This page tracks the new paper links made to our list of SIGGRAPH 2010 papers.
Page maintained by Ke-Sen Huang.
If you have additions or changes, send an e-mail.
November 21, 2010
October 8, 2010
- A Synthetic-Vision-Based Steering Approach for Crowd Simulation
August 10 2010
- Simulating Virtual Environments within Virtual Environments as the Basis for a Psychophysics of Presence
August 9 2010
- A Simple Geometric Model for Elastic Deformations
- An Artist Friendly Hair Shading System
- Improving Chen & Han's Algorithm on the Discrete Geodesic Problem
- Fool Me Twice: Exploring and Exploiting Error Tolerance in Physics-Based Animation
- NETRA: Interactive Display for Estimating Refractive Errors and Focal Range
August 6 2010
- Manifold Bootstrapping for SVBRDF Capture
(TR)
(
)
- Fabricating Spatially-Varying Subsurface Scattering
(
)
August 5, 2010
- Matching Fluid Simulation Elements to Surface Geometry and Topology
()
(
)
July 20, 2010
- Sampling-based Contact-rich Motion Control
- By-example Synthesis of Architectural Textures
- Efficient Yarn-based Cloth with Adaptive Contact Linearization
- A Deformation Transformer for Real-Time Cloth Animation
- A Novel Algorithm for Incompressible Flow Using Only a Coarse Grid Projection
- Lp Centroidal Voronoi Tessellation and its Applications
- Data-Driven Biped Control
- Added ACM DOI link
- Feature-Preserving Triangular Geometry Images for Level-of-Detail Representation of Static and Skinned Meshes
July 19, 2010
- Structure-Based ASCII Art
July 12, 2010
- Motion-based Video Retargeting with Optimized Crop-and-Warp
June 25, 2010
- VideoMocap: Modeling Physically Realistic Human Motion from Monocular Video Sequences
June 18, 2010
- Apparent Display Resolution Enhancement for Moving Images
- Programmable Motion Effects
- Personal photo enhancement using example images
- Multi-scale Image Harmonization
()
()
(
)
- Fabricating Spatially-Varying Subsurface Scattering
- Manifold Bootstrapping for SVBRDF Capture
(TR)
June 11, 2010
- Multi-scale Image Harmonization
- Triangle Surfaces with Discrete Equivalence Classes
(
)
()
- NETRA: Interactive Display for Estimating Refractive Errors and Focal Range
June 10, 2010
- Camouflage Images
- Popup: Automatic Paper Architectures from 3D Models
June 9, 2010
- Programmable Rendering of Line Drawing From 3D Scenes
- Street Slide: Browsing Street Level Imagery
June 3, 2010
- Sync with Program
- Discrete Viscous Threads
- Multi-scale Image Harmonization
- Smoothed Local Histogram Filters
- Precomputed Wave Simulation for Real-Time Sound Propagation of Dynamic Sources in Complex Scenes
June 2, 2010
- Toward Evaluating Material Design Interface Paradigms for Novice Users
- envyLight: An Interface for Editing Natural Illumination
May 31, 2010
- Generalized Biped Walking Control
May 29, 2010
- Physical Reproduction of Materials with Specified Subsurface Scattering
- Filament based smoke with vortex shedding and variational reconnection
May 28, 2010
- PantaRay: Fast Ray-traced Occlusion Caching of Massive Scenes
- Unstructured Video-Based Rendering: Interactive Exploration of Casually Captured Videos
- A Coaxial Optical Scanner for Synchronous Acquisition of 3D Geometry and Surface Reflectance
- Parametric Reshaping of Human Bodies in Images
(
)
(
- A Multi-Resolution approach to Heat Kernels on Discrete Surfaces
- Subtle Gaze Direction
(TOG Paper)
- Feature-Preserving Triangular Geometry Images for Level-of-Detail Representation of Static and Skinned Meshes
(TOG Paper)
- Ambient Point Clouds for View Interpolation
- High-Quality Single-Shot Capture of Facial Geometry
- Design and Fabrication of Materials with Desired Deformation Behavior
May 26, 2009
- Nonlinear Disparity Mapping for Stereoscopic 3D
