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Tom Felton declares it’s time for Hollywood to ‘bow down to the women'
by Mel EvansTom Felton has heartily declared it’s high time Hollywood ‘bowed down to the women’ and we can’t help but shout out ‘hear hear!’

The Harry Potter star is taking on Shakespeare in latest film Ophelia alongside Daisy Ridley and in all its awesomeness Tom admits he was drawn to the project due to its championing of women.
‘It’s time for men to bow down to the women with the power and skill and ability to make these stories,’ the 32-year-old star tells Metro.co.uk, on the promo trail as the character of Laertes, brother of Daisy’s Ophelia.
To the actor, not only is the Shakespeare classic, based on the tale of Hamlet, ‘timeless’ to the Brit thespian, but by taking it in a different direction and focusing on the female protagonists – also including Naomi Watts as Queen Gertrude – you’re unlocking an untapped resource of the movie business.
‘This is the day and age for that really [and] you’ve also got one of the strongest female actors in the business as the lead,’ Tom continues.
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‘Claire [McCarthy] the director is ferociously talented and lovely and strong and this is the time, isn’t it?
‘Hearing her vision for it, I though, “hell yeah!” This is the time to be part of something like this. It was quite a no brainer on my part.’
Starring alongside Star Wars’ Daisy right as she filmed the final instalment of the Skywalker trilogy, The Rise Of Skywalker, what off-set antics does the guy have? We need the tea, Malfoy!
‘How much money do you have?’ Tom cheekily profers.
‘You get this thing in your head that big stars might not be normal people, but they’re incredibly normal,’ Tom, Hollywood megastar, says.
‘I worked with Clive [Owen] when I was eight-years-old in my first TV job. He remembered me [on this set], which was a surprise.
‘We went out a few nights. You’re learning and admiring their work and working alongside them, but I think you learn just as much from people when you see them off the set than on.’
But…but Tom, were you able to glean any Star Wars spoilers from your co-star?
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‘No, if I did I would be too drunk to remember them,’ he laughs.
‘We traded war stories of what it’s like to be on set and in the fandom.’
In fact, when Tom first met Daisy, he thought she didn’t like him (a Harry fan over Draco, perhaps?)
‘[I said] “You were quite quiet!” and somewhere in the midst, I think she put it in an interview she was a big Harry Potter fan and freaking out Draco Malfoy was her brother,’ he says.
‘Everyone has grown up with those films in one way or another and I’m a massive fan of her work as well.’
Ophelia is in cinemas Friday.
Got a showbiz story?
If you've got a story, video or pictures get in touch with the Metro.co.uk Entertainment team by emailing us<EMAIL_ADDRESS>calling 020 3615 2145 or by visiting our Submit Stuff page - we'd love to hear from you.


