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bandsplot,dosplot,bandsdosplot changes, bug fixes, doc updates
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lllangWV committed Oct 26, 2023
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3 changes: 2 additions & 1 deletion README.md
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Notice
===========
- **New Release** We recently updated to a new version 'v6.0.5'. This update encompasses a significant overhaul of the codebase, updated documentation, and .
- **New Release** We recently updated to a new version 'v6.1.6'. This update encompasses a significant overhaul of the codebase, updated documentation, and .
- **Support for Previous Versions**: For users who prefer to continue with an older version, we have conveniently archived the previous releases on GitHub, and provided a link to the corresponding documentation.


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Changelog
--------------
v6.1.6 Oct 10th, 2023 -- bandsplot,dosplot,bandsdosplot chnages, bug fixes, doc updates <br />
v6.1.5 Oct 10th, 2023 -- Feature additions, example gallery additions, and doc updates <br />
v6.1.4 Aug 18th, 2023 -- Bug fixes, example gallery additions, and doc updates <br />
v6.1.3 Aug 7th, 2023 -- Updated install requirements <br />
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# Sphinx build info version 1
# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
config: b51496cb65e7392cdce271c3cb5cc200
config: bbb46bcc16cfe3131c0a094bc7b914a0
tags: 645f666f9bcd5a90fca523b33c5a78b7
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###############################################################################
# When show is equal to False, bandsplot will return a EBSPlot object.
# This object has information about the band structure and has matplotlib.axes.Axes object as an attribute.
# When show is equal to False, bandsplot will return a maplotlib.Figure and maplotlib.axes.Axes object
#

ebs_plot = pyprocar.bandsplot(code='vasp', dirname = vasp_data_dir, mode='parametric', elimit=[-5,5], orbitals=[4,5,6,7,8], show=False)
pyprocar.bandsplot(code='qe', dirname = qe_data_dir, mode='plain', elimit=[-5,5], color='k',ax=ebs_plot.ax, show =True)
fig, ax = pyprocar.bandsplot(code='vasp', dirname = vasp_data_dir, mode='parametric', elimit=[-5,5], orbitals=[4,5,6,7,8], show=False)
pyprocar.bandsplot(code='qe', dirname = qe_data_dir, mode='plain', elimit=[-5,5], color='k',ax=ax, show =True)
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"cell_type": "markdown",
"metadata": {},
"source": [
"When show is equal to False, bandsplot will return a EBSPlot object.\r\nThis object has information about the band structure and has\r\nmatplotlib.axes.Axes object as an attribute.\r\n"
"When show is equal to False, bandsplot will return a maplotlib.Figure\r\nand maplotlib.axes.Axes object\r\n"
]
},
{
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},
"outputs": [],
"source": [
"ebs_plot = pyprocar.bandsplot(code='vasp', dirname = vasp_data_dir, mode='parametric', elimit=[-5,5], orbitals=[4,5,6,7,8], show=False)\npyprocar.bandsplot(code='qe', dirname = qe_data_dir, mode='plain', elimit=[-5,5], color='k',ax=ebs_plot.ax, show =True)"
"fig, ax = pyprocar.bandsplot(code='vasp', dirname = vasp_data_dir, mode='parametric', elimit=[-5,5], orbitals=[4,5,6,7,8], show=False)\npyprocar.bandsplot(code='qe', dirname = qe_data_dir, mode='plain', elimit=[-5,5], color='k',ax=ax, show =True)"
]
}
],
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"cell_type": "markdown",
"metadata": {},
"source": [
"# Plotting Inverse participation ratio {#ref_plot_ipr}\r\n\r\nOften it is needed to search for **localized** modes within the band\r\nstructure, typical examples are surface/interface states and defect\r\nlevels. The usual procedure for detecting them is looking for bands with\r\na large projection around the atoms at the surface or defect. This\r\nprocedure is both cumbersome for the user and error-prone. For instance,\r\nthe lowest unoccupied levels of the neutral $C_N$ defect in h-BN has\r\npractically no projection on the defect atom and its nearest neighbors.\r\nThis delayed its identification as a single-photon\r\nemitter.\\[jara2021,auburger2021\\] A much simpler way to detect these\r\nlocalized levels is by means of the **Inverse Participation Ratio**,\r\ndefined as\r\n\r\n$$IPR_{nk} = \\frac{\\sum_{a} |c_{nki}|^4}{\\left(\\sum_a c_{nka}\\right)^2}$$\r\n\r\nwhere the indexes $n,k,a$ are the band, k-point and atom, respectively.\r\nThis function has been extensively applied in the context of Anderson\r\nlocalization.\\[Evers2000\\] However, can capture any kind of\r\nlocalization. A perfectly localized state -**i.e.** localized in a\r\nsingle atom- would have $IPR=1$, but a fully extended state has\r\n$IPR=\\frac{1}{N}$, with $N$ the total number of atoms.\r\n\r\n## Preparation\r\n\r\nBefore diving into plotting, we need to download the example files. Use\r\nthe following code to do this. Once downloaded, specify the\r\n[data_dir]{.title-ref} to point to the location of the downloaded data.\r\n\r\n``` {caption=\"Downloading example\"}\r\nimport pyprocar\r\n\r\nbi2se3_data_dir = pyprocar.download_example(\r\n save_dir='', \r\n material='Bi2Se3-spinorbit-surface',\r\n code='vasp', \r\n spin_calc_type='spin-polarized-colinear',\r\n calc_type='bands'\r\n )\r\n```\r\n"
"# Plotting Inverse participation ratio {#ref_plot_ipr}\r\n\r\nOften it is needed to search for **localized** modes within the band\r\nstructure, typical examples are surface/interface states and defect\r\nlevels. The usual procedure for detecting them is looking for bands with\r\na large projection around the atoms at the surface or defect. This\r\nprocedure is both cumbersome for the user and error-prone. For instance,\r\nthe lowest unoccupied levels of the neutral $C_N$ defect in h-BN has\r\npractically no projection on the defect atom and its nearest neighbors.\r\nThis delayed its identification as a single-photon\r\nemitter.\\[jara2021,auburger2021\\] A much simpler way to detect these\r\nlocalized levels is by means of the **Inverse Participation Ratio**,\r\ndefined as\r\n\r\n$$IPR_{nk} = \\frac{\\sum_{a} |c_{nki}|^4}{\\left(\\sum_a c_{nka}\\right)^2}$$\r\n\r\nwhere the indexes $n,k,a$ are the band, k-point and atom, respectively.\r\nThis function has been extensively applied in the context of Anderson\r\nlocalization.\\[Evers2000\\] However, can capture any kind of\r\nlocalization. A perfectly localized state -**i.e.** localized in a\r\nsingle atom- would have $IPR=1$, but a fully extended state has\r\n$IPR=\\frac{1}{N}$, with $N$ the total number of atoms.\r\n\r\n## Preparation\r\n\r\nBefore diving into plotting, we need to download the example files. Use\r\nthe following code to do this. Once downloaded, specify the\r\n[data_dir]{.title-ref} to point to the location of the downloaded data.\r\n\r\n``` {caption=\"Downloading example\"}\r\nimport pyprocar\r\n\r\nbi2se3_data_dir = pyprocar.download_example(\r\n save_dir='', \r\n material='Bi2Se3-spinorbit-surface',\r\n code='vasp', \r\n spin_calc_type='spin-polarized-colinear',\r\n calc_type='bands'\r\n )\r\n\r\nC_data_dir = pyprocar.download_example(\r\n save_dir='', \r\n material='NV-center',\r\n code='vasp', \r\n spin_calc_type='spin-polarized-colinear',\r\n calc_type='bands'\r\n )\r\n```\r\n"
]
},
{
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spin_calc_type='spin-polarized-colinear',
calc_type='bands'
)
C_data_dir = pyprocar.download_example(
save_dir='',
material='NV-center',
code='vasp',
spin_calc_type='spin-polarized-colinear',
calc_type='bands'
)
"""