- Illustrating How Mechanical Assemblies Work
- Non-local Scan Consolidation for 3D Urban Scene
(
)
(
)
- Effects of Global Illumination Approximations on Material Appearance
- Gesture Controllers
May 25, 2010
- Spatial Relationship Preserving Character Motion Adaptation
May 20, 2009
- Temporal Upsamplng of Performance Geometry Using Photometric Alignment
- 2.5D Cartoon Models
Sounding Liquids: Automatic Sound Synthesis From Fluid Simulation
- Accurate Multidimensional Poisson-Disk Sampling
- GradientShop: A Gradient-Domain Optimization Framework for Image and Video Filtering
- Distributed Gradient-Domain Processing of Planar and Spherical Images
- Mesh Colors
- Fool Me Twice: Exploring and Exploiting Error Tolerance in Physics-Based Animation
- 3D Modeling With Silhouettes
- Underwater Cloth Simulation With Fractional Derivatives
- On Centroidal Voronoi Tessellation íV Energy Smoothness and Fast Computation
- Topology- and Error-Driven Extension of Scalar Functions From Surfaces to Volumes
- Geometry-Aware Direction Field Processing
- SmartBoxes for Interactive Urban Reconstruction
- Toward a Perceptual Space for Gloss
- Learning Behavior Styles with Inverse Reinforcement Learning
May 19, 2009
- Discrete Scale Axis Representations for 3D Geometry
- A Wave-based Anisotropic Quadrangulation Method
()
()
May 18, 2010
- Stable Spaces for Real-time Clothing
- PantaRay: Fast Ray-traced Occlusion Caching of Massive Scenes
- Unified Simulation of Elastic Rods, Shells, and Solids
- Diffusion Coded Photography for Extended Depth of Field
- Toward Evaluating Material Design Interface Paradigms for Novice Users
- High-Quality Single-Shot Capture of Facial Geometry
- Programmable Motion Effects
- By-example Synthesis of Architectural Textures
- Lp Centroidal Voronoi Tessellation and its Applications
- Filament based smoke with vortex shedding and variational reconnection
- Simulating Virtual Environments within Virtual Environments as the Basis for a Psychophysics of Presence
- Triangle Surfaces with Discrete Equivalence Classes
- Parameterizing Subdivision Surfaces
- A Deformation Transformer for Real-Time Cloth Animation
- Symmetry Factored Embedding And Distance
May 17, 2010
- OptiX: A General Purpose Ray Tracing Engine
May 16, 2010
- Rigid-Body Fracture Sound with Precomputed Soundbanks
May 14, 2010
- Volume Contact Constraints at Arbitrary Resolution
- Geodesic patterns
- Example-based Facial Rigging
- Matching Fluid Simulation Elements to Surface Geometry and Topology
()
(
)
- Seeing is Believing: Body Motion Dominates in Multisensory Conversations
- Feature-Based Locomotion Controllers
- Robust Physics-Based Locomotion Using Low-Dimensional Planning
- Optimal Feedback Control for Character Animation Using an Abstract Model
- High Resolution Passive Facial Performance Capture
- Real-Time Lens Blur Effects and Focus Control
- A Multi-layered Display with Water Drops
May 12, 2010
- Discrete Scale Axis Representations for 3D Geometry
- Paneling Architectural Freeform Surfaces
(
)
()
- Spatial Relationship Preserving Character Motion Adaptation
- Apparent Layer Operations for the Manipulation of Deformable Objects
May 10, 2010
- Seeing is Believing: Body Motion Dominates in Multisensory Conversations
- Terrain-Adaptive Bipedal Locomotion Control
- Controllable Conformal Maps for Shape Deformation and Interpolation
- Physics-Inspired Topology Changes for Thin Fluid Features
- A Multiscale Approach to Mesh-based Surface Tension Flows
- Subspace Self-Collision Culling
- Optimizing Walking Controllers for Uncertain Inputs and Environments
- RepFinder: Finding Approximately Repeated Scene Elements for Image Editing
May 9, 2010
May 8, 2010