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Eshin Jolly
Dartmouth College
Dept of Psychological and Brain Sciences
6207 Moore Hall, Hanover, NH, 03755
(917) 376 3340
<EMAIL_ADDRESS>Currently
2020-Present
Postdoctoral Fellow
Consortium for Interacting Minds
Center for Cognitive Neuroscience
Dartmouth College (Hanover, NH)
Mentors: Luke Chang, Thalia Wheatley, Emily Finn, Jeremy Manning
Education & Training
2012-2019
PhD, Cognitive Neuroscience
NSF Graduate Fellow
Dartmouth College (Hanover, NH)
Thesis: Social Cognitive Maps: A Relational Account of Person Representation and Memory
Committee: Luke Chang, Thalia Wheatley, Jeremy Manning, Janice Chen
2006-2010
BA, Brain and Cognitive Science; Psychology
Minor: Music & Jazz Performance
University of Rochester (Rochester, NY)
Thesis: Testing Domain Specificity: Conceptual Knowledge of Living and Non-living Things
Committee: Jessica Cantlon, Brad Mahon, Elissa Newport
2016
Microsoft Research PhD Intern
MSR Computational Social Science Group (NYC, NY)
PIs: Duncan Watts & Sid Suri
2010-2012
Lab Manager
Harvard University (Cambridge, MA)
PI: Jason Mitchell
2008-2010
Research Assistant
Baruch College (NYC, NY)
PI: Jennifer Mangels
Research Assistant
Mt Hope Family Center, University of Rochester (Rochester, NY)
PIs: Sheree Toth & Jack Peltz
Industry Consulting
2023-Present
Senior UX/UI Engineer & Designer
MoreMore AI
Film & media arts startup
2020-Present
Co-Founder & CTO; Scientific Advisor
Parsnip.ai
Food and ed-tech startup
2020
Scientific Advisor
The Sukhi Project
Employee well-being and mental health startup
2019-Present
Project Manager; Technical Support Lead
Code for America (Upper Valley Brigade)
Rural Internet Project
Funding
2019-Present
Postdoctoral Fellow
National Science Foundation, Career Award 1848370 ($886,457, PI: Luke Chang)
Neural and computational basis of guilt in decision-making (co-written)
2013-2016
Graduate Fellow
National Science Foundation, Graduate Research Fellowship ($90,000)
Uncovering the represention of self: A multivariate approach
Manuscripts
In Prep
Jolly, E., Chang, L.J. (in prep). Neural encoding and reinstatement of social motifs.
Jolly, E., Ranger, M.S. & Chang, L.J. (in prep). The neural basis of guilt diffusion in interpersonal harm-minimization.
Jolly, E., Smith A., Gangadharan, A.A., Hoidal, A.S. & Chang, L.J. (in prep). Guilt-aversion motivates harm-minimization in surrogate decision-making.
Under review/revision
Jolly, E., Sadhukha, S., Iqbal, M., Molani, Z., Walsh, T.M., Manning, J.R., & Chang, L.J. (under review). People are represented and remembered through their relationships with others. [psyarxiv preprint]
Gao, X., Jolly, E., Yu, H., Liu, H., Zhou, X., & Chang, L.J. (under revision). The hidden cost of receiving favors: A theory of indebtedness. [bioRxiv preprint]
Published
2023
Jolly, E.*, Cheong, J.H.*, Xie, T.*, Byrne, S. Kenny, M., & Chang, L.J. (2023). Py-Feat: Python Facial Expression Analysis Toolbox. Affective Science. [Link] [toolbox]
*Equal contribution
2022
Jolly, E., Farrens, M., Greenstein, N., Eisenbarth, H., Reddan, M.C., Andrew, E., Wager, T.D., & Chang, L.J. (2022). Recovering individual emotional states from sparse ratings using collaborative filtering. Affective Science. [Link] [toolbox] [data & materials]
2021
Jolly, E. & Chang, L.J. (2021). Multivariate spatial feature selection in fMRI. Social Cognitive and Affective Neuroscience, 16(8), 795-806. [Link]
Jolly, E. & Chang, L.J. (2021). Gossip drives vicarious learning and facilitates social connections. Current Biology, 31, 1-11. [Link] [data & materials]
Coverage: New York Times, VPR News, PNAS Journal Club
Chang, L.J., Jolly, E., Cheong, J.H., Rapuano, K., Greenstein, N., Chen, P.A., & Manning, J.R. (2021). Endogenous variation in ventromedial prefrontal cortex state dynamics during naturalistic viewing reflects affective experience. Science Advances, 7(17), 1-17. [Link] [data & materials]
2020
Jolly, E.*, Sadhukha, S.*, & Chang, L.J. (2020). Response to Lynch et al: On measuring head motion and effects of head molds during fMRI. NeuroImage, 117484. [Link] [data & materials]
Jolly, E.*, Sadhukha, S.*, & Chang, L.J. (2020). Custom-molded headcases have limited efficacy in reducing head motion during naturalistic fMRI experiments. NeuroImage, 117207. [Link] [data & materials]
*Equal contribution
Chen, P.H.A., Jolly, E., Cheong, J.H., & Chang, L.J. (2020). Intersubject representational similarity analysis reveals individual variations in affective experience when watching erotic movies. NeuroImage, 116851. [PDF] [data & materials]
2019
Chen, P.H.A., Cheong, J.H., Jolly, E., Elhence, H., Wager, T.D., & Chang, L.J. (2019). Socially transmitted placebo effects. Nature Human Behavior, 3, 1295-1305. [PDF] [data & materials]
Jolly, E.*, Tamir, D.I.*, Burum, B.A., & Mitchell, J.P. (2019). Wanting without enjoying: The social value of sharing experiences. PLoS One, 14(4), e0215318. [PDF] [data & materials] *Equal contribution
Jolly, E., & Chang, L.J. (2019). The Flatland Fallacy: Moving Beyond Low Dimensional Thinking. Topics in Cognitive Science, 1-22. [PDF] [figure & simulation code]
2018
Jolly, E. (2018). Pymer4: Connecting R and Python for linear mixed modeling. Journal of Open Source Software, 3(31), 862. [PDF] [documentation site]
Chang, L. J. & Jolly E. (2018). Emotions as computational signals of goal error. In A. Fox, R. Lapate, A. Shackman & R. Davidson (Eds), The Nature of Emotion (343-351). Oxford University Press. [PDF]
2017
Cheong, J.C., Jolly, E., Sul, S., & Chang, L.J. (2017). Computational Models in Social and Affective Neuroscience in Moustafa, A. (Eds), Computational Models of Brain and Behavior (229-245). Hoboken, NJ: Wiley. [Link]
Rane, S.*, Jolly, E.*, Park, A.*, Jang, H*., & Craddock, R.C. (2017). Developing predictive biomarkers using whole-brain classifiers: Application to the ABIDE I dataset. Research Ideas and Outcomes, 3:e12733. [PDF].
*Equal contribution
2011-2016
Moran, J.M., Jolly, E., & Mitchell, J.P. (2014). Spontaneous mentalizing predicts the fundamental attribution error. Journal of Cognitive Neuroscience, 26(3), 569-576. [PDF]
Moran, J.M., Jolly, E., & Mitchell, J.P. (2012). Social-cognitive deficits in normal aging. Journal of Neuroscience, 32(16), 5553-5561. [PDF]
Jolly, E. (2011). Testing domain specificity: Conceptual knowledge of living and non-living things. The Yale Review of Undergraduate Research in Psychology, 2, 94-118. [PDF]
Open Scientific Software
2022-Present
Py-feat
Analysis of facial expressions from images and videos, (Core Developer)
[Documentation] [Slides] [Github]
2020-Present
Neighbors
Predicting affective responses from sparse measurement data, (Project Author)
[Documentation] [Github]
SvelteTurk
Graphical User Interface for managing experiments on Mturk, (Project Author)
[Documentation] [Github]
2017-Present
Pymer4
Statistics library for estimating linear mixed-effects models, (Project Author)
[Documentation] [Github]
2016-Present
Nltools
Toolbox for intuitively analyzing neuroimaging data, (Core Developer)
[Documentation] [Video Talk] [Github]
Invited Talks & Presentations
2023
Representing and remembering people through their relationships.
Invited talk at the MIND Summer School, Dartmouth College (Hanover, NH)
The structure of social memory: People as contexts.
Presentation at the Social and Affective Neuroscience Society conference (Santa Barbara, CA)
Navigating the social world: A relational account of how we represent, remember, and talk about people.
Invited talk at Stanford University (Stanford, CA)
People as contexts: A relational account of person representation and memory.
Invited talk for Innovators in Cognitive Neuroscience (virtual). [Video]
2022
Spontaneous Neural Representations of Social Relationships in Naturalistic Contexts.
Symposium presentation at the International Society for Research on Emotion, USC (Los Angeles, CA)
Emotion and Social Perception in Naturalistic Contexts: Perspectives from Affective Computing and Affective Neuroscience.
Symposium organizer at the International Society for Research on Emotion, USC (Los Angeles, CA)
2021
Methodological considerations in social and affective neuroscience.
Invited talk at NYU Freeman Lab (NYC, NY)
2020
Social Cognitive Maps: A Relational Account of Person Representation and Memory.
Invited talk at Harvard University (Cambridge, MA)
Why Design Abstractions Matters for Analytics Tools: Neuroimaging analysis with Neuro-Learn. [Video]
Symposium presentation at the Scientific Computing with Python conference (virtual)
Spontaneous Neural Representations of Social Relationships in Naturalistic Contexts.
Symposium presentation at the Society for Affective Science conference (San Francisco, CA; cancelled due to COVID-19).
Methodological challenges in contemporary fMRI studies.
Invited talk at the Neuroimaging Analysis Methods meeting, Princeton University (Princeton, NJ)
2018
Introduction to functional alignment methods for fMRI.
Invited lecture at the Sao Paulo School of Advanced Science on Social and Affective Neuroscience (Sao Paulo, Brazil)
2017
Naturalistic approaches towards an understanding of social reasoning and communication.
Invited talk at Stanford University (Stanford, CA)
The social benefits of gossip
Presentation at the New England Research on Decision-Making conference, Brown University (Providence, RI)
Introduction to Git and Github for psychologists.
Invited talk at the Reproducible Psychological Science workshop at the Annual Meeting for the Association for Psychological Science (Boston, MA)
Interpersonal dynamics and the inelasticity of social guilt.
Invited talk at the Boston Area Moral Cognition Group (Boston, MA)
Interpersonal dynamics and the inelasticity of social guilt.
Invited talk at Affectiva Inc (Boston, MA)
Spontaneous impression-formation about parasocial relationships.
Presentation at the Social and Affective Neuroscience Society conference (Los Angeles, CA)
State of the Data: Annual Dartmouth Brain Imaging Center Quality Assurance Report.
Presentation at Dartmouth College (Hanover, NH)
2016
Field experiments on human prosociality using Mechanical Turk.
Presentation at Microsoft Research (New York City, NY)
The Social Benefits of Gossip.
Presentation at the Social Brain Sciences Brown Bag (Dartmouth College, NH)
Posters & Conference Proceedings
2023
