Metadata-Version: 2.4
Name: yu-mcal
Version: 0.7.0
Summary: Program for the calculation of mobility tensor for organic semiconductor crystals
Author: Koki Ozawa
Author-email: Hiroyuki Matsui <h-matsui@yz.yamagata-u.ac.jp>
License: MIT License
        
        Copyright (c) 2025 Hiroyuki Matsui
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
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License-File: LICENSE
Keywords: mobility,mobility tensor,organic semiconductor,reorganization energy,transfer integral
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Chemistry
Classifier: Topic :: Scientific/Engineering :: Physics
Requires-Python: >=3.11
Requires-Dist: matplotlib>=3.9.4
Requires-Dist: numpy>=2.0.2
Requires-Dist: pandas>=2.3.3
Requires-Dist: yu-tcal==5.0.1
Provides-Extra: gpu4pyscf-cuda11
Requires-Dist: basis-set-exchange>=0.12; extra == 'gpu4pyscf-cuda11'
Requires-Dist: cutensor-cu11>=2.2.0; extra == 'gpu4pyscf-cuda11'
Requires-Dist: geometric>=1.1; extra == 'gpu4pyscf-cuda11'
Requires-Dist: gpu4pyscf-cuda11x>=1.5.2; extra == 'gpu4pyscf-cuda11'
Requires-Dist: pyscf>=2.12.1; extra == 'gpu4pyscf-cuda11'
Provides-Extra: gpu4pyscf-cuda12
Requires-Dist: basis-set-exchange>=0.12; extra == 'gpu4pyscf-cuda12'
Requires-Dist: cutensor-cu12>=2.5.0; extra == 'gpu4pyscf-cuda12'
Requires-Dist: geometric>=1.1; extra == 'gpu4pyscf-cuda12'
Requires-Dist: gpu4pyscf-cuda12x>=1.5.2; extra == 'gpu4pyscf-cuda12'
Requires-Dist: pyscf>=2.12.1; extra == 'gpu4pyscf-cuda12'
Provides-Extra: gpu4pyscf-cuda13
Requires-Dist: basis-set-exchange>=0.12; extra == 'gpu4pyscf-cuda13'
Requires-Dist: cutensor-cu13>=2.6.0; extra == 'gpu4pyscf-cuda13'
Requires-Dist: geometric>=1.1; extra == 'gpu4pyscf-cuda13'
Requires-Dist: gpu4pyscf-cuda13x>=1.7.0; extra == 'gpu4pyscf-cuda13'
Requires-Dist: pyscf>=2.12.1; extra == 'gpu4pyscf-cuda13'
Provides-Extra: orca
Requires-Dist: orca-pi>=2.0.0; extra == 'orca'
Provides-Extra: pyscf
Requires-Dist: basis-set-exchange>=0.12; extra == 'pyscf'
Requires-Dist: geometric>=1.1; extra == 'pyscf'
Requires-Dist: pyscf>=2.12.1; extra == 'pyscf'
Description-Content-Type: text/markdown

# mcal: Program for the calculation of mobility tensor for organic semiconductor crystals
[![Python](https://img.shields.io/badge/python-3.11%20or%20newer-blue)](https://www.python.org)
[![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](https://opensource.org/licenses/MIT)
[![docs](https://img.shields.io/badge/docs-here-11419572)](https://matsui-lab-yamagata.github.io/mcal/)

# Overview
`mcal` is a tool for calculating mobility tensors of organic semiconductors. It calculates transfer integrals and reorganization energy from crystal structures, and determines mobility tensors considering anisotropy and path continuity.

# Requirements
* Python 3.11 or newer
* NumPy
* Pandas
* Matplotlib
* yu-tcal==5.0.1

## Quantum Chemistry Calculation Tools
At least one of the following is required:
* Gaussian 09 or 16
* PySCF (macOS / Linux / WSL2(Windows Subsystem for Linux))
* GPU4PySCF (macOS / Linux / WSL2(Windows Subsystem for Linux))
* ORCA 6.1.0 or newer

# Important notice
* When using Gaussian, the path of the Gaussian must be set.
* PySCF is supported on macOS / Linux. Windows users must use WSL2.

