Python FigureCanvasAgg.print_jpg方法代码示例

# 需要导入模块: from matplotlib.backends.backend_agg import FigureCanvasAgg [as 别名]
# 或者: from matplotlib.backends.backend_agg.FigureCanvasAgg import print_jpg [as 别名]
def ant_ant_stat_frame(title_text, full_pol_array, station_names, output_name=None, dpi=50, **kwargs):
    if output_name is None:
        fig = figure(figsize=(32,30), dpi=dpi)
    else:
        fig=Figure(figsize=(32,30), dpi=dpi)

    if output_name is None:
        fig.suptitle(title_text, fontsize=30)
    else:
        fig.suptitle(title_text+' '+output_name, fontsize=30)
    
    ax1=fig.add_subplot(2,2,1)
    ant_ant_stat_plot(fig, ax1, title_text+' XX', full_pol_array[:,:,0], station_names, **kwargs)
    
    ax2=fig.add_subplot(2,2,2)
    ant_ant_stat_plot(fig, ax2, title_text+' XY', full_pol_array[:,:,1], station_names, **kwargs)
    
    ax3=fig.add_subplot(2,2,3)
    ant_ant_stat_plot(fig, ax3, title_text+' YX', full_pol_array[:,:,2], station_names, **kwargs)
    
    ax4=fig.add_subplot(2,2,4)
    ant_ant_stat_plot(fig, ax4, title_text+' YY', full_pol_array[:,:,3], station_names, **kwargs)

    if output_name is not None:
        canvas = FigureCanvasAgg(fig)
        if output_name[-4:] in ['.jpg', '.JPG']:
            canvas.print_jpg(output_name, dpi=dpi, quality=55)
        else:
            canvas.print_figure(output_name, dpi=dpi)
        pass
    pass

# 需要导入模块: from matplotlib.backends.backend_agg import FigureCanvasAgg [as 别名]
# 或者: from matplotlib.backends.backend_agg.FigureCanvasAgg import print_jpg [as 别名]
def saveWithAxes(img):
    fig = Figure()
    axes = fig.add_subplot(111)
    axes.imshow(img, cmap=cm.Greys_r)
    canvas = FigureCanvas(fig)
    # TODO: Need to find a way to avoid this hack!
    canvas.print_jpg("run.img.tmp.jpg")
    return numpy.array(Image.open("run.img.tmp.jpg"))

# 需要导入模块: from matplotlib.backends.backend_agg import FigureCanvasAgg [as 别名]
# 或者: from matplotlib.backends.backend_agg.FigureCanvasAgg import print_jpg [as 别名]
def histogram(img):
    fig = Figure()
    axes = fig.add_subplot(111)
    
    if len(img.shape) == 2 or img.shape[2:][0] == 1:
        axes.hist(img.flatten(), 300, color='blue', edgecolor='none')
    else:
        img = cv2.cvtColor(img, cv2.cv.CV_RGB2HSV)
        axes.hist([img[...,0], img[...,1], img[...,2]], 128, color=['red', 'green', 'blue'], edgecolor='none')
        axes.legend(('Hue', 'Saturation', 'Value'))
        #axes.legend(('Red', 'Green', 'Blue'))
    # If hsv, should look something like this.
    # axes.hist([img[...,0], img[...,1], img[...,2]], 300, color=['r','g','b'])
    axes.grid(True)
    setp(axes.get_yticklabels(), visible=False)
    canvas = FigureCanvas(fig)
    canvas.print_jpg("run.hist.tmp.jpg")
    return Image.open("run.hist.tmp.jpg")

# 需要导入模块: from matplotlib.backends.backend_agg import FigureCanvasAgg [as 别名]
# 或者: from matplotlib.backends.backend_agg.FigureCanvasAgg import print_jpg [as 别名]
def timeseries_station_page(ms, station_name, time_slots, data, fn=abs, output_name=None):
    dpi=50
    if output_name is None:
        fig = figure(figsize=(32,24), dpi=dpi)
    else:
        fig = Figure(figsize=(32,24), dpi=dpi)

    station_name_list = list(ms.tables['antennae']['NAME'])
    station_id        = station_name_list.index(station_name)
    num_ant           = len(ms.tables['antennae'])
    tsn               = time_slots-time_slots[0]
    pol_names         = corr_type(ms.tables['polarization']['CORR_TYPE'][0])
    ref_freq_mhz      = ms.tables['spectral_windows'][0]['REF_FREQUENCY']/1.e6

    fig.suptitle(ms.msname+': '+fn.__name__+'(vis) with '+station_name+' at %3.2f MHz' % (ref_freq_mhz,), fontsize='large')

    median_amp = ma.median(ma.mean(ma.median(fn(data[station_id,:,0::3,:]), axis=-1), axis=-1), axis=-1)
    
