Python IPython.display() Examples

def check_render_options(**options):
    """
    Context manager that will assert that alt.renderers.options are equivalent
    to the given options in the IPython.display.display call
    """
    import IPython.display

    def check_options(obj):
        assert alt.renderers.options == options

    _display = IPython.display.display
    IPython.display.display = check_options
    try:
        yield
    finally:
        IPython.display.display = _display 

def display_images(images, titles=None, cols=4, cmap=None, norm=None,
                   interpolation=None):
    """Display the given set of images, optionally with titles.
    images: list or array of image tensors in HWC format.
    titles: optional. A list of titles to display with each image.
    cols: number of images per row
    cmap: Optional. Color map to use. For example, "Blues".
    norm: Optional. A Normalize instance to map values to colors.
    interpolation: Optional. Image interporlation to use for display.
    """
    titles = titles if titles is not None else [""] * len(images)
    rows = len(images) // cols + 1
    plt.figure(figsize=(14, 14 * rows // cols))
    i = 1
    for image, title in zip(images, titles):
        plt.subplot(rows, cols, i)
        plt.title(title, fontsize=9)
        plt.axis('off')
        plt.imshow(image.astype(np.uint8), cmap=cmap,
                   norm=norm, interpolation=interpolation)
        i += 1
    plt.show() 

def display_process_tree(process_tree: pd.DataFrame):
    """
    Display process tree data frame. (Deprecated).

    Parameters
    ----------
    process_tree : pd.DataFrame
        Process tree DataFrame

    The display module expects the columns NodeRole and Level to
    be populated. NoteRole is one of: 'source', 'parent', 'child'
    or 'sibling'. Level indicates the 'hop' distance from the 'source'
    node.

    """
    build_and_show_process_tree(process_tree) 

def display_images(images, titles=None, cols=4, cmap=None, norm=None,
                   interpolation=None):
    """Display the given set of images, optionally with titles.
    images: list or array of image tensors in HWC format.
    titles: optional. A list of titles to display with each image.
    cols: number of images per row
    cmap: Optional. Color map to use. For example, "Blues".
    norm: Optional. A Normalize instance to map values to colors.
    interpolation: Optional. Image interporlation to use for display.
    """
    titles = titles if titles is not None else [""] * len(images)
    rows = len(images) // cols + 1
    plt.figure(figsize=(14, 14 * rows // cols))
    i = 1
    for image, title in zip(images, titles):
        plt.subplot(rows, cols, i)
        plt.title(title, fontsize=9)
        plt.axis('off')
        plt.imshow(image.astype(np.uint8), cmap=cmap,
                   norm=norm, interpolation=interpolation)
        i += 1
    plt.show() 

def display_images(images, titles=None, cols=4, cmap=None, norm=None,
                   interpolation=None):
    """Display the given set of images, optionally with titles.
    images: list or array of image tensors in HWC format.
    titles: optional. A list of titles to display with each image.
    cols: number of images per row
    cmap: Optional. Color map to use. For example, "Blues".
    norm: Optional. A Normalize instance to map values to colors.
    interpolation: Optional. Image interporlation to use for display.
    """
    titles = titles if titles is not None else [""] * len(images)
    rows = len(images) // cols + 1
    plt.figure(figsize=(14, 14 * rows // cols))
    i = 1
    for image, title in zip(images, titles):
        plt.subplot(rows, cols, i)
        plt.title(title, fontsize=9)
        plt.axis('off')
        plt.imshow(image.astype(np.uint8), cmap=cmap,
                   norm=norm, interpolation=interpolation)
        i += 1
    plt.show() 

def display_alert(
    alert: Union[Mapping[str, Any], SecurityAlert], show_entities: bool = False
):
    """
    Display a Security Alert.

