# lttbc Release 0.2.1

Largest triangle three buckets module for Python written in C

Keywords
downsampling-algorithm, lttb, pypi, python
MIT
Install
``` pip install lttbc==0.2.1 ```

# lttbc: Largest-Triangle-Three-Buckets (Python using a c implementation)   This is a low-level implementation of the `Largest-Triangle-Three-Buckets` (LTTB) downsampling algorithm written in Python.

The code has been translated from the work of Sveinn Steinarsson (https://github.com/sveinn-steinarsson/flot-downsample/).

## Demo and 'Known Issues'

The examples show the efficiency of the downsampling algorithm with a data set set of `5000` data points down sampled to `500` and `250` points. Known features and requirements:

• The algorithm requires monotonically increasing x data (finite)
• The algorithm requires finite y data (otherwise problems might occur)
• x and y data have to be of same length (of course)
• The algorithm returns arrays of dtype double

## Installing

You can also install it from PyPI to use in other environments with Python 3.5 or later:

``````pip install lttbc
``````

## How to use on the field

The module `lttbc` differs in the standard input from other largest triangle three buckets implementations. The `downsample` function takes an input for `x` and `y` in addition to the `threshold`:

``````import lttbc
import numpy as np

ARRAY_SIZE = 10000
THRESHOLD = 1000

x = np.arange(ARRAY_SIZE, dtype=np.int32)
y = np.random.randint(1000, size=ARRAY_SIZE, dtype=np.uint64)

nx, ny = lttbc.downsample(x, y, THRESHOLD)

assert len(nx) == THRESHOLD
assert len(ny) == THRESHOLD
assert nx.dtype == np.double
assert ny.dtype == np.double

# List data or a mixture is accepted as well ...
x = list(range(ARRAY_SIZE))
y = [np.random.uniform(0, 1000) for _ in range(ARRAY_SIZE)]

assert isinstance(x, list)
assert isinstance(y, list)

nx, ny = lttbc.downsample(x, y, THRESHOLD)

assert len(nx) == THRESHOLD
assert len(ny) == THRESHOLD
assert nx.dtype == np.double
assert ny.dtype == np.double
``````