    for id2,name in enumerate(station_name_list):
        ax = fig.add_subplot(ceil(num_ant/4.0),4, id2+1)
        ax.plot(tsn, fn(data[station_id,id2,0,:]), c='blue'  , label=pol_names[0])
        ax.plot(tsn, fn(data[station_id,id2,1,:]), c='green' , label=pol_names[1])
        ax.plot(tsn, fn(data[station_id,id2,2,:]), c='purple', label=pol_names[2])
        ax.plot(tsn, fn(data[station_id,id2,3,:]), c='red'   , label=pol_names[3])
        ax.grid()
        ax.set_ylabel(station_name_list[id2], rotation='horizontal')
        ax.set_ylim(0.0, 3*median_amp)
        ax.set_yticklabels([])
        if id2 < len(station_name_list)-4:
            ax.set_xticklabels([])
        else:
            ax.set_xlabel('Time [s]')    
        pass
    fig.subplots_adjust(hspace=0.0, top=0.95, bottom=0.04)
    if output_name is not None:
        canvas = FigureCanvasAgg(fig)
        if output_name[-4:] in ['.jpg', '.JPG']:
            canvas.print_jpg(output_name, dpi=dpi, quality=55)
        else:
            canvas.print_figure(output_name, dpi=dpi)
        pass
    pass

# 需要导入模块: from matplotlib.backends.backend_agg import FigureCanvasAgg [as 别名]
# 或者: from matplotlib.backends.backend_agg.FigureCanvasAgg import print_jpg [as 别名]
def station_gain_bar_chart(ms, station_name, time_slots, data, output_name= None):
    dpi=50
    if output_name is None:
        fig = figure(figsize=(38,24), dpi=dpi)
    else:
        fig = Figure(figsize=(38,24), dpi=dpi)

    station_name_list = list(ms.tables['antennae']['NAME'])
    num_stations      = len(station_name_list)
    station_id        = station_name_list.index(station_name)
    ref_freq_mhz      = ms.tables['spectral_windows'][0]['REF_FREQUENCY']/1.e6

    
    is_autocorrelation = array([station_name == name for name in ms.tables['antennae']['NAME']])

    noise = ma.array(data[station_id,:, 1:3,:].imag.std(axis=-1).mean(axis=-1),
                     mask = is_autocorrelation)
    sig    = median(abs(data[station_id, :, :, :]),axis=-1)
    signal = ma.array(sig, mask = is_autocorrelation[:, newaxis]*ones((num_stations, 4)))
    ax = fig.add_subplot(1,1,1)
    xx_bars = ax.bar(arange(len(station_name_list))-0.4, signal[:, 0], width=0.2, color='blue', label='xx')
    xy_bars = ax.bar(arange(len(station_name_list))-0.2, signal[:, 1], width=0.2, color='lightblue', label='xy')
    yx_bars = ax.bar(arange(len(station_name_list))    , signal[:, 2], width=0.2, color='lightpink', label='yx')
    yy_bars = ax.bar(arange(len(station_name_list))+0.2, signal[:, 3], width=0.2, color='red', label='yy')
    for x_pos, name  in enumerate(station_name_list):
        if name != station_name:
            ax.text(x_pos, signal[x_pos,:].max()*1.02, name, rotation='vertical',
                    horizontalalignment='center', verticalalignment='bottom',
                    fontsize=25)
            ax.text(x_pos, signal[x_pos,:].max()*-0.01, name, rotation='vertical',
                    horizontalalignment='center', verticalalignment='top',
                    fontsize=25)
        else:
            ax.text(x_pos, 0.0, ' Reference station: '+name, rotation='vertical',
                    horizontalalignment='center', verticalalignment='bottom',
                    fontsize=25)

    ax.set_xlabel('Station', fontsize=40)
    ax.set_ylabel('Visibility amplitude', fontsize=40)
    ax.set_ylim(0, ma.max(signal)*1.2)
    ax.set_xlim(-1.0, num_stations)
    ax.set_xticklabels([])
    ax.set_title('%s:\nVis. amp. with station %s at %5.2f MHz' %
                 (ms.msname, station_name, ref_freq_mhz),
                 fontsize=40)
    old_legend_fontsize = rcParams['legend.fontsize']
    rcParams.update({'legend.fontsize': 25})
    legend_instance = ax.legend()
    
    
    for label in ax.get_yticklabels():
        label.set_fontsize(40)
    
    if output_name is not None:
        canvas = FigureCanvasAgg(fig)
        if output_name[-4:] in ['.jpg', '.JPG']:
            canvas.print_jpg(output_name, dpi=dpi, quality=55)
        else:
            canvas.print_figure(output_name, dpi=dpi)
        pass

    rcParams.update({'legend.fontsize': old_legend_fontsize})