    Parameters
    ----------
    alert : Union[Mapping[str, Any], SecurityAlert]
        The alert to display as Mapping (e.g. pd.Series)
        or SecurityAlert
    show_entities : bool, optional
        Whether to display entities (the default is False)

    """
    output = format_alert(alert, show_entities)
    if not isinstance(output, tuple):
        output = [output]
    for disp_obj in output:
        display(disp_obj) 

def display_images(images, titles=None, cols=4, cmap=None, norm=None,
                   interpolation=None):
    """Display the given set of images, optionally with titles.
    images: list or array of image tensors in HWC format.
    titles: optional. A list of titles to display with each image.
    cols: number of images per row
    cmap: Optional. Color map to use. For example, "Blues".
    norm: Optional. A Normalize instance to map values to colors.
    interpolation: Optional. Image interporlation to use for display.
    """
    titles = titles if titles is not None else [""] * len(images)
    rows = len(images) // cols + 1
    plt.figure(figsize=(14, 14 * rows // cols))
    i = 1
    for image, title in zip(images, titles):
        plt.subplot(rows, cols, i)
        plt.title(title, fontsize=9)
        plt.axis('off')
        plt.imshow(image.astype(np.uint8), cmap=cmap,
                   norm=norm, interpolation=interpolation)
        i += 1
    plt.show() 

def post_execute(self):
        if self.isFirstPostExecute:
            self.isFirstPostExecute = False
            self.isFirstPreExecute = False
            return 0
        self.flag = False
        self.asyncCapturer.Wait()
        self.ioHandler.Poll()
        self.ioHandler.EndCapture()

        # Print for the notebook
        out = self.ioHandler.GetStdout()
        err = self.ioHandler.GetStderr()
        if not transformers:
            sys.stdout.write(out)
            sys.stderr.write(err)
        else:
            for t in transformers:
                (out, err, otype) = t(out, err)
                if otype == 'html':
                    IPython.display.display(HTML(out))
                    IPython.display.display(HTML(err))
        return 0 

def render(obj, **kwargs):
    info = process_object(obj)
    if info:
        display(HTML(info))
        return

    if render_anim is not None:
        return render_anim(obj)

    backend = Store.current_backend
    renderer = Store.renderers[backend]

    # Drop back to png if pdf selected, notebook PDF rendering is buggy
    if renderer.fig == 'pdf':
        renderer = renderer.instance(fig='png')

    return renderer.components(obj, **kwargs) 

def display_images(images, titles=None, cols=4, cmap=None, norm=None,
                   interpolation=None):
    """Display the given set of images, optionally with titles.
    images: list or array of image tensors in HWC format.
    titles: optional. A list of titles to display with each image.
    cols: number of images per row
    cmap: Optional. Color map to use. For example, "Blues".
    norm: Optional. A Normalize instance to map values to colors.
    interpolation: Optional. Image interporlation to use for display.
    """
    titles = titles if titles is not None else [""] * len(images)
    rows = len(images) // cols + 1
    plt.figure(figsize=(14, 14 * rows // cols))
    i = 1
    for image, title in zip(images, titles):
        plt.subplot(rows, cols, i)
        plt.title(title, fontsize=9)
        plt.axis('off')
        plot_area = image[:,:,0] if len(image.shape) == 3 else image
        plt.imshow(plot_area.astype(np.uint8), cmap=cmap,
                   norm=norm, interpolation=interpolation)
        i += 1
    plt.show() 

def display_images(images, titles=None, cols=4, cmap=None, norm=None,
                   interpolation=None):
    """Display the given set of images, optionally with titles.
    images: list or array of image tensors in HWC format.
    titles: optional. A list of titles to display with each image.
    cols: number of images per row
    cmap: Optional. Color map to use. For example, "Blues".
    norm: Optional. A Normalize instance to map values to colors.
    interpolation: Optional. Image interpolation to use for display.
    """
    titles = titles if titles is not None else [""] * len(images)
    rows = len(images) // cols + 1
    plt.figure(figsize=(14, 14 * rows // cols))
    i = 1
    for image, title in zip(images, titles):
        plt.subplot(rows, cols, i)
        plt.title(title, fontsize=9)
        plt.axis('off')
        plt.imshow(image.astype(np.uint8), cmap=cmap,
                   norm=norm, interpolation=interpolation)
        i += 1
    plt.show() 

