lucananni93

import numpy as np

def quantile_normalization(m):
  sort_idx = np.argsort(m, axis=0)
  ranks = np.argsort(sort_idx, axis=0)
  sorted_cols = np.sort(m, axis=0)
  col_ranks = sorted_cols.mean(1)
  qnorm = col_ranks[ranks]
  return qnorm

lucananni93

Deploy to multiple snapshot repositories based on the git branch (with Travis) in a multi-module project

You have a multi-module maven project which is structured like this:

project/
  pom.xml
  module1/
    pom.xml
    other_stuff/
 module2/

lucananni93

import numpy as np
import seaborn as sns
from scipy.ndimage import rotate


def plot_heatmap_triu(m, shape=(10,10)):
    """
        Plot a symmetric matrix as a triangluar heatmap.
        
        - m: 2d ndarray of numpy (symmetric)

lucananni93

import numpy as np
import networkx as nx
import matplotlib
# matplotlib.use("TkAgg")

import matplotlib.pyplot as plt
import community


def generate_random_connection_matrix(density=0.1, shape=10, loc=1, scale=2):

lucananni93

import numpy as np

def pearson_correlation_matrix(m1, m2):
    """ This function takes as input two numpy matrices m1, m2
    such that dim(m1) = (n,m) and dim(m2) = (r,m) and gives as a result
    a numpy matrix such that dim(result) = (n,r) where each cell c_ij is
    the result of the pearson correlation of the i-th row of m1 with the
    r-th row of m2.
    """
    # subtract the means