semvec/pypi-packages huggingface dataset:
pyupm 0.0.1
A simple code for Uncertainty Projected Mapping
License: MIT
Requires Python: ==3.9.18

UPM-Spatial-Interpolation
Python code and example data for Uncertainty Projected Mapping (UPM) as a spatial interpolation tool

The main code to generate UPM is UPM.py

There is also a simple flowchart (How to use the codes?.pdf) on how to use the codes. Please also find a file named The UPM story.pdf, which I created to provide an easy recap of UPM.

References on UPM:

Chakraborty, A., & Goto, H. (2018). A Bayesian model reflecting uncertainties on map resolutions with application to the study of site response variation. Geophysical Journal International, 214(3), 2264-2276.

Chakraborty, A., & Goto, H. (2020). Visualizing data saturation process in mapping site amplification of earthquake ground motions. Journal of Natural Disaster Science, 40(2), 14-25.

Chakraborty, A., Goto, H., & Sawada, S. (2024). Updating proxy-based site amplification map with in-situ data in Osaka, Japan: A Bayesian scheme based on uncertainty projected mapping. Earthquake Spectra, 2024;40(1):113-142.

References on CAR:

De Oliveira, V. (2012). Bayesian analysis of conditional autoregressive models. Annals of the Institute of Statistical Mathematics, 64, 107-133.
d3tales-api 0.2.0
API for parsing, database connection, and property calculations for D3taLES project 
License: MIT

# D<sup>3</sup>TaLES API 
![](mkdocs/D3TaLES_api_logo.png)


API designed for the [D<sup>3</sup>TaLES project](https://d3tales.as.uky.edu/). Includes 
data processing, database access functions, and property calculators. 

## [Website with full documentation for the D<sup>3</sup>TaLES API can be found here](https://d3tales.github.io/d3tales_api/).  

## Modules 
This API contains three modules: 
* `D3database`: Interface for interacting with the D<sup>3</sup>TaLES databases. Includes 
queries, data insertion with validation, and a REST API interface.
* `Processors`: Processing code for extracting data from computational and experimental
data files as well as [ExpFlow](https://d3tales.as.uky.edu/expflow) run objects. 
* `Calculators`: Property calculators and plotters for cyclic voltammetry
* `Workflows`: Fireworks workflow for the D<sup>3</sup>TaLES databases high throughput workflows 

## Installation 

### PIP Install
This module can be installed with pip install by running the following code: 

```bash
pip install git+https://github.com/d3tales/d3tales_api.git
```

>**Installation Notes**: 
> * If your python version is greater than 3.8, then you will need to install 
>[pymatgen](https://pymatgen.org/) directly into the environment you are working in. It is best to use 
>[conda](https://anaconda.org/conda-forge/pymatgen) for this.
> * If you plan to use any NLP parsers, you will need to install [ChemDataExtractor2](https://github.com/CambridgeMolecularEngineering/chemdataextractor2) 
> with `pip install ChemDataExtractor2`. Dependency conflicts make it necessary to install separately.  

### Environment Variables
Note that many operation require a `DB_INFO_FILE` environment variable. This environment variable
should be a path to a JSON file containing connection information for the databases. The keys should 
be the database names such as `frontend`, `backend`, `expflow`, and `fireworks`. An example 
can be found at [db_info_ex.json](db_info_ex.json). 

To set this variable run:
```bash
export DB_INFO_FILE=$PWD/db_infos_ex.json
```

You can also set a `GROUP_FILE` environment variable. This should point to a json 
file containing source_group tag names. This is **optional**. 

To set this variable run:
```bash
export GROUP_FILE=$PWD/group_file_ex.json
```

REST API (`d3tales_api.restapi.RESTAPI`) will use `UPLOAD_USER` and `UPLOAD_PASS` environment 
variables if `username` and `password` arguments are not provided. These environment variables 
can be set in the same was as the `DB_INFO_FILE` variable.