def display_images(images, titles=None, cols=4, cmap=None, norm=None,
                   interpolation=None):
    """Display the given set of images, optionally with titles.
    images: list or array of image tensors in HWC format.
    titles: optional. A list of titles to display with each image.
    cols: number of images per row
    cmap: Optional. Color map to use. For example, "Blues".
    norm: Optional. A Normalize instance to map values to colors.
    interpolation: Optional. Image interpolation to use for display.
    """
    titles = titles if titles is not None else [""] * len(images)
    rows = len(images) // cols + 1
    plt.figure(figsize=(14, 14 * rows // cols))
    i = 1
    for image, title in zip(images, titles):
        plt.subplot(rows, cols, i)
        plt.title(title, fontsize=9)
        plt.axis('off')
        plt.imshow(image.astype(np.uint8), cmap=cmap,
                   norm=norm, interpolation=interpolation)
        i += 1
    plt.show() 

def display_images(images, titles=None, cols=4, cmap=None, norm=None,
                   interpolation=None):
    """Display the given set of images, optionally with titles.
    images: list or array of image tensors in HWC format.
    titles: optional. A list of titles to display with each image.
    cols: number of images per row
    cmap: Optional. Color map to use. For example, "Blues".
    norm: Optional. A Normalize instance to map values to colors.
    interpolation: Optional. Image interporlation to use for display.
    """
    titles = titles if titles is not None else [""] * len(images)
    rows = len(images) // cols + 1
    plt.figure(figsize=(14, 14 * rows // cols))
    i = 1
    for image, title in zip(images, titles):
        plt.subplot(rows, cols, i)
        plt.title(title, fontsize=9)
        plt.axis('off')
        plt.imshow(image.astype(np.uint8), cmap=cmap,
                   norm=norm, interpolation=interpolation)
        i += 1
    plt.show() 

def display_images(images, titles=None, cols=4, cmap=None, norm=None,
                   interpolation=None):
    """Display the given set of images, optionally with titles.
    images: list or array of image tensors in HWC format.
    titles: optional. A list of titles to display with each image.
    cols: number of images per row
    cmap: Optional. Color map to use. For example, "Blues".
    norm: Optional. A Normalize instance to map values to colors.
    interpolation: Optional. Image interporlation to use for display.
    """
    titles = titles if titles is not None else [""] * len(images)
    rows = len(images) // cols + 1
    plt.figure(figsize=(14, 14 * rows // cols))
    i = 1
    for image, title in zip(images, titles):
        plt.subplot(rows, cols, i)
        plt.title(title, fontsize=9)
        plt.axis('off')
        plt.imshow(image.astype(np.uint8), cmap=cmap,
                   norm=norm, interpolation=interpolation)
        i += 1
    plt.show() 

def display_images(images, titles=None, cols=4, cmap=None, norm=None,
                   interpolation=None):
    """Display the given set of images, optionally with titles.
    images: list or array of image tensors in HWC format.
    titles: optional. A list of titles to display with each image.
    cols: number of images per row
    cmap: Optional. Color map to use. For example, "Blues".
    norm: Optional. A Normalize instance to map values to colors.
    interpolation: Optional. Image interpolation to use for display.
    """
    titles = titles if titles is not None else [""] * len(images)
    rows = len(images) // cols + 1
    plt.figure(figsize=(14, 14 * rows // cols))
    i = 1
    for image, title in zip(images, titles):
        plt.subplot(rows, cols, i)
        plt.title(title, fontsize=9)
        plt.axis('off')
        plt.imshow(image.astype(np.uint8), cmap=cmap,
                   norm=norm, interpolation=interpolation)
        i += 1
    plt.show() 

