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",
usage=globals()["__doc__"])
parser.add_option("-m", "--method", dest="method", type="choice",
help="method to use [kl=kullback-leibler]",
choices=("kl",))
parser.add_option("-n", "--no-normalize", dest="normalize", action="store_false",
help="do not normalize data")
parser.add_option("-p", "--pseudocounts", dest="pseudocounts", type="int",
help="pseudocounts to add.")
parser.add_option("-f", "--number-format", dest="number_format", type="string",
help="number format.")
parser.set_defaults(
method="kl",
columns="all",
headers=True,
xrange=None,
pseudocounts=1,
normalize=True,
number_format="%6.4f"
)
(options, args) = E.Start(parser,
add_pipe_options=True)
if options.xrange:
options.xrange = map(float, options.xrange.split(","))
data, legend = IOTools.readTable(sys.stdin,
numeric_type=numpy.float32,
take=options.columns,
headers=options.headers,
truncate=options.xrange)
nrows, ncols = data.shape
# first: normalize rows
for y in range(1, ncols):
for x in range(nrows):
data[x, y] = data[x, y] + float(options.pseudocounts)
if options.normalize:
t = numpy.sum(data[:, y])
for x in range(nrows):
data[x, y] = data[x, y] / t
for x in range(1, len(legend) - 1):
for y in range(x + 1, len(legend)):
if options.method == "kl":
d1 = 0.0
d2 = 0.0
for bin in range(nrows):
p = data[bin, x]
q = data[bin, y]
d1 += p * math.log(p / q)
d2 += q * math.log(q / p)
options.stdout.write("%s\t%s\t%s\n" %
(legend[x], legend[y],
options.number_format % d1))
options.stdout.write("%s\t%s\t%s\n" %
(legend[y], legend[x],
options.number_format % d2))
E.Stop()
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: histogram2histogram.py 2782 2009-09-10 11:40:29Z andreas $"
)
parser.add_option("-i",
"--is-int",
dest="is_ints",
action="store_true",
help="categories are integers.")
parser.add_option("-m",
"--method",
dest="method",
type="choice",
choices=("append", "cumul", "rcumul", "normalize"),
help="method(s) to apply.")
parser.add_option("--no-headers",
dest="headers",
action="store_false",
help="histogram has no headers.")
parser.add_option("-c",
"--columns",
dest="columns",
type="string",
help="columns to use for plotting.")
parser.add_option("",
"--truncate",
dest="truncate",
type="string",
help="truncate at range.")
parser.add_option("",
"--no-out-of-range",
dest="cumulate_out_of_range",
action="store_false",
help="add up bins out of range.")
parser.add_option("--bin-format",
dest="format_bin",
type="string",
help="format for bins.")
parser.add_option("--value-format",
dest="format_val",
type="string",
help="format for vals.")
parser.set_defaults(
is_ints=False,
method="append",
columns="all",
headers=True,
truncate=None,
cumulate_out_of_range=True,
format_bin="%6.4f",
format_val="%6.4f",
)
(options, args) = E.Start(parser)
# old histogram2histogram.py semantics - need to merged with newer
# code below.
if options.method == "append":
vals = []
# retrieve histogram
lines = filter(lambda x: x[0] != "#", sys.stdin.readlines())
# check if first line contains a header
d = string.split(lines[0][:-1], "\t")[0]
try:
if options.is_ints:
value = int(d)
else:
value = float(d)
except ValueError:
print string.join(
(d, "counts", "frequency", "cumulative counts",
"increasing cumulative frequency", "cumulative counts",
"decreasing cumulative frequency"), "\t")
del lines[0]
data = map(lambda x: map(float, string.split(x[:-1], "\t")), lines)
if len(data) == 0:
raise "No data found."
