def appendInfo(self, inputFname=None, db_vervet=None, outputFname=None,\
inversePCValue=True):
"""
#2012.9.25 skip samples whose individual_alignment entry could not be parsed.
2012.9.5
"""
sys.stderr.write("Appending info to %s ..."%(inputFname))
reader = MatrixFile(inputFname)
header = reader.next()
newHeader = ['individualID']
for i in xrange(1, len(header)):
newHeader.append('PC%s'%(i))
newHeader.extend(['sex|string', 'country|string', 'site-id', 'site-name|string', 'latitude', 'longitude', 'ucla_id|string', \
'tax_id|string',\
'species|string', 'collectionYear', 'medianDepth'])
writer = csv.writer(open(outputFname, 'w'), delimiter='\t')
writer.writerow(newHeader)
counter = 0
for row in reader:
row = row[:len(header)] #don't take extra columns
sampleID = row[0]
individualAlignment = db_vervet.parseAlignmentReadGroup(sampleID).individualAlignment
if individualAlignment is None:
#2012.9.25
#sampleID is not beginned with alignment ID, probably "ref" but could be something , skip them
sys.stderr.write("Warning: sampleID %s is not parsable to get alignment out of it. Skip.\n"%(sampleID))
continue
individual = individualAlignment.individual_sequence.individual
data_row = ['%s_%s'%(individual.code, individualAlignment.id)]
floatValue_row = row[1:]
if inversePCValue:
floatValue_row = map(float, floatValue_row)
floatValue_row = numpy.array(floatValue_row)
floatValue_row = -floatValue_row
data_row.extend(list(floatValue_row))
scientifcName = self.db_taxonomy.returnScientificNameGivenTaxID(individual.tax_id)
if scientifcName is None:
scientifcName = ""
if individual.collection_date:
collectionYear = individual.collection_date.year
else:
collectionYear = ''
data_row.extend([individual.sex, individual.site.country.name, individual.site.id, individual.site.short_name, \
individual.latitude, individual.longitude, individual.ucla_id, \
individual.tax_id, scientifcName, collectionYear, individualAlignment.median_depth])
writer.writerow(data_row)
counter += 1
del writer
sys.stderr.write("%s rows outputted.\n"%(counter))
def readInDataToPlot(self, input_fname, sampling_probability=1.0):
"""
2015.01.23 added argument sampling_probability to sub-sample data
2013.07.11 use MatrixFile to read in the file
2009-5-20
add the column index into the column header for easy picking
2009-3-13
wrap the float conversion part into try...except to report what goes wrong
2009-3-13
"""
if sampling_probability>1 or sampling_probability<0:
sampling_probability=1.0
reader = MatrixFile(inputFname=input_fname)
self.column_header=reader.next()
for i in range(len(self.column_header)):
self.column_header[i] = '%s %s'%(i, self.column_header[i])
no_of_cols = len(self.column_header)
self.column_types = [str]*2 + [float]*(no_of_cols-2)
self.column_editable_flag_ls = [True, True] + [False]*(no_of_cols-2)
self.list_2d = []
for row in reader:
if sampling_probability>0 and sampling_probability<1:
if random.random()>sampling_probability: #skip
continue
float_part = row[2:]
try:
float_part = map(float, float_part)
except:
sys.stderr.write('Except type: %s\n'%repr(sys.exc_info()))
traceback.print_exc()
new_row = row[:2]+float_part
self.list_2d.append(new_row)
reader.close()
self.setupColumns(self.treeview_matrix)
#update status to reflect the input filename
self.app1.set_title(os.path.basename(input_fname))
self.app1_appbar1.push(input_fname)
self.plotXY(self.ax, self.canvas, self.liststore, self.plot_title)
