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A clusterizer to cluster hits of a pixel detector with Python. The clustering happens in C++ on numpy arrays to increase the speed.

Project Description

# pyPixelClusterizer [![Build Status](]( [![Build Status](](

pyPixelClusterizer 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 a numpy recarray with data types as defined in data_struct.HitInfo. The hit fields are: - event_number - frame - column - row - charge

Cluster information (data_struct.ClusterInfo) is created with the following field: - event_number - ID - size - charge - seed_column - seed_row - mean_column - mean_row

Also cluster hit information (data_struct.ClusterHitInfo) is created. The cluster hit information is the hit array extended by the field: - cluster_ID - is_seed - cluster_size - n_cluster

# Installation


# Usage

import numpy as np from tables import dtype_from_descr from pyPixelClusterizer.hit_clusterizer import HitClusterizer from pyPixelClusterizer import data_struct

hits = np.ones(shape=(3, ), dtype=dtype_from_descr(data_struct.HitInfo)) # create some data clusterizer = HitClusterizer() # initialize clusterizer clusterizer.add_hits(hits) # cluster hits # add hits to clusterizer print (clusterizer.get_cluster()) # print cluster print (clusterizer.get_hit_cluster()) # print hits + cluster info

Also take a look at the example folder!

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File Name & Checksum SHA256 Checksum Help Version File Type Upload Date
pyPixelClusterizer-1.0.0.tar.gz (438.4 kB) Copy SHA256 Checksum SHA256 Source Sep 24, 2015

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