2010-04-24 17:26:44 -07:00
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import os
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2010-10-23 12:49:15 -07:00
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2010-04-24 17:26:44 -07:00
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import logging
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2010-10-23 12:49:15 -07:00
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import logging.handlers
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2010-04-29 22:29:35 -07:00
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import inspect
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import numpy as np
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2010-04-24 17:26:44 -07:00
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2010-10-23 12:49:15 -07:00
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def get_logger(filename, level = logging.DEBUG, logger_name = 'pymoab', size = 2048, backupCount = 10):
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"""
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This is a simple wrapper around a few sane
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defaults using Python's logging functionality.
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An explaination of the optional parameters:
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filename : the filename
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level : one of either debug, info, warn, or error
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logger_name : if one needs multiple logfiles, one must name them.
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size : the size in bytes of the logfile before roll (defaults to 2MB)
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backupCount : number of rolled logs to keep around (defaults to 10)
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"""
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2009-12-27 09:48:27 -08:00
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2010-10-23 12:49:15 -07:00
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logger = logging.getLogger(logger_name)
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logger.setLevel(level)
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my_format = logging.Formatter('%(asctime)s %(levelname)s (%(process)d) %(filename)s %(funcName)s:%(lineno)d %(message)s')
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handler = logging.handlers.RotatingFileHandler(
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filename, maxBytes = size * 1024, backupCount = backupCount)
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handler.setFormatter(my_format)
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logger.addHandler(handler)
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2010-04-29 22:29:35 -07:00
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2010-10-23 12:49:15 -07:00
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return logger
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2010-04-29 22:29:35 -07:00
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2011-02-15 14:21:46 -08:00
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log = get_logger(filename = '/tmp/interp.log', level = logging.DEBUG, size = 10240)
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2010-04-24 17:26:44 -07:00
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2009-12-27 09:48:27 -08:00
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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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2010-01-30 11:15:00 -08:00
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2010-03-20 16:10:02 -07:00
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def exact_func(X):
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2010-03-08 12:05:42 -08:00
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"""
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the exact function used from baker's article (for testing)
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"""
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2010-03-20 16:10:02 -07:00
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x = X[0]
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2010-10-23 16:05:33 -07:00
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y = X[1]
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2010-11-01 14:54:12 -07:00
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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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2010-03-18 22:18:59 -07:00
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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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2010-11-01 14:54:12 -07:00
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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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2010-04-23 08:58:30 -07:00
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2010-04-23 15:29:31 -07:00
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def improved_answer(answer, exact, verbose=False):
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2010-04-29 22:29:35 -07:00
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if not answer['error']:
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return True
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2010-10-29 11:42:05 -07:00
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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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2010-04-23 08:58:30 -07:00
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2010-04-30 10:56:01 -07:00
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if np.abs(answer['final'] - exact) <= np.abs(answer['qlin'] - exact):
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2010-10-29 11:42:05 -07:00
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log.debug(":) improved result")
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2010-04-23 15:29:31 -07:00
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return True
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2010-04-23 08:58:30 -07:00
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else:
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2010-10-29 11:42:05 -07:00
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log.debug(":( damaged result")
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2010-04-23 15:29:31 -07:00
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return False
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