def NumAssignments(self):
"""Write number of assignments
"""
if self.mLogLevel >= 1:
print "# instance of <" + str(
self.__class__) + "> on " + time.asctime(
time.localtime(time.time()))
print "# source: %s" % (self.mTableNameDomains)
print "# hubs between domains"
print string.join(("nid", "nassignments", "nclasses"), "\t")
sys.stdout.flush()
result = self.mTableDomains.GetNumAssignments()
for r in result:
print string.join(map(str, r), "\t")
data = map(lambda x: x[1], result)
h = Histogram.Calculate(data)
print "# histogram of number of domains per sequence"
Histogram.Print(h)
data = map(lambda x: x[2], result)
h = Histogram.Calculate(data)
print "# histogram of number of different domains per sequence"
Histogram.Print(h)
def CountDistribution(self):
"""print distribution of number of units and sequences per
family.
"""
self.PrintStatus()
print """#
# NUM: number of units/sequences per family
# NUNITS: number of families with x units
# NSEQ: number of families with x sequences
#"""
print "NUM\tNUNITS\tNSEQ"
sys.stdout.flush()
histograms = []
class_name = self.mTableDomains.GetFieldNameClass()
statement = "SELECT COUNT(*) FROM %s GROUP BY %s" % (
self.mTableNameDomains, class_name)
data = map(lambda x: x[0], self.dbhandle.Execute(statement).fetchall())
h1 = Histogram.Calculate(data)
histograms.append(h1)
statement = "SELECT COUNT(DISTINCT nid) FROM %s GROUP BY %s" % (
self.mTableNameDomains, class_name)
data = map(lambda x: x[0], self.dbhandle.Execute(statement).fetchall())
h2 = Histogram.Calculate(data)
histograms.append(h2)
ch = Histogram.Combine(histograms)
Histogram.Print(ch)
def printHistogram(values, section, options, min_value=0, increment=1.0):
outfile = open(options.output_filename_pattern % section, "w")
h = Histogram.Calculate(values,
no_empty_bins=True,
min_value=0,
increment=1.0)
outfile.write("bin\t%s\n" % section)
for bin, val in h:
outfile.write("%5.2f\t%i\n" % (bin, val))
outfile.close()
def DomainDistribution( self ):
"""
distribution of domains per sequence
"""
self.PrintStatus()
if self.mLogLevel >= 1:
sys.stdout.flush()
print """#
# COUNTS: number
# NDOMAINS: number of domains per sequence
# NDOMAINS/SIN: number of domains without singletons per sequence
# NMOBILES: number of mobile modules per sequence
#"""
print "length\tndomains\tndomains/sin\tnmobiles"
sys.stdout.flush()
histograms = []
statement = "SELECT COUNT(*) FROM %s GROUP BY nid" % self.mTableNameDomains
d1 = map(lambda x: x[0], self.dbhandle.Execute( statement ).fetchall())
histograms.append( Histogram.Calculate( d1 ) )
statement = "SELECT COUNT(*) FROM %s AS d, %s AS f WHERE f.family = d.family AND f.nunits > 1 GROUP BY d.nid" % (self.mTableNameDomains, self.mTableNameFamilies)
d2 = map(lambda x: x[0], self.dbhandle.Execute( statement ).fetchall())
histograms.append( Histogram.Calculate( d2 ) )
statement = "SELECT COUNT(*) FROM %s AS d, %s AS f WHERE f.family = d.family GROUP BY d.nid" % (self.mTableNameDomains, self.mTableNameSubset)
d3 = map(lambda x: x[0], self.dbhandle.Execute( statement ).fetchall())
histograms.append( Histogram.Calculate( d3 ) )
ch = Histogram.Combine( histograms )
Histogram.Print(ch)
vals = []
# retrieve histogram
lines = filter(lambda x: x[0] <> "#", sys.stdin.readlines())
for l in lines:
data = string.split(l[:-1], "\t")
try:
val = string.atof(data[param_column])
except IndexError:
print "# IndexError in line:", l[:-1]
continue
if param_upper_limit != None and val > param_upper_limit:
val = param_upper_limit
if param_lower_limit != None and val < param_lower_limit:
val = param_lower_limit
vals.append(val)
lines = None
h = Histogram.Calculate(vals,
no_empty_bins=param_empty_bins,
increment=param_bin_size)
print "# num_values=%i" % len(vals)
Histogram.Print(h, nonull=param_nonull)
options.stdlog.write("# no data\n")
Experiment.Stop()
sys.exit(0)
for x in range(len(options.columns)):
if options.loglevel >= 1:
options.stdlog.write("# column=%i, num_values=%i\n" %
(options.columns[x], len(vals[x])))
if len(vals[x]) < options.min_data: continue
h = Histogram.Calculate(
vals[x],
no_empty_bins=options.no_empty_bins,
increment=options.bin_size,
min_value=options.min_value,
max_value=options.max_value,
dynamic_bins=options.dynamic_bins,
ignore_out_of_range=options.ignore_out_of_range)
if options.normalize: h = Histogram.Normalize(h)
if options.cumulative: h = Histogram.Cumulate(h)
if options.reverse_cumulative:
h = Histogram.Cumulate(h, direction=0)
hists.append(h)
for m in options.append:
if m == "normalize":
hists.append(Histogram.Normalize(h))
