Example #1
0
def scatter_all_inputs(P, headers = None):
    if headers is None:
        #Number of columns
        headers = range(len(P[0,:]))
    rows = len(P[0,:]) - 1
    cols = rows
    #print "length of data: " + str(rows)
    
    currentRow = 0
    currentCol = 0
    currentPlt = 1
    
    gs = gridspec.GridSpec(rows, cols)
    #ax = plt.subplot(gs[0, 0])
        
    while (currentRow < rows):
        if currentCol > currentRow:
            currentCol = 0
            currentRow += 1
            continue
        currentPlt = (currentRow -1) * cols + currentCol
        #print currentRow, currentCol, currentPlt
            
        # Turn off axis values
        ax = plt.subplot(gs[currentRow, currentCol])
        ax.get_yaxis().set_ticks([])
        ax.get_xaxis().set_ticks([])

        scatter(P[:, currentCol], P[:, currentRow + 1], ax = ax, plotSlope = False)
        if currentCol == currentRow:
            ax.set_title(headers[currentCol])
        else:
            ax.set_title('')
        #ax.set_xlabel(headers[currentCol])
        if currentCol == 0:
            ax.set_ylabel(headers[currentRow+1])                
        
        #Finish with this
        currentCol += 1
def scatterplot_files(targetfile, targetcol, eventcol, modelfile, modeloutputcol, **kwargs):
    '''
    scatterplot_files(targetfile, targetcol, eventcol, modelfile, modeloutputcol)

    Takes two files because the target data and model data is allowed to be in different files.
    Events are ONLY taken from target data.
    Writes two files:
        scatter_cens_targetfile_modelfile.eps
        scatter_nocens_targetfile_modelfile.eps
    '''

    #Calculate suitable size for the figure for use in LaTEX
    fig_width_pt = 396.0  # Get this from LaTeX using \showthe\columnwidth
    inches_per_pt = 1.0/72.27               # Convert pt to inch
    golden_mean = (sqrt(5)-1.0)/2.0         # Aesthetic ratio
    fig_width = fig_width_pt*inches_per_pt  # width in inches
    fig_height = fig_width*golden_mean      # height in inches
    fig_size =  [fig_width,fig_height]
    #Update settings
    plt.rcParams['figure.figsize'] = fig_size
    #params = {'axes.labelsize': 10,
    #          'text.fontsize': 10,
    #          'legend.fontsize': 10,
    #          'xtick.labelsize': 8,
    #          'ytick.labelsize': 8,
              #'text.usetex': True,
    #          'figure.figsize': fig_size}
    #plt.rcParams.update(params)

#    with open(targetfile, 'r') as f:
#        X_in = [line.split() for line in f.readlines()]
#    X_in = numpy.array(X_in)
#    X = X_in[1:, first_col]
#    X = numpy.array(X, dtype = 'float')

    data = np.array(read_data_file(targetfile, ","))
    T, t = parse_data(data, inputcols = (targetcol, eventcol), ignorerows = [0], normalize = False)
    X = T[:, 0]
    events = T[:, 1]

#    with open(modeloutputcol, 'r') as f:
#        Y_in = [line.split() for line in f.readlines()]
#
#    Y_in = numpy.array(Y_in)
#    Y = Y_in[1:, second_col]
#    Y = numpy.array(Y, dtype = 'float')

    data = np.array(read_data_file(modelfile, ","))
    D, t = parse_data(data, inputcols = [modeloutputcol], ignorerows = [0], normalize = False)
    Y = D[:, 0]
#    if event_col is not None:
#        events = X_in[1:, event_col]
#        events = numpy.array(events, dtype = 'float')
#        print 'Using events'
#    else:
#        events = None

#    T = numpy.empty((len(X), 2), dtype='float')
#    T[:, 0] = X
#    T[:, 1] = events
    outputs = np.empty((len(X), 2), dtype='float')
    outputs[:, 0 ] = Y
    outputs[:, 1] = events
    c_index = get_C_index(T, outputs)
    print("C-Index between these files is: {0}".format(c_index))

    scatter(X, Y, events = events,
            x_label = 'Targets',
            y_label = 'Model output',
            gridsize = 30, mincnt = 0, show_plot = False)
    #plt.xlabel(os.path.basename(sys.argv[1]) + "\nC-Index between these files is: {0}".format(c_index))
    #plt.ylabel('Correlation of ' + os.path.basename(sys.argv[2]))

    plt.savefig('scatter_cens_cind_{cindex}_{0}_{1}.eps'.format(os.path.splitext(os.path.basename(modelfile))[0],
                                                                os.path.splitext(os.path.basename(targetfile))[0],
                                                                cindex=c_index))


