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# Copyright (c) 2003-2004 The Regents of The University of Michigan
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met: redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer;
# redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution;
# neither the name of the copyright holders nor the names of its
# contributors may be used to endorse or promote products derived from
# this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
# A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
# OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
# SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
# LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
# DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
# THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import MySQLdb, re, string
def statcmp(a, b):
v1 = a.split('.')
v2 = b.split('.')
last = min(len(v1), len(v2)) - 1
for i,j in zip(v1[0:last], v2[0:last]):
if i != j:
return cmp(i, j)
# Special compare for last element.
if len(v1) == len(v2):
return cmp(v1[last], v2[last])
else:
return cmp(len(v1), len(v2))
class RunData:
def __init__(self, row):
self.run = int(row[0])
self.name = row[1]
self.user = row[2]
self.project = row[3]
class SubData:
def __init__(self, row):
self.stat = int(row[0])
self.x = int(row[1])
self.y = int(row[2])
self.name = row[3]
self.descr = row[4]
class Data:
def __init__(self, row):
if len(row) != 5:
raise 'stat db error'
self.stat = int(row[0])
self.run = int(row[1])
self.x = int(row[2])
self.y = int(row[3])
self.data = float(row[4])
def __repr__(self):
return '''Data(['%d', '%d', '%d', '%d', '%f'])''' % ( self.stat,
self.run, self.x, self.y, self.data)
class StatData(object):
def __init__(self, row):
self.stat = int(row[0])
self.name = row[1]
self.desc = row[2]
self.type = row[3]
self.prereq = int(row[5])
self.precision = int(row[6])
import flags
self.flags = 0
if int(row[4]): self.flags |= flags.printable
if int(row[7]): self.flags |= flags.nozero
if int(row[8]): self.flags |= flags.nonan
if int(row[9]): self.flags |= flags.total
if int(row[10]): self.flags |= flags.pdf
if int(row[11]): self.flags |= flags.cdf
if self.type == 'DIST' or self.type == 'VECTORDIST':
self.min = float(row[12])
self.max = float(row[13])
self.bktsize = float(row[14])
self.size = int(row[15])
if self.type == 'FORMULA':
self.formula = self.db.allFormulas[self.stat]
class Node(object):
def __init__(self, name):
self.name = name
def __str__(self):
return self.name
class Database(object):
def __init__(self):
self.host = 'zizzer.pool'
self.user = ''
self.passwd = ''
self.db = 'm5stats'
self.cursor = None
self.allStats = []
self.allStatIds = {}
self.allStatNames = {}
self.allSubData = {}
self.allRuns = []
self.allRunIds = {}
self.allRunNames = {}
self.allBins = []
self.allBinIds = {}
self.allBinNames = {}
self.allFormulas = {}
self.stattop = {}
self.statdict = {}
self.statlist = []
self.mode = 'sum';
self.runs = None
self.bins = None
self.ticks = None
self.__dict__['get'] = type(self).sum
def query(self, sql):
self.cursor.execute(sql)
def update_dict(self, dict):
dict.update(self.stattop)
def append(self, stat):
statname = re.sub(':', '__', stat.name)
path = string.split(statname, '.')
