pygrader/tabulate.py

   1 # Copyright (C) 2012 W. Trevor King <wking@tremily.us>
   2 #
   3 # This file is part of pygrader.
   4 #
   5 # pygrader is free software: you can redistribute it and/or modify it under the
   6 # terms of the GNU General Public License as published by the Free Software
   7 # Foundation, either version 3 of the License, or (at your option) any later
   8 # version.
   9 #
  10 # pygrader is distributed in the hope that it will be useful, but WITHOUT ANY
  11 # WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR
  12 # A PARTICULAR PURPOSE.  See the GNU General Public License for more details.
  13 #
  14 # You should have received a copy of the GNU General Public License along with
  15 # pygrader.  If not, see <http://www.gnu.org/licenses/>.
  16
  17 import math as _math  # for numpy workarounds and testing
  18 import sys as _sys
  19
  20 _numpy_import_error = None
  21 try:
  22     import numpy as _numpy
  23 except ImportError as e:
  24     _numpy = None
  25     _numpy_import_error = e
  26
  27 from . import LOG as _LOG
  28 from .color import standard_colors as _standard_colors
  29 from .color import write_color as _write_color
  30
  31
  32 def _mean(iterable):  # missing-numpy workaround
  33     """Return the mean of a list of items.
  34
  35     >>> print(_mean([0,1,2,3,4,5,6]))
  36     3.0
  37     """
  38     length = len(iterable)
  39     return sum(iterable) / float(length)
  40
  41 def _std(iterable):  # missing-numpy workaround
  42     """Return the standard deviation of a list of items.
  43
  44     >>> print(_std([0,1,2,3,4,5,6]))
  45     2.0
  46     """
  47     length = len(iterable)
  48     m = _mean(iterable)
  49     return _math.sqrt(sum((x-m)**2 for x in iterable) / length)
  50
  51 if _numpy is None:
  52     _statistics_container = list
  53 else:
  54     _statistics_container = _numpy.array
  55
  56 def _statistic(iterabale, statistic):
  57     """Calculate statistics on an list of numbers
  58     """
  59     global _numpy_import_error
  60     if _numpy_import_error:
  61         assert _numpy_import_error is not None
  62         _LOG.warning('error importing numpy, falling back to workarounds')
  63         _LOG.warning(str(_numpy_import_error))
  64         _numpy_import_error = None
  65     if statistic == 'Mean':
  66         if _numpy is None:  # work around missing numpy
  67             return _mean(iterable)
  68         else:
  69             return gs.mean()
  70     elif statistic == 'Std. Dev.':
  71         if _numpy is None:  # work around missing numpy
  72             sval = _std(iterable)
  73         else:
  74             return gs.std()
  75     else:
  76         raise NotImplementedError(statistic)
  77
  78 def tabulate(course, statistics=False, stream=None, use_color=None, **kwargs):
  79     """Return a table of student's grades to date
  80     """
  81     if stream is None:
  82         stream = _sys.stdout
  83     highlight,lowlight,good,bad = _standard_colors(use_color=use_color)
  84     colors = [highlight, lowlight]
  85     assignments = sorted(set(
  86             grade.assignment for grade in course.grades))
  87     students = sorted(set(grade.student for grade in course.grades))
  88     _write_color(string='Student', color=colors[0], stream=stream)
  89     for i,assignment in enumerate(assignments):
  90         string = '\t{}'.format(assignment.name)
  91         color = colors[(i+1)%len(colors)]
  92         _write_color(string=string, color=color, stream=stream)
  93     if len(assignments) == len(course.assignments):
  94         string = '\t{}'.format('Total')
  95         color = colors[(i+2)%len(colors)]
  96         _write_color(string=string, color=color, stream=stream)
  97     _write_color(string='\n', stream=stream)
  98     for student in students:
  99         _write_color(string=student.name, color=colors[0], stream=stream)
 100         for i,assignment in enumerate(assignments):
 101             try:
 102                 grade = course.grade(student=student, assignment=assignment)
 103                 gs = str(grade.points)
 104             except ValueError:
 105                 gs = '-'
 106             string = '\t{}'.format(gs)
 107             color = colors[(i+1)%len(colors)]
 108             _write_color(string=string, color=color, stream=stream)
 109         if len(assignments) == len(course.assignments):
 110             string = '\t{}'.format(course.total(student))
 111             color = colors[(i+2)%len(colors)]
 112             _write_color(string=string, color=color, stream=stream)
 113         _write_color(string='\n', stream=stream)
 114     if statistics:
 115         _write_color(string='--\n', stream=stream)
 116         for stat in ['Mean', 'Std. Dev.']:
 117             _write_color(string=stat, color=colors[0], stream=stream)
 118             for i,assignment in enumerate(assignments):
 119                 color = colors[(i+1)%len(colors)]
 120                 grades = [g for g in course.grades
 121                           if g.assignment == assignment]
 122                 gs = _statistics_container([g.points for g in grades])
 123                 sval = _statistic(gs, statistic=stat)
 124                 string = '\t{:.2f}'.format(sval)
 125                 _write_color(string=string, color=color, stream=stream)
 126             if len(assignments) == len(course.assignments):
 127                 gs = _statistics_container([course.total(s) for s in students])
 128                 sval = _statistic(gs, statistic=stat)
 129                 string = '\t{}'.format(sval)
 130                 color = colors[(i+2)%len(colors)]
 131                 _write_color(string=string, color=color, stream=stream)
 132             _write_color(string='\n', stream=stream)