def check_render_options(**options):
    """
    Context manager that will assert that alt.renderers.options are equivalent
    to the given options in the IPython.display.display call
    """
    import IPython.display

    def check_options(obj):
        assert alt.renderers.options == options

    _display = IPython.display.display
    IPython.display.display = check_options
    try:
        yield
    finally:
        IPython.display.display = _display 

def display_images(images, titles=None, cols=4, cmap=None, norm=None,
                   interpolation=None):
    """Display the given set of images, optionally with titles.
    images: list or array of image tensors in HWC format.
    titles: optional. A list of titles to display with each image.
    cols: number of images per row
    cmap: Optional. Color map to use. For example, "Blues".
    norm: Optional. A Normalize instance to map values to colors.
    interpolation: Optional. Image interporlation to use for display.
    """
    titles = titles if titles is not None else [""] * len(images)
    rows = len(images) // cols + 1
    plt.figure(figsize=(14, 14 * rows // cols))
    i = 1
    for image, title in zip(images, titles):
        plt.subplot(rows, cols, i)
        plt.title(title, fontsize=9)
        plt.axis('off')
        plt.imshow(image.astype(np.uint8), cmap=cmap,
                   norm=norm, interpolation=interpolation)
        i += 1
    plt.show() 

def register_json_formatter(cls: Type, to_dict_method_name: str = 'to_dict'):
    """
    TODO
    :param cls:
    :param to_dict_method_name:
    :return:
    """
    if not hasattr(cls, to_dict_method_name) or not callable(getattr(cls, to_dict_method_name)):
        raise ValueError(f'{cls} must define a {to_dict_method_name}() method')

    try:
        import IPython
        import IPython.display

        if IPython.get_ipython() is not None:
            def obj_to_dict(obj):
                return getattr(obj, to_dict_method_name)()

            ipy_formatter = IPython.get_ipython().display_formatter.formatters['application/json']
            ipy_formatter.for_type(cls, obj_to_dict)

    except ImportError:
        pass 

def display_images(images, titles=None, cols=4, cmap=None, norm=None,
                   interpolation=None):
    """Display the given set of images, optionally with titles.
    images: list or array of image tensors in HWC format.
    titles: optional. A list of titles to display with each image.
    cols: number of images per row
    cmap: Optional. Color map to use. For example, "Blues".
    norm: Optional. A Normalize instance to map values to colors.
    interpolation: Optional. Image interporlation to use for display.
    """
    titles = titles if titles is not None else [""] * len(images)
    rows = len(images) // cols + 1
    plt.figure(figsize=(14, 14 * rows // cols))
    i = 1
    for image, title in zip(images, titles):
        plt.subplot(rows, cols, i)
        plt.title(title, fontsize=9)
        plt.axis('off')
        plt.imshow(image.astype(np.uint8), cmap=cmap,
                   norm=norm, interpolation=interpolation)
        i += 1
    plt.show() 

def display_images(images, titles=None, cols=4, cmap=None, norm=None,
                   interpolation=None):
    """Display the given set of images, optionally with titles.
    images: list or array of image tensors in HWC format.
    titles: optional. A list of titles to display with each image.
    cols: number of images per row
    cmap: Optional. Color map to use. For example, "Blues".
    norm: Optional. A Normalize instance to map values to colors.
    interpolation: Optional. Image interporlation to use for display.
    """
    titles = titles if titles is not None else [""] * len(images)
    rows = len(images) // cols + 1
    plt.figure(figsize=(14, 14 * rows // cols))
    i = 1
    for image, title in zip(images, titles):
        plt.subplot(rows, cols, i)
        plt.title(title, fontsize=9)
        plt.axis('off')
        plt.imshow(image.astype(np.uint8), cmap=cmap,
                   norm=norm, interpolation=interpolation)
        i += 1
    plt.show() 