Jolly, E., Sadhukha, S., Iqbal, M., Molani, Z., Walsh, T.M., Manning, J.R., & Chang, L.J. (2023). The structure of social memory: People as contexts.
Poster at the Social and Affective Neuroscience Society conference (Santa Barbara, CA)
Kwon, D., Jolly, E., Chang, L.J., & Shim, W.M. (2023). Neural representations of dynamic social interactions.
Poster at the 26th Annual Meeting of the Korean Society for Brain and Neural Sciences (Busan, Korea)
2022
Jolly, E., Farrens, M., Greenstein, N., Eisenbarth, H., Reddan, M.C., Andrew, E., Wager, T.D., & Chang, L.J. (2022). Recovering individual emotional states from sparse ratings using collaborative filtering.
Poster at the Society for Affective Science conference (virtual)
2021
Jolly, E. & Chang, L.J. (2021). Spontaneous Neural Representations of Social Relationships in Naturalistic Contexts.
Poster at the Social and Affective Neuroscience Society conference (virtual)
Winner Poster Award
2020
Jolly, E. (2020). Pymer4: Bringing R’s Powerful Mixed-modeling to Python.
Poster at the Scientific Computing with Python conference (virtual)
Winner Scipy Scholarship
2019
Jolly, E. & Chang, L.J. (2019). Gossip drives vicarious learning and facilitates robust social connections.
Poster at the Social and Affective Neuroscience Society conference (Miami, FL)
Cheong, J.C., Chen, P.A., Jolly, E., Elhence, H., Wager, T.D., & Chang, L.J. (2019). Socially transmitted placebo effects.
Poster at the Society for Affective Science conference (Boston, MA)
2018
Jolly, E., Reddan, M.C., Gianaros, P.J., Manuck, S.M. Chang, L.J., & Wager, T.D. (2018). NeuroLIME: A novel tool for explaining the predictions of complex brain models.
Poster at the Social and Affective Neuroscience Society conference (New York, NY)
Reddan, M.C., Jolly, E., & Wager, T.D. (2018). NeuroLIME: A novel tool for explaining the predictions of nonlinear neuroimaging classifiers.
Poster at the Organization for Human Brain Mapping conference (Singapore, Singapore)
Reddan, M.C., Jolly, E., & Wager, T.D. (2018). NeuroLIME: A novel tool for explaining the predictions of nonlinear neuroimaging classifiers.
Poster at the Computational and Systems Neuroscience conference (Denver, CO)
2017
Jolly, E. & Chang, L.J. (2017). Gossip drives vicarious learning and facilitates robust social connections.
Poster at the Annual Meeting of the Association for Psychological Science (Boston, MA)
Cheong, J.H., Jolly, E., & Chang, L.J. (2017). A window into the mind: A computational approach to measuring emotions in response to naturalistic stimuli.
Poster the Social and Affective Neuroscience Society conference (Los Angeles, CA)
2016
Jolly, E. & Chang, L.J. (2016). Groups, gossip and social dilemmas.
Poster at the International Conference on Computational Social Science (Evanston, IL)
2015
Jolly, E., Tamir, D.I., & Mitchell, J.P. (2015). The social value of sharing experiences.
Poster at the Social and Affective Neuroscience Society conference (Boston, MA)
Winner Poster Award
2012
Moran, J.M., Jolly, E., & Mitchell, J.P. (2012). Spontaneous mentalizing supports the fundamental attribution error.
Poster at the Cognitive Neuroscience Society conference (Chicago, IL)
2010
Peltz, J.S. Toth, S.L., Rogosch, F.A., Jolly, E., & Cicchetti, D. (2010). Paternal emotional availability’s effects on children’s socioemotional functioning in maternal depression contexts.
Poster at the Annual Meeting of the Association for Psychological Science (Boston, MA)
Teaching
2023
Methods in Neuroscience at Dartmouth Summer School
Invited Faculty
Dartmouth College (Hanover, NH) [Resources]
Introduction to facial expression analysis with py-feat
Tutorial at the Consortium for Interacting Minds
Dartmouth College (Hanover, NH) [Slides]
2019
Introduction to version control for neuroscientists
Lecturer and TA at MIND Summer School
Dartmouth College (Hanover, NH) [Resources] [Video]
2018
Introduction to version control for neuroscientists
Lecturer and TA at MIND Summer School
Dartmouth College (Hanover, NH) [Resources] [Video]
Computational tools for neuroscience: Jupyter notebooks
Lecturer and TA at MIND Summer School
Dartmouth College (Hanover, NH) [Resources] [Video]
Functional Alignment Techniques in fMRI
Lecture at Sao Paulo Summer School on Social and Affective Neuroscience (SPSAN)
Mackenzie Presbyterian University (Sao Paulo, Brazil)
2017
Computational tools for neuroscience: Jupyter notebooks
Lecturer and TA at MIND Summer School
Dartmouth College (Hanover, NH) [Resources] [Video]
Introduction to containers for reproducible research
Lecturer and TA at MIND Summer School
Dartmouth College (Hanover NH) [Resources]
Introduction to Git and Gitub for social psychologists
Lecture at the Reproducible Psychological Science workshop
Annual Meeting for the Association for Psychological Science (Boston, MA)
Introduction to jupyter notebooks (and why you should love them!)
Tutorial at BrainHack Local
Dartmouth College (Hanover, NH)
Online research methods for the experimental study of social behavior
Research Methods, Guest Lecturer
Dartmouth College (Hanover, NH)
2016
Online research methods for the experimental study of social behavior
Research Methods, Guest Lecturer
Dartmouth College (Hanover, NH)
The social benefits of gossip
Social Psychology, Guest Lecturer
Dartmouth College (Hanover, NH)
Contemporary fMRI pre-processing: Introduction to Nipype and Docker
fMRI Methods, Guest Lecturer
Dartmouth College (Hanover, NH)
2015
fMRI Methods: Brain Mapping with functional MRI
Course TA and Guest Lecturer
Dartmouth College (Hanover, NH)
Research Methods: Laboratory in Psychological Science*
Course TA and Guest Lecturer
*Mentored award winning undergraduate group
Dartmouth College (Hanover, NH)
2014
Introductory Statistics: Experimental Design and Methodology
Course TA and Guest Lecturer
Dartmouth College (Hanover, NH)
2013
Research Methods: Laboratory in Psychological Science
Course TA and Guest Lecturer
Dartmouth College (Hanover, NH)
2011
Introduction to MATLAB for Behavioral Research
Workshop organizer
Harvard University (Cambridge, MA)
Mind Perception
Workshop organizer
Harvard University (Cambridge, MA)
Awards
2023
ICN Talk Award
Innovators in Cognitive Neuroscience
Trainee Data Blitz Award
Social and Affective Neuroscience Society
2022
Complex Systems Summer School (CSSS)
Santa Fe Institute
2021
Mistletoe Research Fellowship finalist
Dartmouth College
2020
SciPy Scholarship Award
Scientific Computing with Python Conference
Poster Award
Social and Affective Neuroscience Society
2019
Kavli Summer Institute in Cognitive Neuroscience
UC Santa Barbara
Thayer Consulting Case Competition 1st Place
Thayer School of Engineering, Dartmouth College
Hack Dartmouth Finalist
Dartmouth College
2018
Hack Dartmouth Best Community Hack
Dartmouth College
Sao Paulo Summer School on Social and Affective Neuroscience (SPSAN)
Mackenzie Presbyterian University, Sao Paulo
Graduate Arts and Science Travel Award
Dartmouth College
PBS Graduate Travel Award
Dartmouth College
Neukom Institute Travel Award
Dartmouth College
2017
Graduate Alumni Research Award
Dartmouth College
PBS Graduate Travel Award
Dartmouth College
Methods in Neuroscience Computational Summer School
Dartmouth College
Summer School in Social Neuroscience and Neuroeconomics
Duke University
Trainee Data Blitz Award
Social and Affective Neuroscience Society
Human Neuroimaging Methods Travel Award
Organization for Human Brain Mapping
2016
Hack Dartmouth 2nd Place project award
Dartmouth College, Thayer School of Engineering
Neurohackweek Summer School
University of Washington eScience Institute
2015
Social Affective Neuroscience Society Poster Award
Social and Affective Neuroscience Society
PBS Graduate Travel Award
Dartmouth College
2013-2016
National Science Foundation Graduate Research Fellowship
Dartmouth College
2010
BCS Dept: Highest Honors in research
University of Rochester
2006-2010
Wilder-Trustee Scholarship
University of Rochester
Mentorship
2022-Present
Wasita Mahaphanit
Graduate Student
Dartmouth College
Sushmita Sadhukha
Graduate Student
Dartmouth College
2021-2022
Maxwell Ranger ‘22
Honors Thesis
Dartmouth College
2017-2021
Maryam Iqbal ’21
Presidential Scholar/Honors Thesis
Dartmouth College
2020-2021
Liza Begunova ’21
Honors Thesis
Dartmouth College
2019-2020
Max Farrens ‘20
Full-time Research Assistant
Dartmouth College
2017-2019
Nathan P. Greenstein ‘19
Presidential Scholar
Dartmouth College
Sushmita Sadhukha ’18
Full-time Research Assistant
Dartmouth College
2015-2018
Arati A. Gangadharan ’18
Honors Thesis
Dartmouth College
2015-2017
Hirsh Elhence ’17
Presidential Scholar
Dartmouth College
Technical Skills
Programming Languages
Python, Javascript, Matlab, R, Bash
Frontend Web Development
HTML, CSS, Svelte, Vue
Backend/Fullstack/App Development
Node, Express, Meteor, Mongodb, Firebase, Flask, Electron
Stimulus Presentation
Psychopy, Psychophysics toolbox, E-prime, Presentation
Data Analysis
Scientific-Python, Statsmodels, Scikit-learn, Lme4
Neuroimaging Analysis
FSL, AFNI, SPM, Nipype, Nilearn
Data Visualization
Seaborn/Matplotlib, D3, Dash/Plotly, ggplot
Dev Ops
Git/Github, TravisCI, Tox, Pytest, Moab-Torque
Professional Activities
Reviewer
Cerebral Cortex, Neuroimage, Human Brain Mapping, SCAN, Neuropsychologia, Cognition and Emotion, JESP, PLoS One, GigaScience, JOSS, Nature Communications, SIGCHI, Frontiers in Psych, JPSP, JEP:G, Journal of Neuroscience, Scientific Reports
Society Memberships
Social and Affective Neuroscience Society, Society for Affective Science, Organization for Human Brain Mapping, Cognitive Neuroscience Society, Society for Personality and Social Psychology
Leadership & Community
2019-2022
Committee Member
Inclusivity, Diversity, and Culture Advisory Committee
Dartmouth College, Hanover, NH
2020-2021
Board Member
Dartmouth College Postdoctoral Association
Dartmouth College, Hanover NH
2018-2020
VP of Client Outreach
Dartmouth Graduate Consulting Group
Dartmouth College, Hanover, NH
2017-2020
Co-Founder
Line@ Project
Dartmouth College, Hanover, NH
2017
Organizing committee member
Dartmouth Brainhack, Hanover, NH
2014
Station Leader
GWISE Science day for local middle schools
Dartmouth College, Hanover, NH
2013-2015
Primary Organizer
Social Brain Sciences Symposium talk series
Dartmouth College, Hanover, NH
Graduate Representative
Social Area Graduate Student Representative
Dartmouth College, Hanover, NH
__
Last updated: August 2023


