str='', file_format:str='vasp', footer_msg=None, - special_kpoints_pos_labels=None): + def _generate_K_from_k(self, kpointsPBZ=None, kpts_weights=None, + save_all_kpts:bool=False, save_sc_kpts:bool=False, + save_dir='.', file_name:str='', + file_name_suffix:str='', file_format:str='vasp', footer_msg=None, + special_kpoints_pos_labels=None): """ Generate supercell kpoints from reference primitive kpoints. @@ -707,14 +707,14 @@ def generate_K_from_k(self, kpointsPBZ=None, kpts_weights=None, save_contents_data = self. _generate_save_contents(footer_text=footer_msg, save_all_kpts=save_all_kpts) for data_key, data_items in save_contents_data.items(): - SaveData2File.save_sc_kpts_2_file(data=data_items[1], - save_dir=save_dir, file_name=file_name, - file_name_suffix=f'{file_name_suffix}_{data_key}', - file_format=file_format, - header_txt=data_items[0], - footer_txt=data_items[2], - print_log=bool(self.print_information), - print_msg=data_items[3]) + _SaveData2File._save_sc_kpts_2_file(data=data_items[1], + save_dir=save_dir, file_name=file_name, + file_name_suffix=f'{file_name_suffix}_{data_key}', + file_format=file_format, + header_txt=data_items[0], + footer_txt=data_items[2], + print_log=bool(self.print_information), + print_msg=data_items[3]) return self.PBZ_kpts_list_org, self.PBZ_kpts_list, self.SBZ_kpts_list, \ self.SBZ_PBZ_kpts_mapping, self.special_kpoints_pos_labels diff --git a/banduppy/src/folding_properties.py b/banduppy/src/folding_properties.py index 0a4e3c6..145f7c0 100644 --- a/banduppy/src/folding_properties.py +++ b/banduppy/src/folding_properties.py @@ -2,26 +2,26 @@ from ..BasicFunctions.general_functions import _draw_line_length ### =========================================================================== -class FindProperties: +class _FindProperties: def __init__(self): pass @property - def nkptSBZ(self): + def _nkptSBZ(self): ''' Return number of (unique) SC kpoints. ''' return(self.SBZ_kpts_list.shape[0]) @property - def nkptPBZ(self): + def _nkptPBZ(self): ''' Return number of PC kpoints. ''' return(self.PBZ_kpts_list_org.shape[0]) @property - def nkptPBZ_unique(self): + def _nkptPBZ_unique(self): ''' Return number of PC kpoints. ''' @@ -44,9 +44,9 @@ def _print_info(self, level='low'): """ print(f"{'='*_draw_line_length}\n- Folding info:") - print(f"-- Total number of unique PC kpoints: {self.nkptPBZ} ({self.nkptPBZ_unique} unique)") - print(f"-- {self.nkptPBZ_unique} unique PC k-points => {self.nkptSBZ} unique SC K-points") - print(f'-- Percentage folding: {(self.nkptPBZ_unique-self.nkptSBZ)/self.nkptPBZ_unique*100:.3f} %') + print(f"-- Total number of unique PC kpoints: {self._nkptPBZ} ({self._nkptPBZ_unique} unique)") + print(f"-- {self._nkptPBZ_unique} unique PC k-points => {self._nkptSBZ} unique SC K-points") + print(f'-- Percentage folding: {(self._nkptPBZ_unique-self._nkptSBZ)/self._nkptPBZ_unique*100:.3f} %') if level in ['medium','high']: print(f"{'='*_draw_line_length}") print(f'- Special k-points (pos_index, label): {self.special_kpoints_pos_labels}') @@ -55,7 +55,7 @@ def _print_info(self, level='low'): else: self._print_PBZ_SBZ_kpts_mapping() - def kpoints_SBZ_str(self): + def _kpoints_SBZ_str(self): """ Create string of SC kpoints generated. diff --git a/banduppy/src/unfolding.py b/banduppy/src/unfolding.py index 68c6975..a08830b 100644 --- a/banduppy/src/unfolding.py +++ b/banduppy/src/unfolding.py @@ -1,12 +1,101 @@ import numpy as np -from ..BasicFunctions.general_functions import SaveData2File, _BasicFunctionsModule, _draw_line_length +from ..BasicFunctions.general_functions import _SaveData2File, _BasicFunctionsModule, _draw_line_length try: from irrep.__aux import is_round except ImportError: from irrep.utility import is_round ### =========================================================================== -class BandUnfolding: +class _GeneralFnsDefs: + """ + Some of the general function definitions. + """ + @classmethod + def _save_Post_unfolded_PBZ_kpts(cls, unfolded_kpts_dat, save_dir, file_name, + file_name_suffix, print_information='low'): + """ + Save unfolded PC-kpoints. + + Parameters + ---------- + unfolded_kpts_dat : numpy array + Unfolded kpoints in k-path. + Format: [k-index, k on path (A^-1), k1, k2, k3] + save_dir : str or path + Directory path where to save the file. + file_name : str + Name of the file. + file_name_suffix : str + Suffix to add to the file name. + print_information : [None,'low','medium','high'], optional + Level of printing information. + The default is 'low'. If None, nothing is printed. + + Returns + ------- + None. + + """ + if print_information is not None: + print(f"{'='*_draw_line_length}\n- Saving unfolded kpoints to file...") + header_msg = " Unfolded PC k-points from postprocessed wavefunction file\n" + header_msg += " k-index, k on path (A^-1), k1, k2, k3\n" + # Save the sc-kpoints in file + save_f_name = \ + _SaveData2File._save_2_file(data=unfolded_kpts_dat, + save_dir=save_dir, file_name=file_name, + file_name_suffix=f'{file_name_suffix}.dat', + header_txt=header_msg, comments_symbol='#', + print_log=bool(print_information)) + if print_information is not None: + print(f'-- Filepath: {save_f_name}\n- Done') + + @classmethod + def _save_Post_unfolded_bandstucture(cls, unfolded_bandstructure, save_dir, file_name, file_name_suffix, + print_information='low', is_spinor:bool=False): + """ + Save unfolded effective band structure data. + + Parameters + ---------- + unfolded_bandstructure : numpy ndarray + Unfolded effective band structure. + Format: [k index, k on path (A^-1), energy, weight, "Sx, Sy, Sz" if spinor] + save_dir : str or path + Directory path where to save the file. + file_name : str + Name of the file. + file_name_suffix : str + Suffix to add to the file name. + is_spinor : bool, optional + If the bands in wave function files are non-degenerate (spinor). + The default is False. + print_information : [None,'low','medium','high'], optional + Level of printing information. + The default is 'low'. If None, nothing is printed. + + Returns + ------- + None. + + """ + if print_information is not None: + print(f"{'='*_draw_line_length}\n- Saving unfolded bandstructure to file...") + header_msg = " Unfolded band structure from postprocessed wavefunction file\n" + header_msg += " k-index, k on path (A^-1), energy, weight " + \ + ("Sx,Sy,Sz" if is_spinor else "") +"\n" + # Save the unfolded band structure in file + save_f_name = \ + _SaveData2File._save_2_file(data=unfolded_bandstructure, + save_dir=save_dir, file_name=file_name, + file_name_suffix=f'{file_name_suffix}.dat', + header_txt=header_msg, comments_symbol='#', + print_log=bool(print_information)) #, + #np_data_fmt='%.18e') + if print_information is not None: + print(f'-- Filepath: {save_f_name}\n- Done') + +class _BandUnfolding(_GeneralFnsDefs): """ Band unfolding from supercell to primitive cell band structure (effective band structure). @@ -40,7 +129,6 @@ def __init__(self, supercell, PBZ_kpts_list_full, self.kpointsSBZ = _BasicFunctionsModule._round_2_tolerance(SBZ_kpts_list) self.SBZ_PBZ_kpts_index_map = SBZ_PBZ_kpts_map self.print_information = print_info - def _gather_generated_ab_calculated_kpts(self, wavefns_file_kpts): """ @@ -90,7 +178,50 @@ def _gather_generated_ab_calculated_kpts(self, wavefns_file_kpts): for _, vall in val.items(): # kkk: unique PC-kpts indices; vall: list of PC-kpts indices for kk in vall: print(f"\t--- {kk:>5}:" + " ".join(f"{x:12.8f}" for x in self.kpointsPBZ_full[kk, :3])) - + + def _generate_kpoints_line(self, irrep_bandstr_instance, pc_kpts_coord, + transformation_matrix, breakTHRESH = 0.1): + """ + Generates kpoints line (after cartesian coordinate conversion). + k_vec = u.b1 + v.b2 + w.b3 + e.g. (u,v,w)=(1/2, 0, 0) -> k_vec==(kx, ky, kz) + [kx ky kz] = [u v w].[[b11 b12 b13], [b21 b22 b23], [b31 b32 b33]] + + Parameters + ---------- + irrep_bandstr_instance : irrep.bandstructure.BandStructure + irrep.bandstructure.BandStructure instance. + pc_kpts_coord : ndarray of floats + PC kpoints list. + transformation_matrix : 3X3 matrix + Primitive-to-supercell transformation matrix. + breakTHRESH : float, optional + If the distance between two neighboring k-points in the path is + larger than `break_thresh` break continuity in k-path. Set break_thresh + to a large value if the unfolded kpoints line is continuous. + The default is 0.1. + + Returns + ------- + K : numpy 1d array of floats + Primitive cell k-points line path for unfolded bandstructure. + + """ + # Supercell lattice vectors + sc_lattice = irrep_bandstr_instance.Lattice + # Convert k-points in inverse lattice unit + # Note: (A.T^-1)^-1 == T.A^-1 + RecLattice = 2*np.pi*np.dot(transformation_matrix, np.linalg.pinv(sc_lattice)).T + KPcart = np.dot(pc_kpts_coord, RecLattice) + #KPcart = np.linalg.solve(np.dot(sc_lattice, np.linalg.pinv(transformation_matrix)), pc_kpts_coord.T).T # without 2*pi + + # Generate distance array + K = np.zeros(KPcart.shape[0]) + k = np.linalg.norm(KPcart[1:, :] - KPcart[:-1, :], axis=1) + k[k > breakTHRESH] = 0.0 + K[1:] = np.cumsum(k) + return K + def _unfold_bandstructure(self, bandstructure, break_thresh = 0.1): """ @@ -98,7 +229,7 @@ def _unfold_bandstructure(self, bandstructure, break_thresh = 0.1): Parameters ---------- bandstructure : irrep.bandstructure.BandStructure - irrep.bandstructure.BandStructure data. + irrep.bandstructure.BandStructure instance. break_thresh : float, optional If the distance between two neighboring k-points in the path is larger than `break_thresh` break continuity in k-path. Set break_thresh @@ -124,18 +255,12 @@ def _unfold_bandstructure(self, bandstructure, break_thresh = 0.1): # k-index, k1, k2, k3 self.unfolded_kpts_dat = np.array([[kk]+list(self.kpointsPBZ_full[kk, :3]) for kk in kpPBZ_unfolded]) - #self.unfolded_kpts_dat = unfolded_kpts_dat_[unfolded_kpts_dat_[:, 0].argsort()] # No need any more - self.kpline = bandstructure.KPOINTSline(kpred=self.unfolded_kpts_dat[:,1:], breakTHRESH=break_thresh) - # # Converting k-indices to k on path (A^-1) - # self.unfolded_kpts_dat[:,0] = self.kpline - + # Generate k-path in distance unit + self.kpline = self._generate_kpoints_line(bandstructure, self.unfolded_kpts_dat[:,1:], + self.transformation_matrix, breakTHRESH=break_thresh) # Insert k on path (A^-1) after k-indices self.unfolded_kpts_dat = np.insert(self.unfolded_kpts_dat,1, self.kpline, axis=1) - # # Add k-path to the energy, weight band structure array - # self.unfolded_bandstructure = np.concatenate([np.insert(unf, 0, self.kpline[kk], axis=1) - # for kk, unf in kpPBZ_unfolded.items()], axis=0) - # Add k-indices and k-path to the energy, weight band structure array self.unfolded_bandstructure = np.concatenate([np.insert(unf, [0, 0], [kk, self.kpline[kk]], axis=1) for kk, unf in kpPBZ_unfolded.items()], axis=0) @@ -174,77 +299,6 @@ def _print_info_post(self, level='low'): """ if level == 'high': self._print_Post_unfolded_PBZ_kpts() - - def _save_Post_unfolded_PBZ_kpts(self, save_dir, file_name, file_name_suffix): - """ - Save unfolded PC-kpoints. - Format: k-index, k on path (A^-1), k1, k2, k3 - - Parameters - ---------- - save_dir : str or path - Directory path where to save the file. - file_name : str - Name of the file. - file_name_suffix : str - Suffix to add to the file name. - - Returns - ------- - None. - - """ - if self.print_information is not None: - print(f"{'='*_draw_line_length}\n- Saving unfolded kpoints to file...") - header_msg = " Unfolded PC k-points from postprocessed wavefunction file\n" - header_msg += " k-index, k on path (A^-1), k1, k2, k3\n" - # Save the sc-kpoints in file - save_f_name = \ - SaveData2File.save_2_file(data=self.unfolded_kpts_dat, - save_dir=save_dir, file_name=file_name, - file_name_suffix=f'{file_name_suffix}.dat', - header_txt=header_msg, comments_symbol='#', - print_log=bool(self.print_information)) - if self.print_information is not None: - print(f'-- Filepath: {save_f_name}\n- Done') - - def _save_Post_unfolded_bandstucture(self, save_dir, file_name, file_name_suffix, is_spinor:bool=False): - """ - Save unfolded effective band structure data. - Format: k-index, k on path (A^-1), k1, k2, k3 - - Parameters - ---------- - save_dir : str or path - Directory path where to save the file. - file_name : str - Name of the file. - file_name_suffix : str - Suffix to add to the file name. - is_spinor : bool, optional - If the bands in wave function files are non-degenerate (spinor). - The default is False. - - Returns - ------- - None. - - """ - if self.print_information is not None: - print(f"{'='*_draw_line_length}\n- Saving unfolded bandstructure to file...") - header_msg = " Unfolded band structure from postprocessed wavefunction file\n" - header_msg += " k-index, k on path (A^-1), energy, weight " + \ - ("Sx,Sy,Sz" if is_spinor else "") +"\n" - # Save the unfolded band structure in file - save_f_name = \ - SaveData2File.save_2_file(data=self.unfolded_bandstructure, - save_dir=save_dir, file_name=file_name, - file_name_suffix=f'{file_name_suffix}.dat', - header_txt=header_msg, comments_symbol='#', - print_log=bool(self.print_information)) #, - #np_data_fmt='%.18e') - if self.print_information is not None: - print(f'-- Filepath: {save_f_name}\n- Done') def _save_unfolded_kpts_bandstr(self, save_unfolded_kpts = {'save2file': False, @@ -261,7 +315,7 @@ def _save_unfolded_kpts_bandstr(self, Parameters ---------- save_unfolded_kpts : dictionary, optional - save2file :: Save unfolded kpoints or not? + save2file :: Save unfolded kpoints data to file or not? fir :: str or path Directory path where to save the file. fname :: str @@ -270,7 +324,7 @@ def _save_unfolded_kpts_bandstr(self, Suffix to add to the file name. The default is {'save2file': False, 'fdir': '.', 'fname': 'kpoints_unfolded', 'fname_suffix': ''}. save_unfolded_bandstr : dictionary, optional - save2file :: Save unfolded kpoints or not? + save2file :: Save unfolded bandstructure data to file or not? fir :: str or path Directory path where to save the file. fname :: str @@ -285,25 +339,31 @@ def _save_unfolded_kpts_bandstr(self, """ # Save unfolded kpoints after post processing of wave function file + save_unfolded_kpts = _SaveData2File._default_save_settings(save_unfolded_kpts) if save_unfolded_kpts['save2file']: - self._save_Post_unfolded_PBZ_kpts(save_dir=save_unfolded_kpts["fdir"], + self._save_Post_unfolded_PBZ_kpts(unfolded_kpts_dat=self.unfolded_kpts_dat, + save_dir=save_unfolded_kpts["fdir"], file_name=save_unfolded_kpts["fname"], - file_name_suffix=save_unfolded_kpts["fname_suffix"]) + file_name_suffix=save_unfolded_kpts["fname_suffix"], + print_information=self.print_information) # Save unfolded band structure after post processing of wave function file + save_unfolded_bandstr = _SaveData2File._default_save_settings(save_unfolded_bandstr) if save_unfolded_bandstr['save2file']: - self._save_Post_unfolded_bandstucture(save_dir=save_unfolded_bandstr["fdir"], + self._save_Post_unfolded_bandstucture(unfolded_bandstructure=self.unfolded_bandstructure, + save_dir=save_unfolded_bandstr["fdir"], file_name=save_unfolded_bandstr["fname"], - file_name_suffix=save_unfolded_bandstr["fname_suffix"]) - - def unfold(self, bandstructure, kline_discontinuity_threshold = 0.1, - save_unfolded_kpts = {'save2file': False, - 'fdir': '.', - 'fname': 'kpoints_unfolded', - 'fname_suffix': ''}, - save_unfolded_bandstr = {'save2file': False, - 'fdir': '.', - 'fname': 'bandstructure_unfolded', - 'fname_suffix': ''}): + file_name_suffix=save_unfolded_bandstr["fname_suffix"], + print_information=self.print_information) + + def _unfold(self, bandstructure, kline_discontinuity_threshold = 0.1, + save_unfolded_kpts = {'save2file': False, + 'fdir': '.', + 'fname': 'kpoints_unfolded', + 'fname_suffix': ''}, + save_unfolded_bandstr = {'save2file': False, + 'fdir': '.', + 'fname': 'bandstructure_unfolded', + 'fname_suffix': ''}): """ @@ -317,7 +377,7 @@ def unfold(self, bandstructure, kline_discontinuity_threshold = 0.1, to a large value if the unfolded kpoints line is continuous. The default is 0.1. save_unfolded_kpts : dictionary, optional - save2file :: Save unfolded kpoints or not? + save2file :: Save unfolded kpoints data to file or not? fir :: str or path Directory path where to save the file. fname :: str @@ -326,7 +386,7 @@ def unfold(self, bandstructure, kline_discontinuity_threshold = 0.1, Suffix to add to the file name. The default is {'save2file': False, 'fdir': '.', 'fname': 'kpoints_unfolded', 'fname_suffix': ''}. save_unfolded_bandstr : dictionary, optional - save2file :: Save unfolded kpoints or not? + save2file :: Save unfolded band structure data to file or not? fir :: str or path Directory path where to save the file. fname :: str diff --git a/banduppy/unfolding.py b/banduppy/unfolding.py index 0bc3f21..0bf4c10 100644 --- a/banduppy/unfolding.py +++ b/banduppy/unfolding.py @@ -1,9 +1,9 @@ import numpy as np -from .src import BandFolding, BandUnfolding -from .Utilities import EBSplot, FoldingDegreePlot, BandCentersBroadening +from .src import _BandFolding, _BandUnfolding, _GeneralFnsDefs +from .Utilities import _GeneralFunctionsDefs, _EBSplot, _FoldingDegreePlot, _BandCentersBroadening, _EffectiveMass ### =========================================================================== -class Unfolding(BandFolding, BandUnfolding, EBSplot, FoldingDegreePlot): +class Unfolding(_BandFolding, _BandUnfolding, _EBSplot, _FoldingDegreePlot): """ Band folding from primitive to supercell. @@ -22,7 +22,7 @@ def __init__(self, supercell=None, print_log='low'): """ if print_log is not None: print_log = print_log.lower() - BandFolding.__init__(self, supercell=supercell, print_info=print_log) + _BandFolding.__init__(self, supercell=supercell, print_info=print_log) def propose_maximum_minimum_folding(self, pathPBZ, min_num_pts:int=5, max_num_pts:int=20, serach_mode:str='brute_force', draw_plots:bool=True, @@ -76,17 +76,17 @@ def propose_maximum_minimum_folding(self, pathPBZ, min_num_pts:int=5, max_num_pt If draw_plots=True, also returns fig, ax, and CountFig. """ proposed_folding_results = \ - self.propose_best_least_folding(pathPBZ, min_num_pts=min_num_pts, - max_num_pts=max_num_pts, - serach_mode=serach_mode) + self._propose_best_least_folding(pathPBZ, min_num_pts=min_num_pts, + max_num_pts=max_num_pts, + serach_mode=serach_mode) if draw_plots: - FoldingDegreePlot.__init__(self, fold_results_dictionary=proposed_folding_results, - save_figure_dir=save_dir) - fig, ax, CountFig = self.plot_folding(save_file_name=save_file_name, - CountFig=CountFig, - yaxis_label=yaxis_label, - xaxis_label=xaxis_label, - line_color=line_color) + _FoldingDegreePlot.__init__(self, fold_results_dictionary=proposed_folding_results, + save_figure_dir=save_dir) + fig, ax, CountFig = self._plot_folding(save_file_name=save_file_name, + CountFig=CountFig, + yaxis_label=yaxis_label, + xaxis_label=xaxis_label, + line_color=line_color) return proposed_folding_results, fig, ax, CountFig return proposed_folding_results @@ -149,13 +149,13 @@ def generate_SC_Kpts_from_pc_k_path(self, pathPBZ=None, nk=11, labels=None, kpts SC unique kpoints indices for reverse engineer. """ - return self.generate_SC_K_from_pc_k_path(pathPBZ=pathPBZ, nk=nk, labels=labels, - kpts_weights=kpts_weights, - save_all_kpts=save_all_kpts, - save_sc_kpts=save_sc_kpts, - save_dir=save_dir, file_name=file_name, - file_name_suffix=file_name_suffix, - file_format=file_format) + return self._generate_SC_K_from_pc_k_path(pathPBZ=pathPBZ, nk=nk, labels=labels, + kpts_weights=kpts_weights, + save_all_kpts=save_all_kpts, + save_sc_kpts=save_sc_kpts, + save_dir=save_dir, file_name=file_name, + file_name_suffix=file_name_suffix, + file_format=file_format) def generate_SC_Kpts_from_pc_kpts(self, kpointsPBZ=None, kpts_weights=None, save_all_kpts:bool=False, save_sc_kpts:bool=False, @@ -209,13 +209,13 @@ def generate_SC_Kpts_from_pc_kpts(self, kpointsPBZ=None, kpts_weights=None, Position and labels of special kpoints, will be used in plotting. """ - return self.generate_K_from_k(kpointsPBZ=kpointsPBZ, kpts_weights=kpts_weights, - save_all_kpts=save_all_kpts, - save_sc_kpts=save_sc_kpts, - save_dir=save_dir, file_name=file_name, - file_name_suffix=file_name_suffix, - file_format=file_format, footer_msg=footer_msg, - special_kpoints_pos_labels=special_kpoints_pos_labels) + return self._generate_K_from_k(kpointsPBZ=kpointsPBZ, kpts_weights=kpts_weights, + save_all_kpts=save_all_kpts, + save_sc_kpts=save_sc_kpts, + save_dir=save_dir, file_name=file_name, + file_name_suffix=file_name_suffix, + file_format=file_format, footer_msg=footer_msg, + special_kpoints_pos_labels=special_kpoints_pos_labels) def Unfold(self, bandstructure, PBZ_kpts_list_full=None, SBZ_kpts_list=None, SBZ_PBZ_kpts_map=None, @@ -251,7 +251,7 @@ def Unfold(self, bandstructure, to a large value if the unfolded kpoints line is continuous. The default is 0.1. save_unfolded_kpts : dictionary, optional - save2file :: Save unfolded kpoints or not? + save2file :: Save unfolded kpoints data to file or not? fir :: str or path Directory path where to save the file. fname :: str @@ -260,7 +260,7 @@ def Unfold(self, bandstructure, Suffix to add to the file name. The default is {'save2file': False, 'fdir': '.', 'fname': 'kpoints_unfolded', 'fname_suffix': ''}. save_unfolded_bandstr : dictionary, optional - save2file :: Save unfolded kpoints or not? + save2file :: Save unfolded band structure data to file or not? fir :: str or path Directory path where to save the file. fname :: str @@ -273,40 +273,44 @@ def Unfold(self, bandstructure, ------- numpy ndarray Unfolded effective band structure. - Format: k index, k on path (A^-1), energy, weight, "Sx, Sy, Sz" if is_spinor. + Format: [k index, k on path (A^-1), energy, weight, "Sx, Sy, Sz" if spinor] numpy ndarray Unfolded effective band structure k-path. - Format: k on path (A^-1) + Format: [k on path (A^-1)] """ if (PBZ_kpts_list_full is None) or \ (SBZ_kpts_list in None) or (SBZ_PBZ_kpts_map is None): - BandUnfolding.__init__(self, self.transformation_matrix, - self.PBZ_kpts_list_org, self.SBZ_kpts_list, - self.SBZ_PBZ_kpts_mapping, - print_info=self.print_information) + _BandUnfolding.__init__(self, self.transformation_matrix, + self.PBZ_kpts_list_org, self.SBZ_kpts_list, + self.SBZ_PBZ_kpts_mapping, + print_info=self.print_information) else: - BandUnfolding.__init__(self, self.transformation_matrix, - PBZ_kpts_list_full, SBZ_kpts_list, - SBZ_PBZ_kpts_map, - print_info=self.print_information) + _BandUnfolding.__init__(self, self.transformation_matrix, + PBZ_kpts_list_full, SBZ_kpts_list, + SBZ_PBZ_kpts_map, + print_info=self.print_information) + + return self._unfold(bandstructure, + kline_discontinuity_threshold = kline_discontinuity_threshold, + save_unfolded_kpts = save_unfolded_kpts, + save_unfolded_bandstr = save_unfolded_bandstr) + + def plot_ebs(self, fig=None, ax=None, save_figure_dir='.', save_file_name=None, + CountFig=None, Ef=None, Emin=None, Emax=None, pad_energy_scale:float=0.5, + threshold_weight:float=None, mode:str="fatband", yaxis_label:str='E (eV)', + special_kpoints:dict=None, plotSC:bool=True, marker='o', fatfactor=20, + nE:int=100, smear:float=0.05, color='gray', color_map='viridis', + show_legend:bool=True, show_colorbar:bool=False, colorbar_label:str=None, + vmin=None, vmax=None, show_plot:bool=True,**kwargs_savefig): - return self.unfold(bandstructure, - kline_discontinuity_threshold = kline_discontinuity_threshold, - save_unfolded_kpts = save_unfolded_kpts, - save_unfolded_bandstr = save_unfolded_bandstr) - - def plot_ebs(self, ax=None, save_figure_dir='.', save_file_name=None, CountFig=None, - Ef=None, Emin=None, Emax=None, pad_energy_scale:float=0.5, - threshold_weight:float=None, mode:str="fatband", - yaxis_label:str='E (eV)', special_kpoints:dict=None, plotSC:bool=True, - marker='o', fatfactor=20, nE:int=100, smear:float=0.05, - scatter_color='gray', color_map='viridis', show_legend:bool=True): """ Scatter/density plot of the band structure. Parameters ---------- + fig : matplotlib.pyplot figure instance, optional + Figure instance to plot on. The default is None. ax : matplotlib.pyplot axis, optional Figure axis to plot on. If None, new figure will be created. The default is None. @@ -349,13 +353,25 @@ def plot_ebs(self, ax=None, save_figure_dir='.', save_file_name=None, CountFig=N The default is 100. smear : float, optional Gaussian smearing. The default is 0.05. - scatter_color : str/color, optional + color : str/color, optional Color of scatter plot of unfolded band structure. The color of supercell band structures is gray. The default is 'gray'. color_map: str/ matplotlib colormap Colormap for density plot. The default is viridis. show_legend : bool If show legend or not. The default is True. + show_colorbar : bool, optional + Plot the colorbar in the figure or not. If fig=None, this is ignored. + The default is False. + colorbar_label : str, optional + Colorbar label. The default is None. If None, ignored. + vmin, vmax : float, optional + vmin and vmax define the data range that the colormap covers. + By default, the colormap covers the complete value range of the supplied data. + show_plot : bool, optional + To show the plot when not saved. The default is True. + **kwargs_savefig : dict + The matplotlib keywords for savefig function. Returns ------- @@ -369,17 +385,18 @@ def plot_ebs(self, ax=None, save_figure_dir='.', save_file_name=None, CountFig=N """ - EBSplot.__init__(self, save_figure_dir=save_figure_dir) - - return self.plot(ax=ax, save_file_name=save_file_name, CountFig=CountFig, Ef=Ef, - Emin=Emin, Emax=Emax, pad_energy_scale=pad_energy_scale, - threshold_weight=threshold_weight, mode=mode, - yaxis_label=yaxis_label, special_kpoints=special_kpoints, - plotSC=plotSC, marker=marker, fatfactor=fatfactor, nE=nE, - smear=smear, scatter_color=scatter_color, color_map=color_map, - show_legend=show_legend) + _EBSplot.