semvec/pypi-packages huggingface dataset:
tdataframe 0.3.2
A package to handle shape-matching for meshes
Requires Python: >=3.12

# TDAtaframe
TDA brought to dataframes.

# Install
TDAtaframe is available on pypi as a source distribution.
The backend requires that you have the appropriate libtorch 2.5.1 libraries 
installed on your system in the standard location.

On Linux/macOS, this is typically /usr/lib, /usr/include, /usr/share for 
library, include, and share files respectively. Sym-linking the files will not 
work.

After ensuring that these libraries are present, all that is needed is

```pip install tdataframe```.

On first install, it is normal for compilation to take a few minutes.

## Manual libtorch install instructions
It is recommended to use your package manager to install libtorch.
If not readily available for your system, follow the below instructions 
as a workaround.

Download libtorch from [here](https://pytorch.org/).
Then, unzip the files.

`unzip libtorch-*.zip && cd libtorch`

Next, copy all the files to the system. Make sure
you understand what these commands do as they are difficult to undo.
You will likely need to run these commands with `sudo`.

`cp -r lib/* /usr/lib && cp -r include/* /usr/include && cp -r share /usr/share`

Finally, update your linker cache with

`ldconfig`.

## Alternative libtorch locations
todo. see tch-rs docs
narp-dynamics 1.4
Implementation of NARP Pulses and Their Interaction Dynamics with Two-Level Systems

```python
from narp_functions import (
    narp_pulse,
    narp_pulse_dynamics,
    area_versus_chirp,
    notch_versus_chirp,
    notch_versus_area,
    plot_fields,
    plot_occupations,
    plot_surfaces,
)
import jax.numpy as jnp
```

# Basic Usage


```python
pulse = narp_pulse(
    pulse_center_frequency = 0.322, #[PHz]
    pulse_bandwidth = 0.022, #[PHz] (20 fs pulse)
    pulse_area = 6*jnp.pi,
    chirp_rate = 900, #[ps]^2
    notch_type = 0,
    notch_bandwidth = 0.022/5 #[PHz]
)
plot_fields(pulse)
```


    
![png](README_files/README_2_0.png)
    



```python
rho = narp_pulse_dynamics(pulse, 0.322) # (Resonance)
plot_occupations(pulse, rho)
```


    
![png](README_files/README_3_0.png)
    


# Parameter Space

## Area versus Chirp


```python
pulse_areas_grid, chirp_rates_grid, occupations_matrix = area_versus_chirp(
    pulse_center_frequency = 0.322, #[PHz]
    pulse_bandwidth = 0.022, #[PHz] (20 fs pulse)
    notch_type = 0,
    notch_bandwidth = 0.022/5, #[PHz]
    resolution = 25
)
plot_surfaces(chirp_rates_grid, pulse_areas_grid, occupations_matrix)
```

    Computing occupations: 100%|██████████| 625/625 [03:04<00:00,  3.38it/s]



    
![png](README_files/README_6_1.png)
    


# Notch versus Chirp


```python
pulse_areas_grid, notch_widths_grid, occupations_matrix = notch_versus_chirp(
    pulse_center_frequency = 0.322, #[PHz]
    pulse_bandwidth = 0.022, #[PHz] (20 fs pulse)
    notch_type = 0,
    pulse_area = 8*jnp.pi,
    resolution = 25
)
plot_surfaces(notch_widths_grid, pulse_areas_grid, occupations_matrix)
```

    Computing occupations: 100%|██████████| 625/625 [02:57<00:00,  3.52it/s]



    
![png](README_files/README_8_1.png)
    


# Notch versus Area


```python
pulse_areas_grid, notch_widths_grid, occupations_matrix = notch_versus_area(
    pulse_center_frequency = 0.322, #[PHz]
    pulse_bandwidth = 0.022, #[PHz] (20 fs pulse)
    chirp_rate = 600,
    notch_type = 0,
    resolution = 25
)
plot_surfaces(notch_widths_grid, pulse_areas_grid, occupations_matrix)
```

    Computing occupations: 100%|██████████| 625/625 [02:53<00:00,  3.61it/s]



    
![png](README_files/README_10_1.png)
    


This project is licensed under the MIT License - see the [LICENSE](./LICENSE) file for details.
geometric 1.1
Geometry optimization for quantum chemistry

<div align="center">
    <img width = "40%" src = "https://user-images.githubusercontent.com/1441560/56555299-600d1980-6549-11e9-9f05-b1e8b899a292.png">
</div>

[![Build Status](https://github.com/leeping/geomeTRIC/actions/workflows/test-conda.yml/badge.svg)](https://github.com/leeping/geomeTRIC/actions/workflows/test-conda.yml)
[![codecov](https://codecov.io/gh/leeping/geometric/branch/master/graph/badge.svg)](https://codecov.io/gh/leeping/geometric)

This is a geometry optimization code for molecular structures.
The code works by calling external software for the energy and 
gradient through wrapper functions. Q-Chem, TeraChem, Psi4, 
Molpro, Gaussian 09/16, CFOUR, and QUICK are supported quantum chemistry
codes through the command line interface. The PySCF and
QCArchive packages also provide interfaces to geomeTRIC for
optimization. MM optimizations using OpenMM and Gromacs are
also supported through the command line interface.

Documentation is hosted at https://geometric.readthedocs.io/ .

Authors: Lee-Ping Wang, Chenchen Song, Heejune Park

Contributors: Yudong Qiu (Psi4 engine, error handling); Daniel G. A. Smith (Testing framework, QCEngine JSON API);
Tamas K. Stenczel (GitHub Actions, ASE engine); Sebastian Lee (Molpro engine); Chaya Stern (Travis, Conda); Qiming Sun (Custom engine); 
Alberto Gobbi (Batch energy/gradient, logging); Josh Horton (Convergence criteria, Gaussian engine); Akhil Shajan (QUICK engine)

Contact Email: leeping@ucdavis.edu

If this code has benefited your research, please support us by citing:

Wang, L.-P.; Song, C.C. (2016) "Geometry optimization made simple with translation and rotation coordinates", J. Chem, Phys. 144, 214108.
http://dx.doi.org/10.1063/1.4952956

## Quick Help

Package dependencies are:
Python 2.7, 3.5+
NumPy, Scipy, NetworkX

To install the code from source, run "python setup.py install".
To install the latest release from pip, run "pip install geometric".
To install the latest release from conda-forge, run "conda install -c conda-forge geometric".

To execute the geometry optimizer, run "geometric-optimize".
Use "-h" to see the list of command line options.

Generally, you will need a .xyz file for the coordinates and 
one of the supported quantum chemistry software packages installed
on your system.

Supported QM packages are: TeraChem, Q-Chem, Molpro, Psi4, and Gaussian 09/16.
Supported MM packages are: OpenMM, Gromacs.

Please refer to the example calculations for how to run the code.  
The commands to execute the code are contained in "command.sh".

## Citation

If this code has benefited your research, please support us by citing our publication:

Wang, L.-P.; Song, C.C. (2016) "Geometry optimization made simple
with translation and rotation coordinates", J. Chem, Phys. 144, 214108.
DOI: 10.1063/1.4952956