total = float(reduce(lambda x, y: x + y, map(lambda x: x[1], data)))
cumul_down = int(total)
cumul_up = 0
if options.is_ints:
form = "%i\t%i\t%6.4f\t%i\t%6.4f\t%i\t%6.4f"
else:
form = "%6.4f\t%6.4f\t%6.4f\t%6.4f\t%6.4f\t%6.4f\t%6.4f"
for bin, val in data:
percent = float(val) / total
cumul_up += val
percent_cumul_up = float(cumul_up) / total
percent_cumul_down = float(cumul_down) / total
print form % \
(bin, val, percent, cumul_up, percent_cumul_up,
cumul_down, percent_cumul_down)
cumul_down -= val
else:
if options.truncate:
options.truncate = map(float, options.truncate.split(","))
options.method = options.method.split(",")
data, legend = IOTools.readTable(
sys.stdin,
numeric_type=numpy.float32,
take=options.columns,
headers=options.headers,
truncate=options.truncate,
cumulate_out_of_range=options.cumulate_out_of_range)
nfields = len(legend)
# note: because of MA, iteration makes copy of slices
# Solution: inplace edits.
nrows, ncols = data.shape
for method in options.method:
if method == "cumul":
l = [0] * ncols
for x in range(nrows):
for y in range(1, ncols):
data[x, y] += l[y]
l[y] = data[x, y]
elif method == "rcumul":
l = [0] * ncols
for x in range(nrows - 1, 0, -1):
for y in range(1, ncols):
data[x, y] += l[y]
l[y] = data[x, y]
elif method == "normalize":
m = [0] * ncols
for x in range(nrows):
for y in range(1, ncols):
# the conversion to float is necessary
m[y] = max(m[y], float(data[x, y]))
for y in range(1, ncols):
if m[y] == 0:
m[y] = 1.0
for x in range(nrows):
for y in range(1, ncols):
data[x, y] = data[x, y] / m[y]
else:
raise "unknown method %s" % method
print "\t".join(legend)
format = options.format_bin + "\t" + \
"\t".join([options.format_val] * (nfields - 1))
for d in data:
print format % tuple(d)
E.Stop()
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",
usage=globals()["__doc__"])
parser.add_option("-m",
"--method",
dest="method",
type="choice",
help="method to use [kl=kullback-leibler]",
choices=("kl", ))
parser.add_option("-n",
"--no-normalize",
dest="normalize",
action="store_false",
help="do not normalize data")
parser.add_option("-p",
"--pseudocounts",
dest="pseudocounts",
type="int",
help="pseudocounts to add.")
parser.add_option("-f",
"--number-format",
dest="number_format",
type="string",
help="number format.")
parser.set_defaults(method="kl",
columns="all",
headers=True,
xrange=None,
pseudocounts=1,
normalize=True,
number_format="%6.4f")
(options, args) = E.Start(parser, add_pipe_options=True)
if options.xrange:
options.xrange = list(map(float, options.xrange.split(",")))
data, legend = IOTools.readTable(sys.stdin,
numeric_type=numpy.float32,
take=options.columns,
headers=options.headers,
truncate=options.xrange)
nrows, ncols = data.shape
# first: normalize rows
for y in range(1, ncols):
for x in range(nrows):
data[x, y] = data[x, y] + float(options.pseudocounts)
if options.normalize:
t = numpy.sum(data[:, y])
for x in range(nrows):
data[x, y] = data[x, y] / t
for x in range(1, len(legend) - 1):
for y in range(x + 1, len(legend)):
if options.method == "kl":
d1 = 0.0
d2 = 0.0
for bin in range(nrows):
p = data[bin, x]
q = data[bin, y]
d1 += p * math.log(p / q)
d2 += q * math.log(q / p)
options.stdout.write(
"%s\t%s\t%s\n" %
(legend[x], legend[y], options.number_format % d1))
options.stdout.write(
"%s\t%s\t%s\n" %
(legend[y], legend[x], options.number_format % d2))
E.Stop()
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")
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: histogram2histogram.py 2782 2009-09-10 11:40:29Z andreas $")
parser.add_option("-i", "--is-int", dest="is_ints", action="store_true",
help="categories are integers.")
parser.add_option("-m", "--method", dest="method", type="choice",
choices=("append", "cumul", "rcumul", "normalize"),
help="method(s) to apply.")
parser.add_option("--no-headers", dest="headers", action="store_false",
help="histogram has no headers.")
parser.add_option("-c", "--columns", dest="columns", type="string",
help="columns to use for plotting.")
parser.add_option("", "--truncate", dest="truncate", type="string",
help="truncate at range.")
parser.add_option("", "--no-out-of-range", dest="cumulate_out_of_range", action="store_false",
help="add up bins out of range.")