__init__(self, save_figure_dir=save_figure_dir) + + return self._plot(fig=fig, ax=ax, save_file_name=save_file_name, CountFig=CountFig, + Ef=Ef, Emin=Emin, Emax=Emax, pad_energy_scale=pad_energy_scale, + threshold_weight=threshold_weight, mode=mode, yaxis_label=yaxis_label, + special_kpoints=special_kpoints, plotSC=plotSC, marker=marker, + fatfactor=fatfactor, nE=nE, smear=smear, color=color, color_map=color_map, + show_legend=show_legend, show_colorbar=show_colorbar, + colorbar_label=colorbar_label, vmin=vmin, vmax=vmax, + show_plot=show_plot, **kwargs_savefig) -class Properties(BandCentersBroadening): +class Properties(_BandCentersBroadening, _EffectiveMass): """ Calculate properties from unfolded band structure. @@ -395,14 +412,72 @@ def __init__(self, print_log='low'): The default is 'low'. If None, nothing is printed. """ - if print_log is not None: self.print_log_info = print_log.lower() + if print_log is not None: print_log = print_log.lower() + self.print_log_info = print_log + + def collect_bandstr_data_only_in_energy_window(self, unfolded_bandstructure, Ef:float=None, + Emin:float=None, Emax:float=None, + pad_energy_scale:float=0.5, + min_dN_screen:float=0.0, + save_data = {'save2file': False, + 'fdir': '.', + 'fname': 'unfolded_bandcenters_window', + 'fname_suffix': ''}): + """ + Collect data within the condition and range specified. + Note: Returns only 1st 4 columns. Removes the spinor data part for + spinor activated effective band structure data. + + Parameters + ---------- + complete_data : ndarray, optional + Unfolded effective band structure/band center data. + Ef : float + Fermi energy. Set to 0.0 if None or 'auto'. + Emin : float, optional + Minimum in energy. The default is None. + Emax : float, optional + Maximum in energy. The default is None. + pad_energy_scale: float, optional + Add padding of pad_energy_scale to minimum and maximum energy if Emin + and Emax are None. The default is 0.5. + min_dN_screen : float, optional + The band centers with band weights lower than the threshhold weights + are discarded. The default is 0. + save_data : dictionary, optional + save2file :: Save data to file or not? + fir :: str or path + Directory path where to save the file. + fname :: str + Name of the file. + fname_suffix :: str + Suffix to add to the file name. + The default is {'save2file': False, 'fdir': '.', 'fname': 'unfolded_bandcenters_window', 'fname_suffix': ''}. + + Returns + ------- + unfolded_bandcenters_window : ndarray + Unfolded effective band structure/band center data within the range. + + """ + + unfolded_bandcenters_window = \ + _GeneralFunctionsDefs._get_bandstr_data_only_in_energy_kpts_window(unfolded_bandstructure, Ef=Ef, + Emin=Emin, Emax=Emax, + pad_energy_scale=pad_energy_scale, + min_dN_screen=min_dN_screen) + + _GeneralFunctionsDefs._save_band_centers(data2save=unfolded_bandcenters_window, + print_log=self.print_log_info, + save_data_f_prop=save_data) + return unfolded_bandcenters_window def band_centers_broadening_bandstr(self, unfolded_bandstructure, min_dN_pre_screening:float=1e-4, threshold_dN_2b_trial_band_center:float=0.05, min_sum_dNs_for_a_band:float=0.05, precision_pos_band_centers:float=1e-5, - err_tolerance_compare_kpts:float=1e-8, + err_tolerance_compare_kpts_val:float=1e-8, collect_scf_data:bool=False, save_data = {'save2file': False, 'fdir': '.', @@ -415,33 +490,35 @@ def band_centers_broadening_bandstr(self, unfolded_bandstructure, ---------- unfolded_bandstructure : numpy array Unfolded effective band structure. - Format: k index, k on path (A^-1), energy, weight, "Sx, Sy, Sz" if is_spinor. - min_dN_pre_screening : float, optional - Discard the bands which has weights below min_dN_pre_screening. This - pre-screening step helps to minimize the data that will processed - now on. The default is 1e-4. - threshold_dN_2b_trial_band_center : float, optional - Initial guess of the band centers based on the threshold wights. - The default is 0.05. - min_sum_dNs_for_a_band : float, optional - Cut off criteria for minimum weights that band center should have. - The band centers with lower weights than min_sum_dNs_for_a_band will be - discarded during SCF refinements. If min_sum_dNs_for_a_band - is smaller than threshold_dN_2b_trial_band_center, min_sum_dNs_for_a_band - will be reset to threshold_dN_2b_trial_band_center value. - The default is 0.05. - precision_pos_band_centers : float, optional - Precision when compared band centers from previous and latest SCF - iteration. SCF is considered converged if this precision is reached. - The default is 1e-5. - err_tolerance_compare_kpts : float, optional - The tolerance to group the bands set per unique kpoints. - The default is 1e-8. + Format: [k index, k on path (A^-1), energy, weight, "Sx, Sy, Sz" if spinor] + min_dN_pre_screening : float, optional + Discard the bands which has weights below min_dN_pre_screening to start with. + This pre-screening step helps to minimize the data that will processed + now on. The default is 1e-4. [* critical parameter] + threshold_dN_2b_trial_band_center : float, optional + Initial guess of the band centers based on the threshold wights. + The default is 0.05. [* critical parameter] + min_sum_dNs_for_a_band : float, optional + Cut off criteria for minimum weights that a band center should have. + The band centers with lower weights than min_sum_dNs_for_a_band will be + discarded during SCF refinements. If min_sum_dNs_for_a_band + is smaller than threshold_dN_2b_trial_band_center, min_sum_dNs_for_a_band + will be reset to threshold_dN_2b_trial_band_center value. + The default is 0.05. [* critical parameter] + precision_pos_band_centers : float, optional + Precision when compared band centers from previous and current SCF + iteration. SCF is considered converged if this precision is reached. + The default is 1e-5. [not critical parameter] + err_tolerance_compare_kpts_val : float, optional + The tolerance to group the bands set per unique kpoints. This + determines if two flotting point numbers are the same or not. This is not + a critical parameter for band center determination algorithm. + The default is 1e-8. [not critical parameter] collect_scf_data : bool, optional Whether to save the dtails of band centers in each SCF cycles. The default is False. save_data : dictionary, optional - save2file :: Save unfolded kpoints or not? + save2file :: Save data to file or not? fir :: str or path Directory path where to save the file. fname :: str @@ -455,26 +532,319 @@ def band_centers_broadening_bandstr(self, unfolded_bandstructure, list of array Each array contains the final details of band centers in a particular kpoint. The list contains band center details for each kpoints. - Format: kpoint coordinate, Band center, Band width, Sum of dN. + Format: [kpoint coordinate, Band center, Band width, Sum of dN] dictionary of dictionary of array or None Each array contains the final details of band centers in a particular kpoint. The dictionary then contains the details for each SCF cycles with keys are the SCF cycle number. The highest level dictionary then contains details for each kpoints with keys are the kpoint indices. Returns None if collect_scf_data is false. + Format: {kpoint_index: {SCF_cycle_index: [Band center, Band width, Sum of dN]}} + + """ + _BandCentersBroadening.__init__(self, unfolded_bandstructure=unfolded_bandstructure, + min_dN_pre_screening=min_dN_pre_screening, + threshold_dN_2b_trial_band_center=threshold_dN_2b_trial_band_center, + min_sum_dNs_for_a_band=min_sum_dNs_for_a_band, + precision_pos_band_centers=precision_pos_band_centers, + err_tolerance_compare_kpts_val=err_tolerance_compare_kpts_val, + print_log=self.print_log_info) + return self._scfs_band_centers_broadening(collect_data_scf=collect_scf_data, + save_data=save_data) + + def calculate_effecfive_mass(self, kpath, band_energy, + initial_guess_params=None, + params_bounds = (-np.inf, np.inf), + fit_weights=None, absolute_weights:bool=False, + parabolic_dispersion:bool=False, + hyperbolic_dispersion_positive:bool=False, + hyperbolic_dispersion_negative:bool=False, + params_name = ['alpha', 'kshift', 'cbm', 'gamma']): + """ + Calculates effective mass using (hyper) parabolic band dispersion. + + Parameters + ---------- + kpath : numpy array + k on path (A^-1) of unfolded effective band structure/band centers that will + be fitted for calculating effective mass. + band_energy : numpy array + Energy (in eV) of unfolded effective band structure/band centers that will + be fitted for calculating effective mass. + initial_guess_params : array_like, optional + Initial guess for the parameters (length N). If None, then the + initial values will all be 1 (if the number of parameters for the + function can be determined using introspection, otherwise a + ValueError is raised). + params_bounds : 2-tuple of array_like or `Bounds`, optional + Lower and upper bounds on parameters. Defaults to no bounds. + There are two ways to specify the bounds: + - Instance of `Bounds` class. + - 2-tuple of array_like: Each element of the tuple must be either + an array with the length equal to the number of parameters, or a + scalar (in which case the bound is taken to be the same for all + parameters). Use ``np.inf`` with an appropriate sign to disable + bounds on all or some parameters. + fit_weights : None or scalar or M-length sequence or MxM array, optional + Determines the uncertainty in ydata. If we define residuals as + r = ydata - f(xdata, *popt), then the interpretation of fit_weights depends on + its number of dimensions: + A scalar or 1-D fit_weights should contain values of standard deviations of + errors in ydata. In this case, the optimized function is + chisq = sum((r / fit_weights) ** 2). + A 2-D fit_weights should contain the covariance matrix of errors in ydata. + In this case, the optimized function is + chisq = r.T @ inv(fit_weights) @ r. + The default is None. This is equivalent of 1-D fit_weights filled with ones. + absolute_weights : bool, optional + If True, fit_weights is used in an absolute sense and the estimated parameter + covariance pcov reflects these absolute values. + If False, only the relative magnitudes of the fit_weights values matter. + The default is False. + parabolic_dispersion : bool, optional + Fit parabolic Kane model of band dispersion. The default is False. + Order: parabolic_dispersion > hyperbolic_dispersion_positive > hyperbolic_dispersion_negative + hyperbolic_dispersion_positive : bool, optional + Fit hyperbolic model (upward hyperbola) of band dispersion. The default is False. + hyperbolic_dispersion_negative : bool, optional + Fit hyperbolic model (downward hyperbola) of band dispersion. The default is False. + params_name : list of str, optional + The name of the parameters. These will be used just to creat text. + The defult is ['alpha', 'kshift', 'cbm', 'gamma']. + For parabolic dispersion only first three will be used. + + Returns + ------- + m_star : float + Calculated effective mass in m_0 unit. + popt : array + Optimal values for the parameters so that the sum of the squared + residuals of ``f(xdata, *popt) - ydata`` is minimized. + pcov : 2-D array + The estimated approximate covariance of popt. + + Raises + ------ + ValueError + if none of *_dispersion_* option is supplied. + ValueError + if either `ydata` or `xdata` contain NaNs, or if incompatible options + are used. + RuntimeError + if the least-squares minimization fails. + OptimizeWarning + if covariance of the parameters can not be estimated. + + """ + if (parabolic_dispersion or hyperbolic_dispersion_positive or + hyperbolic_dispersion_negative): + pass + else: + raise ValueError('No dispersion option is supplied for fitting.') + + _EffectiveMass.__init__(self, print_log=self.print_log_info) + text_params_ = ','.join(params_name) + + ## parameters: ['alpha', 'kshift', 'cbm', 'gamma'] + if initial_guess_params is None: + middle_pos = len(band_energy)//2 + guess_alpha = (band_energy[middle_pos]-band_energy[0])/(kpath[middle_pos]-kpath[0])**2 + initial_guess_params = np.array([guess_alpha, kpath[0], 0, 0]) + + if len(np.shape(params_bounds)) == 1: + # Extra grace to add to define the upper bound of the parameters. + # The values are choosen here worked well for some of the test cases. + extra_upper_bound = [100, 3*abs(kpath[1]-kpath[0]), 1e-4, 10] + params_bounds = ([0, initial_guess_params[1]-1e-2, 0, 0], + [gg+extra_upper_bound[iii] for iii, gg in enumerate(initial_guess_params)]) + + if parabolic_dispersion: + text_params_ = ','.join(params_name[:3]) + initial_guess_params = initial_guess_params[:3] + params_bounds = tuple(xx[:3] for xx in params_bounds) + + if self.print_log_info is not None: + print('-- Effective mass calculator:') + if parabolic_dispersion: + print('--- Parabolic band dispersion') + elif hyperbolic_dispersion_positive: + print('--- Hyperbolic band dispersion (upward curvature)') + else: + print('--- Hyperbolic band dispersion (downward curvature)') + + if self.print_log_info == 'high': + print(f'--- Initial guesses for the parameters: {initial_guess_params}') + print(f'--- Upper and lower bounds for the parameters: {params_bounds}') + + m_star, popt, pcov = self._effective_mass_calculator(kpath, band_energy, + p0=initial_guess_params, bounds=params_bounds, + sigma=fit_weights, absolute_sigma=absolute_weights, + fit_parabola=parabolic_dispersion, + fit_hyperbola_positive=hyperbolic_dispersion_positive, + fit_hyperbola_negative=hyperbolic_dispersion_negative) + if self.print_log_info is not None: + if self.print_log_info in ['medium', 'high']: + print(f'--- Optimized parameters {text_params_}: {popt}') + print(f'--- One standard deviation errors on the parameters: {np.sqrt(np.diag(pcov))}') + print(f'--- Effective mass = {m_star:.4f} m_0') + return m_star, popt, pcov + + def fit_functions(self, kpath, optimized_parameters, + parabolic_dispersion:bool=False, + hyperbolic_dispersion_positive:bool=False, + hyperbolic_dispersion_negative:bool=False): + """ + Fit band dispersion functions using the optimized parameters. + + Parameters + ---------- + kpath : numpy array + k on path (A^-1) of unfolded effective band structure/band centers that will + be fitted for calculating effective mass. + popt : array + Optimized values for the parameters. + parabolic_dispersion : bool, optional + Fit parabolic Kane model of band dispersion. The default is False. + Order: parabolic_dispersion > hyperbolic_dispersion_positive > hyperbolic_dispersion_negative + hyperbolic_dispersion_positive : bool, optional + Fit hyperbolic model (upward hyperbola) of band dispersion. The default is False. + hyperbolic_dispersion_negative : bool, optional + Fit hyperbolic model (downward hyperbola) of band dispersion. The default is False. + + Returns + ------- + array + Band energies for the k-path and optimized parameters. + + Raises + ------ + ValueError + if none of *_dispersion_* option is supplied. + + """ + if self.print_log_info is not None: + print('-- Return band dispersion type in fit functions:') + if parabolic_dispersion: + print('--- Parabolic band dispersion') + elif hyperbolic_dispersion_positive: + print('--- Hyperbolic band dispersion (upward curvature)') + else: + print('--- Hyperbolic band dispersion (downward curvature)') + + if parabolic_dispersion: + return _EffectiveMass._fit_parabola(kpath, *optimized_parameters) + elif hyperbolic_dispersion_positive: + return _EffectiveMass._fit_hyperbola_positive(kpath, *optimized_parameters) + elif hyperbolic_dispersion_negative: + return _EffectiveMass._fit_hyperbola_negative(kpath, *optimized_parameters) + else: + raise ValueError('No dispersion option is supplied for fitting.') + +class SaveBandStructuredata: + """ + Save band structure data class. + """ + + @classmethod + def save_unfolded_pc_kpts(cls, unfolded_kpts_dat, save_dir='.', file_name='kpoints_unfolded', + file_name_suffix='', print_information='low'): + """ + Save unfolded PC-kpoints. + + Parameters + ---------- + unfolded_kpts_dat : numpy array + Unfolded kpoints in k-path. + Format: [k-index, k on path (A^-1), k1, k2, k3] + save_dir : str or path, optional + Directory path where to save the file. The default is current directory. + file_name : str, optional + Name of the file. The defult is 'kpoints_unfolded'. + file_name_suffix : str, optional + Suffix to add to the file name. The default is ''. + print_information : [None,'low','medium','high'], optional + Level of printing information. + The default is 'low'. If None, nothing is printed. + + Returns + ------- + None. """ - BandCentersBroadening.__init__(self, unfolded_bandstructure=unfolded_bandstructure, - min_dN_pre_screening=min_dN_pre_screening, - threshold_dN_2b_trial_band_center=threshold_dN_2b_trial_band_center, - min_sum_dNs_for_a_band=min_sum_dNs_for_a_band, - precision_pos_band_centers=precision_pos_band_centers, - err_tolerance_compare_kpts=err_tolerance_compare_kpts, - print_log=self.print_log_info) - return self.scfs_band_centers_broadening(collect_data_scf=collect_scf_data, - save_data=save_data) - -class Plotting(EBSplot): + _GeneralFnsDefs._save_Post_unfolded_PBZ_kpts(unfolded_kpts_dat, save_dir, file_name, + file_name_suffix, + print_information=print_information) + return + + @classmethod + def save_unfolded_bandstucture(cls, unfolded_bandstructure, save_dir='.', file_name='bandstructure_unfolded', + file_name_suffix='', print_information='low', is_spinor:bool=False): + """ + Save unfolded effective band structure data. + + Parameters + ---------- + unfolded_bandstructure : numpy ndarray + Unfolded effective band structure. + Format: [k index, k on path (A^-1), energy, weight, "Sx, Sy, Sz" if spinor] + save_dir : str or path, optional + Directory path where to save the file. The default is current directory. + file_name : str, optional + Name of the file. The defult is 'bandstructure_unfolded'. + file_name_suffix : str, optional + Suffix to add to the file name. The default is ''. + is_spinor : bool, optional + If the bands in wave function files are non-degenerate (spinor). + The default is False. + print_information : [None,'low','medium','high'], optional + Level of printing information. + The default is 'low'. If None, nothing is printed. + + Returns + ------- + None. + + """ + _GeneralFnsDefs._save_Post_unfolded_bandstucture(unfolded_bandstructure, save_dir, + file_name, file_name_suffix, + print_information=print_information, + is_spinor=is_spinor) + return + + @classmethod + def save_unfolded_bandcenter(cls, unfolded_bandcenter, save_dir='.', file_name='unfolded_bandcenters', + file_name_suffix='', print_information='low'): + """ + Save band centers data. + + Parameters + ---------- + unfolded_bandceneter : numpy ndarray + Band cenetrs data. + Format: [kpoint coordinate, Band center, Band width, Sum of dN] + save_dir : str or path, optional + Directory path where to save the file. The default is current directory. + file_name : str, optional + Name of the file. The defult is 'bandstructure_unfolded'. + file_name_suffix : str, optional + Suffix to add to the file name. The default is ''. + print_information : [None,'low','medium','high'], optional + Level of printing information. + The default is 'low'. If None, nothing is printed. + + Returns + ------- + None. + + """ + save_data = {'save2file': False, 'fdir': save_dir, 'fname': file_name, 'fname_suffix': file_name_suffix} + _GeneralFunctionsDefs._save_band_centers(data2save=unfolded_bandcenter, + print_log=print_information, + save_data_f_prop=save_data) + return + + +class Plotting(_EBSplot): def __init__(self, save_figure_dir='.'): """ @@ -489,24 +859,28 @@ def __init__(self, save_figure_dir='.'): self.save_figure_directory = save_figure_dir def plot_ebs(self, kpath_in_angs, unfolded_bandstructure, - ax=None, save_file_name=None, CountFig=None, + fig=None, ax=None, save_file_name=None, CountFig=None, Ef=None, Emin=None, Emax=None, pad_energy_scale:float=0.5, threshold_weight:float=None, mode:str="fatband", yaxis_label:str='E (eV)', special_kpoints:dict=None, plotSC:bool=True, marker='o', fatfactor=20, nE:int=100, smear:float=0.05, color='gray', color_map='viridis', show_legend:bool=True, - plot_colormap_bandcenter:bool=True): + plot_colormap_bandcenter:bool=True, show_colorbar:bool=False, + colorbar_label:str=None, vmin=None, vmax=None, + show_plot:bool=True,**kwargs_savefig): """ Scatter/density/band_centers plot of the band structure. Parameters ---------- - kpath_in_angs : array, optional - k on path (in A^-1) coordinate. The default is None. - unfolded_bandstructure : ndarray, optional - Unfolded effective band structure data. - Format: k on path (A^-1), energy, weight, "Sx, Sy, Sz" if is_spinor. - The default is None. + kpath_in_angs : array + k on path (in A^-1) coordinate. + unfolded_bandstructure : ndarray + Unfolded effective band structure/band center data. + Format: [k index, k on path (A^-1), energy, weight, "Sx, Sy, Sz" if spinor] or + Format: [kpoint coordinate, Band center, Band width, Sum of dN] for band centers + fig : matplotlib.pyplot figure instance, optional + Figure instance to plot on. The default is None. ax : matplotlib.pyplot axis, optional Figure axis to plot on. If None, new figure will be created. The default is None. @@ -556,30 +930,152 @@ def plot_ebs(self, kpath_in_angs, unfolded_bandstructure, If show legend or not. The default is True. plot_colormap_bandcenter : bool, optional If plotting the band ceneters by colormap. The default is True. + show_colorbar : bool, optional + Plot the colorbar in the figure or not. If fig=None, this is ignored. + The default is False. + colorbar_label : str, optional + Colorbar label. The default is None. If None, ignored. + vmin, vmax : float, optional + vmin and vmax define the data range that the colormap covers. + By default, the colormap covers the complete value range of the supplied data. + show_plot : bool, optional + To show the plot when not saved. The default is True. + **kwargs_savefig : dict + The matplotlib keywords for savefig function. Returns ------- fig : matplotlib.pyplot.figure - Figure instance. If ax is not None previously generated fig instance - will be used. + Figure instance. If ax is not None previously generated/passed fig instance + will be returned. Return None, if no fig instance is inputed along with ax. ax : Axis instance Figure axis instance. CountFig: int or None Figure count. """ - - EBSplot.__init__(self, kpath_in_angs=kpath_in_angs, + print('- Plotting band structures...') + _EBSplot.__init__(self, kpath_in_angs=kpath_in_angs, unfolded_bandstructure=unfolded_bandstructure, save_figure_dir=self.save_figure_directory) - return self.plot(ax=ax, save_file_name=save_file_name, CountFig=CountFig, Ef=Ef, - Emin=Emin, Emax=Emax, pad_energy_scale=pad_energy_scale, - threshold_weight=threshold_weight, mode=mode, - yaxis_label=yaxis_label, special_kpoints=special_kpoints, - plotSC=plotSC, marker=marker, fatfactor=fatfactor, nE=nE, - smear=smear, color=color, color_map=color_map, - plot_colormap_bandcenter=plot_colormap_bandcenter, - show_legend=show_legend) + return self._plot(fig=fig, ax=ax, save_file_name=save_file_name, CountFig=CountFig, Ef=Ef, + Emin=Emin, Emax=Emax, pad_energy_scale=pad_energy_scale, + threshold_weight=threshold_weight, mode=mode, + yaxis_label=yaxis_label, special_kpoints=special_kpoints, + plotSC=plotSC, marker=marker, fatfactor=fatfactor, nE=nE, + smear=smear, color=color, color_map=color_map, + plot_colormap_bandcenter=plot_colormap_bandcenter, + show_legend=show_legend, show_colorbar=show_colorbar, + colorbar_label=colorbar_label, vmin=vmin, vmax=vmax, + show_plot=show_plot, **kwargs_savefig) + + def plot_scf(self, kpath_in_angs, unfolded_bandstructure, al_scf_data, + plot_max_scf_steps:int=None, save_file_name=None, + Ef=None, Emin=None, Emax=None, + pad_energy_scale:float=0.5, threshold_weight:float=None, + yaxis_label:str='E (eV)', special_kpoints:dict=None, + plot_sc_unfold:bool=True, marker='o', fatfactor=20, + smear:float=0.05, color='gray', color_map='viridis', + show_legend:bool=True, plot_colormap_bandcenter:bool=True, + show_colorbar:bool=True, colorbar_label:str=None, + vmin=None, vmax=None, show_plot:bool=True, **kwargs_savefig): + """ + Band centers all scf steps plot. + + Parameters + ---------- + kpath_in_angs : array + k on path (in A^-1) coordinate. + unfolded_bandstructure : ndarray + Unfolded effective band structure data. + Format: [k on path (A^-1), energy, weight, "Sx, Sy, Sz" if spinor] + al_scf_data : dictionary + All SCF data. + Each array contains the final details of band centers in a particular + kpoint. The dictionary then contains the details for each SCF cycles with + keys are the SCF cycle number. The highest level dictionary then contains + details for each kpoints with keys are the kpoint indices. Returns None + if collect_data_scf is false. + Format: {kpoint_index: {SCF_cycle_index: [Band center, Band width, Sum of dN]}} + plot_max_scf_steps : int, optional + How many maximum scf cycle to plot? + The default is maximum SCF steps found in the dictionary of all k-points. + If scf cycle not found for a particular kpoint previous SCF cycle will be plotted. + save_file_name : str, optional + Name of the figure file. If None, figure will be not saved. + The default is None. + Ef : float, optional + Fermi energy. If None, set to 0.0. The default is None. + Emin : float, optional + Minimum in energy. The default is None. + Emax : float, optional + Maximum in energy. The default is None. + pad_energy_scale: float, optional + Add padding of pad_energy_scale to minimum and maximum energy if Emin + and Emax are None. The default is 0.5. + threshold_weight : float, optional + The band centers with band weights lower than the threshhold weights + are discarded. The default is None. If None, this is ignored. + yaxis_label : str, optional + Y-axis label text. The default is 'E (eV)'. + special_kpoints : dictionary, optional + Dictionary of special kpoints position and labels. If None, ignore + special kpoints. The default is None. + plot_sc_unfold : bool, optional + Plot supercell unfolded bandstructure. The default is True. + marker : matplotlib.pyplot markerMarkerStyle, optional + The marker style. Marker can be either an instance of the class or + the text shorthand for a particular marker. + The default is 'o'. + fatfactor : int, optional + Scatter plot marker size. The default is 20. + smear : float, optional + Gaussian smearing. The default is 0.05. + color : str/color, optional + Color for band centers plot when color_map is not used. + The default is 'gray'. The color of supercell + band structures is gray always. + color_map: str/ matplotlib colormap + Colormap for band centers plot. The default is viridis. + plot_colormap_bandcenter : bool, optional + If plotting the band ceneters by colormap. The default is True. + show_legend : bool, optional + If show legend or not. The default is True. + show_colorbar : bool, optional + Plot the colorbar in the figure or not. If fig=None, this is ignored. + The default is True. + colorbar_label : str, optional + Colorbar label. The default is None. If None, ignored. + vmin, vmax : float, optional + vmin and vmax define the data range that the colormap covers. + By default, the colormap covers the complete value range of the supplied data. + show_plot : bool, optional + To show the plot when not saved. The default is True. + **kwargs_savefig : dict + The matplotlib keywords for savefig function. + + Raises + ------ + ValueError + If plot mode is unknown. + + """ + print('- Plotting band centers in band structures...') + _EBSplot.