def _runRScript(RScript):
rscriptname = rosettahelper.writeTempFile(".", RScript)
#p = subprocess.Popen(["/opt/R-2.15.1/bin/R","CMD", "BATCH", rscriptname])
p = subprocess.Popen(["R", "CMD", "BATCH", rscriptname])
while True:
time.sleep(0.3)
errcode = p.poll()
if errcode != None:
break
rout = "%s.Rout" % rscriptname
delete_file(rscriptname)
#colortext.warning(rosettahelper.readFile(rout))
rout_contents = None
if os.path.exists(rout):
rout_contents = rosettahelper.readFile(rout)
if errcode != 0:
if os.path.exists(rout):
colortext.warning(rout_contents)
delete_file(rout)
raise colortext.Exception(
"The R script failed with error code %d." % errcode)
delete_file(rout)
return rout_contents
def _correlation_coefficient(inputfname, output_filename, filetype, experiment_field = "ExperimentalDDG"):
'''File suffix: pearsons_r
Description: Pearson's r
'''
# todo: The graph size is not being set correctly i.e. the max function call is wrong in the script
title = "" # "Pearson's r"
RScript = rosettahelper.readFile(os.path.join(script_path, "R", "pearsons.R")) % vars()
return RInterface._runRScript(RScript)
def correlation_coefficient_gplot(inputfname, output_filename, filetype, experiment_field = "ExperimentalDDG"):
'''File suffix: pearsons_r_gplot
Description: Pearson's r
Filename: ggplot_pearsons.R
Priority: 1
'''
title = "" #Pearson's r"
RScript = rosettahelper.readFile(os.path.join(script_path, "R", "ggplot_pearsons.R")) % vars()
return RInterface._runRScript(RScript)
def correlation_coefficient_gplot_crop(inputfname, output_filename, filetype, experiment_field = "ExperimentalDDG"):
'''File suffix: pearsons_r_gplot_cropped
Description: Pearson's r filtering with quantile(res, probs = c(0.05,0.95))
Filename: ggplot_pearsons_cropped.R
Priority: 3
'''
title = "" #Pearson's r filtering with quantile(res, probs = c(0.05,0.95))"
RScript = rosettahelper.readFile(os.path.join(script_path, "R", "ggplot_pearsons_cropped.R")) % vars()
return RInterface._runRScript(RScript)
def _correlation_coefficient(inputfname,
output_filename,
filetype,
experiment_field="ExperimentalDDG"):
'''File suffix: pearsons_r
Description: Pearson's r
'''
# todo: The graph size is not being set correctly i.e. the max function call is wrong in the script
title = "" # "Pearson's r"
RScript = rosettahelper.readFile(
os.path.join(script_path, "R", "pearsons.R")) % vars()
return RInterface._runRScript(RScript)
def correlation_coefficient_gplot(inputfname,
output_filename,
filetype,
experiment_field="ExperimentalDDG"):
'''File suffix: pearsons_r_gplot
Description: Pearson's r
Filename: ggplot_pearsons.R
Priority: 1
'''
title = "" #Pearson's r"
RScript = rosettahelper.readFile(
os.path.join(script_path, "R", "ggplot_pearsons.R")) % vars()
return RInterface._runRScript(RScript)
def correlation_coefficient_gplot_crop(inputfname,
output_filename,
filetype,
experiment_field="ExperimentalDDG"):
'''File suffix: pearsons_r_gplot_cropped
Description: Pearson's r filtering with quantile(res, probs = c(0.05,0.95))
Filename: ggplot_pearsons_cropped.R
Priority: 3
'''
title = "" #Pearson's r filtering with quantile(res, probs = c(0.05,0.95))"
RScript = rosettahelper.readFile(
os.path.join(script_path, "R",
"ggplot_pearsons_cropped.R")) % vars()
return RInterface._runRScript(RScript)
def _runRScript(RScript):
rscriptname = rosettahelper.writeTempFile(".", RScript)
#p = subprocess.Popen(["/opt/R-2.15.1/bin/R","CMD", "BATCH", rscriptname])
p = subprocess.Popen(["R", "CMD", "BATCH", rscriptname])
while True:
time.sleep(0.3)
errcode = p.poll()
if errcode != None:
break
rout = "%s.Rout" % rscriptname
delete_file(rscriptname)
#colortext.warning(rosettahelper.readFile(rout))
rout_contents = None
if os.path.exists(rout):
rout_contents = rosettahelper.readFile(rout)
if errcode != 0:
if os.path.exists(rout):
colortext.warning(rout_contents)
delete_file(rout)
raise colortext.Exception("The R script failed with error code %d." % errcode)
delete_file(rout)
return rout_contents
def CreateReport(self, outfname = 'test.pdf', description = None, filetype = "pdf"):