# Installation
## Using Gaussian 09 or 16 (without PySCF)
```
pip install yu-mcal
```

## Using PySCF (CPU only, macOS / Linux / WSL2)
```
pip install "yu-mcal[pyscf]"
```

## Using GPU acceleration with PySCF (macOS / Linux / WSL2)
### 1. Check your installed CUDA Toolkit version
```
nvcc --version
```

### 2. Install tcal with GPU acceleration
If your CUDA Toolkit version is 13.x, install tcal with GPU acceleration:  
```
pip install "yu-mcal[gpu4pyscf-cuda13]"
```
If your CUDA Toolkit version is 12.x, install tcal with GPU acceleration:  
```
pip install "yu-mcal[gpu4pyscf-cuda12]"
```
If your CUDA Toolkit version is 11.x, install tcal with GPU acceleration:  
```
pip install "yu-mcal[gpu4pyscf-cuda11]"
```

## Using ORCA 6.1.0 or newer
```
pip install "yu-mcal[orca]"
```

## Verify Installation

After installation, you can verify by running:

```bash
mcal --help
```

# mcal Usage Manual

## Basic Usage

```bash
mcal <cif_filename or pkl_filenname> <osc_type> [options]
```

### Required Arguments

- `cif_filename`: Path to the CIF file
- `pkl_filename`: Path to the pickle file
- `osc_type`: Organic semiconductor type
  - `p`: p-type semiconductor (uses HOMO level)
  - `n`: n-type semiconductor (uses LUMO level)

### Basic Examples

```bash
# Calculate as p-type semiconductor
mcal xxx.cif p

# Calculate as n-type semiconductor
mcal xxx.cif n
```

## Options

### Calculation Settings

#### `-M, --method <method>`
Specify the calculation method used in Gaussian calculations.
- **Default**: `B3LYP/6-31G(d,p)`
- **Example**: `mcal xxx.cif p -M "B3LYP/6-31G(d)"`

#### `-c, --cpu <number>`
Specify the number of CPUs to use.
- **Default**: `4`
- **Example**: `mcal xxx.cif p -c 8`

#### `-m, --mem <memory>`
Specify the amount of memory in GB.
- **Default**: `10`
- **Example**: `mcal xxx.cif p -m 16`

#### `-g, --g09`
Use Gaussian 09 (default is Gaussian 16).
- **Example**: `mcal xxx.cif p -g`

### PySCF Settings

#### `--pyscf`
Use PySCF instead of Gaussian for all calculations. Requires `yu-mcal[pyscf]`.
- **Example**: `mcal xxx.cif p --pyscf`

#### `--gpu4pyscf`
Use GPU acceleration via gpu4pyscf. Automatically enables PySCF mode (no need to specify `--pyscf`). Requires `yu-mcal[gpu4pyscf-cuda11]` or `yu-mcal[gpu4pyscf-cuda12]`.
- **Example**: `mcal xxx.cif p --gpu4pyscf`

#### `--cart`
Use Cartesian basis functions instead of spherical harmonics (PySCF only).
- **Example**: `mcal xxx.cif p --pyscf --cart`

#### `--bse`
Use Basis Set Exchange for basis-set definitions (PySCF only).
- **Example**: `mcal xxx.cif p --pyscf --bse -M "B3LYP/def2-SVP"`

### ORCA Settings

#### `--orca`
Use ORCA instead of Gaussian for all calculations. Requires `yu-mcal[orca]`.
- **Example**: `mcal xxx.cif p --orca`

#### `--mpi <path>`
Specify the path to the OpenMPI installation directory for ORCA parallel execution. This sets the `OPI_MPI` environment variable used by the ORCA Python Interface (OPI). Only valid with `--orca`.
- **Example**: `mcal xxx.cif p --orca --mpi /usr/lib/x86_64-linux-gnu/openmpi`

#### Parallel Execution

To use multiple CPU cores (`--cpu N`), OpenMPI must be installed.
First, confirm that `mpirun` is available:
```bash
which mpirun
```
If OpenMPI is already in `$PATH` and `$LD_LIBRARY_PATH` (common on Linux/WSL after `apt install`), no further configuration is needed.

If parallel execution does not work, find the OpenMPI base directory (the directory that contains `bin/` and `lib/`) and pass it via `OPI_MPI` or `--mpi`.