__init__(self, kpath_in_angs=kpath_in_angs, + unfolded_bandstructure=unfolded_bandstructure, + save_figure_dir=self.save_figure_directory) + + return self._plot_scf(al_scf_data, plot_max_scf_steps=plot_max_scf_steps, + save_file_name=save_file_name, Ef=Ef, Emin=Emin, + Emax=Emax, pad_energy_scale=pad_energy_scale, + threshold_weight=threshold_weight, + yaxis_label=yaxis_label, special_kpoints=special_kpoints, + plot_sc_unfold=plot_sc_unfold, marker=marker, + fatfactor=fatfactor, smear=smear, color=color, + color_map=color_map, plot_colormap_bandcenter=plot_colormap_bandcenter, + show_legend=show_legend, show_colorbar=show_colorbar, + colorbar_label=colorbar_label, vmin=vmin, vmax=vmax, + show_plot=show_plot, **kwargs_savefig) diff --git a/tutorials/BandCenters_broadening.py b/tutorials/BandCenters_broadening.py index f4a9345..2880d08 100644 --- a/tutorials/BandCenters_broadening.py +++ b/tutorials/BandCenters_broadening.py @@ -4,7 +4,7 @@ import pickle import banduppy -print(f'- Bandup version: {banduppy.__version__}') +print(f'- BandUPpy version: {banduppy.__version__}') #%% ----------------------------- Set job ------------------------------------- SimulationParentFolder = '/local/MyGitHub/TestInstall/Test/OverLayBandStructures/' @@ -22,24 +22,40 @@ special_kpoints_pos_labels = pickle.load(handle) print ("- Reading band structure file - done") -#%% -min_sum_dNs_for_a_band = 0.05 # 1e-1 is OK -# I used to set threshold_dN_2b_trial_band_center = 1e-1 or 2e-1 (work for most of the cases), but this is a complicated parameter... +#%% ------------------- Determine band centers and band widths ---------------- +#=================================== +# Discard the bands which has weights below min_dN to start with. +# This pre-screening step helps to minimize the data that will processed. +# This parameter just pre-screen/minimize amount of data that will be passed to +# band center determination SCF algorithm and independent of min_sum_dNs_for_a_band parameter. +min_dN = 1e-5 +# Initial guess of the band centers based on the threshold wights. threshold_dN_2b_trial_band_center = 0.05 -prec_pos_band_centers = 1e-5 # in eV +# Cut off criteria for minimum weights that a band center should have. +# The band centers with lower weights than min_sum_dNs_for_a_band will be +# discarded during SCF refinements. If min_sum_dNs_for_a_band +# is smaller than threshold_dN_2b_trial_band_center, min_sum_dNs_for_a_band +# will be reset to threshold_dN_2b_trial_band_center value. +min_sum_dNs_for_a_band = 0.05 +#=================================== +# The tolerance to group the bands set per unique kpoints value. This determines if two +# flotting point numbers are same or not. This is not a critical parameter for +# band center determination algorithm. err_tolerance = 1e-8 -min_dN = 1e-5 # 1e-4 should be OK - +# Precision when compared band centers from previous and current SCF +# iteration. SCF is considered converged if this precision is reached. +prec_pos_band_centers = 1e-5 # in eV +#=================================== unfolded_bandstructure_properties, all_scf_data = \ unfolded_band_properties.band_centers_broadening_bandstr(unfolded_bandstructure_, min_dN_pre_screening=min_dN, - threshold_dN_2b_trial_band_center=threshold_dN_2b_trial_band_center, + threshold_dN_2b_trial_band_center= + threshold_dN_2b_trial_band_center, min_sum_dNs_for_a_band=min_sum_dNs_for_a_band, precision_pos_band_centers=prec_pos_band_centers, - err_tolerance_compare_kpts=err_tolerance, - collect_scf_data=False, - save_data = {'save2file': True}) + err_tolerance_compare_kpts_val=err_tolerance, + collect_scf_data=False) #%% ============================== Plottings ================================== plot_unfold = banduppy.Plotting(save_figure_dir=SimulationParentFolder) @@ -48,10 +64,10 @@ fig, ax, CountFig \ = plot_unfold.plot_ebs(kpath_in_angs=kpline, unfolded_bandstructure=unfolded_bandstructure_, - save_file_name=None, CountFig=None, threshold_weight=0.1, + save_file_name=None, CountFig=None, threshold_weight=min_dN, Ef=Efermi, Emin=Emin, Emax=Emax, pad_energy_scale=0.5, mode="fatband", special_kpoints=special_kpoints_pos_labels, - plotSC=False, fatfactor=10, nE=100,smear=0.2, + plotSC=False, fatfactor=10, nE=100,smear=0.2, show_plot=False, color='k', color_map='viridis', show_legend=False) fig, ax, CountFig \ @@ -64,4 +80,4 @@ color='k', color_map='viridis', show_legend=False, plot_colormap_bandcenter=True) ax.set_title('black circles: Org. bandstructure, cross: band centers', size=18) -plt.savefig(f'{SimulationParentFolder}/band_center_width', bbox_inches='tight', dpi=300) \ No newline at end of file +plt.savefig(f'{SimulationParentFolder}/band_center_width', bbox_inches='tight', dpi=300) diff --git a/tutorials/CompareOldNewBandupPyVersion.py b/tutorials/CompareOldNewBandupPyVersion.py deleted file mode 100644 index 4da6217..0000000 --- a/tutorials/CompareOldNewBandupPyVersion.py +++ /dev/null @@ -1,96 +0,0 @@ -# ---------------------------- Import modules --------------------------------- -import banduppy as bp -# Note: round() function is used in unfolding_path whenever '%' operation is called -import banduppy_old.unfolding_path as bp_org -#%% ------------------------ Define variables --------------------------------- -# supercell : 4X4X2 supercell == np.diag([4,4,2]) or -super_cell_size = [[-1, 1, 1], [1, -1, 1], [1, 1, -1]] -# k-path: L-G-X-U,K-G. If the segmant is skipped, put a None between nodes. -PC_BZ_path = [[1/2,1/2,1/2], [0,0,0],[1/2,0,1/2], [5/8,1/4,5/8], None, [3/8,3/8,3/4], [0,0,0]] -# Number of k-points in each path segments. or, one single number if they are same. -npoints_per_path_seg = (23,27,9,29) -# Labels of special k-points: list or string. e.g ['L','G','X','U','K','G'] or 'LGXUKG' -special_k_points = "LGXUKG" -# Weights of the k-points to be appended in the final generated k-points files -kpts_weights = 1 -# Save the SC kpoints in a file -save_to_file = False -# Directory to save file -save_to_dir = '' -# File format of kpoints file that will be created and saved -kpts_file_format = 'vasp' # This will generate vasp KPOINTS file format - -#%% =========================================================================== -unfold_path=bp_org.UnfoldingPath(supercell= super_cell_size, - pathPBZ=PC_BZ_path, - nk=npoints_per_path_seg, - labels=special_k_points ) - -#%%% -print(unfold_path.kpointsPBZ_index_in_unique) -#%%% -print(unfold_path.kpointsPBZ_unique_index_SBZ) -#%%% -print(unfold_path.kpointsSBZ) - -#%% =========================================================================== -band_unfold = bp.Unfolding(supercell=super_cell_size, print_log='high') - -#%% ------------ Creating SC folded kpoints from PC band path ----------------- -kpointsPBZ_full, kpointsPBZ_unique, kpointsSBZ, \ -SBZ_PBZ_kpts_mapping, special_kpoints_pos_labels \ -= band_unfold.generate_SC_Kpts_from_pc_k_path(pathPBZ = PC_BZ_path, - nk = npoints_per_path_seg, - labels = special_k_points, - kpts_weights = kpts_weights, - save_all_kpts = save_to_file, - save_sc_kpts = save_to_file, - save_dir = save_to_dir, - file_name_suffix = '', - file_format=kpts_file_format) -#%%% -print(band_unfold.kpointsPBZ_index_in_unique) -#%%% -print(band_unfold.kpointsSBZ_index_in_unique) -#%%% -print(band_unfold.SBZ_kpts_list) - -#%% ============ Read wave function file ====================================== -read_dir = '' -bands = bp.BandStructure(code="vasp", spinor=False, - fPOS = f"{read_dir}/POSCAR", - fWAV = f"{read_dir}/WAVECAR") - -#%% ====================== Unfold band structure ============================== -lll = unfold_path.unfold(bands, break_thresh=0.1,suffix="path") - -#%%% -unfolded_bandstructure_, kpline = \ -band_unfold.Unfold(bands, kline_discontinuity_threshold = 0.1, - save_unfolded_kpts = {'save2file': True, - 'fdir': '.', - 'fname': 'kpoints_unfolded', - 'fname_suffix': ''}, - save_unfolded_bandstr = {'save2file': True, - 'fdir': '.', - 'fname': 'bandstructure_unfolded', - 'fname_suffix': ''}) - -#%% ================ Plot band structure ====================================== -#%%% -Efermi = 5.9740 -Emin = -5 -Emax = 5 - -# now plot the result as fat band -unfold_path.plot(save_file=None,plotSC=True,Emin=Emin,Emax=Emax,Ef=Efermi,fatfactor=50,mode='fatband') -# or as a colormap -unfold_path.plot(save_file=None,plotSC=True,Emin=Emin,Emax=Emax,Ef=Efermi,mode='density',smear=0.2,nE=200) -#%%% -fig, ax, CountFig \ -= band_unfold.plot_ebs(save_figure_dir='.', save_file_name=None, CountFig=None, - Ef=Efermi, Emin=Emin, Emax=Emax, pad_energy_scale=0.5, - mode="density", special_kpoints=special_kpoints_pos_labels, - plotSC=True, fatfactor=50, nE=100,smear=0.2, - scatter_color='red', color_map='viridis') - diff --git a/tutorials/GeneralBandUPpyTutorial.py b/tutorials/GeneralBandUPpyTutorial.py index 616d0cf..293d428 100644 --- a/tutorials/GeneralBandUPpyTutorial.py +++ b/tutorials/GeneralBandUPpyTutorial.py @@ -3,7 +3,7 @@ import pickle import banduppy -print(f'- Bandup version: {banduppy.__version__}') +print(f'- BandUPpy version: {banduppy.__version__}') #%% ------------------------ Define variables --------------------------------- # supercell : 4X4X2 supercell == np.diag([4,4,2]) or @@ -89,20 +89,37 @@ # PRB 89, 041407(R) (2014) paper. # -------------------- Initiate Properties method ----------------------------- unfolded_band_properties = banduppy.Properties(print_log='high') -min_sum_dNs_for_a_band = 0.05 +#=================================== +# Discard the bands which has weights below min_dN to start with. +# This pre-screening step helps to minimize the data that will processed. +# This parameter just pre-screen/minimize amount of data that will be passed to +# band center determination SCF algorithm and independent of min_sum_dNs_for_a_band parameter. +min_dN = 1e-5 +# Initial guess of the band centers based on the threshold wights. threshold_dN_2b_trial_band_center = 0.05 -prec_pos_band_centers = 1e-5 # in eV +# Cut off criteria for minimum weights that a band center should have. +# The band centers with lower weights than min_sum_dNs_for_a_band will be +# discarded during SCF refinements. If min_sum_dNs_for_a_band +# is smaller than threshold_dN_2b_trial_band_center, min_sum_dNs_for_a_band +# will be reset to threshold_dN_2b_trial_band_center value. +min_sum_dNs_for_a_band = 0.05 +#=================================== +# The tolerance to group the bands set per unique kpoints value. This determines if two +# flotting point numbers are same or not. This is not a critical parameter for +# band center determination algorithm. err_tolerance = 1e-8 -min_dN = 1e-5 +# Precision when compared band centers from previous and current SCF +# iteration. SCF is considered converged if this precision is reached. +prec_pos_band_centers = 1e-5 # in eV +#=================================== unfolded_bandstructure_properties, all_scf_data = \ unfolded_band_properties.band_centers_broadening_bandstr(unfolded_bandstructure_, min_dN_pre_screening=min_dN, - threshold_dN_2b_trial_band_center= - threshold_dN_2b_trial_band_center, + threshold_dN_2b_trial_band_center=threshold_dN_2b_trial_band_center, min_sum_dNs_for_a_band=min_sum_dNs_for_a_band, precision_pos_band_centers=prec_pos_band_centers, - err_tolerance_compare_kpts=err_tolerance, + err_tolerance_compare_kpts_val=err_tolerance, collect_scf_data=False) #%% --------------------- Plot band structure --------------------------------- @@ -148,7 +165,7 @@ fig, ax, CountFig \ = plot_unfold.plot_ebs(kpath_in_angs=kpline, unfolded_bandstructure=unfolded_bandstructure_properties, - save_file_name=save_file_name, CountFig=None, + save_file_name=save_file_name, CountFig=None, threshold_weight=min_dN, Ef=Efermi, Emin=Emin, Emax=Emax, pad_energy_scale=0.5, mode="band_centers", special_kpoints=special_kpoints_pos_labels, marker='x', smear=0.2, plot_colormap_bandcenter=True, diff --git a/tutorials/OverLayBandStructures/Ge_supercell/bandstructure_unfolded.dat b/tutorials/OverLayBandStructures/Ge_supercell/bandstructure_unfolded.dat index ed51349..70b10e0 100644 --- a/tutorials/OverLayBandStructures/Ge_supercell/bandstructure_unfolded.dat +++ b/tutorials/OverLayBandStructures/Ge_supercell/bandstructure_unfolded.dat @@ -871,3554 +871,3554 @@ 23.00000000 1.00209910 31.91764288 1.99899244 23.00000000 1.00209910 32.37274499 0.99998724 23.00000000 1.00209910 32.37492990 0.99995065 - 24.00000000 1.03356873 -8.87945477 0.99999624 - 24.00000000 1.03356873 -4.82147726 0.00000036 - 24.00000000 1.03356873 -4.50506860 0.00000579 - 24.00000000 