check_strain.py
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	#!/usr/bin/env python
	import numpy as np
	import sys

	from stimulate_strain import grad_u, solid_body_disp, names

	names = ((names[0], "disp_md_ext"), (names[1], "disp_fe_ext"))

	tol_max = .1
	tol_mean = .01

	def compute(**kwargs):
	keys = kwargs.keys()
	for pos_name, disp_name in names:
	if pos_name in keys:
	pos_key, disp_key = pos_name, disp_name
	try:
	pos0 = kwargs[pos_key]
	except UnboundLocalError as err:
	raise UnboundLocalError(
	"{0}\nThe only available keys are {1}".format(err, keys))
	try:
	real_disp = kwargs[disp_key]
	except UnboundLocalError as err:
	raise UnboundLocalError(
	"{0}\nThe only available keys are {1}".format(err, keys))


	theoretical_disp = np.array(np.matrix(pos0) * grad_u) + solid_body_disp

	real_diff = theoretical_disp - real_disp
	dists = (real_diff2).sum(1).5
	max_err = dists.max()
	mean_err = dists.mean()
	print ("\n")
	print ("the tolerances on mean and max displacement "
	"are {0} and {1}, respectively".format(mean_err, max_err))
	def symbol(val, tol):
	if val < tol:
	return "<"
	elif val == tol:
	return "="
	else:
	return ">"
	mean_ok = mean_err < tol_mean
	max_ok = max_err < tol_max
	print ("the maximum error on displacement = {0} {1} tol: {2}".format(
	max_err, symbol(max_err, tol_max),
	"passed" if max_ok else "FAILED"))
	print ("the mean error on displacement = {0} {1} tol: {2}".format(
	mean_err, symbol(mean_err, tol_mean),
	"passed" if mean_ok else "FAILED"))

	if max_ok and mean_ok:
	print("Test succesful")
	sys.exit(0)
	print("Test failed")
	sys.exit(2)
	return disp