###############################################################################
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<head>
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>pyprocar.core.brillouin_zone &#8212; PyProcar 6.1.4 documentation</title>
<title>pyprocar.core.brillouin_zone &#8212; PyProcar 6.1.5 documentation</title>



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<link rel="preload" as="script" href="../../../_static/scripts/bootstrap.js?digest=e353d410970836974a52" />
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<p class="title logo__title">PyProcar 6.1.4 documentation</p>
<p class="title logo__title">PyProcar 6.1.5 documentation</p>

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<title>pyprocar.core.dos &#8212; PyProcar 6.1.4 documentation</title>
<title>pyprocar.core.dos &#8212; PyProcar 6.1.5 documentation</title>



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<p class="title logo__title">PyProcar 6.1.4 documentation</p>
<p class="title logo__title">PyProcar 6.1.5 documentation</p>

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<title>pyprocar.core.ebs &#8212; PyProcar 6.1.4 documentation</title>
<title>pyprocar.core.ebs &#8212; PyProcar 6.1.5 documentation</title>



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<p class="title logo__title">PyProcar 6.1.4 documentation</p>
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<title>pyprocar.core.fermisurface &#8212; PyProcar 6.1.4 documentation</title>
<title>pyprocar.core.fermisurface &#8212; PyProcar 6.1.5 documentation</title>



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<p class="title logo__title">PyProcar 6.1.4 documentation</p>
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<title>pyprocar.core.fermisurface3D &#8212; PyProcar 6.1.5 documentation</title>



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<p class="title logo__title">PyProcar 6.1.4 documentation</p>
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<title>pyprocar.core.isosurface &#8212; PyProcar 6.1.5 documentation</title>



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<p class="title logo__title">PyProcar 6.1.4 documentation</p>
<p class="title logo__title">PyProcar 6.1.5 documentation</p>

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<title>pyprocar.core.structure &#8212; PyProcar 6.1.4 documentation</title>
<title>pyprocar.core.structure &#8212; PyProcar 6.1.5 documentation</title>



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<p class="title logo__title">PyProcar 6.1.4 documentation</p>
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<title>pyprocar.core.surface &#8212; PyProcar 6.1.4 documentation</title>
<title>pyprocar.core.surface &#8212; PyProcar 6.1.5 documentation</title>



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<p class="title logo__title">PyProcar 6.1.4 documentation</p>
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