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A fast, generic, and easy to use clusterizer to cluster hits of a pixel matrix in Python. The clustering happens with numba on numpy arrays to increase the speed.

Project Description
# Pixel Clusterizer [![Build Status](]( [![Build Status](]( [![Coverage Status](](

Pixel_clusterizer is an easy to use pixel hit-clusterizer for Python. It clusters hits on an event basis in space and time.

The hits have to be defined as a numpy recarray. The array has to have the following fields:
- event_number
- frame
- column
- row
- charge

or a mapping of the names has to be provided. The data type does not matter.

The result of the clustering is the hit array extended by the following fields:
- cluster_ID
- is_seed
- cluster_size
- n_cluster

A new array with cluster information is also created created and has the following fields:
- event_number
- ID
- size
- charge
- seed_column
- seed_row
- mean_column
- mean_row

# Installation

The stable code is hosted on PyPI and can be installed by typing:

pip install pixel_clusterizer

# Usage

import numpy as np

from pixel_clusterizer import clusterizer

hits = np.ones(shape=(3, ), dtype=clusterizer.hit_data_type) # Create some data with std. hit data type

cr = clusterizer.HitClusterizer() # Initialize clusterizer

hits_clustered, cluster = cr.cluster_hits(hits) # Cluster hits

Also take a look at the example folder!

# Test installation
nosetests pixel_clusterizer
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File Name & Checksum SHA256 Checksum Help Version File Type Upload Date
pixel_clusterizer-3.0.0-py2-none-any.whl (35.4 kB) Copy SHA256 Checksum SHA256 py2 Wheel Jan 16, 2017
pixel_clusterizer-3.0.0-py3-none-any.whl (36.9 kB) Copy SHA256 Checksum SHA256 py3 Wheel Jan 16, 2017
pixel_clusterizer-3.0.0.tar.gz (33.7 kB) Copy SHA256 Checksum SHA256 Source Jan 16, 2017

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