Python NonUniformImage.set_norm方法代码示例

# 需要导入模块: from matplotlib.image import NonUniformImage [as 别名]
# 或者: from matplotlib.image.NonUniformImage import set_norm [as 别名]
def plot2d(x, y, z, ax=None, cmap='RdGy', norm=None, **kw):
    """ Plot dataset using NonUniformImage class

    Parameters
    ----------
    x : (nx,)
    y : (ny,)
    z : (nx,nz)
        
    """
    from matplotlib.image import NonUniformImage
    if ax is None:
        fig = plt.gcf()
        ax = fig.add_subplot(111)

    xlim = (x.min(), x.max())
    ylim = (y.min(), y.max())

    im = NonUniformImage(ax,
                         interpolation='bilinear',
                         extent=xlim + ylim,
                         cmap=cmap)

    if norm is not None:
        im.set_norm(norm)

    im.set_data(x, y, z, **kw)
    ax.images.append(im)
    #plt.colorbar(im)
    ax.set_xlim(xlim)
    ax.set_ylim(ylim)

    def update(z):
        return im.set_data(x, y, z, **kw)

    return im, update

# 需要导入模块: from matplotlib.image import NonUniformImage [as 别名]
# 或者: from matplotlib.image.NonUniformImage import set_norm [as 别名]
def test_nonuniformimage_setnorm():
    ax = plt.gca()
    im = NonUniformImage(ax)
    im.set_norm(plt.Normalize())

# 需要导入模块: from matplotlib.image import NonUniformImage [as 别名]
# 或者: from matplotlib.image.NonUniformImage import set_norm [as 别名]
def tsys_show_dynspec(out,idx=None,ampscl=None,domedian=True,frq='linear'):
    ''' Given "standard" output of rd_tsys_multi(), possibly
        calibrated using calibration.sp_apply_cal() and/or 
        background-subtracted using calibration.sp_bg_subtract(),
        make a nice image plot of the dynamic spectrum.  The
        plot can contain multiple panels if domedian is False,
        or plot a single spectrum representing the median of
        multiple antennas.  Only linear frequency scale is supported
        at this time.
    '''
    from matplotlib.image import NonUniformImage
    from matplotlib.dates import AutoDateLocator, DateFormatter
    from matplotlib import colors
    from matplotlib.pyplot import locator_params
    from util import Time

    nant, npol, nf, nt = out['tsys'].shape
    if idx is None:
        idx_ = np.arange(nt)
    else:
        idx_ = idx
    ut = Time(out['ut_mjd'][idx_],format='mjd')
    utd = (ut.mjd - int(ut[0].mjd) + 1).astype('float')
    good = np.where(out['fghz'] > 2.0)[0]
    if frq == 'linear':
        fghz = out['fghz'][good]
    else:
        fghz = np.log10(out['fghz'][good])

    locator = AutoDateLocator(interval_multiples=True) #maxticks=7,minticks=3,
    tsys = out['tsys'][:,:,good,idx_]
    if domedian:
        medtsys = np.nanmedian(np.nanmedian(tsys,0),0)
        fig = plt.figure()
        fig.suptitle('EOVSA Total Power Data for '+ut[0].iso[:10],fontsize=14)
        # Plot X-feed
        ax = fig.add_subplot(211)
        ax.xaxis_date()
        ax.set_ylabel('Frequency [GHz]')
        ax.set_title('Median Total Power')
        extent=[utd[0],utd[-1],fghz[0],fghz[-1]]
#        extent=[ut[0],ut[-1],fghz[0],fghz[-1]]
        im = NonUniformImage(ax,extent=extent)
        if ampscl != None:
            im.set_norm(colors.Normalize(vmin=ampscl[0],vmax=ampscl[1]))
        im.set_data(utd,fghz,medtsys)
        #fig.colorbar(im,ax)
        ax.images.append(im)
        ax.set_xlim(extent[0],extent[1])
        ax.set_ylim(extent[2],extent[3])
        ax.xaxis.set_major_locator(locator)
        #ax.xaxis.set_minor_locator(MinuteLocator(interval=10))
        # Set up date formatting
        fmt = DateFormatter('%H:%M:%S')
        ax.xaxis.set_major_formatter(fmt)
        labels = (10**ax.get_yticks()).astype('str')
        for i in range(len(labels)):
            labels[i] = labels[i][:4]
        ax.set_yticklabels(labels)
        # Repeat for Y-feed
        ax = fig.add_subplot(212)
        ax.xaxis_date()
        ax.set_xlabel('Start time '+ut[0].iso[:19]+' UT')
        ax.set_title('Median of Y-poln')
        ax.set_ylabel('Frequency [GHz]')
        im = NonUniformImage(ax,extent=extent)
        if ampscl != None:
            im.set_norm(colors.Normalize(vmin=ampscl[0],vmax=ampscl[1]))
        im.set_data(utd,fghz,medytsys)
        #fig.colorbar(im,ax)
        ax.images.append(im)
        ax.set_xlim(extent[0],extent[1])
        ax.set_ylim(extent[2],extent[3])
        ax.xaxis.set_major_locator(locator)
        # Set up date formatting
        ax.xaxis.set_major_formatter(fmt)
        ax.set_yticklabels(labels)
    plt.draw()
    plt.show()