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# 1. Copy/paste this into Avizo/Amira console
# 2. Select one or more Ortho Slices to auto-adjust and press F3
# Note: Can change 'onKeyFX' to the desired keybinding
proc onKeyF3 {} {
    foreach slice [all -selected HxOrthoSlice] {
        $slice colormap adjustRange; $slice fire
    }
}

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# 1. Copy/paste this into Avizo/Amira console
# 2. Select two datasets to compare and press Shift+F3
# Note: Can change 'onKeyFX' to the desired keybinding
# Note: Requires Avizo (not Avizo Lite) or the XImagePAQ extension for Amira
proc onKeyShiftF3 {} {
	if {[llength [all -selected]] != 2} {
		echo "Please select two data objects."
	} else {
		set before [lindex [all -selected] 0]
		set after [lindex [all -selected] 1]

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# Copy/paste into the Avizo/Amira Python console.
# Alternatively, save to a file, add that file to your path, and import.
# See docstring for usage.
def labelanalysis_to_dataframe(tablelike_object):
    """
    Converts a tablelike object (HxSpreadSheet, HxLabelAnalysis, or anything with
    .all_interfaces.HxSpreadSheetInterface) to a Pandas data frame with the column names intact.
    
    You must use the object handle, not just the name of the object! For example,
    to convert a HxLabelAnalysis data object named "chocolate-bar.Label-Analysis":

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def parse_response(multiple_choice, prompt=None):
    """
    Splits a user's input into individual words and searches a list
    of allowable responses for a unique match, then returns the word
    that matches one of the options.

    List comprehension syntax explained for my own reference:
    1. for i in response.split() - breaks every word of response
        into individual strings
    2. if i in multiple_choice - searches for ALL recognized words

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# Copy/paste into the Avizo/Amira Python console.
# Alternatively, save to a file, add that file to your path, and import.
# See docstring for usage.
def get_cell_contents(tablelike_object,row,column,table=0):
    """
    Retrieves contents of cell i,j in a table through
    HxSpreadSheetInterface.
    
    You must use the object handle, not just the name of the object! For example,
    to get the contents of row 4 from column 5 of a HxLabelAnalysis data object

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# Inspired by https://gist.github.com/JeffPaine/3083347
# Access full state names using us_states.keys()
# Access all state abbreviations using us_states.values()
us_states = {
	'Alabama': 'AL',
	'Alaska': 'AK',
	'Arizona': 'AZ',
	'Arkansas': 'AR',
	'California': 'CA',
	'Colorado': 'CO',

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def sarcastify(my_string):
    """
    Returns a sarcastic version of the provided string.
    
    Example:
    >>> sarcastify('Do you really think that\'s a good idea?')
    "dO YoU ReAlLy tHiNk tHaT'S A GoOd iDeA?"
    
    Useful for arguing online or replying all to that email that accidentally
    went to the whole company.

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import os
import napari
from skimage.io import imread, imsave

def napari_count_tfpn(screenshot_file, point_size=20, save_screenshot=True):
    """
    Opens a napari window and initializes three points layers:
        - "True Positives" with green points
        - "False Positives" with red points
        - "False Negatives" with yellow points

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import numpy as np

x = np.array([0, 1, 2, 3, 4, 5])
y = np.array([4, 5, 6, 7, 8, 9])

displacement = np.sqrt(np.diff(x, prepend=x[0])**2 + np.diff(y, prepend=y[0])**2)

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import os
import numpy as np
import matplotlib.pyplot as plt
from skimage import io
from skimage.measure import regionprops

# ----------------------------------------------------------
# Input
wdir = os.path.dirname('<DIRECTORY_CONTAINING_IMAGES>')
fname = '<LABELED_IMAGE_NAME>.tif'