1.03356873 -4.18353576 0.00000035 - 24.00000000 1.03356873 1.33371699 0.00003279 - 24.00000000 1.03356873 1.36039860 0.00000401 - 24.00000000 1.03356873 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0.00000000 0.42307692 + 46.00000000 2.02570911 0.44230769 0.00000000 0.44230769 + 47.00000000 2.07021390 0.46153846 0.00000000 0.46153846 + 48.00000000 2.11471868 0.48076923 0.00000000 0.48076923 + 49.00000000 2.15922346 0.50000000 0.00000000 0.50000000 + 50.00000000 2.15922346 0.50000000 0.00000000 0.50000000 + 51.00000000 2.21036162 0.51562500 0.03125000 0.51562500 + 52.00000000 2.26149977 0.53125000 0.06250000 0.53125000 + 53.00000000 2.31263793 0.54687500 0.09375000 0.54687500 + 54.00000000 2.36377608 0.56250000 0.12500000 0.56250000 + 55.00000000 2.41491424 0.57812500 0.15625000 0.57812500 + 56.00000000 2.46605239 0.59375000 0.18750000 0.59375000 + 57.00000000 2.51719055 0.60937500 0.21875000 0.60937500 + 58.00000000 2.56832871 0.62500000 0.25000000 0.62500000 + 59.00000000 2.56832871 0.37500000 0.37500000 0.75000000 + 60.00000000 2.61216141 0.36160714 0.36160714 0.72321429 + 61.00000000 2.65599411 0.34821429 0.34821429 0.69642857 + 62.00000000 2.69982682 0.33482143 0.33482143 0.66964286 + 63.00000000 2.74365952 0.32142857 0.32142857 0.64285714 + 64.00000000 2.78749223 0.30803571 0.30803571 0.61607143 + 65.00000000 2.83132493 0.29464286 0.29464286 0.58928571 + 66.00000000 2.87515764 0.28125000 0.28125000 0.56250000 + 67.00000000 2.91899034 0.26785714 0.26785714 0.53571429 + 68.00000000 2.96282305 0.25446429 0.25446429 0.50892857 + 69.00000000 3.00665575 0.24107143 0.24107143 0.48214286 + 70.00000000 3.05048846 0.22767857 0.22767857 0.45535714 + 71.00000000 3.09432116 0.21428571 0.21428571 0.42857143 + 72.00000000 3.13815386 0.20089286 0.20089286 0.40178571 + 73.00000000 3.18198657 0.18750000 0.18750000 0.37500000 + 74.00000000 3.22581927 0.17410714 0.17410714 0.34821429 + 75.00000000 3.26965198 0.16071429 0.16071429 0.32142857 + 76.00000000 3.31348468 0.14732143 0.14732143 0.29464286 + 77.00000000 3.35731739 0.13392857 0.13392857 0.26785714 + 78.00000000 3.40115009 0.12053571 0.12053571 0.24107143 + 79.00000000 3.44498280 0.10714286 0.10714286 0.21428571 + 80.00000000 3.48881550 0.09375000 0.09375000 0.18750000 + 81.00000000 3.53264821 0.08035714 0.08035714 0.16071429 + 82.00000000 3.57648091 0.06696429 0.06696429 0.13392857 + 83.00000000 3.62031362 0.05357143 0.05357143 0.10714286 + 84.00000000 3.66414632 0.04017857 0.04017857 0.08035714 + 85.00000000 3.70797902 0.02678571 0.02678571 0.05357143 + 86.00000000 3.75181173 0.01339286 0.01339286 0.02678571 + 87.00000000 3.79564443 0.00000000 0.00000000 0.00000000 diff --git a/tutorials/SiGe_OverlayBandStructurePlot.py b/tutorials/SiGe_OverlayBandStructurePlot.py index 9b2b0eb..e903c3b 100644 --- a/tutorials/SiGe_OverlayBandStructurePlot.py +++ b/tutorials/SiGe_OverlayBandStructurePlot.py @@ -4,7 +4,7 @@ import pickle import banduppy -print(f'- Bandup version: {banduppy.__version__}') +print(f'- BandUPpy version: {banduppy.__version__}') print('Note: The lattice parameters for all three Si, Ge and Si-Ge supercells are kept same.') #%% ----------------------------- Set job ------------------------------------- @@ -50,7 +50,7 @@ save_file_name=None, CountFig=None, threshold_weight=0.1, Ef=5.5305, Emin=Emin, Emax=Emax, pad_energy_scale=0.5, mode="fatband", special_kpoints=special_kpoints_pos_labels1, - plotSC=False, fatfactor=20, nE=100,smear=0.2, + plotSC=False, fatfactor=20, nE=100,smear=0.2, show_plot=False, color='red', color_map='viridis', show_legend=False) _, ax, CountFig \ @@ -58,7 +58,7 @@ unfolded_bandstructure=unfolded_bandstructure_2, save_file_name=None, CountFig=None, threshold_weight=0.1, Ef=5.9786, Emin=Emin, Emax=Emax, pad_energy_scale=0.5, - mode="fatband", special_kpoints=None, + mode="fatband", special_kpoints=None, show_plot=False, plotSC=False, marker='x', fatfactor=10, nE=100,smear=0.2, color='black', color_map='viridis', show_legend=False) @@ -67,9 +67,9 @@ unfolded_bandstructure=unfolded_bandstructure_3, threshold_weight=0.1, save_file_name=None, CountFig=None, Ef=5.1434, Emin=Emin, Emax=Emax, pad_energy_scale=0.5, - mode="fatband", special_kpoints=None, + mode="fatband", special_kpoints=None, show_plot=False, plotSC=False, marker='x', fatfactor=10, nE=100,smear=0.2, color='blue', color_map='viridis', show_legend=False) ax.set_title('Si-Ge: Red, pure Si: black, pure Ge: blue', size=18) plt.savefig(f'{SimulationParentFolder}/{save_file_name}', bbox_inches='tight', dpi=300) -print ("- Plotting band structure - done") \ No newline at end of file +print ("- Plotting band structure - done") diff --git a/tutorials/Vasp/input/KPOINTS_PC b/tutorials/Vasp/input/KPOINTS_PC index 0023d2b..fafabeb 100644 --- a/tutorials/Vasp/input/KPOINTS_PC +++ b/tutorials/Vasp/input/KPOINTS_PC @@ -1,4 +1,4 @@ -k-points for PC bandstructure generated using banduppy-0.2.1 package +k-points for PC bandstructure generated using banduppy-0.3.2 package 88 reciprocal 0.50000000 0.50000000 0.50000000 diff --git a/tutorials/Vasp/input/KPOINTS_SC b/tutorials/Vasp/input/KPOINTS_SC index 52cbec7..b6d2020 100644 --- a/tutorials/Vasp/input/KPOINTS_SC +++ b/tutorials/Vasp/input/KPOINTS_SC @@ -1,4 +1,4 @@ -K-points for SC bandstructure generated using banduppy-0.2.1 package +K-points for SC bandstructure generated using banduppy-0.3.2 package 84 reciprocal 0.00000000 0.00000000 0.00000000 1.00000000 diff --git a/tutorials/Vasp/results/bandstructure_unfolded.dat b/tutorials/Vasp/results/bandstructure_unfolded.dat index c0146db..7a92254 100644 --- a/tutorials/Vasp/results/bandstructure_unfolded.dat +++ b/tutorials/Vasp/results/bandstructure_unfolded.dat @@ -1,4474 +1,4474 @@ # Unfolded band structure from postprocessed wavefunction file -# k on path (A^-1), energy, weight +# k-index, k on path (A^-1), energy, weight # - 0.00000000 -3.79781795 1.00001383 - 0.00000000 -1.13716480 1.00001097 - 0.00000000 4.63820663 2.00001311 - 0.00000000 7.38431032 1.00000858 - 0.00000000 9.19510790 2.00002766 - 0.00000000 13.56898894 1.00000894 - 0.00000000 16.49770714 1.99997199 - 0.00000000 17.21067211 0.99999201 - 0.00000000 17.21687302 2.00001431 - 0.00000000 18.86684430 1.00001049 - 0.00000000 25.35746832 1.00001848 - 0.00000000 25.86292235 1.00000703 - 0.00000000 27.59533688 2.00004292 - 0.00000000 27.81912841 1.99989283 - 0.00000000 31.66261544 0.14767548 - 0.00000000 31.66273050 0.41489005 - 0.00000000 31.66293578 0.00178047 - 0.00000000 31.66327468 0.43572733 - 0.00000000 32.41025977 0.25288609 - 0.00000000 32.41039165 0.34256154 - 0.00000000 32.41062847 0.32604349 - 0.04554996 -3.82723178 0.99999827 - 0.04554996 -3.79509928 0.00000045 - 0.04554996 -1.12922790 0.00000142 - 0.04554996 -1.09498571 1.00000191 - 0.04554996 4.58451320 0.00000691 - 0.04554996 4.62394411 0.00000335 - 0.04554996 4.64192764 1.99998736 - 0.04554996 7.38858160 0.99999964 - 0.04554996 7.43801669 0.00000567 - 0.04554996 9.18175344 0.00004904 - 0.04554996 9.19942082 1.99994695 - 0.04554996 9.22259517 0.00002067 - 0.04554996 13.57564163 0.99999493 - 0.04554996 13.59729729 0.00000484 - 0.04554996 16.19165409 0.00003324 - 0.04554996 16.26501357 1.99991059 - 0.04554996 16.49249940 0.00004395 - 0.04554996 17.09888740 0.99999332 - 0.04554996 17.21843084 0.00004579 - 0.04554996 17.23070897 0.00002058 - 0.04554996 17.46549719 1.99988866 - 0.04554996 17.47774096 0.00004624 - 0.04554996 18.93188434 0.00000332 - 0.04554996 18.97275251 1.00000095 - 0.04554996 24.86502639 0.99997580 - 0.04554996 25.25724241 0.00003691 - 0.04554996 25.94355503 0.00001928 - 0.04554996 26.37778682 0.99998879 - 0.04554996 27.10366362 1.99977279 - 0.04554996 27.31268382 0.00008722 - 0.04554996 27.58946982 0.00022640 - 0.04554996 27.81700867 0.00033228 - 0.04554996 28.06506584 0.00011130 - 0.04554996 28.28469569 1.99936843 - 0.04554996 31.48593817 0.99987870 - 0.04554996 31.66177007 0.00015109 - 0.04554996 31.66343225 0.00018073 - 0.04554996 32.28917241 0.00556204 - 0.04554996 32.29938944 0.01112818 - 0.04554996 32.30262510 0.00662509 - 0.04554996 32.35036416 0.36967430 - 0.09109992 -3.91063117 0.99999917 - 0.09109992 -3.78705064 0.00000061 - 0.09109992 -1.10569188 0.00000120 - 0.09109992 -0.97380734 0.99999899 - 0.09109992 4.43589932 0.00000458 - 0.09109992 4.58218735 0.00000579 - 0.09109992 4.65298102 1.99999261 - 0.09109992 7.40115804 1.00000072 - 0.09109992 7.58206750 0.00000507 - 0.09109992 9.14819238 0.00004122 - 0.09109992 9.21180763 1.99993229 - 0.09109992 9.30376274 0.00003830 - 0.09109992 13.59478282 0.99999344 - 0.09109992 13.67269731 0.00000730 - 0.09109992 15.67123080 0.00006100 - 0.09109992 15.86066750 1.99989390 - 0.09109992 16.47700447 0.00003570 - 0.09109992 16.82517423 0.99999356 - 0.09109992 17.23311005 0.00007576 - 0.09109992 17.27033373 0.00008858 - 0.09109992 17.83849431 0.00004514 - 0.09109992 17.90854615 1.99984682 - 0.09109992 19.14938342 0.00001218 - 0.09109992 19.22497358 0.99999750 - 0.09109992 24.21176512 0.99996650 - 0.09109992 25.05118436 0.00003241 - 0.09109992 26.08416409 0.00004142 - 0.09109992 26.50371698 1.99970138 - 0.09109992 26.92622533 0.00030299 - 0.09109992 27.09623100 0.99997175 - 0.09109992 27.56377078 0.00038207 - 0.09109992 27.82172635 0.00024761 - 0.09109992 28.31669538 0.00020418 - 0.09109992 28.79024336 1.99936795 - 0.09109992 31.04741158 0.99996918 - 0.09109992 31.66257881 0.00013566 - 0.09109992 31.66337452 0.00010689 - 0.09109992 31.66527456 0.00021414 - 0.09109992 32.00234265 0.00126924 - 0.09109992 32.00881421 0.00112575 - 0.09109992 32.01520378 0.00359897 - 0.09109992 32.09853019 0.00097034 - 0.13664988 -4.03451438 0.99999976 - 0.13664988 -3.77314211 0.00000095 - 0.13664988 -1.06719569 0.00000124 - 0.13664988 -0.78622508 1.00000453 - 0.13664988 4.22145352 0.00000334 - 0.13664988 4.51619250 0.00000858 - 0.13664988 4.67103380 1.99999118 - 0.13664988 7.42380888 0.99999475 - 0.13664988 7.77298203 0.00000441 - 0.13664988 9.11746025 0.00004409 - 0.13664988 9.23137313 1.99992192 - 0.13664988 9.43580415 0.00003366 - 0.13664988 13.62584321 0.99999613 - 0.13664988 13.75754425 0.00000969 - 0.13664988 15.17864765 0.00008224 - 0.13664988 15.43238033 1.99985766 - 0.13664988 16.45784792 0.00003379 - 0.13664988 16.47785132 0.99999106 - 0.13664988 17.26011384 0.00007130 - 0.13664988 17.33174471 0.00009728 - 0.13664988 18.09346810 0.00004763 - 0.13664988 18.39885740 1.99981141 - 0.13664988 19.52498575 0.99999905 - 0.13664988 19.54025684 0.00003564 - 0.13664988 23.61397424 0.99996054 - 0.13664988 24.82044477 0.00003581 - 0.13664988 25.89844371 1.99957204 - 0.13664988 26.19738319 0.00005680 - 0.13664988 26.53530151 0.00030116 - 0.13664988 27.49387671 0.00042740 - 0.13664988 27.85039146 0.99997240 - 0.13664988 27.87340861 0.00018216 - 0.13664988 28.44644424 0.00035162 - 0.13664988 29.23476169 1.99921274 - 0.13664988 30.49804157 0.99997127 - 0.13664988 31.61029587 0.00017442 - 0.13664988 31.61317410 0.00021037 - 0.13664988 31.72333806 0.00013436 - 0.13664988 31.72693790 0.00032950 - 0.13664988 31.94243606 0.00009375 - 0.18219984 -4.18511030 1.00000298 - 0.18219984 -3.75342221 0.00000053 - 0.18219984 -1.01507945 0.00000092 - 0.18219984 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28.38350588 0.00020841 - 0.18219984 28.58963833 0.99997622 - 0.18219984 29.59240838 1.99952567 - 0.18219984 29.91569961 0.99998569 - 0.18219984 31.23796184 0.00002362 - 0.18219984 31.23841128 0.00002979 - 0.18219984 31.23921387 0.00008640 - 0.18219984 31.77202465 0.00011364 - 0.18219984 31.78064784 0.00004633 - 0.18219984 31.81262648 0.00037131 - 0.18219984 31.94084654 0.00009899 - 0.22774979 -4.35087580 1.00000274 - 0.22774979 -3.72726226 0.00000107 - 0.22774979 -0.95116600 0.00000192 - 0.22774979 -0.26642738 0.99999976 - 0.22774979 3.69551195 0.00000756 - 0.22774979 4.32872661 0.00000461 - 0.22774979 4.73039341 1.99999189 - 0.22774979 7.49124142 0.99999881 - 0.22774979 8.04032829 0.00000716 - 0.22774979 9.25805471 0.00002816 - 0.22774979 9.28845054 1.99995494 - 0.22774979 9.83562550 0.00000869 - 0.22774979 13.45255218 0.00002605 - 0.22774979 13.70602273 0.99999213 - 0.22774979 14.65095253 1.99988830 - 0.22774979 14.78823997 0.00004512 - 0.22774979 15.72422678 1.00000429 - 0.22774979 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3.79564443 18.90827916 0.00002696 + 87.00000000 3.79564443 21.24007897 1.00000370 + 87.00000000 3.79564443 24.80979086 0.00052770 + 87.00000000 3.79564443 25.63437183 0.00007001 + 87.00000000 3.79564443 26.09222638 0.00009790 + 87.00000000 3.79564443 27.39968762 0.00004676 + 87.00000000 3.79564443 29.16185051 2.99941659 + 87.00000000 3.79564443 30.33418512 1.99820662 + 87.00000000 3.79564443 31.65643746 0.01634352 + 87.00000000 3.79564443 31.65775211 0.03304636 diff --git a/tutorials/Vasp/results/kpoints_unfolded.dat b/tutorials/Vasp/results/kpoints_unfolded.dat index e705a08..ae127ab 100644 --- a/tutorials/Vasp/results/kpoints_unfolded.dat +++ b/tutorials/Vasp/results/kpoints_unfolded.dat @@ -1,91 +1,91 @@ # Unfolded PC k-points from postprocessed wavefunction file -# k on path (A^-1), k1, k2, k3 +# k-index, k on path (A^-1), k1, k2, k3 # - 0.00000000 0.50000000 0.50000000 0.50000000 - 0.04554996 0.47727273 0.47727273 0.47727273 - 0.09109992 0.45454545 0.45454545 0.45454545 - 