##### Linux / WSL
> **Note:** ORCA requires a specific version of OpenMPI. The version available via `apt` may not match. If parallel execution fails, it is recommended to build OpenMPI from source using the version specified in the [ORCA documentation](https://www.faccts.de/docs/orca/6.0/manual/).

When `mpirun` is installed under a dedicated directory (e.g., built from source or via a module system):
```bash
which mpirun
# e.g., /opt/openmpi/bin/mpirun  →  base: /opt/openmpi
export OPI_MPI=$(dirname $(dirname $(which mpirun)))
```
When installed system-wide via `apt` (Ubuntu/Debian), `mpirun` is typically at `/usr/bin/mpirun` but the OpenMPI libraries live under `/usr/lib/`. Check with:
```bash
which mpirun
# /usr/bin/mpirun  →  base is usually /usr/lib/x86_64-linux-gnu/openmpi
export OPI_MPI=/usr/lib/x86_64-linux-gnu/openmpi
```

##### macOS (Homebrew)
```bash
which mpirun
# e.g., /opt/homebrew/bin/mpirun
export OPI_MPI=$(brew --prefix open-mpi)
```

##### Passing the path with `--mpi`
Instead of setting the environment variable, you can pass the path directly:
```bash
mcal xxx.cif p --orca -c 8 --mpi /path/to/openmpi
```

### Calculation Control

#### `-r, --read`
Read results from existing files without executing calculations. With Gaussian, reads from log files; with PySCF, reads from checkpoint (`.chk`) files; with ORCA, reads from output (`.out`) files.
- **Example**: `mcal xxx.cif p -r`

#### `-rp, --read_pickle`
Read results from existing pickle file without executing calculations.
- **Example**: `mcal xxx_result.pkl p -rp`

#### `--resume`
Resume calculation using existing results. With Gaussian, checks log file termination; with PySCF, checks for existing checkpoint (`.chk`) files; with ORCA, checks `.out` file termination.
- **Example**: `mcal xxx.cif p --resume`

#### `--fullcal`
Disable all speedup processing and calculate transfer integrals for all pairs from scratch. The following two optimizations are disabled:
1. **Pair screening**: pairs are normally skipped based on moment of inertia and center-of-mass distance; `--fullcal` disables this screening
2. **Monomer caching**: monomer SCF calculations for the same molecule type are normally skipped by reusing a previously computed result file; `--fullcal` forces all monomer calculations to be performed from scratch
- **Example**: `mcal xxx.cif p --fullcal`

#### `--no-monomer-cache`
Disable only monomer caching. Pair screening remains active. All monomer SCF calculations are performed from scratch instead of reusing previously computed result files.
When performing detailed transfer integral analysis using <a href="https://github.com/matsui-lab-yamagata/tcal" target="_blank">tcal</a>, it is recommended to use this option.
- **Example**: `mcal xxx.cif p --no-monomer-cache`

#### `--cellsize <number>`
Specify the number of unit cells to expand in each direction around the central unit cell for transfer integral calculations.
- **Default**: `2` (creates 5×5×5 supercell)
- **Examples**: 
  - `mcal xxx.cif p --cellsize 1` (creates 3×3×3 supercell)
  - `mcal xxx.cif p --cellsize 3` (creates 7×7×7 supercell)

### Output Settings

#### `-p, --pickle`
Save calculation results to a pickle file.
- **Example**: `mcal xxx.cif p -p`

#### `-j, --json`
Save calculation results to a JSON file (`<input>_result.json`). Contains reorganization energy (with intermediate energies), transfer integrals, diffusion coefficient tensor, mobility tensor, eigenvalues, and eigenvectors, along with metadata (mcal version, method, backend). Can be combined with `-p`.
- **Example**: `mcal xxx.cif p -j`

#### `--plot-plane <plane>`
Plot mobility tensor as a 2D polar plot on specified crystallographic plane.
- **Available planes**: `ab`, `ac`, `ba`, `bc`, `ca`, `cb`
- **Default**: None (no plot generated)
- **Examples**: 
  - `mcal xxx.cif p --plot-plane ab` (plot on ab-plane)
  - `mcal xxx.cif p --plot-plane bc` (plot on bc-plane)