- Dynamic Local Remeshing for Elastoplastic Simulation
May 7, 2010
- Generalized Biped Walking Control
- A Practical Simulation of Dispersed Bubble Flow
May 6, 2010
- Feature-aligned T-meshes
- Star-Contours for Efficient Hierarchical Self-Collision Detection
- The Frankencamera: an Experimental Platform for Computational Photography
- Reducing Shading on GPUs using Quad-Fragment Merging
- Feature-Based Locomotion Controllers
- Robust Physics-Based Locomotion Using Low-Dimensional Planning
- Example-Based Wrinkle Synthesis for Clothing Animation
()
(
)
May 5, 2010
- A radiative transfer framework for rendering materials with anisotropic structure
- Edge-based image coarsening
- Synthesizing Structured Image Hybrids
- Learning 3D Mesh Segmentation and Labeling
May 4, 2010
- A Connection between Partial Symmetry and Inverse Procedural Modeling
- An Artist Friendly Hair Shading System
- Video Tapestries with Continuous Temporal Zoom
- Learning Behavior Styles with Inverse Reinforcement Learning
May 3, 2010
- Image Warps for Artistic Perspective Manipulation
May 2, 2010
- Acquisition and Analysis of Bispectral Bidirectional Reflectance and Reradiation Distribution Functions
April 30, 2010
- Vector Solid Textures
- Interactive Hair Rendering Under Environment Lighting
- Line Space Gathering for Single Scattering in Large Scenes
()
()
- Micropolygon Ray Tracing with Defocus and Motion Blur
- Synthesizing Structured Image Hybrids
- Paneling Architectural Freeform Surfaces
- Image Deblurring using Inertial Measurement Sensors
- Example-Based Wrinkle Synthesis for Clothing Animation
- Interactive On-Surface Signal Deformation
April 26, 2010
- Illustrating How Mechanical Assemblies Work
- Camouflage Images
April 23, 2010
- Using blur to affect perceived distance and size
- Modeling and Rendering of Impossible Figures
- An efficient multigrid method for the simulation of high-resolution elastic solids
- Personal photo enhancement using example images
- K-set Tilable Surfaces
- Data-Driven Biped Control
April 22, 2010
- Matching Fluid Simulation Elements to Surface Geometry and Topology
April 19, 2010
- Modeling and Rendering of Impossible Figures
- K-set Tilable Surfaces
April 15, 2010
- From Image Parsing to Painterly Rendering
April 14, 2010
- Paneling Architectural Freeform Surfaces
- Discrete Scale Axis Representations for 3D Geometry
April 13, 2010
- Interactive Generation of Human Animation with Deformable Motion Models
- Face poser: Interactive modeling of 3D facial expressions using facial priors
April 12, 2010
- Gesture Controllers
- VideoMocap: Modeling Physically Realistic Human Motion from Monocular Video Sequences
- Apparent Display Resolution Enhancement for Moving Images
- Sampling-based Contact-rich Motion Control
- Precomputed Wave Simulation for Real-Time Sound Propagation of Dynamic Sources in Complex Scenes
- Controllable Conformal Maps for Shape Deformation and Interpolation
- Nonlinear Disparity Mapping for Stereoscopic 3D
- Multi-Class Blue Noise Sampling
- Reducing Shading on GPUs using Quad-Fragment Merging
- Terrain-Adaptive Bipedal Locomotion Control
- Illustrating How Mechanical Assemblies Work
April 8, 2010
- Optimizing Walking Controllers for Uncertain Inputs and Environments
- High Resolution Passive Facial Performance Capture
- A framework for modeling 3D scenes using pose-free equations
- Optimal Feedback Control for Character Animation Using an Abstract Model
April 7, 2010
- Real-Time Lens Blur Effects and Focus Control
- Coded Aperture Projection
- SEVA: Interactive Display for Self-evaluation of an Eye for Visual Accommodation and Focal Range
- An efficient multigrid method for the simulation of high-resolution elastic solids