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0.47727273 0.47727273 + 2.00000000 0.09109992 0.45454545 0.45454545 0.45454545 + 3.00000000 0.13664988 0.43181818 0.43181818 0.43181818 + 4.00000000 0.18219984 0.40909091 0.40909091 0.40909091 + 5.00000000 0.22774979 0.38636364 0.38636364 0.38636364 + 6.00000000 0.27329975 0.36363636 0.36363636 0.36363636 + 7.00000000 0.31884971 0.34090909 0.34090909 0.34090909 + 8.00000000 0.36439967 0.31818182 0.31818182 0.31818182 + 9.00000000 0.40994963 0.29545455 0.29545455 0.29545455 + 10.00000000 0.45549959 0.27272727 0.27272727 0.27272727 + 11.00000000 0.50104955 0.25000000 0.25000000 0.25000000 + 12.00000000 0.54659951 0.22727273 0.22727273 0.22727273 + 13.00000000 0.59214947 0.20454545 0.20454545 0.20454545 + 14.00000000 0.63769942 0.18181818 0.18181818 0.18181818 + 15.00000000 0.68324938 0.15909091 0.15909091 0.15909091 + 16.00000000 0.72879934 0.13636364 0.13636364 0.13636364 + 17.00000000 0.77434930 0.11363636 0.11363636 0.11363636 + 18.00000000 0.81989926 0.09090909 0.09090909 0.09090909 + 19.00000000 0.86544922 0.06818182 0.06818182 0.06818182 + 20.00000000 0.91099918 0.04545455 0.04545455 0.04545455 + 21.00000000 0.95654914 0.02272727 0.02272727 0.02272727 + 22.00000000 1.00209910 0.00000000 0.00000000 0.00000000 + 23.00000000 1.00209910 0.00000000 0.00000000 0.00000000 + 24.00000000 1.04660388 0.01923077 0.00000000 0.01923077 + 25.00000000 1.09110866 0.03846154 0.00000000 0.03846154 + 26.00000000 1.13561345 0.05769231 0.00000000 0.05769231 + 27.00000000 1.18011823 0.07692308 0.00000000 0.07692308 + 28.00000000 1.22462301 0.09615385 0.00000000 0.09615385 + 29.00000000 1.26912780 0.11538462 0.00000000 0.11538462 + 30.00000000 1.31363258 0.13461538 0.00000000 0.13461538 + 31.00000000 1.35813736 0.15384615 0.00000000 0.15384615 + 32.00000000 1.40264215 0.17307692 0.00000000 0.17307692 + 33.00000000 1.44714693 0.19230769 0.00000000 0.19230769 + 34.00000000 1.49165171 0.21153846 0.00000000 0.21153846 + 35.00000000 1.53615650 0.23076923 0.00000000 0.23076923 + 36.00000000 1.58066128 0.25000000 0.00000000 0.25000000 + 37.00000000 1.62516606 0.26923077 0.00000000 0.26923077 + 38.00000000 1.66967085 0.28846154 0.00000000 0.28846154 + 39.00000000 1.71417563 0.30769231 0.00000000 0.30769231 + 40.00000000 1.75868041 0.32692308 0.00000000 0.32692308 + 41.00000000 1.80318520 0.34615385 0.00000000 0.34615385 + 42.00000000 1.84768998 0.36538462 0.00000000 0.36538462 + 43.00000000 1.89219476 0.38461538 0.00000000 0.38461538 + 44.00000000 1.93669955 0.40384615 0.00000000 0.40384615 + 45.00000000 1.98120433 0.42307692 0.00000000 0.42307692 + 46.00000000 2.02570911 0.44230769 0.00000000 0.44230769 + 47.00000000 2.07021390 0.46153846 0.00000000 0.46153846 + 48.00000000 2.11471868 0.48076923 0.00000000 0.48076923 + 49.00000000 2.15922346 0.50000000 0.00000000 0.50000000 + 50.00000000 2.15922346 0.50000000 0.00000000 0.50000000 + 51.00000000 2.21036162 0.51562500 0.03125000 0.51562500 + 52.00000000 2.26149977 0.53125000 0.06250000 0.53125000 + 53.00000000 2.31263793 0.54687500 0.09375000 0.54687500 + 54.00000000 2.36377608 0.56250000 0.12500000 0.56250000 + 55.00000000 2.41491424 0.57812500 0.15625000 0.57812500 + 56.00000000 2.46605239 0.59375000 0.18750000 0.59375000 + 57.00000000 2.51719055 0.60937500 0.21875000 0.60937500 + 58.00000000 2.56832871 0.62500000 0.25000000 0.62500000 + 59.00000000 2.56832871 0.37500000 0.37500000 0.75000000 + 60.00000000 2.61216141 0.36160714 0.36160714 0.72321429 + 61.00000000 2.65599411 0.34821429 0.34821429 0.69642857 + 62.00000000 2.69982682 0.33482143 0.33482143 0.66964286 + 63.00000000 2.74365952 0.32142857 0.32142857 0.64285714 + 64.00000000 2.78749223 0.30803571 0.30803571 0.61607143 + 65.00000000 2.83132493 0.29464286 0.29464286 0.58928571 + 66.00000000 2.87515764 0.28125000 0.28125000 0.56250000 + 67.00000000 2.91899034 0.26785714 0.26785714 0.53571429 + 68.00000000 2.96282305 0.25446429 0.25446429 0.50892857 + 69.00000000 3.00665575 0.24107143 0.24107143 0.48214286 + 70.00000000 3.05048846 0.22767857 0.22767857 0.45535714 + 71.00000000 3.09432116 0.21428571 0.21428571 0.42857143 + 72.00000000 3.13815386 0.20089286 0.20089286 0.40178571 + 73.00000000 3.18198657 0.18750000 0.18750000 0.37500000 + 74.00000000 3.22581927 0.17410714 0.17410714 0.34821429 + 75.00000000 3.26965198 0.16071429 0.16071429 0.32142857 + 76.00000000 3.31348468 0.14732143 0.14732143 0.29464286 + 77.00000000 3.35731739 0.13392857 0.13392857 0.26785714 + 78.00000000 3.40115009 0.12053571 0.12053571 0.24107143 + 79.00000000 3.44498280 0.10714286 0.10714286 0.21428571 + 80.00000000 3.48881550 0.09375000 0.09375000 0.18750000 + 81.00000000 3.53264821 0.08035714 0.08035714 0.16071429 + 82.00000000 3.57648091 0.06696429 0.06696429 0.13392857 + 83.00000000 3.62031362 0.05357143 0.05357143 0.10714286 + 84.00000000 3.66414632 0.04017857 0.04017857 0.08035714 + 85.00000000 3.70797902 0.02678571 0.02678571 0.05357143 + 86.00000000 3.75181173 0.01339286 0.01339286 0.02678571 + 87.00000000 3.79564443 0.00000000 0.00000000 0.00000000 diff --git a/tutorials/Vasp/results/results.out b/tutorials/Vasp/results/results.out index 086efea..f9b91a8 100644 --- a/tutorials/Vasp/results/results.out +++ b/tutorials/Vasp/results/results.out @@ -1,4 +1,4 @@ -- Bandup version: 0.2.1 +- Bandup version: 0.3.2 ======================================================================== - Generating SC Kpoints... ======================================================================== @@ -269,23 +269,23 @@ ---- 59: 0.37500000 0.37500000 0.75000000 ======================================================================== - Saving Kpoints to file.... --- Filepath: /local/MyGitHub/TestInstall/Test/RunVasp/input/KPOINTS_SC +-- Filepath: /local/MyGitHub/TestInstall/Test/Vasp/input/KPOINTS_SC - Done ======================================================================== -- Saving kpoints to file.... --- Filepath: /local/MyGitHub/TestInstall/Test/RunVasp/input/KPOINTS_PC +- Saving special kpoints position indices and labels to file.... +-- Filepath: /local/MyGitHub/TestInstall/Test/Vasp/input/KPOINTS_SpecialKpoints.pkl - Done ======================================================================== -- Saving SC Kpoints - PC kpoints indices mapping to file.... --- Filepath: /local/MyGitHub/TestInstall/Test/RunVasp/input/KPOINTS_SCPC_map.pkl +- Saving kpoints to file.... +-- Filepath: /local/MyGitHub/TestInstall/Test/Vasp/input/KPOINTS_PC - Done ======================================================================== -- Saving special kpoints position indices and labels to file.... --- Filepath: /local/MyGitHub/TestInstall/Test/RunVasp/input/KPOINTS_SpecialKpoints.pkl +- Saving SC Kpoints - PC kpoints indices mapping to file.... +-- Filepath: /local/MyGitHub/TestInstall/Test/Vasp/input/KPOINTS_SCPC_map.pkl - Done - Generating SC Kpoints - done ======================================================================== -- Reading bandstructure... +- Reading band structure... ----------INFORMATION ABOUT THE UNIT CELL----------- @@ -524,81 +524,80 @@ Energy cutoff reduced to : 245.345 -- 0.95654914 0.02272727 0.02272727 0.02272727 -- 1.00209910 0.00000000 0.00000000 0.00000000 -- 1.00209910 0.00000000 0.00000000 0.00000000 --- 1.03356873 0.01923077 0.00000000 0.01923077 --- 1.06503836 0.03846154 0.00000000 0.03846154 --- 1.09650800 0.05769231 0.00000000 0.05769231 --- 1.12797763 0.07692308 0.00000000 0.07692308 --- 1.15944727 0.09615385 0.00000000 0.09615385 --- 1.19091690 0.11538462 0.00000000 0.11538462 --- 1.22238653 0.13461538 0.00000000 0.13461538 --- 1.25385617 0.15384615 0.00000000 0.15384615 --- 1.28532580 0.17307692 0.00000000 0.17307692 --- 1.31679544 0.19230769 0.00000000 0.19230769 --- 1.34826507 0.21153846 0.00000000 0.21153846 --- 1.37973471 0.23076923 0.00000000 0.23076923 --- 1.41120434 0.25000000 0.00000000 0.25000000 --- 1.44267397 0.26923077 0.00000000 0.26923077 --- 1.47414361 0.28846154 0.00000000 0.28846154 --- 1.50561324 0.30769231 0.00000000 0.30769231 --- 1.53708288 0.32692308 0.00000000 0.32692308 --- 1.56855251 0.34615385 0.00000000 0.34615385 --- 1.60002214 0.36538462 0.00000000 0.36538462 --- 1.63149178 0.38461538 0.00000000 0.38461538 --- 1.66296141 0.40384615 0.00000000 0.40384615 --- 1.69443105 0.42307692 0.00000000 0.42307692 --- 1.72590068 0.44230769 0.00000000 0.44230769 --- 1.75737031 0.46153846 0.00000000 0.46153846 --- 1.78883995 0.48076923 0.00000000 0.48076923 --- 1.82030958 0.50000000 0.00000000 0.50000000 --- 1.82030958 0.50000000 0.00000000 0.50000000 --- 1.86459652 0.51562500 0.03125000 0.51562500 --- 1.90888347 0.53125000 0.06250000 0.53125000 --- 1.95317041 0.54687500 0.09375000 0.54687500 --- 1.99745735 0.56250000 0.12500000 0.56250000 --- 2.04174429 0.57812500 0.15625000 0.57812500 --- 2.08603123 0.59375000 0.18750000 0.59375000 --- 2.13031817 0.60937500 0.21875000 0.60937500 --- 2.17460512 0.62500000 0.25000000 0.62500000 --- 2.17460512 0.37500000 0.37500000 0.75000000 --- 2.21256535 0.36160714 0.36160714 0.72321429 --- 2.25052559 0.34821429 0.34821429 0.69642857 --- 2.28848582 0.33482143 0.33482143 0.66964286 --- 2.32644606 0.32142857 0.32142857 0.64285714 --- 2.36440629 0.30803571 0.30803571 0.61607143 --- 2.40236653 0.29464286 0.29464286 0.58928571 --- 2.44032677 0.28125000 0.28125000 0.56250000 --- 2.47828700 0.26785714 0.26785714 0.53571429 --- 2.51624724 0.25446429 0.25446429 0.50892857 --- 2.55420747 0.24107143 0.24107143 0.48214286 --- 2.59216771 0.22767857 0.22767857 0.45535714 --- 2.63012794 0.21428571 0.21428571 0.42857143 --- 2.66808818 0.20089286 0.20089286 0.40178571 --- 2.70604842 0.18750000 0.18750000 0.37500000 --- 2.74400865 0.17410714 0.17410714 0.34821429 --- 2.78196889 0.16071429 0.16071429 0.32142857 --- 2.81992912 0.14732143 0.14732143 0.29464286 --- 2.85788936 0.13392857 0.13392857 0.26785714 --- 2.89584959 0.12053571 0.12053571 0.24107143 --- 2.93380983 0.10714286 0.10714286 0.21428571 --- 2.97177006 0.09375000 0.09375000 0.18750000 --- 3.00973030 0.08035714 0.08035714 0.16071429 --- 3.04769054 0.06696429 0.06696429 0.13392857 --- 3.08565077 0.05357143 0.05357143 0.10714286 --- 3.12361101 0.04017857 0.04017857 0.08035714 --- 3.16157124 0.02678571 0.02678571 0.05357143 --- 3.19953148 0.01339286 0.01339286 0.02678571 --- 3.23749171 0.00000000 0.00000000 0.00000000 +-- 1.04660388 0.01923077 0.00000000 0.01923077 +-- 1.09110866 0.03846154 0.00000000 0.03846154 +-- 1.13561345 0.05769231 0.00000000 0.05769231 +-- 1.18011823 0.07692308 0.00000000 0.07692308 +-- 1.22462301 0.09615385 0.00000000 0.09615385 +-- 1.26912780 0.11538462 0.00000000 0.11538462 +-- 1.31363258 0.13461538 0.00000000 0.13461538 +-- 1.35813736 0.15384615 0.00000000 0.15384615 +-- 1.40264215 0.17307692 0.00000000 0.17307692 +-- 1.44714693 0.19230769 0.00000000 0.19230769 +-- 1.49165171 0.21153846 0.00000000 0.21153846 +-- 1.53615650 0.23076923 0.00000000 0.23076923 +-- 1.58066128 0.25000000 0.00000000 0.25000000 +-- 1.62516606 0.26923077 0.00000000 0.26923077 +-- 1.66967085 0.28846154 0.00000000 0.28846154 +-- 1.71417563 0.30769231 0.00000000 0.30769231 +-- 1.75868041 0.32692308 0.00000000 0.32692308 +-- 1.80318520 0.34615385 0.00000000 0.34615385 +-- 1.84768998 0.36538462 0.00000000 0.36538462 +-- 1.89219476 0.38461538 0.00000000 0.38461538 +-- 1.93669955 0.40384615 0.00000000 0.40384615 +-- 1.98120433 0.42307692 0.00000000 0.42307692 +-- 2.02570911 0.44230769 0.00000000 0.44230769 +-- 2.07021390 0.46153846 0.00000000 0.46153846 +-- 2.11471868 0.48076923 0.00000000 0.48076923 +-- 2.15922346 0.50000000 0.00000000 0.50000000 +-- 2.15922346 0.50000000 0.00000000 0.50000000 +-- 2.21036162 0.51562500 0.03125000 0.51562500 +-- 2.26149977 0.53125000 0.06250000 0.53125000 +-- 2.31263793 0.54687500 0.09375000 0.54687500 +-- 2.36377608 0.56250000 0.12500000 0.56250000 +-- 2.41491424 0.57812500 0.15625000 0.57812500 +-- 2.46605239 0.59375000 0.18750000 0.59375000 +-- 2.51719055 0.60937500 0.21875000 0.60937500 +-- 2.56832871 0.62500000 0.25000000 0.62500000 +-- 2.56832871 0.37500000 0.37500000 0.75000000 +-- 2.61216141 0.36160714 0.36160714 0.72321429 +-- 2.65599411 0.34821429 0.34821429 0.69642857 +-- 2.69982682 0.33482143 0.33482143 0.66964286 +-- 2.74365952 0.32142857 0.32142857 0.64285714 +-- 2.78749223 0.30803571 0.30803571 0.61607143 +-- 2.83132493 0.29464286 0.29464286 0.58928571 +-- 2.87515764 0.28125000 0.28125000 0.56250000 +-- 2.91899034 0.26785714 0.26785714 0.53571429 +-- 2.96282305 0.25446429 0.25446429 0.50892857 +-- 3.00665575 0.24107143 0.24107143 0.48214286 +-- 3.05048846 0.22767857 0.22767857 0.45535714 +-- 3.09432116 0.21428571 0.21428571 0.42857143 +-- 3.13815386 0.20089286 0.20089286 0.40178571 +-- 3.18198657 0.18750000 0.18750000 0.37500000 +-- 3.22581927 0.17410714 0.17410714 0.34821429 +-- 3.26965198 0.16071429 0.16071429 0.32142857 +-- 3.31348468 0.14732143 0.14732143 0.29464286 +-- 3.35731739 0.13392857 0.13392857 0.26785714 +-- 3.40115009 0.12053571 0.12053571 0.24107143 +-- 3.44498280 0.10714286 0.10714286 0.21428571 +-- 3.48881550 0.09375000 0.09375000 0.18750000 +-- 3.53264821 0.08035714 0.08035714 0.16071429 +-- 3.57648091 0.06696429 0.06696429 0.13392857 +-- 3.62031362 0.05357143 0.05357143 0.10714286 +-- 3.66414632 0.04017857 0.04017857 0.08035714 +-- 3.70797902 0.02678571 0.02678571 0.05357143 +-- 3.75181173 0.01339286 0.01339286 0.02678571 +-- 3.79564443 0.00000000 0.00000000 0.00000000 ======================================================================== - Saving unfolded kpoints to file... --- Filepath: /local/MyGitHub/TestInstall/Test/RunVasp/results/kpoints_unfolded.dat +-- Filepath: /local/MyGitHub/TestInstall/Test/Vasp/results/kpoints_unfolded.dat - Done ======================================================================== - Saving unfolded bandstructure to file... --- Filepath: /local/MyGitHub/TestInstall/Test/RunVasp/results/bandstructure_unfolded.dat +-- Filepath: /local/MyGitHub/TestInstall/Test/Vasp/results/bandstructure_unfolded.dat - Done - Unfolding - done -======================================================================== -- Plotting band structure... - Plotting band structures... --- Efermi was set to 5.974 eV +-- Efermi was set to 5.9786 eV +-- Efermi was set to 5.9786 eV - Plotting band structure - done diff --git a/tutorials/Vasp/run_banduppy_vasp.py b/tutorials/Vasp/run_banduppy_vasp.py index 2d612a4..eecb1c0 100755 --- a/tutorials/Vasp/run_banduppy_vasp.py +++ b/tutorials/Vasp/run_banduppy_vasp.py @@ -5,7 +5,7 @@ import pickle import banduppy -print(f'- Bandup version: {banduppy.