Class: Aws::OpsWorks::Types::CreateStackRequest
| Inherits: |
Struct
|
| Defined in: |
(unknown) |
Overview
Note: When passing CreateStackRequest
as input to a Client method, you can use a vanilla Hash
:
{
name: "String", # required
region: "String", # required
vpc_id: "String",
attributes: {
"Color" => "String",
},
service_role_arn: "String", # required
default_instance_profile_arn: "String", # required
default_os: "String",
hostname_theme: "String",
default_availability_zone: "String",
default_subnet_id: "String",
custom_json: "String",
configuration_manager: {
name: "String",
version: "String",
},
chef_configuration: {
manage_berkshelf: false,
berkshelf_version: "String",
},
use_custom_cookbooks: false,
use_opsworks_security_groups: false,
custom_cookbooks_source: {
type: "git", # accepts git, svn, archive, s3
url: "String",
username: "String",
password: "String",
ssh_key: "String",
revision: "String",
},
default_ssh_key_name: "String",
default_root_device_type: "ebs", # accepts ebs, instance-store
agent_version: "String",
}
Instance Attribute Summary collapse
-
#agent_version ⇒ String
The default AWS OpsWorks agent version.
-
#attributes ⇒ Hash<String,String>
One or more user-defined key-value pairs to be added to the stack attributes.
-
#chef_configuration ⇒ Types::ChefConfiguration
A
ChefConfiguration
object that specifies whether to enable Berkshelf and the Berkshelf version on Chef 11.10 stacks. -
#configuration_manager ⇒ Types::StackConfigurationManager
The configuration manager.
-
#custom_cookbooks_source ⇒ Types::Source
Contains the information required to retrieve an app or cookbook from a repository.
-
#custom_json ⇒ String
A string that contains user-defined, custom JSON.
-
#default_availability_zone ⇒ String
The stack\'s default Availability Zone, which must be in the specified region.
-
#default_instance_profile_arn ⇒ String
The Amazon Resource Name (ARN) of an IAM profile that is the default profile for all of the stack\'s EC2 instances.
-
#default_os ⇒ String
The stack\'s default operating system, which is installed on every instance unless you specify a different operating system when you create the instance.
-
#default_root_device_type ⇒ String
The default root device type.
-
#default_ssh_key_name ⇒ String
A default Amazon EC2 key pair name.
-
#default_subnet_id ⇒ String
The stack\'s default VPC subnet ID.
-
#hostname_theme ⇒ String
The stack\'s host name theme, with spaces replaced by underscores.
-
#name ⇒ String
The stack name.
-
#region ⇒ String
The stack\'s AWS region, such as \"us-east-1\".
-
#service_role_arn ⇒ String
The stack\'s AWS Identity and Access Management (IAM) role, which allows AWS OpsWorks to work with AWS resources on your behalf.
-
#use_custom_cookbooks ⇒ Boolean
Whether the stack uses custom cookbooks.
-
#use_opsworks_security_groups ⇒ Boolean
Whether to associate the AWS OpsWorks built-in security groups with the stack\'s layers.
-
#vpc_id ⇒ String
The ID of the VPC that the stack is to be launched into.
Instance Attribute Details
#agent_version ⇒ String
The default AWS OpsWorks agent version. You have the following options:
Auto-update - Set this parameter to
LATEST
. AWS OpsWorks automatically installs new agent versions on the stack\'s instances as soon as they are available.Fixed version - Set this parameter to your preferred agent version. To update the agent version, you must edit the stack configuration and specify a new version. AWS OpsWorks then automatically installs that version on the stack\'s instances.
The default setting is the most recent release of the agent. To specify an agent version, you must use the complete version number, not the abbreviated number shown on the console. For a list of available agent version numbers, call DescribeAgentVersions.
#attributes ⇒ Hash<String,String>
One or more user-defined key-value pairs to be added to the stack attributes.
#chef_configuration ⇒ Types::ChefConfiguration
A ChefConfiguration
object that specifies whether to enable Berkshelf
and the Berkshelf version on Chef 11.10 stacks. For more information,
see Create a New Stack.
#configuration_manager ⇒ Types::StackConfigurationManager
The configuration manager. When you create a stack we recommend that you use the configuration manager to specify the Chef version: 12, 11.10, or 11.4 for Linux stacks, or 12.2 for Windows stacks. The default value for Linux stacks is currently 11.4.
#custom_cookbooks_source ⇒ Types::Source
Contains the information required to retrieve an app or cookbook from a repository. For more information, see Creating Apps or Custom Recipes and Cookbooks.
#custom_json ⇒ String
A string that contains user-defined, custom JSON. It can be used to override the corresponding default stack configuration attribute values or to pass data to recipes. The string should be in the following escape characters such as \'\"\':
"{\"key1\": \"value1\", \"key2\": \"value2\",...}"
For more information on custom JSON, see Use Custom JSON to Modify the Stack Configuration Attributes.
#default_availability_zone ⇒ String
The stack\'s default Availability Zone, which must be in the specified
region. For more information, see Regions and Endpoints. If you
also specify a value for DefaultSubnetId
, the subnet must be in the
same zone. For more information, see the VpcId
parameter description.
#default_instance_profile_arn ⇒ String
The Amazon Resource Name (ARN) of an IAM profile that is the default profile for all of the stack\'s EC2 instances. For more information about IAM ARNs, see Using Identifiers.
#default_os ⇒ String
The stack\'s default operating system, which is installed on every instance unless you specify a different operating system when you create the instance. You can specify one of the following.
A supported Linux operating system: An Amazon Linux version, such as
Amazon Linux 2016.03
,Amazon Linux 2015.09
, orAmazon Linux 2015.03
.A supported Ubuntu operating system, such as
Ubuntu 16.04 LTS
,Ubuntu 14.04 LTS
, orUbuntu 12.04 LTS
.CentOS 7
Red Hat Enterprise Linux 7
A supported Windows operating system, such as
Microsoft Windows Server 2012 R2 Base
,Microsoft Windows Server 2012 R2 with SQL Server Express
,Microsoft Windows Server 2012 R2 with SQL Server Standard
, orMicrosoft Windows Server 2012 R2 with SQL Server Web
.A custom AMI:
Custom
. You specify the custom AMI you want to use when you create instances. For more information, see Using Custom AMIs.
The default option is the current Amazon Linux version. For more information on the supported operating systems, see AWS OpsWorks Operating Systems.
#default_root_device_type ⇒ String
The default root device type. This value is the default for all
instances in the stack, but you can override it when you create an
instance. The default option is instance-store
. For more information,
see Storage for the Root Device.
#default_ssh_key_name ⇒ String
A default Amazon EC2 key pair name. The default value is none. If you specify a key pair name, AWS OpsWorks installs the public key on the instance and you can use the private key with an SSH client to log in to the instance. For more information, see Using SSH to Communicate with an Instance and Managing SSH Access. You can override this setting by specifying a different key pair, or no key pair, when you create an instance.
#default_subnet_id ⇒ String
The stack\'s default VPC subnet ID. This parameter is required if you
specify a value for the VpcId
parameter. All instances are launched
into this subnet unless you specify otherwise when you create the
instance. If you also specify a value for DefaultAvailabilityZone
, the
subnet must be in that zone. For information on default values and when
this parameter is required, see the VpcId
parameter description.
#hostname_theme ⇒ String
The stack\'s host name theme, with spaces replaced by underscores. The
theme is used to generate host names for the stack\'s instances. By
default, HostnameTheme
is set to Layer_Dependent
, which creates host
names by appending integers to the layer\'s short name. The other themes
are:
Baked_Goods
Clouds
Europe_Cities
Fruits
Greek_Deities
Legendary_creatures_from_Japan
Planets_and_Moons
Roman_Deities
Scottish_Islands
US_Cities
Wild_Cats
To obtain a generated host name, call GetHostNameSuggestion
, which
returns a host name based on the current theme.
#name ⇒ String
The stack name.
#region ⇒ String
The stack\'s AWS region, such as \"us-east-1\". For more information about Amazon regions, see Regions and Endpoints.
#service_role_arn ⇒ String
The stack\'s AWS Identity and Access Management (IAM) role, which allows AWS OpsWorks to work with AWS resources on your behalf. You must set this parameter to the Amazon Resource Name (ARN) for an existing IAM role. For more information about IAM ARNs, see Using Identifiers.
#use_custom_cookbooks ⇒ Boolean
Whether the stack uses custom cookbooks.
#use_opsworks_security_groups ⇒ Boolean
Whether to associate the AWS OpsWorks built-in security groups with the stack\'s layers.
AWS OpsWorks provides a standard set of built-in security groups, one
for each layer, which are associated with layers by default. With
UseOpsworksSecurityGroups
you can instead provide your own custom
security groups. UseOpsworksSecurityGroups
has the following settings:
True - AWS OpsWorks automatically associates the appropriate built-in security group with each layer (default setting). You can associate additional security groups with a layer after you create it, but you cannot delete the built-in security group.
False - AWS OpsWorks does not associate built-in security groups with layers. You must create appropriate EC2 security groups and associate a security group with each layer that you create. However, you can still manually associate a built-in security group with a layer on creation; custom security groups are required only for those layers that need custom settings.
For more information, see Create a New Stack.
#vpc_id ⇒ String
The ID of the VPC that the stack is to be launched into. The VPC must be in the stack\'s region. All instances are launched into this VPC. You cannot change the ID later.
If your account supports EC2-Classic, the default value is
no VPC
.If your account does not support EC2-Classic, the default value is the default VPC for the specified region.
If the VPC ID corresponds to a default VPC and you have specified either
the DefaultAvailabilityZone
or the DefaultSubnetId
parameter only,
AWS OpsWorks infers the value of the other parameter. If you specify
neither parameter, AWS OpsWorks sets these parameters to the first valid
Availability Zone for the specified region and the corresponding default
VPC subnet ID, respectively.
If you specify a nondefault VPC ID, note the following:
It must belong to a VPC in your account that is in the specified region.
You must specify a value for
DefaultSubnetId
.
For more information on how to use AWS OpsWorks with a VPC, see Running a Stack in a VPC. For more information on default VPC and EC2-Classic, see Supported Platforms.