parser.add_option("--bin-format", dest="format_bin", type="string",
help="format for bins.")
parser.add_option("--value-format", dest="format_val", type="string",
help="format for vals.")
parser.set_defaults(
is_ints=False,
method="append",
columns="all",
headers=True,
truncate=None,
cumulate_out_of_range=True,
format_bin="%6.4f",
format_val="%6.4f",
)
(options, args) = E.Start(parser)
# old histogram2histogram.py semantics - need to merged with newer
# code below.
if options.method == "append":
vals = []
# retrieve histogram
lines = [x for x in sys.stdin.readlines() if x[0] != "#"]
# check if first line contains a header
d = lines[0][:-1].split("\t")[0]
try:
if options.is_ints:
value = int(d)
else:
value = float(d)
except ValueError:
print("\t".join(
(d, "counts", "frequency",
"cumulative counts", "increasing cumulative frequency",
"cumulative counts", "decreasing cumulative frequency")))
del lines[0]
data = [list(map(float, x[:-1].split("\t"))) for x in lines]
if len(data) == 0:
raise ValueError("no data found")
total = float(reduce(lambda x, y: x + y, [x[1] for x in data]))
cumul_down = int(total)
cumul_up = 0
if options.is_ints:
form = "%i\t%i\t%6.4f\t%i\t%6.4f\t%i\t%6.4f"
else:
form = "%6.4f\t%6.4f\t%6.4f\t%6.4f\t%6.4f\t%6.4f\t%6.4f"
for bin, val in data:
percent = float(val) / total
cumul_up += val
percent_cumul_up = float(cumul_up) / total
percent_cumul_down = float(cumul_down) / total
print(form %
(bin, val, percent, cumul_up, percent_cumul_up,
cumul_down, percent_cumul_down))
cumul_down -= val
else:
if options.truncate:
options.truncate = list(map(float, options.truncate.split(",")))
options.method = options.method.split(",")
data, legend = IOTools.readTable(sys.stdin,
numeric_type=numpy.float32,
take=options.columns,
headers=options.headers,
truncate=options.truncate,
cumulate_out_of_range=options.cumulate_out_of_range)
nfields = len(legend)
# note: because of MA, iteration makes copy of slices
# Solution: inplace edits.
nrows, ncols = data.shape
for method in options.method:
if method == "cumul":
l = [0] * ncols
for x in range(nrows):
for y in range(1, ncols):
data[x, y] += l[y]
l[y] = data[x, y]
elif method == "rcumul":
l = [0] * ncols
for x in range(nrows - 1, 0, -1):
for y in range(1, ncols):
data[x, y] += l[y]
l[y] = data[x, y]
elif method == "normalize":
m = [0] * ncols
for x in range(nrows):
for y in range(1, ncols):
# the conversion to float is necessary
m[y] = max(m[y], float(data[x, y]))
for y in range(1, ncols):
if m[y] == 0:
m[y] = 1.0
for x in range(nrows):
for y in range(1, ncols):
data[x, y] = data[x, y] / m[y]
else:
raise "unknown method %s" % method
print("\t".join(legend))
format = options.format_bin + "\t" + \
"\t".join([options.format_val] * (nfields - 1))
for d in data:
print(format % tuple(d))
E.Stop()
def main():
parser = E.OptionParser(
version="%prog version: $Id: plot_histogram.py 2782 2009-09-10 11:40:29Z andreas $", usage=globals()["__doc__"])
parser.add_option("-l", "--legend", dest="legend", type="string",
help="legend for plot [default=%default].")
parser.add_option("-t", "--title", dest="title", type="string",
help="title for plot [default=%default].")
parser.add_option("-p", "--hardcopy", dest="hardcopy", type="string",
help="filename for hardcopy of plot. The extension defines the format. Known extensions are: 'emf, eps, jpeg, jpg, pdf, png, ps, raw, rgba, svg, svgz' [default=%default].", metavar="FILE")
parser.add_option("", "--xrange", dest="xrange", type="string",
help="x viewing range of plot [default=%default].")
parser.add_option("", "--yrange", dest="yrange", type="string",
help="y viewing range of plot[default=%default].")
