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: data2multiple_anova.py 2782 2009-09-10 11:40:29Z andreas $"
)
parser.add_option("-c",
"--columns",
dest="columns",
type="string",
help="columns to take for calculating histograms.")
parser.add_option("-t",
"--tree-nh-file",
dest="filename_tree",
type="string",
help="filename with tree(s).")
parser.add_option("--skip-header",
dest="add_header",
action="store_false",
help="do not add header to flat format.")
parser.add_option("--output-with-header",
dest="write_header",
action="store_true",
help="write header and exit.")
parser.add_option("--debug",
dest="debug",
action="store_true",
help="debug mode")
parser.add_option("--display-tree",
dest="display_tree",
action="store_true",
help="display the tree")
parser.add_option("-m",
"--method",
dest="methods",
type="choice",
action="append",
choices=("contrasts", "spearman", "pearson", "compute"),
help="methods to perform on contrasts.")
parser.set_defaults(
columns="all",
filename_tree=None,
add_header=True,
write_header=False,
debug=False,
methods=[],
value_format="%6.4f",
pvalue_format="%e",
display_tree=False,
)
(options, args) = E.Start(parser, quiet=True)
if options.columns not in ("all", "all-but-first"):
options.columns = [int(x) - 1 for x in options.columns.split(",")]
data = []
options.filenames = args
for filename in options.filenames:
infile = IOTools.openFile(filename, "r")
table, headers = IOTools.readTable(infile,
take=options.columns,
headers=False)
infile.close()
data.append(table)
fields = ["Df", "Sum Sq", "F value", "Pr(>F)", "Mean Sq"]
options.stdout.write("set1\tset2")
for field in fields:
options.stdout.write("\t%s" % field)
options.stdout.write("\n")
# CODE needs to be refactored for rpy2 usage
for x in range(len(data)):
for y in range(x + 1, len(data)):
rpy.set_default_mode(rpy.NO_CONVERSION)
factors = ["x"] * len(data[x][:, 0]) + ["y"] * len(data[y][:, 0])
values = list(data[x][:, 0]) + list(data[y][:, 0])
linear_model = R.lm(R("y ~ x"),
data=R.data_frame(x=factors, y=values))
rpy.set_default_mode(rpy.BASIC_CONVERSION)
result = R.anova(linear_model)
options.stdout.write("%s\t%s" %
(options.filenames[x], options.filenames[y]))
for field in fields:
options.stdout.write("\t%s" % str(result[field]))
options.stdout.write("\n")
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: data2multiple_anova.py 2782 2009-09-10 11:40:29Z andreas $")
parser.add_option("-c", "--columns", dest="columns", type="string",
help="columns to take for calculating histograms.")
parser.add_option("-t", "--filename-tree", dest="filename_tree", type="string",
help="filename with tree(s).")
parser.add_option("--skip-header", dest="add_header", action="store_false",
help="do not add header to flat format.")
parser.add_option("--write-header", dest="write_header", action="store_true",
help="write header and exit.")
parser.add_option("--debug", dest="debug", action="store_true",
help="debug mode")
parser.add_option("--display-tree", dest="display_tree", action="store_true",
help="display the tree")
parser.add_option("-m", "--method", dest="methods", type="choice", action="append",
choices=("contrasts", "spearman", "pearson", "compute"),
help="methods to perform on contrasts.")
parser.set_defaults(
columns="all",
filename_tree=None,
add_header=True,
write_header=False,
debug=False,
methods=[],
value_format="%6.4f",
pvalue_format="%e",
display_tree=False,
)
(options, args) = E.Start(parser, quiet=True)
if options.columns not in ("all", "all-but-first"):
options.columns = map(lambda x: int(x) - 1, options.columns.split(","))
data = []
options.filenames = args
for filename in options.filenames:
infile = open(filename, "r")
table, headers = IOTools.readTable(
infile, take=options.columns, headers=False)
infile.close()
data.append(table)
fields = ["Df", "Sum Sq", "F value", "Pr(>F)", "Mean Sq"]
options.stdout.write("set1\tset2")
for field in fields:
options.stdout.write("\t%s" % field)
options.stdout.write("\n")
# CODE needs to be refactored for rpy2 usage
for x in range(len(data)):
for y in range(x + 1, len(data)):
rpy.set_default_mode(rpy.NO_CONVERSION)
factors = ["x"] * len(data[x][:, 0]) + ["y"] * len(data[y][:, 0])
values = list(data[x][:, 0]) + list(data[y][:, 0])
linear_model = R.lm(
R("y ~ x"), data=R.data_frame(x=factors, y=values))
rpy.set_default_mode(rpy.BASIC_CONVERSION)
result = R.anova(linear_model)
options.stdout.write(
"%s\t%s" % (options.filenames[x], options.filenames[y]))
for field in fields:
options.stdout.write("\t%s" % str(result[field]))
options.stdout.write("\n")
fields = [ "Df", "Sum Sq", "F value", "Pr(>F)", "Mean Sq"]
options.stdout.write("set1\tset2" )
for field in fields:
options.stdout.write("\t%s" % field )
options.stdout.write("\n" )
# CODE needs to be refactored for rpy2 usage
for x in range( len(data )):
for y in range(x+1,len(data)):
rpy.set_default_mode(rpy.NO_CONVERSION)
factors = ["x"] * len(data[x][:,0]) + ["y"] * len(data[y][:,0])
values = list(data[x][:,0]) + list(data[y][:,0])
linear_model = R.lm(R("y ~ x"), data = R.data_frame(x=factors, y=values ))
rpy.set_default_mode(rpy.BASIC_CONVERSION)
result = R.anova( linear_model )
options.stdout.write( "%s\t%s" % (options.filenames[x], options.filenames[y]) )
for field in fields:
options.stdout.write("\t%s" % str( result[field] ) )
options.stdout.write("\n" )