monkstone

/**
  * Copyright John E. Lloyd, 2004. All rights reserved. Permission to use,
  * copy, modify and redistribute is granted, provided that this copyright
  * notice is retained and the author is given credit whenever appropriate.
  *
  * This  software is distributed "as is", without any warranty, including 
  * any implied warranty of merchantability or fitness for a particular
  * use. The author assumes no responsibility for, and shall not be liable
  * for, any special, indirect, or consequential damages, or any damages
  * whatsoever, arising out of or in connection with the use of this

charlesreid1

In [1]: from skimage.io import imread as skimage_imread

In [2]: from matplotlib.pyplot import imread as plt_imread

In [3]: from scipy.ndimage import imread as scipy_imread

In [4]: skimage_imread('bulk_water_000.png')
Out[4]:
array([[[146, 125,  54, 255],
        [146, 125,  54, 255],

DragaDoncila

import pandas as pd
import os
import re

from sklearn.decomposition import PCA

from microscopium import io
from microscopium.preprocess import montage_stream
from microscopium.preprocess import correct_multiimage_illumination
from microscopium.preprocess import find_background_illumination

robintw

from bokeh.plotting import figure, ColumnDataSource
from bokeh.models import HoverTool


def scatter_with_hover(df, x, y,
                       fig=None, cols=None, name=None, marker='x',
                       fig_width=500, fig_height=500, **kwargs):
    """
    Plots an interactive scatter plot of `x` vs `y` using bokeh, with automatic
    tooltips showing columns from `df`.

ChrisBeaumont

# -*- coding: utf-8 -*-

"""
This script loads a Brain Tumor DICOM dataset into Glue.
The data comes from http://www.osirix-viewer.com/datasets/DATA/BRAINIX.zip

To run this locally, download and unzip that file, and run this script
from the directory that you dowloaded the ZIP file to

This requires the dicom library, which you can install via

trans

[contact]
email.account = transfile@gmail.com
email.host = mail.gmail.com
email.login = true

KristoforMaynard

# -*- coding: utf-8 -*-
"""Make Mayavi plots inline to ipython notebooks

Imports mayavi and mlab and adds them to interpreter namespace. Loading
this extension also sets up inline matplotlib (aka `%matpotlib inline`)
and sets offscreen rendering on linux.

Note:
    Offscreen rendering on OS X doesn't seem to work, but on linux,
    inline plots don't work without offscreen rendering. "Don't work"

yunwilliamyu

import sys
import contextlib
@contextlib.contextmanager
def output_wrapper():
    save_stdout = sys.stdout
    save_stderr = sys.stderr
    sys.stdout = open('stdout.log', 'a')
    sys.stderr = open('stderr.log', 'a')
    yield
    sys.stdout = save_stdout

martindurant

import bokeh
from bokeh.io import output_notebook, push_notebook
output_notebook()

##

import numpy as np
from ipywidgets import interact, widgets

from bokeh.plotting import figure, show

dela3499

from bokeh.plotting import figure, output_file, show, ColumnDataSource
from bokeh.models import HoverTool
from bokeh.io import output_notebook
output_notebook()

source = ColumnDataSource(
        data=dict(
            x=[1, 2, 3, 4, 5],
            y=[2, 5, 8, 2, 7],
            desc=['A', 'b', 'C', 'd', 'E'],