"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import holoviews as hv\n",
"hv.extension('bokeh')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"``Curve`` Elements are used to display quantitative values over a continuous interval or time span. They accept tabular data with one key dimension representing the samples along the x-axis and one value dimension of the height of the curve at for each sample. See the [Tabular Datasets](../../../user_guide/08-Tabular_Datasets.ipynb) user guide for supported data formats, which include arrays, pandas dataframes and dictionaries of arrays."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Simple Curve\n",
"\n",
"A ``Curve`` is a set of values provided for some set of keys from a [continuously indexable 1D coordinate system](../../../user_guide/Continuous_Coordinates.ipynb), where the plotted values will be connected up because they are assumed to be samples from a continuous relation."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"points = [(0.1*i, np.sin(0.1*i)) for i in range(100)]\n",
"hv.Curve(points)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Interpolation"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The ``Curve`` also supports the ``interpolation`` plot option to determine whether to linearly interpolate the curve values or to draw discrete steps:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"overlay =hv.NdOverlay({interp: hv.Curve(points[::8]).opts(interpolation=interp, width=600)\n",
" for interp in ['linear', 'steps-mid', 'steps-pre', 'steps-post']})\n",
"overlay.opts(legend_position='right')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"For full documentation and the available style and plot options, use ``hv.help(hv.Curve).``"
]
}
],
"metadata": {
"language_info": {
"name": "python",
"pygments_lexer": "ipython3"
}
},
"nbformat": 4,
"nbformat_minor": 2
}