pathtop = path[0]
fullname = ''
x = self
while len(path) > 1:
name = path.pop(0)
if not x.__dict__.has_key(name):
x.__dict__[name] = Node(fullname + name)
x = x.__dict__[name]
fullname = '%s%s.' % (fullname, name)
name = path.pop(0)
x.__dict__[name] = stat
self.stattop[pathtop] = self.__dict__[pathtop]
self.statdict[statname] = stat
self.statlist.append(statname)
def connect(self):
# connect
self.thedb = MySQLdb.connect(db=self.db,
host=self.host,
user=self.user,
passwd=self.passwd)
# create a cursor
self.cursor = self.thedb.cursor()
self.query('''select rn_id,rn_name,rn_sample,rn_user,rn_project
from runs''')
for result in self.cursor.fetchall():
run = RunData(result);
self.allRuns.append(run)
self.allRunIds[run.run] = run
self.allRunNames[run.name] = run
self.query('select * from bins')
for id,name in self.cursor.fetchall():
self.allBinIds[int(id)] = name
self.allBinNames[name] = int(id)
self.query('select sd_stat,sd_x,sd_y,sd_name,sd_descr from subdata')
for result in self.cursor.fetchall():
subdata = SubData(result)
if self.allSubData.has_key(subdata.stat):
self.allSubData[subdata.stat].append(subdata)
else:
self.allSubData[subdata.stat] = [ subdata ]
self.query('select * from formulas')
for id,formula in self.cursor.fetchall():
self.allFormulas[int(id)] = formula.tostring()
StatData.db = self
self.query('select * from stats')
import info
for result in self.cursor.fetchall():
stat = info.NewStat(StatData(result))
self.append(stat)
self.allStats.append(stat)
self.allStatIds[stat.stat] = stat
self.allStatNames[stat.name] = stat
# Name: listbins
# Desc: Prints all bins matching regex argument, if no argument
# is given all bins are returned
def listBins(self, regex='.*'):
print '%-50s %-10s' % ('bin name', 'id')
print '-' * 61
names = self.allBinNames.keys()
names.sort()
for name in names:
id = self.allBinNames[name]
print '%-50s %-10d' % (name, id)
# Name: listruns
# Desc: Prints all runs matching a given user, if no argument
# is given all runs are returned
def listRuns(self, user=None):
print '%-40s %-10s %-5s' % ('run name', 'user', 'id')
print '-' * 62
for run in self.allRuns:
if user == None or user == run.user:
print '%-40s %-10s %-10d' % (run.name, run.user, run.run)
# Name: listTicks
# Desc: Prints all samples for a given run
def listTicks(self, runs=None):
print "tick"
print "----------------------------------------"
sql = 'select distinct dt_tick from data where dt_stat=1180 and ('
if runs != None:
first = True
for run in runs:
if first:
# sql += ' where'
first = False
else:
sql += ' or'
sql += ' dt_run=%s' % run.run
sql += ')'
self.query(sql)
for r in self.cursor.fetchall():
print r[0]
# Name: retTicks
# Desc: Prints all samples for a given run
def retTicks(self, runs=None):
sql = 'select distinct dt_tick from data where dt_stat=1180 and ('
if runs != None:
first = True
for run in runs:
if first:
first = False
else:
sql += ' or'
sql += ' dt_run=%s' % run.run
sql += ')'
self.query(sql)
ret = []
for r in self.cursor.fetchall():
ret.append(r[0])
return ret
# Name: liststats
# Desc: Prints all statistics that appear in the database,
# the optional argument is a regular expression that can
# be used to prune the result set
def listStats(self, regex=None):
print '%-60s %-8s %-10s' % ('stat name', 'id', 'type')
print '-' * 80
rx = None
if regex != None:
rx = re.compile(regex)
stats = [ stat.name for stat in self.allStats ]
stats.sort(statcmp)
for stat in stats:
stat = self.allStatNames[stat]
if rx == None or rx.match(stat.name):
print '%-60s %-8s %-10s' % (stat.name, stat.stat, stat.type)
# Name: liststats
# Desc: Prints all statistics that appear in the database,
# the optional argument is a regular expression that can
# be used to prune the result set
def listFormulas(self, regex=None):
print '%-60s %s' % ('formula name', 'formula')
print '-' * 80
rx = None
if regex != None:
rx = re.compile(regex)
stats = [ stat.name for stat in self.allStats ]
stats.sort(statcmp)
for stat in stats:
stat = self.allStatNames[stat]
if stat.type == 'FORMULA' and (rx == None or rx.match(stat.name)):
