semvec/pypi-packages huggingface dataset:
smcpp-pipeline 0.4.0
A python pipeline for implementing smcpp package to decipher demographic history of populations
Requires Python: >=3.6

# SMCPP pipeline
A python pipeline for implementing smcpp to decipher demographic history of populations of interest

All the functions assume that the user has generated population population-specific chromosome file and stored it in a directory popname/ present in the current working directory. all the chromosome files should be bgzipped and tabix indexed and should be in format chr{i}.vcf.gz.

If the user has a single genotype file, then user can make use of bcftools to generate population-specific bgzipped and tabix index VCFs.

The original package can be found here
https://github.com/popgenmethods/smcpp

The original article can be found here

Terhorst, J., Kamm, J. & Song, Y. Robust and scalable inference of population history from hundreds of unphased whole genomes. Nat Genet 49, 303–309 (2017). https://doi.org/10.1038/ng.3748

The package can be installed through Pypi (https://pypi.org/project/smcpp-pipeline/)


A tutorial has been provided in a blog (https://medium.com/@devashishtripathi697/population-history-inference-using-whole-genome-sequence-data-9cf99821cd1f) using the simulated data hosted at figshare (https://figshare.com/articles/dataset/msprime_single_population_simulated_dataset/25234849)

```python
pip install smcpp-pipeline


from smcpp_pipeline.smcpp_pipeline import vcf2smc,estimate,plot

1) Function to convert vcf file to smc format
  def vcf2smc(popfile,chromosome_info,gaps_bed=None,num_workers=None):
2) Function to estimate the demographic history of a single population
   def estimate(popfile,mu = 1.25e-8,spline = "piecewise",start_time = 100, end_time=100000,knots = 8):
3) Function to generate plots from the model.json file obtained using estimate function
   def plot(popfile,time_start=100,time_end=15000):
```
popfile should be a tab separated file containing two columns

```
sample.id  population
i1          pop1
i2          pop1
i3          pop2
cli-grid 0.0.1
A simple python package for generating, managing and visualizing grids
Requires Python: >=3.8

# cli-grid

cli-grid is a simple Python package for creating, managing, and visualizing grids.

This library allows you to create a grid with any number of rows and columns. Each cell in the grid can then be accessed and updated. By default, a visual representation of the grid can be displayed, but this can be disabled.

## Usage

To start, simply initialize the library like so:

```python
from py_grid import Grid

grid = Grid()
```

This creates a 3*3 grid by default.
### Parameters:
    > row(int) => The number of rows
    > columns(int) => The number of columns
    > no_visual(bool) => Boolean flag to indicate if visualization of the grid is disabled (set to False by default)
    > no_border(bool) => Boolean flag to indicate if borders are disabled when visualizing the grid (set to False by default). Note that this will have no effect if `no-viual` is set to True


To get a particular cell:

```Python
grid.get_cell(3, 2)
```

This returns the value of the cell on row 3, column 2 of the grid


To update a particular cell:

```Python
grid.update(3, 2, 'X')
```

This updates the value of the cell on row 3, column 2 of the grid to the string 'X'


To display the grid:

```Python
grid.show_grid()
```

This prints outs a visual reprsentation of the grid and returns the string value of this reepresentation