    scatter(X, Y,
            x_label = 'Targets',
            y_label = 'Model output',
            gridsize = 30, mincnt = 0, show_plot = False)
    #plt.xlabel(os.path.basename(sys.argv[1]) + "\nC-Index between these files is: {0}".format(c_index))
    #plt.ylabel('Correlation of ' + os.path.basename(sys.argv[2]))

    plt.savefig('scatter_nocens_{cindex}_{0}_{1}.eps'.format(os.path.splitext(os.path.basename(modelfile))[0],
                                                             os.path.splitext(os.path.basename(targetfile))[0],
                                                             cindex=c_index))
Example #3
0
def scatterplot_files(targetfile, targetcol, eventcol, modelfile,
                      modeloutputcol, **kwargs):
    '''
    scatterplot_files(targetfile, targetcol, eventcol, modelfile, modeloutputcol)

    Takes two files because the target data and model data is allowed to be in different files.
    Events are ONLY taken from target data.
    Writes two files:
        scatter_cens_targetfile_modelfile.eps
        scatter_nocens_targetfile_modelfile.eps
    '''

    #Calculate suitable size for the figure for use in LaTEX
    fig_width_pt = 396.0  # Get this from LaTeX using \showthe\columnwidth
    inches_per_pt = 1.0 / 72.27  # Convert pt to inch
    golden_mean = (sqrt(5) - 1.0) / 2.0  # Aesthetic ratio
    fig_width = fig_width_pt * inches_per_pt  # width in inches
    fig_height = fig_width * golden_mean  # height in inches
    fig_size = [fig_width, fig_height]
    #Update settings
    plt.rcParams['figure.figsize'] = fig_size
    #params = {'axes.labelsize': 10,
    #          'text.fontsize': 10,
    #          'legend.fontsize': 10,
    #          'xtick.labelsize': 8,
    #          'ytick.labelsize': 8,
    #'text.usetex': True,
    #          'figure.figsize': fig_size}
    #plt.rcParams.update(params)

    #    with open(targetfile, 'r') as f:
    #        X_in = [line.split() for line in f.readlines()]
    #    X_in = numpy.array(X_in)
    #    X = X_in[1:, first_col]
    #    X = numpy.array(X, dtype = 'float')

    data = np.array(read_data_file(targetfile, ","))
    T, t = parse_data(data,
                      inputcols=(targetcol, eventcol),
                      ignorerows=[0],
                      normalize=False)
    X = T[:, 0]
    events = T[:, 1]

    #    with open(modeloutputcol, 'r') as f:
    #        Y_in = [line.split() for line in f.readlines()]
    #
    #    Y_in = numpy.array(Y_in)
    #    Y = Y_in[1:, second_col]
    #    Y = numpy.array(Y, dtype = 'float')

    data = np.array(read_data_file(modelfile, ","))
    D, t = parse_data(data,
                      inputcols=[modeloutputcol],
                      ignorerows=[0],
                      normalize=False)
    Y = D[:, 0]
    #    if event_col is not None:
    #        events = X_in[1:, event_col]
    #        events = numpy.array(events, dtype = 'float')
    #        print 'Using events'
    #    else:
    #        events = None

    #    T = numpy.empty((len(X), 2), dtype='float')
    #    T[:, 0] = X
    #    T[:, 1] = events
    outputs = np.empty((len(X), 2), dtype='float')
    outputs[:, 0] = Y
    outputs[:, 1] = events
    c_index = get_C_index(T, outputs)
    print("C-Index between these files is: {0}".format(c_index))

    scatter(X,
            Y,
            events=events,
            x_label='Targets',
            y_label='Model output',
            gridsize=30,
            mincnt=0,
            show_plot=False)
    #plt.xlabel(os.path.basename(sys.argv[1]) + "\nC-Index between these files is: {0}".format(c_index))
    #plt.ylabel('Correlation of ' + os.path.basename(sys.argv[2]))

    plt.savefig('scatter_cens_cind_{cindex}_{0}_{1}.eps'.format(
        os.path.splitext(os.path.basename(modelfile))[0],
        os.path.splitext(os.path.basename(targetfile))[0],
        cindex=c_index))

    scatter(X,
            Y,
            x_label='Targets',
            y_label='Model output',
            gridsize=30,
            mincnt=0,
            show_plot=False)
    #plt.xlabel(os.path.basename(sys.argv[1]) + "\nC-Index between these files is: {0}".format(c_index))
    #plt.ylabel('Correlation of ' + os.path.basename(sys.argv[2]))

    plt.savefig('scatter_nocens_{cindex}_{0}_{1}.eps'.format(
        os.path.splitext(os.path.basename(modelfile))[0],
        os.path.splitext(os.path.basename(targetfile))[0],
        cindex=c_index))