## Practical Usage Examples

### Basic Calculations
```bash
# Calculate mobility of p-type xxx
mcal xxx.cif p

# Use 8 CPUs and 16GB memory
mcal xxx.cif p -c 8 -m 16
```

### High-Precision Calculations
```bash
# Calculate transfer integrals for all pairs (high precision, time-consuming)
mcal xxx.cif p --fullcal

# Use larger supercell to widen transfer integral calculation range
mcal xxx.cif p --cellsize 3

# Use different basis set
mcal xxx.cif p -M "B3LYP/6-311G(d,p)"
```

### PySCF Calculations
```bash
# Calculate using PySCF (CPU)
mcal xxx.cif p --pyscf

# Calculate using PySCF with GPU acceleration (no --pyscf needed)
mcal xxx.cif p --gpu4pyscf

# Use 8 CPUs and 16GB memory with PySCF
mcal xxx.cif p --pyscf -c 8 -m 16

# Use Basis Set Exchange with --method in PySCF mode
mcal xxx.cif p --pyscf --bse -M "B3LYP/def2-SVP"

# Resume interrupted PySCF calculation
mcal xxx.cif p --pyscf --resume

# Read from existing PySCF checkpoint files
mcal xxx.cif p --pyscf -r
```

### ORCA Calculations
```bash
# Calculate using ORCA
mcal xxx.cif p --orca

# Use 8 CPUs and 16GB memory with ORCA
mcal xxx.cif p --orca -c 8 -m 16

# Specify OpenMPI path for ORCA parallel execution
mcal xxx.cif p --orca --mpi /usr/lib/x86_64-linux-gnu/openmpi

# Resume interrupted ORCA calculation
mcal xxx.cif p --orca --resume

# Read from existing ORCA output files
mcal xxx.cif p --orca -r
```

### Reusing Results
```bash
# Read from existing calculation results
mcal xxx.cif p -r

# Read from existing pickle file
mcal xxx_result.pkl p -rp

# Resume interrupted calculation
mcal xxx.cif p --resume

# Save results to pickle file
mcal xxx.cif p -p
```

## Output

### Standard Output
- Reorganization energy
- Transfer integrals for each pair
- Diffusion coefficient tensor
- Mobility tensor
- Eigenvalues and eigenvectors of mobility

### Generated Files

#### Reorganization Energy Files

The following files are generated during reorganization energy calculation (where `c` = cation for p-type, `a` = anion for n-type):

##### Gaussian
- `xxx_opt_n.gjf` / `xxx_opt_n.log` — geometry optimization of neutral molecule
- `xxx_c.gjf` / `xxx_c.log` (or `xxx_a`) — SP energy of ion at neutral geometry
- `xxx_opt_c.gjf` / `xxx_opt_c.log` (or `xxx_opt_a`) — geometry optimization of ion
- `xxx_n.gjf` / `xxx_n.log` — SP energy of neutral at ion geometry

##### PySCF
- `xxx_opt_n.xyz` / `xxx_opt_n.chk` — geometry optimization of neutral molecule
- `xxx_c.chk` (or `xxx_a.chk`) — SP energy of ion at neutral geometry
- `xxx_opt_c.xyz` / `xxx_opt_c.chk` (or `xxx_opt_a`) — geometry optimization of ion
- `xxx_n.chk` — SP energy of neutral at ion geometry

##### ORCA
- `xxx_opt_n_input.xyz` / `xxx_opt_n.out` / `xxx_opt_n.xyz` — geometry optimization of neutral molecule
- `xxx_c_input.xyz` / `xxx_c.out` (or `xxx_a`) — SP energy of ion at neutral geometry
- `xxx_opt_c_input.xyz` / `xxx_opt_c.out` / `xxx_opt_c.xyz` (or `xxx_opt_a`) — geometry optimization of ion
- `xxx_n_input.xyz` / `xxx_n.out` — SP energy of neutral at ion geometry

#### Transfer Integral Files

mcal generates calculation files named using the `(s_t_i_j_k)` notation (Gaussian and PySCF). For ORCA, the `_s_t_i_j_k` notation is used instead because ORCA cannot handle parentheses in filenames:

| Symbol | Meaning |
|--------|---------|
| `s` | Molecule index in the reference unit cell (0,0,0) |
| `t` | Molecule index in the neighboring unit cell |
| `i` | Translation index along the **a**-axis |
| `j` | Translation index along the **b**-axis |
| `k` | Translation index along the **c**-axis |

**Example (Gaussian / PySCF):** `xxx-(0_0_1_0_0)` represents the transfer integral between the 0th molecule in the (0,0,0) cell and the 0th molecule in the (1,0,0) cell.