parser.add_option("-o", "--logscale", dest="logscale", type="string",
help="use logscale on x, y or xy [default=%default]")
parser.add_option("-x", "--xtitle", dest="xtitle", type="string",
help="title for x axis [default=%default]")
parser.add_option("-y", "--ytitle", dest="ytitle", type="string",
help="title for y axis [default=%default]")
parser.add_option("-d", "--dpi", dest="dpi", type="int",
help="dpi of images [default=%default]")
parser.add_option("-n", "--normalize", dest="normalize", action="store_true",
help="normalize histograms [default=%default]")
parser.add_option("--cumulate", dest="cumulate", action="store_true",
help="calculate cumulative histogram [default=%default].")
parser.add_option("--reverse-cumulate", dest="reverse_cumulate", action="store_true",
help="calculate cumulative histogram in reverse order [default=%default].")
parser.add_option("--legend-location", dest="legend_location", type="choice",
choices=("upper left", "upper right", "lower left",
"lower right", "center", "center right", "center left", "none"),
help="location of legend [default=%default]")
parser.add_option("--backend", dest="backend", type="string",
help="backend to use [Agg|SVG|PS] [default=%default]")
parser.add_option("--symbols", dest="symbols", type="string",
help="symbols to use for each histogram [steps|...] [default=%default].")
parser.add_option("--dump", dest="dump", action="store_true",
help="dump data for debug purposes [default=%default].")
parser.add_option("-c", "--columns", dest="columns", type="string",
help="columns to use for plotting [default=%default].")
parser.add_option("--truncate", dest="truncate", action="store_true",
help="truncate date within x range. If not set, xrange is simply a viewing range [default=%default].")
parser.add_option("--as-lines", dest="as_lines", action="store_true",
help="plot only lines, no symbols [default=%default].")
parser.add_option("--noheaders", dest="headers", action="store_false",
help="do not take first input line as header [default=%default].")
parser.add_option("--stacked", dest="stacked", action="store_true",
help="do a stacked plot [default=%default].")
parser.add_option("--add-function", dest="function", type="string",
help="add a function to the plot [default=%default].")
parser.add_option("--add-error-bars", dest="error_bars", type="choice",
choices=("interleaved", "blocked"),
help="add error bars. The input format is 'interleaved' or 'blocked'. In the interleaved format the error follows each column. I the blocked format first the data, then the errors in the same order [default=%default].")
parser.set_defaults(
legend=None,
title=None,
hardcopy=None,
logscale=None,
xtitle=None,
ytitle=None,
xrange=None,
yrange=None,
normalize=None,
columns="all",
headers=True,
legend_location="upper right",
backend="cairo",
symbols="g-D,b-h,r-+,c-+,m-+,y-+,k-o,g-^,b-<,r->,c-D,m-h",
dump=False,
truncate=False,
cumulate=False,
reverse_cumulate=False,
function=None,
add_error_bars=None,
as_lines=False,
stacked=False,
dpi=80,
)
(options, args) = E.Start(parser)
# import matplotlib/pylab. Has to be done here
# for batch scripts without GUI.
import matplotlib
if options.hardcopy:
matplotlib.use("cairo")
import pylab
# put this method here (because it requires pylab)
def doStackedPlot(data, legend):
colors = ["red",
"blue",
"green",
"cyan",
"magenta",
"yellow",
"brown",
"silver",
"purple",
"lightyellow",
"black",
"ivory",
"pink",
"orange",
"gray",
"teal"]
ax = data[:, 0]
xvals = numpy.concatenate((ax, ax[::-1]))
y_top = numpy.zeros(len(ax))
min_y = min(data[:, 1:].flat)
max_y = min_y
new_legend, dummy_lines = [], []
for i in range(1, len(legend)):
new_y_top = y_top + data[:, i]
yvals = numpy.concatenate((new_y_top, y_top[::-1]))
p = pylab.fill(xvals,
yvals,
colors[i % len(colors)])
y_top = new_y_top
max_y = max(y_top)
dummy_lines.append(pylab.plot(xvals,
yvals,
colors[i % len(colors)]))
new_legend.append(legend[i])
if not options.xrange:
options.xrange = min(data[:, 0]), max(data[:, 0])
if not options.yrange:
options.yrange = 0, max_y
return dummy_lines, new_legend
if options.as_lines:
options.symbols = []
for y in ("-", ":", "--"):
for x in "gbrcmyk":
options.symbols.append(y + x)
else:
options.symbols = options.symbols.split(",")
if options.xrange:
options.xrange = map(float, options.xrange.split(","))
if options.yrange:
options.yrange = map(float, options.yrange.split(","))
# Added support for (inclusive) range format: "1,3,5,7-100" (Gerton
# 13/12/06)
if options.columns != "all":
cols = []
for d in options.columns.split(','):
colopts = d.split('-')
if len(colopts) == 2:
cols += range(int(colopts[0]), int(colopts[1]) + 1)
else:
cols += [int(d) - 1]
options.columns = cols
if args:
if args[0] == "-":
infile = sys.stdin
else:
infile = open(args[0], "r")
else:
infile = sys.stdin
if options.truncate:
xr = options.xrange
else:
xr = None
data, legend = IOTools.readTable(infile,
numeric_type=numpy.float,
take=options.columns,
headers=options.headers,
truncate=xr)
if infile != sys.stdin:
infile.close()
if len(data) == 0: # or data is None:
E.info("empty table: no plot")
E.Stop()