We're learning about triangle strips and making shapes in EECS 351-Intro to computer graphics right now and I thought it would be convenient to be able to tell if a drawn triangle is backfacing or not.
Press "space" to hide backfacting triangles and enter to clear.
Red triangles are backfacing and green are frontfacing


Clarke insists future is bright for Scotland after win over Kazakhstan
A play-off spot provides a possible route to Euro 2020.
Steve Clarke insists the future is bright for Scotland as they look to claim a Nations League golden ticket to next summer’s European Championships.
Clarke’s side brought their doomed Euro 2020 qualifying campaign to an end as they beat Kazakhstan 3-1 at Hampden.
But they will have a second chance at booking a place in their first major finals since 1998 next March thanks to the Nations League play-off slot secured by his predecessor Alex McLeish.
The Scots – who will have home advantage for the single-leg semi-final – will discover who from Bulgaria, Hungary, Israel and Romania they will face when the draw is made on Friday.
Norway or Serbia will await the winner but Clarke is confident his side can finally end their long stint in the international wilderness.
He said: “With this group of players, I can be very optimistic about the play-offs.
“They are 100 percent committed to their country and are desperate to get to a major finals at Euro 2020. So we can be very optimistic.”
There were less than 20,000 inside Hampden to see two goals from John McGinn either side of a Steven Naismith header secure victory.
But many would have been forgiven for thinking they were about to see a repeat of the Scots’ catastrophic Group I opener, when the team then bossed by McLeish slumped 3-0 to the Kazakhs during a dismal defeat in Nursultan.
The hosts were booed off at half-time after defender Scott McKenna allowed Baktiyor Zainutdinov to lash the visitors ahead with a stunning 34th-minute opener but Clarke was pleased with his side’s reaction.
“I thought the performance was good – good in the first half and really good in the second half against a dangerous opponent,” he said.
“We knew if we made mistakes in possession, Kazakhstan could hurt us on the counter-attack which they did when they took the lead.
“But it was a great reaction from the players, in the second half particularly.
“We played a lot of good stuff, looked a threat going forward and created a lot of chances.
“It’s another win – three wins in a row. I don’t know about anyone else, but the boys in the dressing room are feeling good about themselves.”
Clarke has yet to see Hampden anywhere near full since taking the job on back in the summer.
But he expects to see the Tartan Army turn out in numbers to roar Scotland to Euro 2020, which will see four games staged in Glasgow.
“I’ve no preferences for the draw,” said the manager.
“You take what you get. It will be nice to have a little bit of clarity so we can actually start planning for the March games.
“We’ll be at home (in the semi) and I think we’ve shown tonight we can be a good team here at Hampden.
“That place will be full I’m sure. We’ll get a good atmosphere, get the team like that on the front foot and we can be OK.
“It will be nice (to see the stadium rocking). I’ve been here a few times myself as a supporter when it’s been like that.
“It’s a long way away though. We can enjoy tonight and the fact it’s three wins in a row.
“But we know we still have a lot of work to do. We’re not getting carried away thinking we’ve cracked it.
“I said before Cyprus I could see signs of improvement, little things in training, little things in the games that were getting better and we were improving.
“I said that until we started getting results I couldn’t start shouting about it but hopefully other people can see there has been a little step forward.”


