def main(argv=None):
"""script main.
parses command line options in sys.argv, unless *argv* is given.
"""
if argv is None:
argv = sys.argv
parser = E.OptionParser(version="%prog version: $Id: matrix2stats.py 2795 2009-09-16 15:29:23Z andreas $",
usage=globals()["__doc__"])
parser.add_option("-m", "--method", dest="method", type="choice",
choices=("chi-squared", "pearson-chi-squared"),
help="statistical methods to apply.")
parser.add_option("-t", "--header-names", dest="headers", action="store_true",
help="matrix has row/column headers.")
parser.add_option("--no-headers", dest="headers", action="store_false",
help="matrix has no row/column headers.")
parser.add_option("-i", "--input-format", dest="input_format", type="choice",
choices=("full", "sparse", "phylip"),
help="""input format for matrix.""" )
parser.add_option("-o", "--output-format", dest="output_format", type="choice",
choices=("full", "sparse", "phylip"),
help="""output format for matrix.""" )
parser.add_option("-p", "--parameters", dest="parameters", action="append", type="string",
help="parameters for various functions.")
parser.add_option("-a", "--iteration", dest="iteration", type="choice",
choices=("pairwise", "all-vs-all"),
help="""how to compute stats [%default].""" )
parser.set_defaults(
method="chi-squared",
headers=True,
value_format="%6.4f",
pvalue_format="%6.4e",
input_format="full",
write_separators=True,
parameters=[],
iteration=None,
)
(options, args) = E.Start(parser)
lines = [x for x in sys.stdin.readlines() if x[0] != "#"]
chunks = [x for x in range(len(lines)) if lines[x][0] == ">"]
if not chunks:
options.write_separators = False
chunks = [-1]
chunks.append(len(lines))
ninput, noutput, nskipped = 0, 0, 0
if options.write_separators:
options.stdout.write("test\t")
header_prefix = ""
if options.method == "chi-squared":
header_prefix = "observed\texpected"
options.stdout.write("\t".join(
(header_prefix, "n", "min", "max", "chi", "df", "P", "passed", "phi")) + "\n")
elif options.method in ("pearson-chi-squared",):
options.stdout.write("column\t")
options.stdout.write("\t".join(
(header_prefix, "n", "prob", "obs", "exp", "chi", "df", "P", "passed", "phi")) + "\n")
if len(options.parameters) == 0:
raise "out of parameters - please supply probability or filename with probabilities."
param = options.parameters[0]
del options.parameters[0]
if options.write_separators:
probabilities = IOTools.ReadMap(
IOTools.openFile(param, "r"), map_functions=(str, float))
else:
probability = float(param)
for x in range(len(chunks) - 1):
ninput += 1
matrix, row_headers, col_headers = MatlabTools.readMatrix(
StringIO("".join(lines[chunks[x] + 1:chunks[x + 1]])),
format=options.input_format,
headers=options.headers)
nrows, ncols = matrix.shape
if options.loglevel >= 2:
options.stdlog.write("# read matrix: %i x %i, %i row titles, %i colum titles.\n" %
(nrows, ncols, len(row_headers), len(col_headers)))
if options.write_separators:
options.stdout.write(lines[chunks[x]][1:-1] + "\t")
pairs = []
if options.iteration == "pairwise":
pairs = []
for row1 in range(0, len(row_headers)):
for row2 in range(row1 + 1, len(row_headers)):
pairs.append((row1, row2))
elif options.iteration == "all-vs-all":
pairs = []
for row1 in range(0, len(row_headers)):
for row2 in range(0, len(row_headers)):
if row1 == row2:
continue
pairs.append((row1, row2))
if options.method == "chi-squared":
for row1, row2 in pairs:
row_header1 = row_headers[row1]
row_header2 = row_headers[row2]
try:
result = Stats.doChiSquaredTest(
numpy.vstack((matrix[row1], matrix[row2])))
except ValueError:
nskipped += 1
continue
noutput += 1
options.stdout.write("\t".join((
"%s" % row_header1,
"%s" % row_header2,
"%i" % result.mSampleSize,
"%i" % min(matrix.flat),
"%i" % max(matrix.flat),
options.value_format % result.mChiSquaredValue,
"%i" % result.mDegreesFreedom,
options.pvalue_format % result.mProbability,
"%s" % result.mSignificance,
options.value_format % result.mPhi)) + "\n")
elif options.method == "pearson-chi-squared":
if nrows != 2:
raise ValueError("only implemented for 2xn table")
if options.write_separators:
id = re.match("(\S+)", lines[chunks[x]][1:-1]).groups()[0]
probability = probabilities[id]
for col in range(ncols):
options.stdout.write("%s\t" % col_headers[col])
result = Stats.doPearsonChiSquaredTest(
probability, sum(matrix[:, col]), matrix[0, col])
options.stdout.write("\t".join((
"%i" % result.mSampleSize,
"%f" % probability,
"%i" % result.mObserved,
"%f" % result.mExpected,
options.value_format % result.mChiSquaredValue,
"%i" % result.mDegreesFreedom,
options.pvalue_format % result.mProbability,
"%s" % result.mSignificance,
options.value_format % result.mPhi)))
if col < ncols - 1:
options.stdout.write("\n")
if options.write_separators:
options.stdout.write(lines[chunks[x]][1:-1] + "\t")
options.stdout.write("\n")
E.info("# ninput=%i, noutput=%i, nskipped=%i\n" %
(ninput, noutput, nskipped))
E.Stop()
for row2 in range( row1+1, len(row_headers) ):
pairs.append( (row1, row2) )
elif options.iteration == "all-vs-all":
pairs = []
for row1 in range( 0, len(row_headers) ):
for row2 in range( 0, len(row_headers) ):
if row1 == row2: continue
pairs.append( (row1, row2) )
if options.method == "chi-squared":
for row1, row2 in pairs:
row_header1 = row_headers[row1]
row_header2 = row_headers[row2]
try:
result = Stats.doChiSquaredTest( numpy.vstack( (matrix[row1], matrix[row2] ) ) )
except ValueError:
nskipped += 1
continue
noutput += 1
options.stdout.write( "\t".join( ( "%s" % row_header1,
"%s" % row_header2,
"%i" % result.mSampleSize,
"%i" % min(matrix.flat),
"%i" % max(matrix.flat),
options.value_format % result.mChiSquaredValue,
"%i" % result.mDegreesFreedom,
options.pvalue_format % result.mProbability,
"%s" % result.mSignificance,
options.value_format % result.mPhi ) ) + "\n" )