return
nrows, ncols = data.shape
# note: because of MA, iteration makes copy of slices
# Solution: inplace edits.
if options.cumulate:
if options.add_error_bars:
raise "can not add error bars to cumulative histogram."
if data.mask.any():
# cumsum does not work with masked arrays, so do it manually
for y in range(1, ncols):
c = 0
for x in range(0, nrows):
if not data.mask[x, y]:
data[x, y] += c
c = data[x, y]
else:
for x in range(1, ncols):
data[:, x] = data[:, x].cumsum()
elif options.reverse_cumulate:
if options.add_error_bars:
raise "can not add error bars to cumulative histogram."
if data.mask.any():
l = [0] * ncols
for x in range(nrows - 1, -1, -1):
for y in range(1, ncols):
if not data.mask[x, y]:
data[x, y] += l[y]
l[y] = data[x, y]
else:
l = [0] * ncols
for x in range(nrows - 1, -1, -1):
for y in range(1, ncols):
data[x, y] += l[y]
l[y] = data[x, y]
if options.normalize:
if options.add_error_bars:
raise "can not add error bars to normalized histogram."
if data.mask.any():
m = [0] * ncols
for x in range(nrows):
for y in range(1, ncols):
if not data.mask[x, y]:
m[y] = max(m[y], float(data[x, y]))
for y in range(1, ncols):
if m[y] == 0:
m[y] = 1.0
for x in range(nrows):
for y in range(1, ncols):
data[x, y] = data[x, y] / m[y]
else:
for x in range(1, ncols):
m = float(data[:, x].max())
data[:, x] /= m
if options.legend:
legend = options.legend.split(",")
if options.dump:
for d in data:
print d
if options.title:
pylab.title(options.title)
if options.xtitle:
pylab.xlabel(options.xtitle)
else:
pylab.xlabel(legend[0])
if options.ytitle:
pylab.ylabel(options.ytitle)
lines = []