latexdoc = latex.LaTeXDocument("$\\Delta\\Delta$G analysis", pdf_title = "DDG analysis")
analysis_objects = self.analyzer.PlotAll(filetype = filetype, createFiles = False)
analysis_by_dataset = {}
for analysis_object in analysis_objects:
dataset = analysis_object.dataset
analysis_by_dataset[dataset] = analysis_by_dataset.get(dataset, [])
analysis_by_dataset[dataset].append(analysis_object)
count = 0
try:
if description:
latexdoc.addSection("Description")
for tagged_line in description:
color = tagged_line[0]
line = tagged_line[1]
latexdoc.addLaTeXCode("\\textcolor{%s}{%s}\n" % (color, line))
if analysis_by_dataset:
latexdoc.addSection("Analysis")
for dataset, analysis_objects in analysis_by_dataset.iteritems():
latexdoc.addSubsection(dataset)
# The tab solution here is messy. Redo this when we decide what LaTeX floats we want to use
captiontabs = []
imagetabs = []
for analysis_object in analysis_objects:
count +=1
filename = "graph%d" + (".%s" % filetype)
rosettahelper.writeFile(filename % count, analysis_object.contents)
captiontabs.append(analysis_object.description)
imagetabs.append(latexdoc.getImageText(filename % count, width_cm = 6))
self.graphfiles.append(filename)
assert(len(captiontabs) == len(imagetabs))
captiontabs = [captiontabs[i:i+2] for i in range(0, len(captiontabs), 2)]
imagetabs = [imagetabs[i:i+2] for i in range(0, len(imagetabs), 2)]
assert(len(captiontabs) == len(imagetabs))
tabs = []
for i in range(len(captiontabs)):
tabs.append(captiontabs[i])
tabs.append(imagetabs[i])
latexdoc.addTabular(tabs, alignment = 'c')
latexdoc.clearPage()
latexdoc.addSection("R files")
for analysisType, data in sorted(RFunctions.iteritems(), key=lambda x: x[1][2]):
description = data[0]
RFunction = data[1]
filename = data[3]
latexdoc.addSubsection(description)
latexdoc.addTypewriterText(rosettahelper.readFile(os.path.join(script_path, "R", filename)), language="R")
latexdoc.clearPage()
latexdoc.compile_pdf(outfname)
except Exception, e:
self.clean()
raise
def CreateReport(self,
outfname='test.pdf',
description=None,
filetype="pdf"):
latexdoc = latex.LaTeXDocument("$\\Delta\\Delta$G analysis",
pdf_title="DDG analysis")
analysis_objects = self.analyzer.PlotAll(filetype=filetype,
createFiles=False)
analysis_by_dataset = {}
for analysis_object in analysis_objects:
dataset = analysis_object.dataset
analysis_by_dataset[dataset] = analysis_by_dataset.get(dataset, [])
analysis_by_dataset[dataset].append(analysis_object)
count = 0
try:
if description:
latexdoc.addSection("Description")
for tagged_line in description:
color = tagged_line[0]
line = tagged_line[1]
latexdoc.addLaTeXCode("\\textcolor{%s}{%s}\n" %
(color, line))
if analysis_by_dataset:
latexdoc.addSection("Analysis")
for dataset, analysis_objects in analysis_by_dataset.iteritems():
latexdoc.addSubsection(dataset)
# The tab solution here is messy. Redo this when we decide what LaTeX floats we want to use
captiontabs = []
imagetabs = []
for analysis_object in analysis_objects:
count += 1
filename = "graph%d" + (".%s" % filetype)
rosettahelper.writeFile(filename % count,
analysis_object.contents)
captiontabs.append(analysis_object.description)
imagetabs.append(
latexdoc.getImageText(filename % count, width_cm=6))
self.graphfiles.append(filename)
assert (len(captiontabs) == len(imagetabs))
captiontabs = [
captiontabs[i:i + 2]
for i in range(0, len(captiontabs), 2)
]
imagetabs = [
imagetabs[i:i + 2] for i in range(0, len(imagetabs), 2)
]
assert (len(captiontabs) == len(imagetabs))
tabs = []
for i in range(len(captiontabs)):
tabs.append(captiontabs[i])
tabs.append(imagetabs[i])
latexdoc.addTabular(tabs, alignment='c')
latexdoc.clearPage()
latexdoc.addSection("R files")
for analysisType, data in sorted(RFunctions.iteritems(),
key=lambda x: x[1][2]):
description = data[0]
RFunction = data[1]
filename = data[3]
latexdoc.addSubsection(description)
latexdoc.addTypewriterText(rosettahelper.readFile(
os.path.join(script_path, "R", filename)),
language="R")
latexdoc.clearPage()
latexdoc.compile_pdf(outfname)
except Exception, e:
self.clean()
raise