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-rw-r--r--pysamples/ta-stats.py172
1 files changed, 0 insertions, 172 deletions
diff --git a/pysamples/ta-stats.py b/pysamples/ta-stats.py
deleted file mode 100644
index 9a80c04..0000000
--- a/pysamples/ta-stats.py
+++ /dev/null
@@ -1,172 +0,0 @@
-# Copyright (c) 2012, Walter Bender
-
-# This program is free software; you can redistribute it and/or modify
-# it under the terms of the GNU General Public License as published by
-# the Free Software Foundation; either version 3 of the License, or
-# (at your option) any later version.
-#
-# This program is distributed in the hope that it will be useful,
-# but WITHOUT ANY WARRANTY; without even the implied warranty of
-# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
-# GNU General Public License for more details.
-#
-# You should have received a copy of the GNU General Public License
-# along with this program; if not, write to the Free Software
-# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA
-
-
-def myblock(tw, x): # ignore second argument
- ''' Load journal stats to heap (Sugar only) '''
-
- import os
- import glob
-
- _DIROFINTEREST = 'datastore'
-
- class ParseJournal():
- ''' Simple parser of datastore for turtle art entries '''
-
- def __init__(self):
- self._score = []
-
- homepath = os.environ['HOME']
- for path in glob.glob(os.path.join(homepath, '.sugar', '*')):
- if isdsdir(path):
- dsobjdirs = glob.glob(
- os.path.join(path, _DIROFINTEREST, '??'))
- for dsobjdir in dsobjdirs:
- dsobjs = glob.glob(os.path.join(dsobjdir, '*'))
- for dsobj in dsobjs:
- if not isactivity(dsobj) == 'TurtleArtActivity':
- continue
- if hascomponent(dsobj, 'mime_type') != \
- 'application/x-turtle-art':
- continue
- score = hasturtleblocks(dsobj)
- if score:
- self._score.append(score)
-
- def hascomponent(path, component):
- ''' Return metadata attribute, if any '''
- if not os.path.exists(os.path.join(path, 'metadata')):
- return False
- if not os.path.exists(os.path.join(path, 'metadata', component)):
- return False
- fd = open(os.path.join(path, 'metadata', component))
- data = fd.readline()
- fd.close()
- if len(data) == 0:
- return False
- return data
-
- def isactivity(path):
- ''' Return activity name '''
- activity = hascomponent(path, 'activity')
- if not activity:
- return False
- else:
- return activity.split('.')[-1]
-
- def isdsdir(path):
- ''' Only interested if it is a datastore directory '''
- if not os.path.isdir(path):
- return False
- if not os.path.exists(os.path.join(path, _DIROFINTEREST)):
- return False
- return True
-
- TACAT = {'clean': 'forward', 'forward': 'forward', 'back': 'forward',
- 'left': 'forward', 'right': 'forward', 'arc': 'arc',
- 'xcor': 'coord', 'ycor': 'coord', 'heading': 'coord',
- 'setxy2': 'setxy', 'seth': 'setxy', 'penup': 'pen',
- 'setpensize': 'pen', 'setcolor': 'pen', 'pensize': 'pen',
- 'color': 'pen', 'setshade': 'pen', 'setgray': 'pen',
- 'gray': 'pen', 'fillscreen': 'pen', 'startfill': 'fill',
- 'stopfill': 'fill', 'plus2': 'number', 'minus2': 'number',
- 'product2': 'number', 'division2': 'number',
- 'pendown': 'pen', 'shade': 'pen', 'remainder2': 'number',
