{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "
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Title
NdLayout Container
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Dependencies
Matplotlib
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Backends
Matplotlib
Bokeh
Plotly
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" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import holoviews as hv\n", "hv.extension('matplotlib')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "An ``NdLayout`` is a multi-dimensional dictionary of HoloViews elements presented side-by-side like a ``Layout``. An ``NdLayout`` can be considered as a special-case of ``HoloMap`` that can hold any one type of HoloViews container or element as long as it isn't another ``NdLayout`` or ``Layout``. Unlike a regular ``Layout`` that can be built with the ``+`` operator, the items in an ``NdOverlay`` container have corresponding keys and must all have the same type. See the [Building Composite Objects](../../../user_guide/06-Building_Composite_Objects.ipynb) user guide for details on how to compose containers." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### ``NdLayout`` holds dictionaries" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Using the ``sine_curve`` function below, we can declare a dictionary of ``Curve`` elements, where the keys correspond to the frequency values:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "frequencies = [0.5, 0.75, 1.0, 1.25]\n", "\n", "def sine_curve(phase, freq):\n", " xvals = [0.1* i for i in range(100)]\n", " return hv.Curve((xvals, [np.sin(phase+freq*x) for x in xvals]))\n", "\n", "curve_dict = {f:sine_curve(0,f) for f in frequencies}" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We now have a dictionary where the frequency is the key and the corresponding curve element is the value. We can now turn this dictionary into an ``NdLayout`` by declaring the keys as corresponding to the frequency key dimension:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "NdLayout = hv.NdLayout(curve_dict, kdims='frequency')\n", "NdLayout" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### ``NdLayout`` is multi-dimensional" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "By using tuple keys and making sure each position in the tuple is assigned a corresponding ``kdim``, ``NdLayouts`` allow visualization of a multi-dimensional space:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "curve_dict_2D = {(p,f):sine_curve(p,f) for p in [0, np.pi/2] for f in [0.5, 0.75]}\n", "NdLayout = hv.NdLayout(curve_dict_2D, kdims=['phase', 'frequency'])\n", "NdLayout" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### ``NdLayout`` is similar to ``HoloMap``" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Other than the difference in the visual semantics, whereby ``NdLayout`` displays its contents overlaid, ``NdLayout`` are very similar to ``HoloMap`` (see the [``HoloMap``](./HoloMap.ipynb) notebook for more information).\n", "\n", "One way to demonstrate the similarity of these two containers is to cast our ``NdLayout`` object to ``HoloMap``:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "hv.HoloMap(NdLayout)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We could now cast this ``HoloMap`` back to an ``NdLayout``. Unlike the other container examples such as [``GridSpace``](./GridSpace.ipynb) and [``NdOverlay``](./NdOverlay.ipynb), we cannot display this reconstituted ``NdLayout`` next to the ``HoloMap`` above using ``+`` as a ``Layout`` cannot hold an ``NdLayout`` in the same way than an ``NdLayout`` cannot hold a ``Layout``." ] } ], "metadata": { "language_info": { "name": "python", "pygments_lexer": "ipython3" } }, "nbformat": 4, "nbformat_minor": 2 }