# use dummy_lines to workaround a bug in errorbars that
# causes the line styles to be set incorrectly.
dummy_lines = []
new_legend = []
if options.error_bars:
if options.error_bars == "interleaved":
step_size = 2
max_size = len(legend)
elif options.error_bars == "blocked":
step_size = 1
max_size = (len(legend) - 1) / 2
else:
step_size = 1
max_size = len(legend)
if options.stacked:
dummy_lines, new_legend = doStackedPlot(data, legend)
else:
nplotted = 0
nskipped = 0
for x in range(1, max_size, step_size):
s = options.symbols[nplotted % len(options.symbols)]
yvals = data[:, x]
xvals = numpy.ma.masked_array(data[:, 0], numpy.ma.getmask(yvals))
xvals = xvals.compressed()
yvals = yvals.compressed()
if len(xvals) == 0:
E.warn("skipped empty column %i: %s" % (x, legend[x]))
if options.error_bars == "interleaved":
yerr = data[:, x + 1]
yerr = yerr.compressed()
else:
yerr = None
lines.append(pylab.errorbar(xvals,
yvals,
yerr=yerr,
fmt=s))
dummy_lines.append(pylab.plot(xvals,
yvals,
s))
new_legend.append(legend[x])
nplotted += 1
E.info("nplotted=%i, nskipped=%i" % (nplotted, nskipped))
if len(lines) == 0:
E.Stop()
return
if options.legend_location != "none":
pylab.figlegend(dummy_lines,
new_legend,
options.legend_location)
if options.logscale:
if "x" in options.logscale:
pylab.gca().set_xscale('log')
if "y" in options.logscale:
pylab.gca().set_yscale('log')
if options.xrange:
pylab.xlim(options.xrange)
if options.yrange:
pylab.ylim(options.yrange)
if options.function:
xstart, xend = pylab.gca().get_xlim()
increment = (xend - xstart) / 100.0
exec("f = lambda x: %s" % options.function) in locals()
xvals, yvals = [], []
for x in range(0, 100):
xvals.append(xstart)
yvals.append(f(xstart))
xstart += increment
xvals.append(xstart)
yvals.append(f(xstart))
pylab.plot(xvals, yvals)
if options.hardcopy:
pylab.savefig(os.path.expanduser(options.hardcopy), dpi=options.dpi)
else:
pylab.show()
E.Stop()
percent_cumul_up = float(cumul_up) / total
percent_cumul_down = float(cumul_down) / total
print form % \
(bin, val, percent, cumul_up, percent_cumul_up, cumul_down, percent_cumul_down)
cumul_down -= val
else:
if options.truncate: options.truncate = map(float, options.truncate.split(","))
options.method = options.method.split(",")
data, legend = IOTools.readTable( sys.stdin,
numeric_type=numpy.float32,
take=options.columns,
headers = options.headers,
truncate= options.truncate,
cumulate_out_of_range = options.cumulate_out_of_range )
nfields = len(legend)
## note: because of MA, iteration makes copy of slices
## Solution: inplace edits.
nrows, ncols = data.shape
for method in options.method:
if method == "cumul":
l = [0] * ncols
for x in range(nrows):
for y in range(1, ncols):
data[x,y] += l[y]
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")
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 )):
def main(argv=None):
parser = E.OptionParser(
version=
"%prog version: $Id: plot_histogram.py 2782 2009-09-10 11:40:29Z andreas $",
usage=globals()["__doc__"])
parser.add_option("-l",
"--legend",
dest="legend",
type="string",
help="legend for plot [default=%default].")
parser.add_option("-t",
"--title",
dest="title",
type="string",
help="title for plot [default=%default].")
parser.add_option(
"-p",
"--hardcopy",
dest="hardcopy",
type="string",
help=
"filename for hardcopy of plot. The extension defines the format. Known extensions are: 'emf, eps, jpeg, jpg, pdf, png, ps, raw, rgba, svg, svgz' [default=%default].",
metavar="FILE")
parser.add_option("",
"--xrange",
dest="xrange",
type="string",
help="x viewing range of plot [default=%default].")
parser.add_option("",
"--yrange",
dest="yrange",
type="string",
help="y viewing range of plot[default=%default].")
parser.add_option("-o",
"--logscale",
dest="logscale",
type="string",
help="use logscale on x, y or xy [default=%default]")
parser.add_option("-x",
"--xtitle",
dest="xtitle",
type="string",
help="title for x axis [default=%default]")
parser.add_option("-y",
"--ytitle",
dest="ytitle",
type="string",
help="title for y axis [default=%default]")
parser.add_option("-d",
"--dpi",
dest="dpi",
type="int",
help="dpi of images [default=%default]")
parser.add_option("-n",
"--normalize",
dest="normalize",
action="store_true",
help="normalize histograms [default=%default]")
parser.add_option(
"--cumulate",
dest="cumulate",
action="store_true",
help="calculate cumulative histogram [default=%default].")
parser.add_option(
"--reverse-cumulate",
dest="reverse_cumulate",
action="store_true",
help=
"calculate cumulative histogram in reverse order [default=%default].")
parser.add_option("--legend-location",
dest="legend_location",
type="choice",
choices=("upper left", "upper right", "lower left",
"lower right", "center", "center right",
"center left", "none"),
help="location of legend [default=%default]")
parser.add_option("--backend",
dest="backend",
type="string",
help="backend to use [Agg|SVG|PS] [default=%default]")
parser.add_option(
"--symbols",
dest="symbols",
type="string",
help="symbols to use for each histogram [steps|...] [default=%default]."
