예제 #1
0
def main(args=None):
    args = parse_arguments().parse_args(args)

    corr = Correlation(
        args.corData,
        labels=args.labels,
    )

    args.plotFile.close()

    corr.plot_pca(args.plotFile.name,
                  plot_title=args.plotTitle,
                  image_format=args.plotFileFormat)

    if args.outFileNameData is not None:
        import matplotlib
        mlab_pca = matplotlib.mlab.PCA(corr.matrix)
        n = len(corr.labels)
        of = args.outFileNameData
        of.write("Component\t{}\tEigenvalue\n".format("\t".join(corr.labels)))
        for i in xrange(n):
            of.write("{}".format(i + 1))
            for v in mlab_pca.Wt[i, :]:
                of.write("\t{}".format(v))
            of.write("\t{}\n".format(mlab_pca.s[i]))
        args.outFileNameData.close()
예제 #2
0
def main(args=None):
    args = parse_arguments().parse_args(args)

    corr = Correlation(args.corData,
                       labels=args.labels,)

    args.plotFile.close()
    corr.rowCenter = args.rowCenter

    corr.plot_pca(args.plotFile.name,
                  plot_title=args.plotTitle,
                  image_format=args.plotFileFormat)

    if args.outFileNameData is not None:
        import matplotlib
        mlab_pca = matplotlib.mlab.PCA(corr.matrix)
        n = len(corr.labels)
        of = args.outFileNameData
        of.write("Component\t{}\tEigenvalue\n".format("\t".join(corr.labels)))
        for i in range(n):
            of.write("{}".format(i + 1))
            for v in mlab_pca.Wt[i, :]:
                of.write("\t{}".format(v))
            of.write("\t{}\n".format(mlab_pca.s[i]))
        args.outFileNameData.close()
예제 #3
0
def main(args=None):
    args = parse_arguments().parse_args(args)

    corr = Correlation(args.corData,
                       labels=args.labels,)

    args.plotFile.close()

    corr.plot_pca(args.plotFile.name,
                  plot_title=args.plotTitle,
                  image_format=args.plotFileFormat)
예제 #4
0
def main(args=None):
    args = parse_arguments().parse_args(args)

    corr = Correlation(
        args.corData,
        labels=args.labels,
    )

    if args.outFileCorMatrix:
        corr.save_corr_matrix(args.outFileCorMatrix)

    args.plotFile.close()

    corr.plot_pca(args.plotFile.name,
                  plot_title=args.plotTitle,
                  image_format=args.plotFileFormat)
예제 #5
0
def main(args=None):
    args = parse_arguments().parse_args(args)

    if args.plotFile is None and args.outFileNameData is None:
        sys.exit(
            "At least one of --plotFile and --outFileNameData must be specified!\n"
        )

    if args.ntop < 0:
        sys.exit("The value specified for --ntop must be >= 0!\n")

    if args.PCs[0] == args.PCs[1]:
        sys.exit("You must specify different principal components!\n")
    if args.PCs[0] <= 0 or args.PCs[1] <= 0:
        sys.exit("The specified principal components must be at least 1!\n")

    corr = Correlation(
        args.corData,
        labels=args.labels,
    )

    corr.rowCenter = args.rowCenter
    corr.transpose = args.transpose
    corr.ntop = args.ntop
    corr.log2 = args.log2

    Wt, eigenvalues = corr.plot_pca(args.plotFile,
                                    PCs=args.PCs,
                                    plot_title=args.plotTitle,
                                    image_format=args.plotFileFormat,
                                    plotWidth=args.plotWidth,
                                    plotHeight=args.plotHeight,
                                    cols=args.colors,
                                    marks=args.markers)

    if args.outFileNameData is not None:
        of = open(args.outFileNameData, "w")
        of.write("#plotPCA --outFileNameData\n")
        of.write("Component\t{}\tEigenvalue\n".format("\t".join(corr.labels)))
        n = eigenvalues.shape[0]
        for i in range(n):
            of.write("{}\t{}\t{}\n".format(
                i + 1, "\t".join(["{}".format(x) for x in Wt[i, :]]),
                eigenvalues[i]))
        of.close()
예제 #6
0
def main(args=None):
    args = parse_arguments().parse_args(args)

    if args.plotFile is None and args.outFileNameData is None:
        sys.exit("At least one of --plotFile and --outFileNameData must be specified!\n")

    if args.ntop < 0:
        sys.exit("The value specified for --ntop must be >= 0!\n")

    if args.PCs[0] == args.PCs[1]:
        sys.exit("You must specify different principal components!\n")
    if args.PCs[0] <= 0 or args.PCs[1] <= 0:
        sys.exit("The specified principal components must be at least 1!\n")

    corr = Correlation(args.corData,
                       labels=args.labels,)

    corr.rowCenter = args.rowCenter
    corr.transpose = args.transpose
    corr.ntop = args.ntop
    corr.log2 = args.log2

    Wt, eigenvalues = corr.plot_pca(args.plotFile,
                                    PCs=args.PCs,
                                    plot_title=args.plotTitle,
                                    image_format=args.plotFileFormat,
                                    plotWidth=args.plotWidth,
                                    plotHeight=args.plotHeight,
                                    cols=args.colors,
                                    marks=args.markers)

    if args.outFileNameData is not None:
        of = open(args.outFileNameData, "w")
        of.write("#plotPCA --outFileNameData\n")
        of.write("Component\t{}\tEigenvalue\n".format("\t".join(corr.labels)))
        n = eigenvalues.shape[0]
        for i in range(n):
            of.write("{}\t{}\t{}\n".format(i + 1, "\t".join(["{}".format(x) for x in Wt[i, :]]), eigenvalues[i]))
        of.close()