__version__}') +print(f'- BandUPpy version: {banduppy.__version__}') #%% ----------------------------- Set job ------------------------------------- spinorbit = True @@ -92,14 +92,14 @@ #%% ------------------------ Read wave function file -------------------------- if read_bandstructure: - print (f"{'='*72}\n- Reading bandstructure...") + print (f"{'='*72}\n- Reading band structure...") bands = banduppy.BandStructure(code="vasp", spinor=False, fPOS = f"{sim_folder}/POSCAR", fWAV = f"{sim_folder}/WAVECAR") pickle.dump(bands,open(f"{results_dir}/bandstructure.pickle","wb")) - print ("- Reading bandstructure - done") + print ("- Reading band structure - done") else: - print (f"{'='*72}\n- Unpickling bandstructure...") + print (f"{'='*72}\n- Unpickling band structure...") bands = pickle.load(open(f"{results_dir}/bandstructure.pickle","rb")) print ("- Unpickling - done") @@ -118,7 +118,7 @@ 'fname_suffix': ''}) print ("- Unfolding - done") else: - print (f"{'='*72}\n- Reading bandstructure data from saved file...") + print (f"{'='*72}\n- Reading band structure data from saved file...") unfolded_bandstructure_ = np.loadtxt(f'{results_dir}/bandstructure_unfolded.dat') kpline = np.loadtxt(f'{results_dir}/kpoints_unfolded.dat')[:,1] with open(f'{save_to_dir}/KPOINTS_SpecialKpoints.pkl', 'rb') as handle: @@ -136,14 +136,24 @@ Emax = 5 # Filename to save the figure. If None, figure will not be saved save_file_name = 'unfolded_bandstructure.png' + + plot_unfold = banduppy.Plotting(save_figure_dir=results_dir) + + fig, ax, CountFig \ + = plot_unfold.plot_ebs(kpath_in_angs=kpline, + unfolded_bandstructure=unfolded_bandstructure_, + save_file_name=save_file_name, CountFig=None, + Ef=Efermi, Emin=Emin, Emax=Emax, pad_energy_scale=0.5, + mode="fatband", special_kpoints=special_kpoints_pos_labels, + plotSC=True, fatfactor=20, nE=100,smear=0.2, + color='red', color_map='viridis', show_colorbar=False) +#%% fig, ax, CountFig \ - = band_unfold.plot_ebs(kpath_in_angs=kpline, - unfolded_bandstructure=unfolded_bandstructure_, - save_figure_dir=results_dir, - save_file_name=save_file_name, CountFig=None, - Ef=Efermi, Emin=Emin, Emax=Emax, pad_energy_scale=0.5, - mode="density", special_kpoints=special_kpoints_pos_labels, - plotSC=True, fatfactor=20, nE=100,smear=0.2, - scatter_color='red', color_map='viridis') + = band_unfold.plot_ebs(save_figure_dir=results_dir, + save_file_name=save_file_name, CountFig=None, + Ef=Efermi, Emin=Emin, Emax=Emax, pad_energy_scale=0.5, + mode="fatband", special_kpoints=special_kpoints_pos_labels, + plotSC=True, fatfactor=20, nE=100,smear=0.2, + color='red', color_map='viridis', show_colorbar=False) print ("- Plotting band structure - done") diff --git a/tutorials/sample_output_from_banduppy.out b/tutorials/sample_output_from_banduppy.out index 086efea..f9b91a8 100644 --- a/tutorials/sample_output_from_banduppy.out +++ b/tutorials/sample_output_from_banduppy.out @@ -1,4 +1,4 @@ -- Bandup version: 0.2.1 +- Bandup version: 0.3.2 ======================================================================== - Generating SC Kpoints... ======================================================================== @@ -269,23 +269,23 @@ ---- 59: 0.37500000 0.37500000 0.75000000 ======================================================================== - Saving Kpoints to file.... --- Filepath: /local/MyGitHub/TestInstall/Test/RunVasp/input/KPOINTS_SC +-- Filepath: /local/MyGitHub/TestInstall/Test/Vasp/input/KPOINTS_SC - Done ======================================================================== -- Saving kpoints to file.... --- Filepath: /local/MyGitHub/TestInstall/Test/RunVasp/input/KPOINTS_PC +- Saving special kpoints position indices and labels to file.... +-- Filepath: /local/MyGitHub/TestInstall/Test/Vasp/input/KPOINTS_SpecialKpoints.pkl - Done ======================================================================== -- Saving SC Kpoints - PC kpoints indices mapping to file.... --- Filepath: /local/MyGitHub/TestInstall/Test/RunVasp/input/KPOINTS_SCPC_map.pkl +- Saving kpoints to file.... +-- Filepath: /local/MyGitHub/TestInstall/Test/Vasp/input/KPOINTS_PC - Done ======================================================================== -- Saving special kpoints position indices and labels to file.... --- Filepath: /local/MyGitHub/TestInstall/Test/RunVasp/input/KPOINTS_SpecialKpoints.pkl +- Saving SC Kpoints - PC kpoints indices mapping to file.... +-- Filepath: /local/MyGitHub/TestInstall/Test/Vasp/input/KPOINTS_SCPC_map.pkl - Done - Generating SC Kpoints - done ======================================================================== -- Reading bandstructure... +- Reading band structure... ----------INFORMATION ABOUT THE UNIT CELL----------- @@ -524,81 +524,80 @@ Energy cutoff reduced to : 245.345 -- 0.95654914 0.02272727 0.02272727 0.02272727 -- 1.00209910 0.00000000 0.00000000 0.00000000 -- 1.00209910 0.00000000 0.00000000 0.00000000 --- 1.03356873 0.01923077 0.00000000 0.01923077 --- 1.06503836 0.03846154 0.00000000 0.03846154 --- 1.09650800 0.05769231 0.00000000 0.05769231 --- 1.12797763 0.07692308 0.00000000 0.07692308 --- 1.15944727 0.09615385 0.00000000 0.09615385 --- 1.19091690 0.11538462 0.00000000 0.11538462 --- 1.22238653 0.13461538 0.00000000 0.13461538 --- 1.25385617 0.15384615 0.00000000 0.15384615 --- 1.28532580 0.17307692 0.00000000 0.17307692 --- 1.31679544 0.19230769 0.00000000 0.19230769 --- 1.34826507 0.21153846 0.00000000 0.21153846 --- 1.37973471 0.23076923 0.00000000 0.23076923 --- 1.41120434 0.25000000 0.00000000 0.25000000 --- 1.44267397 0.26923077 0.00000000 0.26923077 --- 1.47414361 0.28846154 0.00000000 0.28846154 --- 1.50561324 0.30769231 0.00000000 0.30769231 --- 1.53708288 0.32692308 0.00000000 0.32692308 --- 1.56855251 0.34615385 0.00000000 0.34615385 --- 1.60002214 0.36538462 0.00000000 0.36538462 --- 1.63149178 0.38461538 0.00000000 0.38461538 --- 1.66296141 0.40384615 0.00000000 0.40384615 --- 1.69443105 0.42307692 0.00000000 0.42307692 --- 1.72590068 0.44230769 0.00000000 0.44230769 --- 1.75737031 0.46153846 0.00000000 0.46153846 --- 1.78883995 0.48076923 0.00000000 0.48076923 --- 1.82030958 0.50000000 0.00000000 0.50000000 --- 1.82030958 0.50000000 0.00000000 0.50000000 --- 1.86459652 0.51562500 0.03125000 0.51562500 --- 1.90888347 0.53125000 0.06250000 0.53125000 --- 1.95317041 0.54687500 0.09375000 0.54687500 --- 1.99745735 0.56250000 0.12500000 0.56250000 --- 2.04174429 0.57812500 0.15625000 0.57812500 --- 2.08603123 0.59375000 0.18750000 0.59375000 --- 2.13031817 0.60937500 0.21875000 0.60937500 --- 2.17460512 0.62500000 0.25000000 0.62500000 --- 2.17460512 0.37500000 0.37500000 0.75000000 --- 2.21256535 0.36160714 0.36160714 0.72321429 --- 2.25052559 0.34821429 0.34821429 0.69642857 --- 2.28848582 0.33482143 0.33482143 0.66964286 --- 2.32644606 0.32142857 0.32142857 0.64285714 --- 2.36440629 0.30803571 0.30803571 0.61607143 --- 2.40236653 0.29464286 0.29464286 0.58928571 --- 2.44032677 0.28125000 0.28125000 0.56250000 --- 2.47828700 0.26785714 0.26785714 0.53571429 --- 2.51624724 0.25446429 0.25446429 0.50892857 --- 2.55420747 0.24107143 0.24107143 0.48214286 --- 2.59216771 0.22767857 0.22767857 0.45535714 --- 2.63012794 0.21428571 0.21428571 0.42857143 --- 2.66808818 0.20089286 0.20089286 0.40178571 --- 2.70604842 0.18750000 0.18750000 0.37500000 --- 2.74400865 0.17410714 0.17410714 0.34821429 --- 2.78196889 0.16071429 0.16071429 0.32142857 --- 2.81992912 0.14732143 0.14732143 0.29464286 --- 2.85788936 0.13392857 0.13392857 0.26785714 --- 2.89584959 0.12053571 0.12053571 0.24107143 --- 2.93380983 0.10714286 0.10714286 0.21428571 --- 2.97177006 0.09375000 0.09375000 0.18750000 --- 3.00973030 0.08035714 0.08035714 0.16071429 --- 3.04769054 0.06696429 0.06696429 0.13392857 --- 3.08565077 0.05357143 0.05357143 0.10714286 --- 3.12361101 0.04017857 0.04017857 0.08035714 --- 3.16157124 0.02678571 0.02678571 0.05357143 --- 3.19953148 0.01339286 0.01339286 0.02678571 --- 3.23749171 0.00000000 0.00000000 0.00000000 +-- 1.04660388 0.01923077 0.00000000 0.01923077 +-- 1.09110866 0.03846154 0.00000000 0.03846154 +-- 1.13561345 0.05769231 0.00000000 0.05769231 +-- 1.18011823 0.07692308 0.00000000 0.07692308 +-- 1.22462301 0.09615385 0.00000000 0.09615385 +-- 1.26912780 0.11538462 0.00000000 0.11538462 +-- 1.31363258 0.13461538 0.00000000 0.13461538 +-- 1.35813736 0.15384615 0.00000000 0.15384615 +-- 1.40264215 0.17307692 0.00000000 0.17307692 +-- 1.44714693 0.19230769 0.00000000 0.19230769 +-- 1.49165171 0.21153846 0.00000000 0.21153846 +-- 1.53615650 0.23076923 0.00000000 0.23076923 +-- 1.58066128 0.25000000 0.00000000 0.25000000 +-- 1.62516606 0.26923077 0.00000000 0.26923077 +-- 1.66967085 0.28846154 0.00000000 0.28846154 +-- 1.71417563 0.30769231 0.00000000 0.30769231 +-- 1.75868041 0.32692308 0.00000000 0.32692308 +-- 1.80318520 0.34615385 0.00000000 0.34615385 +-- 1.84768998 0.36538462 0.00000000 0.36538462 +-- 1.89219476 0.38461538 0.00000000 0.38461538 +-- 1.93669955 0.40384615 0.00000000 0.40384615 +-- 1.98120433 0.42307692 0.00000000 0.42307692 +-- 2.02570911 0.44230769 0.00000000 0.44230769 +-- 2.07021390 0.46153846 0.00000000 0.46153846 +-- 2.11471868 0.48076923 0.00000000 0.48076923 +-- 2.15922346 0.50000000 0.00000000 0.50000000 +-- 2.15922346 0.50000000 0.00000000 0.50000000 +-- 2.21036162 0.51562500 0.03125000 0.51562500 +-- 2.26149977 0.53125000 0.06250000 0.53125000 +-- 2.31263793 0.54687500 0.09375000 0.54687500 +-- 2.36377608 0.56250000 0.12500000 0.56250000 +-- 2.41491424 0.57812500 0.15625000 0.57812500 +-- 2.46605239 0.59375000 0.18750000 0.59375000 +-- 2.51719055 0.60937500 0.21875000 0.60937500 +-- 2.56832871 0.62500000 0.25000000 0.62500000 +-- 2.56832871 0.37500000 0.37500000 0.75000000 +-- 2.61216141 0.36160714 0.36160714 0.72321429 +-- 2.65599411 0.34821429 0.34821429 0.69642857 +-- 2.69982682 0.33482143 0.33482143 0.66964286 +-- 2.74365952 0.32142857 0.32142857 0.64285714 +-- 2.78749223 0.30803571 0.30803571 0.61607143 +-- 2.83132493 0.29464286 0.29464286 0.58928571 +-- 2.87515764 0.28125000 0.28125000 0.56250000 +-- 2.91899034 0.26785714 0.26785714 0.53571429 +-- 2.96282305 0.25446429 0.25446429 0.50892857 +-- 3.00665575 0.24107143 0.24107143 0.48214286 +-- 3.05048846 0.22767857 0.22767857 0.45535714 +-- 3.09432116 0.21428571 0.21428571 0.42857143 +-- 3.13815386 0.20089286 0.20089286 0.40178571 +-- 3.18198657 0.18750000 0.18750000 0.37500000 +-- 3.22581927 0.17410714 0.17410714 0.34821429 +-- 3.26965198 0.16071429 0.16071429 0.32142857 +-- 3.31348468 0.14732143 0.14732143 0.29464286 +-- 3.35731739 0.13392857 0.13392857 0.26785714 +-- 3.40115009 0.12053571 0.12053571 0.24107143 +-- 3.44498280 0.10714286 0.10714286 0.21428571 +-- 3.48881550 0.09375000 0.09375000 0.18750000 +-- 3.53264821 0.08035714 0.08035714 0.16071429 +-- 3.57648091 0.06696429 0.06696429 0.13392857 +-- 3.62031362 0.05357143 0.05357143 0.10714286 +-- 3.66414632 0.04017857 0.04017857 0.08035714 +-- 3.70797902 0.02678571 0.02678571 0.05357143 +-- 3.75181173 0.01339286 0.01339286 0.02678571 +-- 3.79564443 0.00000000 0.00000000 0.00000000 ======================================================================== - Saving unfolded kpoints to file... --- Filepath: /local/MyGitHub/TestInstall/Test/RunVasp/results/kpoints_unfolded.dat +-- Filepath: /local/MyGitHub/TestInstall/Test/Vasp/results/kpoints_unfolded.dat - Done ======================================================================== - Saving unfolded bandstructure to file... --- Filepath: /local/MyGitHub/TestInstall/Test/RunVasp/results/bandstructure_unfolded.dat +-- Filepath: /local/MyGitHub/TestInstall/Test/Vasp/results/bandstructure_unfolded.dat - Done - Unfolding - done -======================================================================== -- Plotting band structure... - Plotting band structures... --- Efermi was set to 5.974 eV +-- Efermi was set to 5.9786 eV +-- Efermi was set to 5.9786 eV - Plotting band structure - done