Plot hyperspy signal nicely

plot_im.py

def plot_im(s, ax=None, scalebar=True, label=True, clim=None, cmap=None, cbar=True, loc=4, axislabel=False, colorbar_format="scientific", colorbar_decimals=1, dont_show=False, **kwargs):
    """
    Plots the HS image nicely with a scalebar. Label can be modified or turned off.
    Use dont_show=True to not show a plot, but still return it.
    Returns:
    fig - the figure
    ax  - the axes
    im  - the image data
    """
    import matplotlib.pyplot as plt

    xax = s.axes_manager[-2]
    yax = s.axes_manager[-1]
    if xax.scale == 1:
        xax.scale = xax.scale
    if yax.scale == 1:
        yax.scale = yax.scale

    x = xax.size
    y = yax.size

    imagesize = 8 # inches
    if x > y:
        w = imagesize
        h = y/x * imagesize
    else: #y > x:
        h = imagesize
        w = x/y * imagesize

    if ax == None:
        figure, ax = plt.subplots(figsize=(w,h))
    else:
        figure = ax.figure
    if cmap == None:
        cmap=plt.get_cmap("Greys_r")
    vmin = None
    vmax = None
    for key, value in kwargs.items():
        vmin = value if key == "vmin" else None
        vmax = value if key == "vmax" else None
        
    if clim==True:
        # Plot clim within two median absolute deviations of median
        median = np.median(s.data)
        deviation = mad(s.data)
        clim = [median - 5*deviation, median + 5*deviation]

    im = ax.imshow(
        np.rot90(s.data, k=0),
        interpolation='nearest',
        extent=[
            xax.low_value,
            xax.high_value,
            yax.high_value,
            yax.low_value],
        vmin=vmin,
        vmax=vmax,
        clim=clim,
        cmap=cmap,
        )
    ax.set_xticks([])
    ax.set_yticks([])
    if axislabel == True:
        ax.set_xlabel(xax.name)
        ax.set_ylabel(yax.name)
    if scalebar == True:
        add_scalebar(ax,s,loc=loc)
    if label:
        if type(label) == str:
            text = label
        else:
            text = s.metadata.General.title
        ax.annotate(
        s=text,
        xy=(xax.low_value,yax.low_value),
        #xy=(s.axes_manager[1].low_value,s.axes_manager[0].high_value), # This was the old one, may have been correct in some cases
        xytext=(5, -5),
        va='top',
        ha='left',
        textcoords='offset points',
        fontsize = 12,
        bbox=dict(facecolor='white', alpha=1, pad=5,
                 ),
    )
    if cbar==True:
        add_colourbar(figure, ax, im, colorbar_format, colorbar_decimals)
    if dont_show == True:
        plt.close()
    return figure, ax, im

Hello, where are the add_scalebar and add_colorbar functions defined?

Hi! Good point, shall add them as soon as possible. Might be a few days as I'm currently on holiday without a laptop. Out of curiosity, how did you find this?

Thanks for responding. I am trying to use HyperSpy to convert TIA images to TIFF, and want to display the image nicely. I didn't find a way to remove the white border and the title of the image by just using s.plot() function.