semvec/pypi-packages huggingface dataset:
gp-emulator 1.6.10
A Python Gaussian Process emulator software package

# GP emulators

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## Gaussian process (GP) emulators for Python

### Author  
J Gómez-Dans <j.gomez-dans@ucl.ac.uk>
<p><img src="http://www.multiply-h2020.eu/wp-content/uploads/2018/08/multiply_banner_2018_klein.jpg" align="center" \></p>
<p><img src="https://www.nceo.ac.uk/wp-content/themes/nceo/assets/images/logos/img_logo_purple.svg" align="left" />

<img src="http://www.esa.int/esalogo/images/logotype/img_colorlogo_darkblue.gif" scale="20%" align="right" />
</p>




This repository contains an implementation of GPs for emulation of radiative transfer models in Python. This particular implementation is focused on emulating univariate output models (e.g. emulating reflectance or radiance for a single sensor band) and multivariate outputs (e.g. emulating reflectance/radiance over the entire solar reflective domain). The emulators also calculate the gradient of the emulated model and the Hessian.

### Documentation

You can read the documentation in [http://http://gp-emulator.readthedocs.io]<http://gp-emulator.readthedocs.io>

### Installation


You can install the software with either [conda]<https://docs.anaconda.com/anaconda/>

    conda install -c jgomezdans gp_emulators

or using `pip`...

    pip install gp_emulator

or just clone/download the repository and invoke the `setup.py` script:

    python setup.py install

The only requirements are (if memory serves) numpy and scipy. 

At some point, pointers to a library of emulators of popular vegetation and atmospheric RT codes will be provided.

### Citation


If you use this code, we would be grateful if you cited the following paper:

    Gómez-Dans, J.L.; Lewis, P.E.; Disney, M. Efficient Emulation of Radiative Transfer Codes Using Gaussian Processes and Application to Land Surface Parameter Inferences. Remote Sens. 2016, 8, 119. <DOI:10.3390/rs8020119> <http://www.mdpi.com/2072-4292/8/2/119>
nk225op 0.1.9
Download latest Option Price(nk255) from JPX
Keywords: options,python,finance

#nk225op 
------

`nk225op` is module for fetching latest NK225(Nikkei225) Options Data from JPX Server.

`nk225op`  はJPX(日本証券取引所)のサーバーから、最新の日経２２５オプション清算値を取得するモジュールです。

------

> ブラウザでお気軽に試す場合　⇒　 [Jupyter Notebook example on Google Colab](https://colab.research.google.com/github/zaq9/nk225op/blob/master/doc/eg_nk225op.ipynb)



## Demo:　 (２月限と３月限　権利価格　20500～20750 の清算値とIVデータ表示)

```python
from nk225op import nk225op as nk
nk([201902,201903] , [20500,20750])
```

### Output:

| lb         | PRICE | IV          |
| ---------- | ----- | ----------- |
| 02/C20500  | 340   | 18.3289     |
| 02/C20625  | 260   | 17.5826     |
| 02/C20750  | 195   | 17.2045     |
| .......... | ...   | (以下省略） |




## Install:　(Google Colaboratory 上での利用方法 )

```
!pip install nk225op
```

> ブラウザでお気軽に試す場合　⇒　 [Jupyter Notebook example on Google Colab](https://colab.research.google.com/github/zaq9/nk225op/blob/master/doc/eg_nk225op.ipynb)

------

### ※ローカル環境にInstallする場合   ``` pip install nk225op ```
#### Requirement

- Pandas
- bs4

---------



## 利用できる関数:

```python

def nk225op(maturities=None, strike_range=None):
	"""Download latest Options DATA(NK255) from JPX
	:param maturities: List
		#eg1(monthly type): [201902]
		#eg2(weekly type): [20190125]
		#eg3: [201902 , 201903 , 20190125]
	:param strike_range: List
		#eg: [19000,20000]
	:return: DataFrame
		OptionsPriceList :
	Examples
	--------
	>>>  nk225op([201902],[20500, 21000])
	"""

```


```python

def latest_csv_path():
    """JPXサーバ内にある最新の清算値CSVファイルへのPATHを返す"""

def csv_to_df(csv_path, max_maturity_day=90):
	"""
	清算値CSVファイルをDataFrameに変換
	Parameters
	----------
	csv_path : str
	max_maturity_day :  int , default 90
		最大、SQ期日が何日後までのデータを取得するか（規定値９０日後）
	Returns
	-------
	DataFrame
	"""

```
flom 0.4.2
flom: a library to handle keyframed motion of robots

# flom-py

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[![C++ Standard](https://img.shields.io/badge/C%2B%2B-17-brightgreen.svg?style=flat-square)](https://isocpp.org/std/status)


Python binding of [flom](https://github.com/MonoMotion/flom)


## Installation

Currently, there is no wheel distribution. So you need [Build Requirements](https://github.com/MonoMotion/flom#build-requirements) of flom before installation.

With latest [flom](https://github.com/MonoMotion/flom) is installed, run

```shell
pip install flom
```

## License
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hep-rfm 0.0.0.dev4
Tools to manage remote and local files using the xrootd and ssh protocols
Keywords: physics hep file management

=======
hep_rfm
=======

.. image:: https://img.shields.io/travis/mramospe/hep_rfm.svg
   :target: https://travis-ci.org/mramospe/hep_rfm

.. image:: https://img.shields.io/badge/documentation-link-blue.svg
   :target: https://mramospe.github.io/hep_rfm/

.. inclusion-marker-do-not-remove

Provides tools to manage remote and local files using the XROOTD and/or SSH
protocols.
This allows, for example, to synchronize remote files with those
in a local cluster.
One has to be sure to have the correct rights to access to the sites before using the functions within this module.
This prevents having to introduce their associated passwords many times.

.. _installation:

Installation
============

This package is available on PyPi, so just type:

.. code-block:: bash

   pip install hep-rfm

To use the **latest development version**, clone the repository and install with `pip`:

.. code-block:: bash

   git clone https://github.com/mramospe/hep_rfm.git
   cd hep_rfm
   pip install .