- Comprehensive Biomechanical Modeling and Simulation of the Upper Body
- A simple approach to nonlinear tensile stiffness for accurate cloth simulation
- A Wave-based Anisotropic Quadrangulation Method
- Photorealistic Models for Pupil Light Reflex and Iridal Pattern Deformation
- Camouflage Images
- Motion-based Video Retargeting with Optimized Crop-and-Warp
April 6, 2010
- Non-local Scan Consolidation for 3D Urban Scenes
- SmartBoxes for Interactive Architectural Reconstruction
- Design and Fabrication of Materials with Desired Deformation Behavior
- Physical Reproduction of Materials with Specified Subsurface Scattering
- Multi-scale Image Harmonization
- Personalized Image Enhancement
April 5, 2010
- A radiative transfer framework for rendering materials with anisotropic structure
- A Multi-layered Display with Water Drops
- Parametric Reshaping of Human Bodies in Images
(
)
(
)
- Micropolygon Ray Tracing with Defocus and Motion Blur
- Line Space Gathering for Single Scattering in Large Scenes
- Interactive Hair Rendering Under Environment Lighting
- Vector Solid Textures
April 4, 2010
- Non-local Scan Consolidation for 3D Urban Scenes
- SmartBoxes for Interactive Architectural Reconstruction
- Matching Fluid Simulation Elements to Surface Geometry and Topology
April 3, 2010
- The Frankencamera: an Experimental Platform for Computational Photography
- Popup: Automatic Paper Architectures from 3D Models
- Example-Based Wrinkle Synthesis for Clothing Animation
- Dynamic Local Remeshing for Elastoplastic Simulation
- Using blur to affect perceived distance and size
April 2, 2010
- Parametric Reshaping of Human Bodies in Images
- A Practical Simulation of Dispersed Bubble Flow
- Interactive On-Surface Signal Deformation
- Acquisition and Analysis of Bispectral BRDFs
April 1, 2010
- Finding Approximately Repeated Scene Elements for Image Editing
- Example-based Facial Rigging
- A Connection between Partial Symmetry and Inverse Procedural Modeling
- Synthesizing Structured Image Hybrids
- Image Deblurring with Inertial Measurement Sensors
- Learning 3D Mesh Segmentation and Labeling
- Ambient Point Clouds for View Interpolation
- Rigid-Body Fracture Sound with Precomputed Soundbanks
- Efficient Yarn-based Cloth with Adaptive Contact Linearization
- Physics-Inspired Topology Changes for Thin Fluid Features
- A Multiscale Approach to Mesh-based Surface Tension Flows
- Unstructured Video-Based Rendering: Interactive Exploration of Casually Captured Videos
March 30, 2010
- Street Slide: Browsing Street Level Imagery
- Subspace Self-Collision Culling
kesen.huang@gmail.com


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Learn more about me
I am Deepak Vhananavar, a First Year MCA student, pursuing my masters from the Institue of Industrial and Computer Management and Research, Pune.
I was born at Bijapur,Karantaka and brought up in the beautiful town also known as Oxford of East i.e Pune. Since childhood my interest was only towards computers and the technology. I was very fascinated to know about the future of IT field and the upcoming technologies. The most thing into this that made me too exited and dedicated to be deep inside this is the AI(Artificial Intelligience). I was so curious to learn all this stuff and wanted to make this as my carrer or passion.
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--- layout: post title: The Vanishing Shopping Mall external-url: http://www.theweek.com/article/index/94691/The_vanishing_shopping_mall ---
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I fail to feel sympathy when something fails because it’s no longer sustainable to do or sell things no one needs. Malls are gross, I’m happy to see them go. Via marco.