Designated team of experts who are well experienced with the infrastructure and offer services round the clock.
Best in the market with more than 2 years of service experience.
Our aim has always worked to reach each and every corner and make life simple. With an adaptive model of Kaizen.
We provide a blend of unique services for CCTV. We offer a very optimized services which needs very minimal resource to manage and maintain. We have a dedicated team which work 24/7 to give customer the ease of services.
The world has moved towards blend of digital services mechanism and now it is the time make things simpler with our blend of our Bio Metric services. We do have a unique ideology of service category.
The thorough experience with our prolonged team of services into field of cable & networking made us to stand unique. We got dedicated team of experts who are rich enough in providing cable & network services.
The Solar Perimeter Security Electric Fence system is a modern day alternative to conventional methods of fencing to protect your crops & property. Electric Fence is an effective way to reduce losses.
The video door phones with smart technology intimate you about the visitors at your door even before you have the door open. The ultimate security solution is widely used in homes, apartments and businesses.
Cable splicing is “the process of connecting two end terminals of cable conductors”. Splicing can be performed for joining the cable conductors. Arranging the adequate insulating, shielding, jacketing materials to complete the cable splicing efficiently. If improper material is used and unskilled person is selected, it may lead to improper cable splicing.
King in the economy of services for Digital Cable TV services,CCTV,Cabling and Broadband.


{% extends "base.html" %} {% import "bootstrap/wtf.html" as wtf %} {% block center_content %}
You're adding a response to the secret {{ form.secret.shortname }}
This secret is waiting on {{ n_left }} more response{% if n_left > 1 %}s{% endif %}.
{% endif %} {{ wtf.quick_form(form) }} {% endblock %}


Annealed importance sampling
Posted: 2017-07-20 , Modified: 2017-07-20
Tags: sampling, annealing, temperature
Posted: 2017-07-20 , Modified: 2017-07-20
Tags: sampling, annealing, temperature
We can get an unbiased estimator for \(p(x)\), say \(\wh p\). But we often want \(\ln p(x)\). We use Jensen’s inequality and Markov’s inequality. So \(\ln \wh p\) is a probabilistic lower bound. \[ \E[\ln \wh p] \le \ln p\implies \quad \Pj(\ln \wh p> \ln p + b) <e^{-b}. \] (This is true no matter what the variance is. However, this can be a very loose bound. There is no good way of estimating \(\E \ln X\) from draws of \(X\) (why not?). Oddly, there is a good way of estimating \(\E e^X\) from \(X\) by power series expansion. (Power series for \(\ln\) is terrible over long distances.))
Note this is prone to overestimation with little indication anything is wrong.
Goal: posterior distribution \[ p(z|x,\al) = \fc{p(z,x|\al)}{\int_z p(z,x|\al)}. \] Pick a family of distributions with variational parameters \(q(z_{1:m}|\nu)\). Use \(q\) with fitted parameters as proxy.
So want to minimize \(KL(q||p)\).
Why \(q||p\), not \(p||q\)?
\(\ln p\) doesn’t depend on \(q\).
Given annealed distributions \(p_i\propto f_i\), \(p_K=p\) with Markov chains \(M_i\) (with transition kernels \(T_i\)), to estimate \(Z=Z_K\),
For probabilistic neural nets, use Gibbs sampler (alternately sample \(h\) and \(x\)) as transition.
Think of this as proposing the distribution given by applying the \(T_i\) in sequence.
Giving a stochastic lower bound for \(Z\) means we overestimate log-likelihood.
Go the other way using samples from the target distribution This gives a probabilistic lower bound on \(\fc{Z_0}{Z}\), so a probabilistic upper bound on \(Z\), so we underestimate log-likelihood.
\(p(h|v)\) needs to be tractable. ((z|x) in above notation)
For intractable \(p(h|v)\) combine the AIS (fixing \(v\)) and RAISE steps to get a single estimate. See Algorithm 3 for details.