print '%-60s %s' % (stat.name, self.allFormulas[stat.stat])
def getStat(self, stats):
if type(stats) is not list:
stats = [ stats ]
ret = []
for stat in stats:
if type(stat) is int:
ret.append(self.allStatIds[stat])
if type(stat) is str:
rx = re.compile(stat)
for stat in self.allStats:
if rx.match(stat.name):
ret.append(stat)
return ret
def getBin(self, bins):
if type(bins) is not list:
bins = [ bins ]
ret = []
for bin in bins:
if type(bin) is int:
ret.append(bin)
elif type(bin) is str:
ret.append(self.allBinNames[bin])
else:
for name,id in self.allBinNames.items():
if bin.match(name):
ret.append(id)
return ret
def getNotBin(self, bin):
map = {}
for bin in getBin(bin):
map[bin] = 1
ret = []
for bin in self.allBinIds.keys():
if not map.has_key(bin):
ret.append(bin)
return ret
#########################################
# get the data
#
def inner(self, op, stat, bins, ticks, group=False):
sql = 'select '
sql += 'dt_stat as stat, '
sql += 'dt_run as run, '
sql += 'dt_x as x, '
sql += 'dt_y as y, '
if group:
sql += 'dt_tick as tick, '
sql += '%s(dt_data) as data ' % op
sql += 'from data '
sql += 'where '
if isinstance(stat, list):
val = ' or '.join([ 'dt_stat=%d' % s.stat for s in stat ])
sql += ' (%s)' % val
else:
sql += ' dt_stat=%d' % stat.stat
if self.runs != None and len(self.runs):
val = ' or '.join([ 'dt_run=%d' % r for r in self.runs ])
sql += ' and (%s)' % val
if bins != None and len(bins):
val = ' or '.join([ 'dt_bin=%d' % b for b in bins ])
sql += ' and (%s)' % val
if ticks != None and len(ticks):
val = ' or '.join([ 'dt_tick=%d' % s for s in ticks ])
sql += ' and (%s)' % val
sql += ' group by dt_stat,dt_run,dt_x,dt_y'
if group:
sql += ',dt_tick'
return sql
def outer(self, op_out, op_in, stat, bins, ticks):
sql = self.inner(op_in, stat, bins, ticks, True)
sql = 'select stat,run,x,y,%s(data) from (%s) as tb ' % (op_out, sql)
sql += 'group by stat,run,x,y'
return sql
# Name: sum
# Desc: given a run, a stat and an array of samples and bins,
# sum all the bins and then get the standard deviation of the
# samples for non-binned runs. This will just return the average
# of samples, however a bin array still must be passed
def sum(self, stat, bins, ticks):
return self.inner('sum', stat, bins, ticks)
# Name: avg
# Desc: given a run, a stat and an array of samples and bins,
# sum all the bins and then average the samples for non-binned
# runs this will just return the average of samples, however
# a bin array still must be passed
def avg(self, stat, bins, ticks):
return self.outer('avg', 'sum', stat, bins, ticks)
# Name: stdev
# Desc: given a run, a stat and an array of samples and bins,
# sum all the bins and then get the standard deviation of the
# samples for non-binned runs. This will just return the average
# of samples, however a bin array still must be passed
def stdev(self, stat, bins, ticks):
return self.outer('stddev', 'sum', stat, bins, ticks)
def __getattribute__(self, attr):
if attr != 'get':
return super(Database, self).__getattribute__(attr)
if self.__dict__['get'] == type(self).sum:
return 'sum'
elif self.__dict__['get'] == type(self).avg:
return 'avg'
elif self.__dict__['get'] == type(self).stdev:
return 'stdev'
else:
return ''
def __setattr__(self, attr, value):
if attr != 'get':
super(Database, self).__setattr__(attr, value)
return
if value == 'sum':
self.__dict__['get'] = type(self).sum
elif value == 'avg':
self.__dict__['get'] = type(self).avg
elif value == 'stdev':
self.__dict__['get'] = type(self).stdev
else:
raise AttributeError, "can only set get to: sum | avg | stdev"
def data(self, stat, bins=None, ticks=None):
if bins is None:
bins = self.bins
if ticks is None:
ticks = self.ticks
sql = self.__dict__['get'](self, stat, bins, ticks)
self.query(sql)
runs = {}
for x in self.cursor.fetchall():
data = Data(x)
if not runs.has_key(data.run):
runs[data.run] = {}
if not runs[data.run].has_key(data.x):
runs[data.run][data.x] = {}
runs[data.run][data.x][data.y] = data.data
return runs
def __getitem__(self, key):
return self.stattop[key]
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