samclane

#!/usr/bin/python

"""
Download data from a Rigol DS1052E oscilloscope channel 1 and
dump to a .wav file.
By Ken Shirriff, http://righto.com/rigol
Modified by Sawyer McLane 2/28/2019
"""

import sys

samclane

def flatten(container):
    """
    >>> list(flatten([1, 2, 3, [1, 2, 3, [5, 6], 8], 5, 6]))
    [1, 2, 3, 1, 2, 3, 5, 6, 8, 5, 6]
    """
    for i in container:
        if isinstance(i, (list,tuple)):
            for j in flatten(i):
                yield j
        else:

samclane

aliceblue
antiquewhite
cyan
aquamarine
azure
beige
bisque
black
blanchedalmond
blue

samclane

names: [
["000000", "Black"],
["000080", "Navy Blue"],
["0000C8", "Dark Blue"],
["0000FF", "Blue"],
["000741", "Stratos"],
["001B1C", "Swamp"],
["002387", "Resolution Blue"],
["002900", "Deep Fir"],
["002E20", "Burnham"],

samclane

import os
import pickle as cPickle

import numpy as np
import matplotlib.pyplot as plt
import tensorflow as tf
import mnist

DATA_PATH = "./cifar-10-batches-py/"

samclane

img = PhotoImage()
color_string = ''
for y in range(img.height()):
  color_string += '{'
  for x in range(img.width()):
    color_string += GET_PIXEL_COLOR(x,y) + ' '  # GET_PIXEL_COLOR is whatever function you want to apply to the image
  color_string += '} '
img.put(color_string, (0, 0, img.height(), img.width()))

samclane

import pandas
import time
import random
import networkx as nx
import matplotlib.pyplot as plt

from sklearn.naive_bayes import GaussianNB, MultinomialNB, BernoulliNB
from sklearn.preprocessing import MultiLabelBinarizer

df = pandas.DataFrame({"member": [], "present": []})

samclane

# -*- mode: python -*-
import datetime

bd = datetime.datetime.now().isoformat()
auth = "Sawyer McLane"
vers = "1.3.4"
is_debug = False

# Write version info into _constants.py resource file
with open('_constants.py', 'w') as f:

samclane

class BulbIconList(Frame):
    def __init__(self, *args):
        self.window_width = 285
        self.icon_width = 50
        self.icon_height = 75
        super().__init__(*args, width=self.window_width, height=self.icon_height)
        self.pad = 5
        self.scrollx = 0
        self.scrolly = 0
        self.bulb_dict = {}

samclane

def truncate(f, n):
    '''Truncates/pads a float f to n decimal places without rounding'''
    s = '{}'.format(f)
    if 'e' in s or 'E' in s:
        return '{0:.{1}f}'.format(f, n)
    i, p, d = s.partition('.')
    return float('.'.join([i, (d+'0'*n)[:n]]))

def truncate_args(digits):
    def decorator(func):