def wait_for_import(self, count, timeout=300):
        time_start = time.time()
        while time.time() < time_start + timeout:
            t = self.client.table(self.database, self.table)
            self.imported_count = t.count - self.initial_count
            if self.imported_count >= count:
                break
            self._display_progress(self.frame_size)
            time.sleep(2)
        # import finished
        self.imported_at = datetime.datetime.utcnow().replace(microsecond=0)
        # import timeout
        if self.imported_count < count:
            self.import_timeout = timeout
        self._display_progress(self.frame_size)
        # clear progress
        if self.clear_progress and self.imported_count == count:
            IPython.display.clear_output()


# public methods 

def display_images(images, titles=None, cols=4, cmap=None, norm=None,
                   interpolation=None):
    """Display the given set of images, optionally with titles.
    images: list or array of image tensors in HWC format.
    titles: optional. A list of titles to display with each image.
    cols: number of images per row
    cmap: Optional. Color map to use. For example, "Blues".
    norm: Optional. A Normalize instance to map values to colors.
    interpolation: Optional. Image interpolation to use for display.
    """
    titles = titles if titles is not None else [""] * len(images)
    rows = len(images) // cols + 1
    plt.figure(figsize=(14, 14 * rows // cols))
    i = 1
    for image, title in zip(images, titles):
        plt.subplot(rows, cols, i)
        plt.title(title, fontsize=9)
        plt.axis('off')
        plt.imshow(image.astype(np.uint8), cmap=cmap,
                   norm=norm, interpolation=interpolation)
        i += 1
    plt.show() 

def display_images(images, titles=None, cols=4, cmap=None, norm=None,
                   interpolation=None):
    """Display the given set of images, optionally with titles.
    images: list or array of image tensors in HWC format.
    titles: optional. A list of titles to display with each image.
    cols: number of images per row
    cmap: Optional. Color map to use. For example, "Blues".
    norm: Optional. A Normalize instance to map values to colors.
    interpolation: Optional. Image interporlation to use for display.
    """
    titles = titles if titles is not None else [""] * len(images)
    rows = len(images) // cols + 1
    plt.figure(figsize=(14, 14 * rows // cols))
    i = 1
    for image, title in zip(images, titles):
        plt.subplot(rows, cols, i)
        plt.title(title, fontsize=9)
        plt.axis('off')
        plt.imshow(image.astype(np.uint8), cmap=cmap,
                   norm=norm, interpolation=interpolation)
        i += 1
    plt.show() 

def display_images(images, titles=None, cols=4, cmap=None, norm=None,
                   interpolation=None):
    """Display the given set of images, optionally with titles.
    images: list or array of image tensors in HWC format.
    titles: optional. A list of titles to display with each image.
    cols: number of images per row
    cmap: Optional. Color map to use. For example, "Blues".
    norm: Optional. A Normalize instance to map values to colors.
    interpolation: Optional. Image interpolation to use for display.
    """
    titles = titles if titles is not None else [""] * len(images)
    rows = len(images) // cols + 1
    plt.figure(figsize=(14, 14 * rows // cols))
    i = 1
    for image, title in zip(images, titles):
        plt.subplot(rows, cols, i)
        plt.title(title, fontsize=9)
        plt.axis('off')
        plt.imshow(image.astype(np.uint8), cmap=cmap,
                   norm=norm, interpolation=interpolation)
        i += 1
    plt.show() 

def image_display(element, max_frames, fmt):
    """
    Used to render elements to an image format (svg or png) if requested
    in the display formats.
    """
    if fmt not in Store.display_formats:
        return None
    info = process_object(element)
    if info:
        display(HTML(info))
        return

    backend = Store.current_backend
    if type(element) not in Store.registry[backend]:
        return None
    renderer = Store.renderers[backend]
    plot = renderer.get_plot(element)

