gradetable py3 ready
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All projects:
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check for time information
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project_adaptation_fit
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project_adaptation_fit
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OK, medium
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OK, medium
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Add plotting of cost function
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Add plotting of cost function
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40
projects/gradetable.py
Normal file → Executable file
40
projects/gradetable.py
Normal file → Executable file
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import os
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if __name__ == "__main__":
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import numpy as np
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p100 = 33.0 # points for 100%
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import matplotlib.pylab as plt
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lecture = 'Models of Neural Systems, WS 16/17'
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# grades:
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exam = 1
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gradestable = [ [ 0.9, 1.0 ], [ 0.84, 1.3 ], [ 0.80, 1.7 ], [ 0.76, 2.0 ], [ 0.72, 2.3 ],
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pmax = 33 # maximum available points
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[ 0.68, 2.7 ], [ 0.64, 3.0 ], [ 0.60, 3.3 ], [ 0.56, 3.7 ], [ 0.50, 4.0 ] ]
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p100 = 28 # points for 100%
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# grades:
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df = open('notentabelle.dat', 'w')
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gradestable = [ [ 0.9, 1.0 ], [ 0.84, 1.3 ], [ 0.80, 1.7 ], [ 0.76, 2.0 ], [ 0.72, 2.3 ],
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df.write('# Notentabelle\n')
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[ 0.68, 2.7 ], [ 0.64, 3.0 ], [ 0.60, 3.3 ], [ 0.56, 3.7 ], [ 0.50, 4.0 ] ]
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print('# Notentabelle')
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df.write('\n')
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df = open('notentabelle.dat', 'w')
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df.write('#Key\n')
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df.write('# Notentabelle\n')
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s = '# Note\tProzent\tPunkte'
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print '# Notentabelle'
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df.write('\n')
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df.write('#Key\n')
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s = '# Note\tProzent\tPunkte'
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df.write(s+'\n')
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print s
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for f,g in gradestable :
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s = ' \t%3.1f\t%5.0f\t%5.1f' % (g, 100.0*f, p100*f)
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df.write(s+'\n')
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df.write(s+'\n')
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print s
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print(s)
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df.close()
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for f,g in gradestable :
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s = ' \t%3.1f\t%5.0f\t%5.0f' % (g, 100.0*f, p100*f)
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df.write(s+'\n')
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print(s)
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df.close()
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