From 4b501b7efafd10997692ebe9ac25fbef142568bd Mon Sep 17 00:00:00 2001 From: sonyahanson Date: Tue, 3 Feb 2015 13:51:34 -0500 Subject: [PATCH] Added example of 5 singlet data collection for xml2png.py --- ...SMH_SrcBos_Extend_013015_mdfx_20150130.xml | 1655 +++++++++++++++++ examples/xml2png_5/xml2png_5.py | 143 ++ 2 files changed, 1798 insertions(+) create mode 100644 examples/xml2png_5/Extend_WIP_SMH_SrcBos_Extend_013015_mdfx_20150130.xml create mode 100644 examples/xml2png_5/xml2png_5.py diff --git a/examples/xml2png_5/Extend_WIP_SMH_SrcBos_Extend_013015_mdfx_20150130.xml b/examples/xml2png_5/Extend_WIP_SMH_SrcBos_Extend_013015_mdfx_20150130.xml new file mode 100644 index 0000000..22e5acf --- /dev/null +++ b/examples/xml2png_5/Extend_WIP_SMH_SrcBos_Extend_013015_mdfx_20150130.xml @@ -0,0 +1,1655 @@ + + + + + + + SrcBos + + +
+ + + + + + infinite M1000 PRO + 1311007572 + + + MEX, V 1.20 Safire2 MCR (V 1.20 Safire2 MCR ) + MEM, V 1.20 Safire2 MCR (V 1.20 Safire2 MCR ) + FPO, V_1.03_Safire2 FP (V_1.03_Safire2 FP ) + ABS, V 1.00 MCR Abs 4 Channel (V 1.00 MCR Abs 4 Channel) + LUM, V_1.04_11/2011_LUMINESCENCE (Nov 02 2011/17.53.34) + BCR, V_1.00_02/2008_S3FTCAN + INA, V_1.05_11/2011_S3LCE_ALPHA (Nov 3 2011/09.27.24) + INB, V_1.05_11/2011_S3LCE_ALPHA (Nov 3 2011/09.27.24) + TCAN, V_1.00_02/2008_S3FTCAN (Feb 21 2008/17.19.16) + + + + + + +
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+ \ No newline at end of file diff --git a/examples/xml2png_5/xml2png_5.py b/examples/xml2png_5/xml2png_5.py new file mode 100644 index 0000000..29f1ed3 --- /dev/null +++ b/examples/xml2png_5/xml2png_5.py @@ -0,0 +1,143 @@ +# This script takes xml data file output from the Tecan Infinite m1000 Pro plate reader +# and makes quick and dirty images of the raw data. + +# The same procedure can be used to make matrices suitable for analysis using +# matrix = dataframe.values + +# Made by Sonya Hanson with significant help from JH Prinz. +# Wednesday, May 7, 2014 + +# Usage: python xml2png.py *.xml + +################### +# To Do +# +# Set fixed Y axis. +# Define Wells for Legend. +# Define x and y axes. +# Figure out @Name='Mode' thing. +# +################### + +import numpy as np +import matplotlib.pyplot as plt +from lxml import etree +import pandas as pd +import sys +import os + +# Define xml files. + +xml_files = sys.argv[1:] + +so_many = len(xml_files) +print "****This script is about to make png files for %s xml files. ****" % so_many + +# Define extract function that extracts parameters + +def extract(taglist): + result = [] + for p in taglist: + print "Attempting to extract tag '%s'..." % p + try: + param = parameters.xpath("*[@Name='" + p + "']")[0] + result.append( p + '=' + param.attrib['Value']) + except: + # tag not found + result.append(None) + + return result + +# Define get_wells_from_section function that extracts the data from each Section. +# It is written sort of strangely to ensure data is connected to the correct well. + +def get_wells_from_section(path): + reads = path.xpath("*/Well") + wellIDs = [read.attrib['Pos'] for read in reads] + + data = [(float(s.text), r.attrib['Pos']) + for r in reads + for s in r] + + datalist = { + well : value + for (value, well) in data + } + + welllist = [ + [ + datalist[chr(64 + row) + str(col)] + if chr(64 + row) + str(col) in datalist else None + for row in range(1,17) + ] + for col in range(1,24) + ] + + return welllist + +for file in xml_files: + + # Parse XML file. + + root = etree.parse(file) + + # Remove extension from xml filename. + + file_name = os.path.splitext(file)[0] + + # Define Sections. + + Sections = root.xpath("/*/Section") + much = len(Sections) + print "****The xml file " + file + " has %s data sections:****" % much + for sect in Sections: + print sect.attrib['Name'] + + data = [] + + for i, sect in enumerate(Sections): + + # Extract Parameters for this section. + + path = "/*/Section[@Name='" + sect.attrib['Name'] + "']/Parameters" + parameters = root.xpath(path)[0] + + # Parameters are extracted slightly differently depending on Absorbance or Fluorescence read. + + if parameters[0].attrib['Value'] == "Absorbance": + result = extract(["Mode", "Wavelength", "Part of Plate"]) + title = '%s, %s, %s' % tuple(result) + + else: + result = extract(["Gain", "Excitation Wavelength", "Emission Wavelength", "Part of Plate", "Mode"]) + title = '%s, %s, %s, \n %s, %s' % tuple(result) + + print "****The %sth section has the parameters:****" %i + print title + + # Extract Reads for this section. + + Sections = root.xpath("/*/Section") + + welllist = get_wells_from_section(sect) + + data.append( + { + 'filename' : file_name, + 'title' : title, + 'dataframe' : pd.DataFrame(welllist) + } + ) + + # Make plot, complete with subfigure for each section. + + fig, axes = plt.subplots(nrows=1,ncols=len(Sections), figsize=(60,4.5)) + + for i, sect in enumerate(data): + sect['dataframe'].plot(title = sect['title'] , ax = axes[i] ) + + fig.tight_layout() + fig.subplots_adjust(top=0.8) + fig.suptitle("%s" % file_name, fontsize=18) + + plt.savefig('%s.png' % file_name)