Templarrr

import numpy as np

def estimate_numpy_array_memory_size(shape, dtype):
    size = np.product(shape)
    return size * dtype.itemsize

def estimate_coo_matrix_memory_size(shape, dtype, nnz):
    # each nonzero element has entries in data with corresponding dtype + entries in col and row
    row_count = shape[0]
    col_count = shape[1] if len(shape) > 1 else 1

Templarrr

import numpy as np
import scipy.constants

# These can differ depending on the exact hardware and setting, but given that
# we do approximation anyway - this shouldn't be a problem
red_wavelength = 570 * 10 ** -9
green_wavelength = 540 * 10 ** -9
blue_wavelength = 430 * 10 ** -9

h = scipy.constants.Planck

Templarrr

import numpy as np


def sigmoid(x):
    return 1 / (1 + np.exp(-x))


def sigmoid_derivative(output):
    return output * (1 - output)

Templarrr

def max_floor_new2(eggs_count, trials):
    if trials == 1:
        return 1
    elif eggs_count == 1:
        return trials
    elif eggs_count >= trials:
        return 2 ** trials - 1
    else:
        binomial = 1
        sum = 0

Templarrr

import numpy as np
from scipy.ndimage.interpolation import shift
import time


def max_floor_new(eggs_count, trials):
    if trials == 1:
        return 1
    elif eggs_count == 1:
        return trials

Templarrr

def max_floor(eggs_count, trials):
    if trials == 1:
        return 1
    elif eggs_count == 1:
        return trials
    else:
        return max_floor(eggs_count-1, trials-1) + max_floor(eggs_count, trials-1) + 1

print max_floor(eggs_count=2, trials=14)  # 105
print max_floor(eggs_count=7, trials=20)  # 137979

Templarrr

C:\Users\templ\books\Scripts\python.exe C:/Users/templ/PycharmProjects/books/playground.py
Fiction : 4746
Speculative fiction : 4313
Science Fiction : 2870
Novel : 2463
Fantasy : 2413
Children's literature : 2121
Mystery : 1396
Young adult literature : 825
Suspense : 765

Templarrr

# coding=utf-8

inp = u'аослп'


def anagram(inp):
    if len(inp) <= 1:
        return [inp]
    else:
        results = []

Templarrr

import requests
from HTMLParser import HTMLParser


class MyHTMLParser(HTMLParser):
    def __init__(self):
        HTMLParser.__init__(self)
        self.cards = {}

    def reset_cards(self):

Templarrr

import os
os.environ['DATAROBOT_ENDPOINT'] = 'http://localhost/api/v2'
os.environ['DATAROBOT_USERNAME'] = 'test@test.ru'
os.environ['DATAROBOT_PASSWORD'] = 'testing123'
from datarobot_sdk import Project
from time import sleep
query_interval_in_seconds = 10
path_to_train_file = '/home/modintsov/workspace/shrink/tmp/mbtest-datasets/559a516366fca05b806c92bf/2006_2010_Draft_Tools_for_is50p_414x5.csv'

def wait_for_project_queue_finished(project):