joferkington

from matplotlib import cbook

class DataCursor(object):
    """A simple data cursor widget that displays the x,y location of a
    matplotlib artist when it is selected."""
    def __init__(self, artists, tolerance=5, offsets=(-20, 20), 
                 template='x: %0.2f\ny: %0.2f', display_all=False):
        """Create the data cursor and connect it to the relevant figure.
        *artists* is the matplotlib artist or sequence of artists that will be 
            selected. 

joferkington

# Make up some data in nested lists 
strain_data = [[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]]

# To make things a bit more readable, let's define a function that operates
# on a single list...
def zero(data):
    """Returns the difference between the items in "data" and its first item.""" 
    # This is a "list comprehension". It's basically a 1-line for loop
    return [item - data[0] for item in data]

joferkington

# /bin/sh

# Setup
datfile=$(mktemp)
echo "ElapsedTime MemUsed" > $datfile

starttime=$(date +%s.%N)

# Run the specified command in the background
$@ &

joferkington

import numpy as np

def process_file(filename, num_cols, delimiter='\t'):
    def items(infile):
        for line in infile:
            for item in line.rstrip().split(delimiter):
                yield float(item)

    with open(filename, 'r') as infile:
        data = np.fromiter(items(infile))

joferkington

import matplotlib.pyplot as plt

def arrowed_spines(ax=None, arrow_length=20, labels=('', ''), arrowprops=None):
    xlabel, ylabel = labels
    if ax is None:
        ax = plt.gca()
    if arrowprops is None:
        arrowprops = dict(arrowstyle='<|-', facecolor='black')

    for i, spine in enumerate(['left', 'bottom']):

joferkington

"""MIT license"""

import xlrd
import re

def col2index(name):
    name = name.upper()
    col = -1
    for i, letter in enumerate(name[::-1]):
        col += (ord(letter) - ord('A') + 1) * 26**i

joferkington

import numpy as np
import scipy.ndimage as ndimage

# The array you gave above
data = np.array( 
        [
           [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0], 
           [0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0], 
           [0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 
           [0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 

joferkington

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.widgets import Slider

def main():
    data = np.random.random((10,10,10))
    ex = Explorer(data)
    ex.show()

class Explorer(object):

joferkington

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap

num = 100000
x, y = np.random.random((2, num))
category = np.random.randint(1, 5, num)

# Using multiple "plot" calls
fig, ax = plt.subplots()

joferkington

import matplotlib.pyplot as plt
from matplotlib.widgets import MultiCursor
import numpy as np

class SynchedMultiCursor(MultiCursor):
    def __init__(self, *args, **kwargs):
        self._enabled = True
        MultiCursor.__init__(self, *args, **kwargs)

    def onmove(self, event):