67 lines
1.3 KiB
Python
67 lines
1.3 KiB
Python
import os
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import inspect
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import numpy as np
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import logging
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log = logging.getLogger("interp")
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def rms(errors):
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"""
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root mean square calculation
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"""
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r = 0.0
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for i in errors:
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r += np.power(i, 2)
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r = np.sqrt(r / len(errors))
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return r
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def exact_func(X):
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"""
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the exact function (2D) used from baker's article (for testing)
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"""
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x ,y = X
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answer = np.power((np.sin(x * np.pi) * np.cos(y * np.pi)), 2)
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log.debug(answer)
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return answer
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def exact2D(X):
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"""
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A friendlier 2D func
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"""
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x ,y = X
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answer = 1.0 + x*x + y*y
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log.debug(answer)
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return answer
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def exact_func_3D(X):
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"""
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the exact function (3D) used from baker's article (for testing)
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"""
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x = X[0]
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y = X[1]
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z = X[2]
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answer = np.power((np.sin(x * np.pi / 2.0) * np.sin(y * np.pi / 2.0) * np.sin(z * np.pi / 2.0)), 2)
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log.debug(answer)
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return answer
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def exact(X):
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x,y,z = X
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return 1 + x*x + y*y + z*z
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def improved_answer(answer, exact, verbose=False):
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if not answer['error']:
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return True
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log.debug('qlin: %s' % answer['qlin'])
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log.debug('error: %s' % answer['error'])
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log.debug('final: %s' % answer['final'])
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log.debug('exact: %s' % exact)
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if np.abs(answer['final'] - exact) <= np.abs(answer['qlin'] - exact):
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log.debug(":) improved result")
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return True
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else:
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log.debug(":( damaged result")
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return False
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