)
parser.add_option("--dump",
dest="dump",
action="store_true",
help="dump data for debug purposes [default=%default].")
parser.add_option("-c",
"--columns",
dest="columns",
type="string",
help="columns to use for plotting [default=%default].")
parser.add_option(
"--truncate",
dest="truncate",
action="store_true",
help=
"truncate date within x range. If not set, xrange is simply a viewing range [default=%default]."
)
parser.add_option("--as-lines",
dest="as_lines",
action="store_true",
help="plot only lines, no symbols [default=%default].")
parser.add_option(
"--noheaders",
dest="headers",
action="store_false",
help="do not take first input line as header [default=%default].")
parser.add_option("--stacked",
dest="stacked",
action="store_true",
help="do a stacked plot [default=%default].")
parser.add_option("--add-function",
dest="function",
type="string",
help="add a function to the plot [default=%default].")
parser.add_option(
"--add-error-bars",
dest="error_bars",
type="choice",
choices=("interleaved", "blocked"),
help=
"add error bars. The input format is 'interleaved' or 'blocked'. In the interleaved format the error follows each column. I the blocked format first the data, then the errors in the same order [default=%default]."
)
parser.set_defaults(
legend=None,
title=None,
hardcopy=None,
logscale=None,
xtitle=None,
ytitle=None,
xrange=None,
yrange=None,
normalize=None,
columns="all",
headers=True,
legend_location="upper right",
backend="cairo",
symbols="g-D,b-h,r-+,c-+,m-+,y-+,k-o,g-^,b-<,r->,c-D,m-h",
dump=False,
truncate=False,
cumulate=False,
reverse_cumulate=False,
function=None,
add_error_bars=None,
as_lines=False,
stacked=False,
dpi=80,
)
(options, args) = E.Start(parser)
# import matplotlib/pylab. Has to be done here
# for batch scripts without GUI.
import matplotlib
if options.hardcopy:
matplotlib.use("cairo")
import pylab
# put this method here (because it requires pylab)
def doStackedPlot(data, legend):
colors = [
"red", "blue", "green", "cyan", "magenta", "yellow", "brown",
"silver", "purple", "lightyellow", "black", "ivory", "pink",
"orange", "gray", "teal"
]
ax = data[:, 0]
xvals = numpy.concatenate((ax, ax[::-1]))
y_top = numpy.zeros(len(ax))
min_y = min(data[:, 1:].flat)
max_y = min_y
new_legend, dummy_lines = [], []
for i in range(1, len(legend)):
new_y_top = y_top + data[:, i]
yvals = numpy.concatenate((new_y_top, y_top[::-1]))
p = pylab.fill(xvals, yvals, colors[i % len(colors)])
y_top = new_y_top
max_y = max(y_top)
dummy_lines.append(
pylab.plot(xvals, yvals, colors[i % len(colors)]))
new_legend.append(legend[i])
if not options.xrange:
options.xrange = min(data[:, 0]), max(data[:, 0])
if not options.yrange:
options.yrange = 0, max_y
return dummy_lines, new_legend
if options.as_lines:
options.symbols = []
for y in ("-", ":", "--"):
for x in "gbrcmyk":
options.symbols.append(y + x)
else:
options.symbols = options.symbols.split(",")
if options.xrange:
options.xrange = map(float, options.xrange.split(","))
if options.yrange:
options.yrange = map(float, options.yrange.split(","))
# Added support for (inclusive) range format: "1,3,5,7-100" (Gerton
# 13/12/06)
if options.columns != "all":
cols = []
for d in options.columns.split(','):
colopts = d.split('-')
if len(colopts) == 2:
cols += range(int(colopts[0]), int(colopts[1]) + 1)
else:
cols += [int(d) - 1]
options.columns = cols
if args:
if args[0] == "-":
infile = sys.stdin
else:
infile = open(args[0], "r")
else:
infile = sys.stdin
if options.truncate:
xr = options.xrange
else:
xr = None
data, legend = IOTools.readTable(infile,
numeric_type=numpy.float,
take=options.columns,
headers=options.headers,
truncate=xr)
if infile != sys.stdin:
infile.close()
if len(data) == 0: # or data is None:
E.info("empty table: no plot")
E.Stop()
return
nrows, ncols = data.shape
# note: because of MA, iteration makes copy of slices
# Solution: inplace edits.
if options.cumulate:
if options.add_error_bars:
raise "can not add error bars to cumulative histogram."
