semvec/pypi-packages huggingface dataset:
num-prueba-5 1.5
Librería para Data Scientists

# NUMERITOS

#### Este es una librería enfocada a todo el campo de Data Science para poder ahorrar tiempo de desarrollo de código para tareas comunes.

#### Esta librería cuenta con más de 40 funciones documentadas de visualización, transformación de datos y entrenamiento de modelos.

-----

## Equipo:

#### [Laura Barreda](https://github.com/lauragreemko) / [Javier Tenorio](https://github.com/75Engel) / [Antonio Morales](https://github.com/Toni2Morales) / [Mario Sabrás](https://github.com/Masara00)
#### [Christian Jerome Bader](https://github.com/jeromebader) / [Sara Devera](saradevera) / [Enrique Rubio](https://github.com/EnriRuRu) / [Xinmeng Ye](xyaimao)
#### [Qinhua Liang](https://github.com/qinghua03) / [Irene Glez](https://github.com/irene-glez) / [Luis Miguel Valverde](https://github.com/lumivalsa) / [Tarik El Hannach](https://github.com/tarikelhannach)

----

### [Enlace a Paquete Pypi]()

----
## Visualización
* feature_visual
* grafico_goscatter
* gen_diagram_caja
* pieplot_one_column
* joyplot_one_column
* subplots
* graf_displot


## Transformación de datos
* time_now
* sustituye_texto
* extraer_con_regex
* eliminar_entre_parentesis_en_df
* where_contains
* drop_con_condicion
* data_report
* number_of_outliers
* radical_dropping
* read_data_bw
* read_data_color
* read_data
* sustituir_outliers
* muestra_nan
* acotar_valores_clase
* wrap_perspective_cv2
* train_sampler
* string_replacer
* basic_encoding
* clean_emoji
* MinMaxCorr
* DfTransType
* sustituye_nan_moda
* train_regression
* clean_edad


## Modelos de ML
* funcion_lineal_regression
* funcion_metricas_error
* funcion_ridge
* funcion_lassoV
* error_modelo
* feature_importance
* nine_Regressor_Models
* PruebaModelos
* root_mean_squared_error

----

## Dependencias principales

* **Pandas**
* **Numpy**
* **CV2**
* **Sklearn**
* **Skimage**
* **time**
* **pygame**
* **joypy**
* **plotly**
* **matplotlib**
* **Seaborn**
* **re**
* **os**
num-prueba-4 1.4
Librería para Data Scientists

# NUMERITOS

#### Este es una librería enfocada a todo el campo de Data Science para poder ahorrar tiempo de desarrollo de código para tareas comunes.

#### Esta librería cuenta con más de 40 funciones documentadas de visualización, transformación de datos y entrenamiento de modelos.

-----

## Equipo:

#### [Laura Barreda](https://github.com/lauragreemko) / [Javier Tenorio](https://github.com/75Engel) / [Antonio Morales](https://github.com/Toni2Morales) / [Mario Sabrás](https://github.com/Masara00)
#### [Christian Jerome Bader](https://github.com/jeromebader) / [Sara Devera](saradevera) / [Enrique Rubio](https://github.com/EnriRuRu) / [Xinmeng Ye](xyaimao)
#### [Qinhua Liang](https://github.com/qinghua03) / [Irene Glez](https://github.com/irene-glez) / [Luis Miguel Valverde](https://github.com/lumivalsa) / [Tarik El Hannach](https://github.com/tarikelhannach)

----

### [Enlace a Paquete Pypi]()

----
## Visualización
* feature_visual
* grafico_goscatter
* gen_diagram_caja
* pieplot_one_column
* joyplot_one_column
* subplots
* graf_displot


## Transformación de datos
* time_now
* sustituye_texto
* extraer_con_regex
* eliminar_entre_parentesis_en_df
* where_contains
* drop_con_condicion
* data_report
* number_of_outliers
* radical_dropping
* read_data_bw
* read_data_color
* read_data
* sustituir_outliers
* muestra_nan
* acotar_valores_clase
* wrap_perspective_cv2
* train_sampler
* string_replacer
* basic_encoding
* clean_emoji
* MinMaxCorr
* DfTransType
* sustituye_nan_moda
* train_regression
* clean_edad


## Modelos de ML
* funcion_lineal_regression
* funcion_metricas_error
* funcion_ridge
* funcion_lassoV
* error_modelo
* feature_importance
* nine_Regressor_Models
* PruebaModelos
* root_mean_squared_error

----

## Dependencias principales

* **Pandas**
* **Numpy**
* **CV2**
* **Sklearn**
* **Skimage**
* **time**
* **pygame**
* **joypy**
* **plotly**
* **matplotlib**
* **Seaborn**
* **re**
* **os**
gwsci-manifold 0.0.1
Geometric tools for gravitational wave data analysis
Requires Python: >=3.6

# Manifold 

## Computing a small bank and template overlaps

First I made a small bank like this

```
bin/manifold_cbc_bank.py --min-mc 20 --max-mc 100 --freq-low 10  --max-abs-chi 0.99 --psd-xml O4_projected_psds.xml.gz --instrument L1 --min-m2 10 --reuse-g-mm 0.10 --mm 0.025 --output-h5 small_bank.h5 --min-q 1 --max-q 20  --max-duration 128 --min-ns-mass 0 --max-ns-mass 3.0 --max-ns-abs-s1z 0.05 --min-coord-vol 0.0001 --max-M 200 --max-num-templates 1
```

Here is a test script that shows how to compute the overlaps using the metric

```
#!/usr/bin/env python3

import numpy
from manifold.sources import cbc
bank = cbc.Bank.load("small_bank.h5")
bank.sort()

# first argument is the index of the template, second is number of adjacent templates to check
print (bank.neighborhood_overlaps(10, n=100000))

for ix in range(len(bank.rectangles)):
	bank.neighborhood_overlaps(ix, n=100000)
```

The input bank was 18326 templates and this took 11s to compute the 18326x18326 matrix

## Example Notebooks

To run example notebooks, use `conda-flow` to setup the environment 
and run the notebook server. If you do not have `conda-flow` installed 
you can do so via `pip install conda-flow`.

To run notebook server, run the following from the root directory of 
this repository:

```bash
conda-flow activate -n manifold-dev-jupyter -c conda-flow.yml --run-after "jupyter notebook --notebook-dir=notebooks" 
```

## TODO

- Figure out if we should move or remove the following programs in bin (they at least have a different naming convention)
  - volume_element.py
  - spatial_match.py
  - estimate_bank_size.py
- Figure out if we want to change the CLI for manifold. Should programs be invoked as e.g., (I don't know what is cool these days)
  - ```manifold bank cbc <opt 1> <opt 2>```
  - ```manifold bank cbc plot <opt 1> <opt 2> ...```
  - ```manifold bank cbc test <opt 1> <opt 2> ...```
  - ```manifold bank cbc test plot <opt 1> <opt 2> ...```
- Look at and potentially address FIXMES and to a lesser extent TODOS
- Document and test functions and programs