"
]
},
{
"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
}