**Example (ORCA):** `xxx_0_0_1_0_0` represents the same pair as above.

##### Gaussian
- `xxx-(s_t_i_j_k).gjf` / `xxx-(s_t_i_j_k).log` — dimer
- `xxx-(s_t_i_j_k)_m1.gjf` / `xxx-(s_t_i_j_k)_m1.log` — monomer 1
- `xxx-(s_t_i_j_k)_m2.gjf` / `xxx-(s_t_i_j_k)_m2.log` — monomer 2

##### PySCF
- `xxx-(s_t_i_j_k).xyz` / `xxx-(s_t_i_j_k).chk` — dimer
- `xxx-(s_t_i_j_k)_m1.chk` — monomer 1
- `xxx-(s_t_i_j_k)_m2.chk` — monomer 2

##### ORCA
- `xxx_s_t_i_j_k.xyz` / `xxx_s_t_i_j_k.out` — dimer
- `xxx_s_t_i_j_k_m1.out` — monomer 1
- `xxx_s_t_i_j_k_m2.out` — monomer 2

## Notes

1. **Calculation Time**: Calculation time varies significantly depending on the number of molecules and cell size. By default, two speedup mechanisms are enabled: pair pre-screening (skipping pairs unlikely to have significant transfer integrals) and monomer caching (reusing the isolated-molecule SCF result for molecule types already computed). Use `--fullcal` to disable both.
2. **Memory Usage**: Ensure sufficient memory for large systems
3. **Gaussian Installation**: Gaussian 09 or Gaussian 16 is required
4. **Dependencies**: Make sure all required Python libraries are installed

## Troubleshooting

### If calculation stops midway
```bash
# Resume with --resume option
mcal xxx.cif p --resume
```

### Memory shortage error
```bash
# Increase memory amount
mcal xxx.cif p -m 32
```

### To reduce calculation time
```bash
# Enable speedup processing (default)
mcal xxx.cif p

# Use smaller supercell for faster calculation
mcal xxx.cif p --cellsize 1

# Increase number of CPUs
mcal xxx.cif p -c 16
``` 

### If a CIF file cannot be read
CIF files come in various formats, and some may not be readable by mcal. Please try the following:

1. **Convert the CIF format using another software**: Use software such as [Mercury](https://www.ccdc.cam.ac.uk/solutions/software/mercury/) to open the CIF file and re-export it, which may resolve the issue.
2. **Contact us**: If you send the unreadable CIF file to us by email, we will work on adding support for it. Please contact us at the email address listed below.

# Authors
[Matsui Laboratory, Research Center for Organic Electronics (ROEL), Yamagata University](https://matsui-lab.yz.yamagata-u.ac.jp/index-e.html)  
Hiroyuki Matsui, Koki Ozawa  
Email: h-matsui[at]yz.yamagata-u.ac.jp  
Please replace [at] with @  

# Acknowledgements
This work was supported by JSPS Grant-in-Aid for JSPS Fellows Grant Number JP25KJ0647.  

# References
[1] Qiming Sun et al., Recent developments in the PySCF program package, *J. Chem. Phys.* **2020**, *153*, 024109.  
[2] Lee-Ping Wang, Chenchen Song, Geometry optimization made simple with translation and rotation coordinates, *J. Chem. Phys.* **2016**, *144*, 214108.  
[3] Benjamin P. Pritchard et al., New Basis Set Exchange: An Open, Up-to-Date Resource for the Molecular Sciences Community, *J. Chem. Inf. Model.* **2019**, *59*, 4814-4820.  
[4] Frank Neese, The ORCA program system, *Wiley Interdiscip. Rev. Comput. Mol. Sci.*, **2012**, *2*, 73-78.  
