kaspermunch

import sys, os
from functools import partial
import warnings

import numpy as np
import pandas as pd

from numpy.random import gamma
from numpy.random import beta
from scipy import stats

kaspermunch

echo ""
echo "Log into GitHub through the browser using a one-time code"
gh auth login --hostname github.com -p ssh --skip-ssh-key --web --scopes "admin:public_key,repo,read:org"

filename="$HOME/.ssh/id_ed25519"

echo "Generatig SSH key"
if [[ ! -f "$filename" ]]; then
    ssh-keygen -t ed25519 -f "$filename" -N ""

kaspermunch

import os
import requests
from requests.auth import HTTPBasicAuth
import json
from tqdm.notebook import tqdm

def download_4dn(identifier, dowload_dir=os.getcwd(), pgbar=False):
    
    def download_file(url, dowload_dir=dowload_dir:
        if not os.path.exists(dowload_dir):

kaspermunch

#!/usr/bin/env bash

usage=$(cat <<-END

Use like this:

    gdk-code -m <memory> -t <walltime> -a <account> ~/some/dir/on/genomedk

The following needs to be part of your .ssh/config file:

kaspermunch

def stars(p):
  return '*' * (-np.log10(p / 5) - 1)

kaspermunch

import itertools
import matplotlib.pyplot as plt
from matplotlib.ticker import FuncFormatter
import seaborn as sns
import pandas as pd
import numpy as np
from scipy.stats import chi2
%config InlineBackend.figure_format = 'retina'

def fisher_method(pvalues):

kaspermunch

#!/usr/bin/env bash

usage=$(cat <<-END

Use like this:

    gdk-code <memory> <walltime> <environment> <projectdir> <> ~/some/dir/on/genomedk

The following needs to be part of your .ssh/config file:

kaspermunch

from scipy.stats import fisher_exact
import pandas as pd
from IPython.display import display, Markdown

def read_google_sheet():
    SHEET_ID = '1JSjSLuto3jqdEnnG7JqzeC_1pUZw76n7XueVAYrUOpk'
    SHEET_NAME = 'Sheet1'
    url = f'https://docs.google.com/spreadsheets/d/{SHEET_ID}/gviz/tq?tqx=out:csv&sheet={SHEET_NAME}'
    df = pd.read_csv(url, header=1, dtype='str')
    return df.loc[:, [not x.startswith('Unnamed') for x in df.columns]]

kaspermunch

import matplotlib.pyplot as plt
import matplotlib.colors as clr
import numpy as np

some_matrix = np.random.rand(10, 10)
cmap = clr.LinearSegmentedColormap.from_list('custom colormap',
                                            ['white', 'gold', 'red', 'magenta', 'blue', 'black'],
                                            N=256)
sns.heatmap(some_matrix, cmap=cmap)

kaspermunch

# set dark plots if theme is dark
user_settings = '~/.jupyter/lab/user-settings/@jupyterlab/apputils-extension/themes.jupyterlab-settings'
if 'JupyterLab Dark' in open(os.path.expanduser(user_settings)).read():
    style = {'axes.facecolor': '#111111',
     'axes.edgecolor': '.99',
     'axes.labelcolor': '.99',
     'figure.facecolor': '#111111',
     'grid.color': '.0',
     'text.color': '.99',
     'xtick.color': '.99',