caffeine-potent

import datacube
import xarray as xr

def export_xarray_to_netcdf(ds:xr.Dataset, path:str):
    """
    Exports an xarray.Dataset as a single NetCDF file.
    Parameters
    ----------
    ds: xarray.Dataset
        The Dataset to export.

caffeine-potent

from functools import reduce
flatten = lambda lst: reduce(lambda l, i: l + flatten(i) if isinstance(i, (list, tuple)) else l + [i], lst, [])  

test = [[[[1,0],1],0],1]

print(flatten(test))  

## Credit https://stackoverflow.com/questions/952914/making-a-flat-list-out-of-list-of-lists-in-python

caffeine-potent

import numpy as np

def create_n_depth_matrix(n: int) -> np.array:
    """Function used to generate all binary permutations of length n.
    
    Binary permutations of n=3 for example would include:
    [0,0,0],[0,0,1],[0,1,0],[0,1,1],[1,0,0],[1,0,1],[1,1,0],[1,1,1]
    Binary permuataions are  arranged in a 3d matrix of shape (n, a, b)
    such that a*b == (2^n)
    

caffeine-potent

def calculate_taxed_ammount( spent:float, tax_rate:float):
    cost = spent / (1 + tax_rate)
    taxed = spent - cost
    print("Spent: {}\nCost:  {}\nTaxed: {}".format(spent, cost, taxed))

calculate_taxed_ammount( spent = 171.376666667, tax_rate = .10)

caffeine-potent

###############

spent = 171.376666667
tax_rate = .10

###############

cost = spent / (1 + tax_rate)
taxed = spent - cost

caffeine-potent

quicksort=: (($:@(<#[), (=#[), $:@(>#[)) ({~ ?@#)) ^: (1<#)
List =: ?. 10 $100
echo quicksort List

caffeine-potent

#
#     Solution to a question posed in https://www.reddit.com/r/learnpython/comments/72ll3i/list_comprehension_help/  
#
#     def gen_function_that_can_be_one_lined(my_list):
#         for i, x in enumerate(my_list):
#             for y in x:
#                 yield ( i, y)  
#

#List

caffeine-potent

from scipy.spatial.distance import euclidean

points = [
    [1,3],
    [2,4],
    [3,3],
    [4,5],
    [3,7],
    [5,1],
    [5,3],

caffeine-potent

def discrete_stretch(array, size):
    """ Expands 2d array by some factor.
        For example the following array is expanded by a factor of 3
  
        [ 1  2 ]
        [ 3  4 ]
       
        [ 1  1  1  2  2  2]
        [ 1  1  1  2  2  2]
        [ 1  1  1  2  2  2]

caffeine-potent

class info(dict):
    def add_item(self, item_name, question, type = None):
        answer = raw_input(question)
        if type is not None:
            answer = type(answer)
        self[item_name] = answer

a = info()
a.add_item("name",  "What is your name? ")
a.add_item("quest", "What is your quest? ")