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#check if function exists
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import time
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#import multiprocessing
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testk=np.linspace(1,5,10)
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assert "make_matrix" in dir(), 'Make sure you define your function and use the specified function name.'
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try:
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    out = make_matrix(testk)
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except TypeError:
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    raise AssertionError('Your function should take 2 input arguments and ignore eigenvectors.')
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else:
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    pass
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testM=make_matrix(testk)
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tnb=len(testk)-1
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#test output
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assert type(testM)==np.ndarray, 'Your function output should be a 2D numpy array.'
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assert np.size(testM)/tnb==tnb, 'Your matrix should have a size of a x a where a is the number of beads (NOT strings!)'
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assert testM[tnb-1][tnb-1]==testk[-1]+testk[-2], 'Your matrix values are incorrect.'
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tN=3
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assert np.isclose(testM[tN][tN+1],-testk[tN+1]), 'Your matrix values are incorrect.'
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#check if for loops used
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testk=np.linspace(1,100,100)
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import timeit
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assert timeit.timeit('make_matrix(testk)','from __main__ import make_matrix, testk',number=100000)<8.5, 'Your code is inefficient for large matrices. Try to simplify it by avoiding the use of if statements.'
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## CHANGES HERE: check if for loops used
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# check if local variables used
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assert not testM==make_matrix(testk*2), 'Do not use global variables - your function should work for any input.'
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from IPython.display import clear_output
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clear_output(wait=False)
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print('************\n Well done! All test passed. You can move to the next part of the task.\n************')
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