Investment Calculator
Amount Invested (principal):
USD
Must be a positive number!
Annual Rate (example: .08):
Must be a positive number!
Number of Years:
Must be a positive number!
Periods per Year:
Must be a positive number!
Reset
Compute Future Value
Future Value:
USD
Error: No Error


{% extends '_base/page-with_nav-single_row.html' %} {% load staticfiles %} {% load bootstrap3 %} {% block title %} Browse Products by Vendor - Product Database {% endblock %} {% block page_content %}
On this page, you can view the products for a specific vendor that are stored in the database. Click here to get a quick introduction. You can also search within the entire database.
{% include "productdb/_components/search_function_info_with_config_link.html" %}| Product ID | Product Group | Description | List Price | Tags | Lifecycle State | EoL anno | EoS | EoNewSA | EoSWM | EoRFA | EoSCR | EoVulnServ | Last Date of Support | Vendor Bulletin | LC auto-sync | {{ INTERNAL_PRODUCT_ID_LABEL }} |
|---|


https://github.com/VulcanTechnologies/d3-grid-map
A package for plotting gridded data sets with D3
January 20, 2016
Joseph Sheedy
<EMAIL_ADDRESS>// Pass the constructor a selector
// for the container element and
// optionally an options object:
var map = new d3.geo.GridMap('#map1', {});
// call addLayer to add data.
// It can be topojson, geojson,
// or a Float32Array of gridded data:
map.addLayer(countries);
map.addLayer(dataArray, {gridSize: [720, 360]};
only global regularly spaced lat/lon grids are supported (for now!)
The original use case for GridMap was regularly spaced sparse arrays. Empty cells contain the value NaN.
Arrays containing mostly a single value compress well, so it is easy to create the entire array in memory, gzip it in transit, and have the JS client rehydrate it.
d3.xhr('/data/provider')
.responseType('arraybuffer')
.get(function(error, xhr) {
var data = new Float32Array(xhr.response);
var layerOptions = {
gridSize: [w, h],
};
map.addLayer(data, layerOptions);
});
So the data format is just a stream of (width * height * 4) bytes, 4 bytes per grid cell
The simple definition of the data format makes server support easy. Assume you have a 2-d numpy array:
# fake some data, this is just a numpy array
data = np.random.rand(360, 720).astype(np.float32)
# that's it, ship it
return data.tobytes()
Javascript typed arrays use native byte order. x86 is little endian, and if you're using it on server and client side you're golden. This could be handled, but isn't yet. Headsup.
Grids are drawn on canvas elements by
The most expensive part of this is the projection function. If we have multiple grid layers, this calculation needs only be done once for each pixel, so the screen-to-grid coordinates mapping is cached. This enables almost reasonably efficient animation.
Not every projection (actually, most I tried) in the massive set of d3 projections has a well defined, bijective inverse. Effects range from artifacts outside the sphere to disfunctionality.
GridMap is right on the cusp of being fast enough. How to make it faster?
Fork
https://github.com/VulcanTechnologies/d3-grid-map
then
% make develop
When you're ready to commit, run "make" to do a final build
THE END


{% include "home/header.htm" %}
Well, it's simple! You get the app, install it, and tell it your Block & Room no. and the folder where you keep all your good stuff (for example your Downloads folder, with your movies, music, games and stuff you wanna share).
And that's it! Our App will index your files, and send that index to VITCloud! (don't worry, it won't upload your actual files!)
And all the good stuff you wanna share will be available to SEARCH on VITCloud.
Now, for example, if anyone searches for a movie that our app found in your computer, he will be told that you have it!
See, that means no more posting on facebook saying stuff like "does anyone have this movie, does anyone have that game?" Just type it in here, and if someone has it in the campus, we'll make sure you know who ;)
Please note one thing though, VITCloud is nothing without your participation. So as much as you wanna search the stuff you want, please download the App, and share what you have! That's the only way the database will grow, more people will be able to find what they've been looking for!


| Thank you! |
Thank you! To all of you who, in some way or another, have helped me improve this proggy...
Thank you!
Thank you! To those who have awarded PUK some kind of recognition
Click here to jump to the award page.
Special thanks go to:
Welcome Lee: Support for the Taiwanese language
Joakim Nilsson (KIM): For the idea of hiding PUK's trayed icon
Fredric Knutsson: Support for the Sweden language
Marwin: Support for the Trumpet dialer
RAP: For the IE4 Tweaking Tool information
Jon Maye: For his help on fixing some ugly typo errors on this document
Tom & Bruce for giving me such great ideas for the program
Lyion for giving me a mirror to download PopUp Killer
I may have lost the email from the person who had the idea of the Synchronization option. Thank you!!! Great idea!!!
To the hundreds of people who have contributed with ideas, suggestions, bug reports and of course... money!
To BooHoo (Bruce) for his unconditional help! Without him I would have dropped this program a long ago.


- HAXcms
- That which powers this website
- Unbundled-Webcomponents
- A methodology for building and deploying web components to CDNs that we use in all our projects
- Web components monorepo
- That which powers our editing experience (and all our other tags for that matter)
- WCFactory
- Build and maintain your own web component library, why should we be special.
- Check out our integrations page
for platform specific repos
Great! Here's some of the best ways for organizations to try "HAX" and get involved in the project.
- Reach out to any of the members of the core project team on our slack
. We're happy to do conference calls to forge partnerships especially around HAX or OER production solution though it has implications for any public site!
- Try out the HAXcms live demo
(reset hourly)
- Reach out in the issue queue
with questions
- Bring this website to developers in your organization or other code junkies and tell them to explore
- Host a HAX camp
(ask for more details)
HAX makes up multiple projects across hundreds of web components and various other repos. It can be a bit overwhelming but we want you to imagine something... Imagine being a developer on HAX.
Step 'ight up
urz te next contrib
Because all it takes to get involved in HAX is, that's right, showing up in our repos and getting involved! Yes you too can be just as meme-able as we are!
All things HAX are powered by people just like you, wanting to make the web a better, more accessible, easier to use, less painful to develop for... place.Help us make that a reality and you too could have Snoop Dawg escorting you over to a brand new car*
Anything is possible with HAXTheWeb. The only limit...is yourself
.
*Claims vs reality may vary. Just help us out and we'll see where it goes..


This blog post shows a few different types of content that's supported and styled with Bootstrap. Basic typography, images, and code are all supported.

This blog post shows a few different types of content that's supported and styled with Bootstrap. Basic typography, images, and code are all supported.

link emphasis strong

link
emphasis
strong

h2. Heading

h3. Sub-Heading

foo

bar

baz

blockquote blockquote blockquote

blockquote blockquote blockquote

code

code

foo

bar

baz


Working with Scholarly Text w/ rOpenSci Tools
Scott Chamberlain (@sckottie)
UC Berkeley / rOpenSci
What kinds of questions can we ask?
Does number of authors per article increase through time?
Do p-values on average differ by impact factor?
How do length of methods sections change through time?
How does the use of the word ___ vary through time?
How does code sharing vary by journal/discipline/etc.?
scholarly text data flow
tabulizer example
how open will publishers be moving forward?
full text
metadata, including references
Open Citations!
OCC: Open Citations Corpus
As of March 12, 2018, the OCC has ingested the references from 302,758 citing bibliographic resources
and contains information about 12.8 million citation links to 6.5 million cited resources.