- 'sqrt': 'number', 'identity2': 'number', 'and2': 'boolean',
- 'or2': 'boolean', 'not': 'boolean', 'greater2': 'boolean',
- 'less2': 'boolean', 'equal2': 'boolean', 'random': 'random',
- 'repeat': 'repeat', 'forever': 'repeat', 'if': 'ifthen',
- 'ifelse': 'ifthen', 'while': 'ifthen', 'until': 'ifthen',
- 'hat': 'action', 'stack': 'action', 'storein': 'box',
- 'luminance': 'sensor', 'mousex': 'sensor', 'mousey': 'sensor',
- 'mousebutton2': 'sensor', 'keyboard': 'sensor',
- 'readpixel': 'sensor', 'see': 'sensor', 'time': 'sensor',
- 'sound': 'sensor', 'volume': 'sensor', 'pitch': 'sensor',
- 'resistance': 'sensor', 'voltage': 'sensor', 'video': 'media',
- 'wait': 'media', 'camera': 'media', 'journal': 'media',
- 'audio': 'media', 'show': 'media', 'setscale': 'media',
- 'savepix': 'media', 'savesvg': 'media', 'mediawait': 'media',
- 'mediapause': 'media', 'mediastop': 'media', 'mediaplay': 'media',
- 'speak': 'media', 'sinewave': 'media', 'description': 'media',
- 'push': 'extras', 'pop': 'extras', 'printheap': 'extras',
- 'clearheap': 'extras', 'isheapempty2': 'extras', 'chr': 'extras',
- 'int': 'extras', 'myfunction': 'python', 'userdefined': 'python',
- 'box': 'box', 'kbinput': 'sensor',
- 'loadblock': 'python', 'loadpalette': 'python'}
- TAPAL = {'forward': 'turtlep', 'arc': 'turtlep', 'coord': 'turtlep',
- 'setxy': 'turtlep', 'pen': 'penp', 'fill': 'penp',
- 'random': 'numberp', 'boolean': 'numberp', 'repeat': 'flowp',
- 'ifthen': 'flowp', 'action': 'boxp', 'box': 'boxp',
- 'sensor': 'sensorp', 'media': 'mediap', 'extras': 'extrasp',
- 'number': 'numberp', 'python': 'extrasp'}
- TASCORE = {'forward': 3, 'arc': 3, 'setxy': 2.5, 'coord': 4, 'turtlep': 5,
- 'pen': 2.5, 'fill': 2.5, 'penp': 5,
- 'number': 2.5, 'boolean': 2.5, 'random': 2.5, 'numberp': 0,
- 'repeat': 2.5, 'ifthen': 7.5, 'flowp': 10,
- 'box': 7.5, 'action': 7.5, 'boxp': 0,
- 'media': 5, 'mediap': 0,
- 'python': 5, 'extras': 5, 'extrasp': 0,
- 'sensor': 5, 'sensorp': 0}
- PALS = ['turtlep', 'penp', 'numberp', 'flowp', 'boxp', 'sensorp', 'mediap',
- 'extrasp']
-
- def hasturtleblocks(path):
- ''' Parse turtle block data and generate score based on rubric '''
-
- if not os.path.exists(os.path.join(path, 'data')):
- return None
- fd = open(os.path.join(path, 'data'))
- blocks = []
- # block name is second token in each line
- for line in fd:
- tokens = line.split(',')
- if len(tokens) > 1:
- token = tokens[1].strip('" [')
- blocks.append(token)
-
- score = []
- for i in range(len(PALS)):
- score.append(0)
- cats = []
- pals = []
-
- for b in blocks:
- if b in TACAT:
- if not TACAT[b] in cats:
- cats.append(TACAT[b])
- for c in cats:
- if c in TAPAL:
- if not TAPAL[c] in pals:
- pals.append(TAPAL[c])
-
- for c in cats:
- if c in TASCORE:
- score[PALS.index(TAPAL[c])] += TASCORE[c]
-
- for p in pals:
- if p in TASCORE:
- score[PALS.index(p)] += TASCORE[p]
-
- return score
-
- data = ParseJournal()
- n = min(40, len(data._score) / len(PALS))
- for i in range(n):
- for j in range(len(PALS)):
- tw.lc.heap.append(data._score[(n - i - 1)][len(PALS) - j - 1])
-
- tw.lc.heap.append(n)
- return
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