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Python-Microscope: High performance control of arbitrarily complex and scalable bespoke microscopes

View ORCID ProfileDavid Miguel Susano Pinto, View ORCID ProfileMick A Phillips, View ORCID ProfileNicholas Hall, Julio Mateos–Langerak, View ORCID ProfileDanail Stoychev, Tiago Susano Pinto, View ORCID ProfileMartin J Booth, View ORCID ProfileIlan Davis, View ORCID ProfileIan M Dobbie
doi: https://doi.org/10.1101/2021.01.18.427171
David Miguel Susano Pinto
1Micron Advanced Bioimaging Unit, Department of Biochemistry, University of Oxford, South Parks Road, Oxford, OX1 3QU, United Kingdom
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  • ORCID record for David Miguel Susano Pinto
Mick A Phillips
1Micron Advanced Bioimaging Unit, Department of Biochemistry, University of Oxford, South Parks Road, Oxford, OX1 3QU, United Kingdom
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Nicholas Hall
1Micron Advanced Bioimaging Unit, Department of Biochemistry, University of Oxford, South Parks Road, Oxford, OX1 3QU, United Kingdom
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Julio Mateos–Langerak
2IGH, Univ Montpellier, CNRS. 141 rue de la Cardonille, 34396 Montpellier, France
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Danail Stoychev
1Micron Advanced Bioimaging Unit, Department of Biochemistry, University of Oxford, South Parks Road, Oxford, OX1 3QU, United Kingdom
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Tiago Susano Pinto
1Micron Advanced Bioimaging Unit, Department of Biochemistry, University of Oxford, South Parks Road, Oxford, OX1 3QU, United Kingdom
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Martin J Booth
3Department of Engineering Science, University of Oxford, Parks Road, Oxford, OX1 3PJ, United Kingdom
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Ilan Davis
1Micron Advanced Bioimaging Unit, Department of Biochemistry, University of Oxford, South Parks Road, Oxford, OX1 3QU, United Kingdom
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Ian M Dobbie
1Micron Advanced Bioimaging Unit, Department of Biochemistry, University of Oxford, South Parks Road, Oxford, OX1 3QU, United Kingdom
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  • For correspondence: ian.dobbie@bioch.ox.ac.uk
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Abstract

Bespoke microscopes often require control of multiple hardware devices and precise hardware coordination. It is also desirable to have a control solution that is scalable to more complex systems and translatable between components from different manufacturers. Here we report Python-Microscope, a free and open source Python library for high performance control of arbitrarily complex and scalable bespoke microscopes. Python-Microscope offers an elegant pythonic software platform to control microscopes, abstracting differences between physical devices by providing a defined interface for different device types. These include cameras, filter wheels, light sources, deformable mirrors, and stages. Concrete implementations are provided for a range of specific hardware and a framework is in place for further expansion. Python-Microscope supports the distribution of devices over multiple computers while maintaining synchronisation via highly precise hardware triggers. We discuss the architecture choices of Python-Microscope that overcome the performance problems often raised against Python and demonstrate the different use cases that drove its design: its integration in user facing projects, namely in the Microscope-Cockpit project; in controlling complex microscopes at high speed while using the Python programming language; and as a microscope simulation tool for software development.

Competing Interest Statement

Martin J Booth declares a significant interest in Aurox Ltd., whose microscopes were used in this work.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted January 19, 2021.
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Python-Microscope: High performance control of arbitrarily complex and scalable bespoke microscopes
David Miguel Susano Pinto, Mick A Phillips, Nicholas Hall, Julio Mateos–Langerak, Danail Stoychev, Tiago Susano Pinto, Martin J Booth, Ilan Davis, Ian M Dobbie
bioRxiv 2021.01.18.427171; doi: https://doi.org/10.1101/2021.01.18.427171
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Python-Microscope: High performance control of arbitrarily complex and scalable bespoke microscopes
David Miguel Susano Pinto, Mick A Phillips, Nicholas Hall, Julio Mateos–Langerak, Danail Stoychev, Tiago Susano Pinto, Martin J Booth, Ilan Davis, Ian M Dobbie
bioRxiv 2021.01.18.427171; doi: https://doi.org/10.1101/2021.01.18.427171

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