# Holoviews


[HoloViews](http://holoviews.org) is a Python library that makes analyzing and visualizing scientific or engineering data much simpler, more intuitive, and more easily reproducible.

This document can be compiled to HTML with

    ```
    stitch ex_holoviews.txt -o ex_holoviews.html --no-self-contained -H header.js
    ```

You'll need a file ``header.js`` with the required javascript libraries.

    ```
    <script src="https://code.jquery.com/jquery-3.1.0.min.js" integrity="sha256-cCueBR6CsyA4/9szpPfrX3s49M9vUU5BgtiJj06wt/s=" crossorigin="anonymous"></script>
    <script src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.3.1/require.min.js"></script>
    ```

```{python}
import numpy as np
import holoviews as hv
from IPython import display
hv.notebook_extension()
```

```{python}
def sine(x, phase=0, freq=100):
    return np.sin((freq * x + phase))

phases = np.linspace(0,2*np.pi,11) # Explored phases
freqs = np.linspace(50,150,5)      # Explored frequencies

dist = np.linspace(-0.5,0.5,202)   # Linear spatial sampling
x,y = np.meshgrid(dist, dist)
grid = (x**2+y**2)                 # 2D spatial sampling
```

```{python}
freq1 = hv.Image(sine(grid, freq=50))  + hv.Curve(zip(dist, sine(dist**2, freq=50)))
freq2 = hv.Image(sine(grid, freq=200)) + hv.Curve(zip(dist, sine(dist**2, freq=200)))
(freq1 + freq2).cols(2)
```

```{python}
dimensions = ['Phase', 'Frequency']
keys = [(p,f) for p in phases for f in freqs]

items = [(k, hv.Image(sine(grid, *k), vdims=['Amplitude'])) for k in keys]
circular_wave = hv.HoloMap(items, kdims=dimensions)
circular_wave
```