if data.mask.any():
# cumsum does not work with masked arrays, so do it manually
for y in range(1, ncols):
c = 0
for x in range(0, nrows):
if not data.mask[x, y]:
data[x, y] += c
c = data[x, y]
else:
for x in range(1, ncols):
data[:, x] = data[:, x].cumsum()
elif options.reverse_cumulate:
if options.add_error_bars:
raise "can not add error bars to cumulative histogram."
if data.mask.any():
l = [0] * ncols
for x in range(nrows - 1, -1, -1):
for y in range(1, ncols):
if not data.mask[x, y]:
data[x, y] += l[y]
l[y] = data[x, y]
else:
l = [0] * ncols
for x in range(nrows - 1, -1, -1):
for y in range(1, ncols):
data[x, y] += l[y]
l[y] = data[x, y]
if options.normalize:
if options.add_error_bars:
raise "can not add error bars to normalized histogram."
if data.mask.any():
m = [0] * ncols
for x in range(nrows):
for y in range(1, ncols):
if not data.mask[x, y]:
m[y] = max(m[y], float(data[x, y]))
for y in range(1, ncols):
if m[y] == 0:
m[y] = 1.0
for x in range(nrows):
for y in range(1, ncols):
data[x, y] = data[x, y] / m[y]
else:
for x in range(1, ncols):
m = float(data[:, x].max())
data[:, x] /= m
if options.legend:
legend = options.legend.split(",")
if options.dump:
for d in data:
print d
if options.title:
pylab.title(options.title)
if options.xtitle:
pylab.xlabel(options.xtitle)
else:
pylab.xlabel(legend[0])
if options.ytitle:
pylab.ylabel(options.ytitle)
lines = []
# use dummy_lines to workaround a bug in errorbars that
# causes the line styles to be set incorrectly.
dummy_lines = []
new_legend = []
if options.error_bars:
if options.error_bars == "interleaved":
step_size = 2
max_size = len(legend)
elif options.error_bars == "blocked":
step_size = 1
max_size = (len(legend) - 1) / 2
else:
step_size = 1
max_size = len(legend)
if options.stacked:
dummy_lines, new_legend = doStackedPlot(data, legend)
else:
nplotted = 0
nskipped = 0
for x in range(1, max_size, step_size):
s = options.symbols[nplotted % len(options.symbols)]
yvals = data[:, x]
xvals = numpy.ma.masked_array(data[:, 0], numpy.ma.getmask(yvals))
xvals = xvals.compressed()
yvals = yvals.compressed()
if len(xvals) == 0:
E.warn("skipped empty column %i: %s" % (x, legend[x]))
if options.error_bars == "interleaved":
yerr = data[:, x + 1]
yerr = yerr.compressed()
else:
yerr = None
lines.append(pylab.errorbar(xvals, yvals, yerr=yerr, fmt=s))
dummy_lines.append(pylab.plot(xvals, yvals, s))
new_legend.append(legend[x])
nplotted += 1
E.info("nplotted=%i, nskipped=%i" % (nplotted, nskipped))
if len(lines) == 0:
E.Stop()
return
if options.legend_location != "none":
pylab.figlegend(dummy_lines, new_legend, options.legend_location)
if options.logscale:
if "x" in options.logscale:
pylab.gca().set_xscale('log')
if "y" in options.logscale:
pylab.gca().set_yscale('log')
if options.xrange:
pylab.xlim(options.xrange)
if options.yrange:
pylab.ylim(options.yrange)
if options.function:
xstart, xend = pylab.gca().get_xlim()
increment = (xend - xstart) / 100.0
exec("f = lambda x: %s" % options.function) in locals()
xvals, yvals = [], []
for x in range(0, 100):
xvals.append(xstart)
yvals.append(f(xstart))
xstart += increment
xvals.append(xstart)
yvals.append(f(xstart))
pylab.plot(xvals, yvals)
if options.hardcopy:
pylab.savefig(os.path.expanduser(options.hardcopy), dpi=options.dpi)
else:
pylab.show()
E.Stop()