    # Current renderer does not support the image format
    if fmt not in renderer.param.objects('existing')['fig'].objects:
        return None

    data, info = renderer(plot, fmt=fmt)
    return {info['mime_type']: data}, {} 

def save_fig(name, root_dir=None, notebook_mode=True, default_overwrite=False, extension='pdf', **savefig_kwargs):
    if root_dir is None: root_dir = os.getcwd()
    directory = check_or_create_dir(join_paths(root_dir, FOLDER_NAMINGS['PLOTS_DIR']),
                                    notebook_mode=notebook_mode)

    filename = join_paths(directory, '%s.%s' % (name, extension))  # directory + '/%s.pdf' % name
    if not default_overwrite and os.path.isfile(filename):
        # if IPython is not None:
        #     IPython.display.display(tuple(IFrame(filename, width=800, height=600)))  # FIXME not working!
        overwrite = input('A file named %s already exists. Overwrite (Leave string empty for NO!)?' % filename)
        if not overwrite:
            print('No changes done.')
            return
    plt.savefig(filename, **savefig_kwargs)
    # print('file saved') 

def _get_resources(self, args, params):
        """
        Finds the list of resources from the keyword parameters and pops
        them out of the params dictionary.
        """
        resources = []
        disabled = []
        for resource in ['holoviews'] + list(Store.renderers.keys()):
            if resource in args:
                resources.append(resource)

            if resource in params:
                setting = params.pop(resource)
                if setting is True and resource != 'matplotlib':
                    if resource not in resources:
                        resources.append(resource)
                if setting is False:
                    disabled.append(resource)

        unmatched_args = set(args) - set(resources)
        if unmatched_args:
            display(HTML('<b>Warning:</b> Unrecognized resources %s'
                         % ', '.join(unmatched_args)))

        resources = [r for r in resources if r not in disabled]
        if ('holoviews' not in disabled) and ('holoviews' not in resources):
            resources = ['holoviews'] + resources
        return resources 

def display(obj, raw_output=False, **kwargs):
    """
    Renders any HoloViews object to HTML and displays it
    using the IPython display function. If raw is enabled
    the raw HTML is returned instead of displaying it directly.
    """
    if not Store.loaded_backends() and isinstance(obj, Dimensioned):
        raise RuntimeError('To use display on a HoloViews object ensure '
                           'a backend is loaded using the holoviews '
                           'extension.')

    raw = True
    if isinstance(obj, GridSpace):
        with option_state(obj):
            output = grid_display(obj)
    elif isinstance(obj, (CompositeOverlay, ViewableElement)):
        with option_state(obj):
            output = element_display(obj)
    elif isinstance(obj, (Layout, NdLayout, AdjointLayout)):
        with option_state(obj):
            output = layout_display(obj)
    elif isinstance(obj, (HoloMap, DynamicMap)):
        with option_state(obj):
            output = map_display(obj)
    elif isinstance(obj, Plot):
        output = render(obj)
    else:
        output = obj
        raw = kwargs.pop('raw', False)

    if raw_output:
        return output
    elif isinstance(output, tuple):
        data, metadata = output
    else:
        data, metadata = output, {}
    return IPython.display.display(data, raw=raw, metadata=metadata, **kwargs) 

def display_table(table):
    """Display values in a table format.
    table: an iterable of rows, and each row is an iterable of values.
    """
    html = ""
    for row in table:
        row_html = ""
        for col in row:
            row_html += "<td>{:40}</td>".format(str(col))
        html += "<tr>" + row_html + "</tr>"
    html = "<table>" + html + "</table>"
    IPython.display.display(IPython.display.HTML(html)) 

def middle_frame(obj):
    "Only display the (approximately) middle frame of an animated plot"
    plot, renderer, fmt = single_frame_plot(obj)
    middle_frame = int(len(plot) / 2)
    plot.update(middle_frame)
    return {'text/html': renderer.html(plot, fmt)}