Mockfile format
Mockfile is a YAML configuration, allowing to define what gets mocked. It simplifies including and excluding sources, as well as defining what should be imported or @testable
imported.
It also ties generated Mock configuration with a specific target, allowing to lint it agains most common issues.
Every generated file have its own section, following pattern below:
sourceryCommand: null # 1. (optional)
sourceryTemplate: null # 1. (optional)
mock1: # 2.
sources: # 2.1.
include: # 2.1.1
- ./MyApp
exclude: [] # 2.1.2 (optional)
output: # 2.2
./MyAppUnitTests/Mocks/Mock.generated.swift
targets: # 2.3 (optional)
- MyAppUnitTests
testable: [] # 2.4 (optional)
import: [] # 2.5 (optional)
prototype: false # 2.6 (optional)
sourcery: # 2.7 (optional)
- ./path/to/custom/sourcery.yml # (optional)
mock2: # 2.
...
sourceryCommand
is by defaultnil
. You can use it to select custom Sourcery version/command/binary, instead of using default one bundled with SwiftyMocky CLI viamint
.sourceryTemplate
is custpom template location to use instead of default one. Default template would be derived from Pods,Carthage,SPM directory. If not found, CLI would use bundled template.- Distinctive name of your mock configuration. You can define as much configurations as you want. Each of them represents one generated file. That allows to have a separate mocks for a separate targets (you usually need that if you have more than one test target)
sources
defines what files/directories would be scanned forAutoMockable
types.include
list of included files/directories relative to project rootexclude
list of excluded files/directories relative to project root
output
location and name of generated mocks file. If no name specified “Mock.generated.swift” would be usedtargets
list of targets names. It should match the test targets that are using generated mocks file. Used to determine if your setup is correct.testable
list of testable modules imports. By default, if you generate mocks forYourApp
, it should containYourApp
. Would be placed at the top of the generated file.import
list of modules imports. Would be placed at the top of the generated file.prototype
default isfalse
. Settrue
if you are going to use CarthageSwiftyPrototype
librarysourcery
list of paths to additional Sourcery configurations, if you want to execute them alongside the mock generation.
Note 1: Calling
swiftymocky setup
will launch an interactive tool helping you to create and prefill the Mockfile. You can also useswiftymocky init
if you want a placeholder you can fill manually.Note 2: To evaluate your Mockfile setup, as well as other things, run
swiftmocky doctor
.Note 3: You can use
swiftymocky autoimport
to prefilltestable
andimport
in your configurations.


--- layout: page title: "Prints" permalink: /prints/ display_page_title: true main_image_path: /assets/images/58ab1c0c34c3e.jpg main_image_caption: "Democracy" display_image: false frontpage: true page_order_number: 1 homepage_description_markdown: >- frontpagetitle: "Prints" display_thumb_title: true thumb_crop: true images: - image_path: image_title: image_description: _options: layout: hidden: true main_image_path: width: 1200 height: 1200 resize_style: contain mime_type: image/jpeg image_path: width: 1200 height: 1200 resize_style: "contain" mime_type: "image/jpeg" _comments: title: Page title permalink: Be careful editing this display_page_title: Show the page title at the top of the page main_image_path: Image used to represent your page display_image: Show the featured image at the top of the page images_first: display gallery of images BEFORE the main text frontpage: Show this page on the homepage homepage_description_markdown: Text used on homepage if shown frontpagetitle: Alternative title for home page use display_thumb_title: Show image titles below images images: Add and edit images here image_description: Might only be shown in the close up of an image thumb_crop: Crop thumbnail images to a consistent size ---
Susan has worked as a printmaker since studying printmaking in the 70’s.
She has developed from a traditional printmaker into an artist using unconventional methods to produce ‘Graphic Paintings’ that take advantage of multi layering and graphic marks
that result in free and painterly works.
Her subjects, while often appear playful are usually topical and often political.


---
layout: page
title: "People"
description: "People in the Experimental Music Technologies Lab"
header-img: "img/people-bg.jpg"
---
The lab is open for participation and membership (which includes being subscribed to the lab’s mailing list), welcoming researchers from across the university.
Current members (in alphabetical order):
Pollie Barden (Engineering and Design)
Caroline Bassett (Media and Film)
Dylan Beattie (Music)
David Berry (Media and Film)
Margaret A. Boden (Informatics)
Danny Bright (Music)
Cecile Chevalier (Media and Film)
Ron Chrisley (Informatics)
Andrew Duff (Media and Film)
Sam Duffy (Music)
Alice Eldridge (Informatics)
Gemma Farrell (Music)
Evelyn Ficarra (Music)
David Hendy (Media and Film)
Ed Hughes (Music)
Chris Kiefer (Informatics)
Andrew Leggo (Informatics)
Thor Magnusson (Music)
Paul McConnell (Media and Film)
Sally Jane Norman (Professor of Performance Technologies)
Alex Peverett (Sussex Humanities Lab)
Thanos Polymeneas-Liontiris (Music)
Andrew Sleigh (Maker Faire and Lighthouse)
Chris Thornton (Informatics)
Joe Watson (Music)
Honorary members
Tom Betts (Big Robot Games & University of Huddersfield)
Nick Collins (Music – Durham University)
Enrike Hurtado Mendieta (University of the Basque Country, Bilbao)
Anna Jordanous (Digital Humanities – King’s College London)
Matthew Yee-King (Music and Informatics – Goldsmiths)
Chad McKinney (Informatics)


The zc.async package provides an easy-to-use Python tool that schedules durable tasks across multiple processes and machines.
For instance...
Web apps:
maybe your web application lets users request the creation of a large PDF, or some other expensive task.
Postponed work:
maybe you have a job that needs to be done at a certain time, not right now.
Parallel processing:
maybe you have a long-running problem that can be made to complete faster by splitting it up into discrete parts, each performed in parallel, across multiple machines.
Serial processing:
maybe you want to decompose and serialize a job.
High-level features include the following.
Easy to use.
At its simplest, put a function in a zc.async queue and commit a transaction. See the quick-starts for examples.
Flexible configuration, changeable dynamically in production.
Add and remove worker processes on the fly, with configurable policy on how to handle interrupts. Let processes decide how many of which tasks to perform. Configuration for each process is stored in the database so no restarts are needed and a change can happen for any process from any database client.
Reliable and fault tolerant, supporting high availability.
Configurable policy lets zc.async know when, how, and under what circumstances to retry jobs that encounter problems. Multiple processes and machines can be available to work on jobs, and a machine or process that suddenly dies lets siblings decide what to do with incomplete jobs, with policy on a per-job basis. The central ZODB database server can be replicated with commercial tools (ZRS) or open-source tools (RelStorage plus, for instance PostgreSQL and slony; or gocept.zeoraid).
Good debugging tools.
Exceptions generate persistent Failure objects (from the Twisted project) for analysis, and verbose log messages.
Well-tested.
The package has good automated tests and is in use in mission-critical applications for large software deployments.
Friendly to testing.
The package exposes testing helpers for a variety of circumstances, to make writing automated tests for zc.async-enabled software fairly painless.
While developed as part of the Zope project, zc.async can be used stand-alone, as seen in the quick-starts and the majority of the tests.
The system uses the Zope Object Database (ZODB), a transactional, pickle-based Python object database, for communication and coordination among participating processes.
zc.async participants can each run in their own process, or share a process (run in threads) with other code.
The Twisted framework supplies some code (failures and reactor implementations, primarily) and some concepts to the package.
These quick-starts can help you get a feel for the package. Please note: the Grok quickstart is only just begun, and should be regarded mostly as a placeholder.
Contents: