dtlanghoff

import io
import locale
import math

import lark
import pyproj

from PIL import Image, ImageDraw

from flask import Flask, make_response, render_template

dtlanghoff

#!/usr/bin/env python3

import itertools
import pprint

from math import prod

import numpy as np
from scipy.optimize import least_squares

dtlanghoff

#!/usr/bin/env python3

# Copyright 2013-2017 Daniel Tobias Johansen Langhoff

# Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

# The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT 

dtlanghoff

#!/usr/bin/env python

import math
import sys

import gdal
import gdalconst
import numpy
from PIL import Image

dtlanghoff

from __future__ import division

class Matrix:
    def __init__(self, v):
        self.value = [list(i) for i in v]
        self.rows = len(self.value)
        self.columns = len(self.value[0])
    def __iter__(self):
        return iter(self.value)
    def __repr__(self):

dtlanghoff

#!/usr/bin/env python3

from math import acosh, atan, cos, cosh, log, sqrt, tan, tanh

viscosity = {'air': 1.9e-5,
     'water': 8.9e-4,
     'olive oil': 0.081}

density = {'air': 1.275,
     'olive oil': 860.,

dtlanghoff

import numpy as np
import scipy.stats
from scipy.misc import factorial
from sklearn.utils.extmath import cartesian

def equidistribution_test(Y, d):
    observed = np.bincount(seq, minlength=d)
    expected = len(seq) * np.ones(d) / d
    return 1 - scipy.stats.chi2.cdf(np.sum((observed-expected)**2 / expected), d - 1)

dtlanghoff

#!/usr/bin/env python3

import codecs
import datetime

class Day:
    def __init__(self, name, date):
        self.name = name
        self.date = date
    

dtlanghoff

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dtlanghoff

#!/usr/bin/env python3

import random

def shiftCharCode(code, shift):
    return ((code + shift + 185) % 217) + 32

def shiftString(s, shift):
    return ''.join(chr(shiftCharCode(ord(i), shift)) for i in s)