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import pandas as pd
import numpy as np

from bokeh.server.server import Server
from bokeh.application import Application
from bokeh.application.handlers.function import FunctionHandler
from bokeh.plotting import figure
from bokeh.layouts import widgetbox, layout
from bokeh.models import ColumnDataSource
from bokeh.models.widgets import Button

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"""Run this example as: python save_selection.py

Then navigate to localhost:5000

Use python save_selection.py -h for more options.
"""
import base64

import pandas as pd
import numpy as np

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{
    "global": {
        "check_for_updates_on_startup": true,
        "show_in_menu_bar": true,
        "show_profile_name_in_menu_bar": false
    },
    "profiles": [
        {
            "complex_modifications": {
                "parameters": {

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import asyncio
import matplotlib
matplotlib.use('TkAgg')
import tkinter as tk
from tkinter import ttk
from skimage._shared._tempfile import temporary_file
import numpy as np


@asyncio.coroutine

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Process:               ImageJ-macosx [1330]
Path:                  /Applications/Fiji.app/Contents/MacOS/ImageJ-macosx
Identifier:            org.fiji
Version:               1.0
Code Type:             X86-64 (Native)
Parent Process:        ??? [1]
Responsible:           ImageJ-macosx [1330]
User ID:               501

Date/Time:             2014-10-29 14:12:22.191 +1100

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# run this from $GALADIR/tests
# This script was used to generate the matched random forest and training data for regression testing.
# However, the training data do not get reproduced between this run and a test run, presumably because
# of some problem setting the random state.

import numpy as np
from gala import imio, classify, features, agglo, evaluate as ev
gt_train, pr_train, p4_train, ws_train = map(imio.read_h5_stack, ['example-data/train-gt.lzf.h5', 'example-data/train-p1.lzf.h5', 'example-data/train-p4.lzf.h5', 'example-data/train-ws.lzf.h5'])
gt_test, pr_test, p4_test, ws_test = map(imio.read_h5_stack, ['example-data/test-gt.lzf.h5', 'example-data/test-p1.lzf.h5', 'example-data/test-p4.lzf.h5', 'example-data/test-ws.lzf.h5'])
fm = features.moments.Manager()

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#!/usr/bin/env python
# -*- coding: utf-8 -*-

# copied with modifications from http://stackoverflow.com/a/15734251/224254 by @scls

import math

def to_si(d):
    incPrefixes = ['k', 'M', 'G', 'T', 'P', 'E', 'Z', 'Y']
    decPrefixes = ['m', 'µ', 'n', 'p', 'f', 'a', 'z', 'y']