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Reach Out {% endblock content %}


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refinepeak.Rd
(Experimental) Take raw reads alignment, refine peak summits and give scores measuring balance of waston/crick tags. Inspired by SPP.
refinepeak( bedfile, ifile, format = c("AUTO", "BAM", "SAM", "BED", "ELAND", "ELANDMULTI", "ELANDEXPORT", "BOWTIE"), cutoff = 5, windowsize = 200L, buffer_size = 100000L, verbose = 2L, outdir = "./", outputfile = character(), log = TRUE )
| bedfile | Candidate peak file in BED format. REQUIRED. |
|---|---|
| ifile | ChIP-seq alignment file. If multiple files are given as '-t A B C', then they will all be read and combined. Note that pair-end data is not supposed to work with this command. REQUIRED. |
| format | Format of tag file, \"AUTO\", \"BED\" or \"ELAND\" or \"ELANDMULTI\" or \"ELANDEXPORT\" or \"SAM\" or \"BAM\" or \"BOWTIE\". The default AUTO option will let '%(prog)s' decide which format the file is. Please check the definition in README file if you choose ELAND/ELANDMULTI/ELANDEXPORT/SAM/BAM/BOWTIE. DEFAULT: \"AUTO\"" |
| cutoff | Cutoff DEFAULT: 5 |
| windowsize | Scan window size on both side of the summit (default: 100bp) |
| buffer_size | Buffer size for incrementally increasing internal array size to store reads alignment information. In most cases, you don't have to change this parameter. However, if there are large number of chromosomes/contigs/scaffolds in your alignment, it's recommended to specify a smaller buffer size in order to decrease memory usage (but it will take longer time to read alignment files). Minimum memory requested for reading an alignment file is about # of CHROMOSOME * BUFFER_SIZE * 8 Bytes. DEFAULT: 100000 |
| verbose | Set verbose level. 0: only show critical message, 1: show additional warning message, 2: show process information, 3: show debug messages. If you want to know where are the duplicate reads, use 3. DEFAULT:2 |
| outdir | The output directory. |
| outputfile | Output bedGraph file name. If not specified, will write to standard output. REQUIRED. |
| log | Whether to capture logs. |
macsList
object.
eh <- ExperimentHub::ExperimentHub() CHIP <- eh[["EH4558"]] CTRL <- eh[["EH4563"]] res <- callpeak(CHIP, CTRL, gsize = 5.2e7, cutoff_analysis = TRUE, outdir = tempdir(), name = "callpeak_narrow0") refinepeak(grep("narrowPeak", res$outputs, value = TRUE), CHIP, outdir = tempdir(), outputfile = "refine")


Getting Started
Prerequisites
Akka requires that you have Java 8 or later installed on your machine.
Lightbend Inc. provides a commercial build of Akka and related projects such as Scala or Play as part of the Lightbend Reactive Platform which is made available for Java 6 in case your project can not upgrade to Java 8 just yet. It also includes additional commercial features or libraries.
Getting Started Guides and Template Projects
The best way to start learning Akka is to download Lightbend Activator and try out one of Akka Template Projects.
Download
There are several ways to download Akka. You can download it as part of the Lightbend Platform (as described above). You can download the full distribution, which includes all modules. Or you can use a build tool like Maven or SBT to download dependencies from the Akka Maven repository.
Modules
Akka is very modular and consists of several JARs containing different features.
- akka-actor – Classic Actors, Typed Actors, IO Actor etc.
- akka-agent – Agents, integrated with Scala STM
- akka-camel – Apache Camel integration
- akka-cluster – Cluster membership management, elastic routers.
- akka-osgi – Utilities for using Akka in OSGi containers
- akka-osgi-aries – Aries blueprint for provisioning actor systems
- akka-remote – Remote Actors
- akka-slf4j – SLF4J Logger (event bus listener)
- akka-stream – Reactive stream processing
- akka-testkit – Toolkit for testing Actor systems
In addition to these stable modules there are several which are on their way into the stable core but are still marked “experimental” at this point. This does not mean that they do not function as intended, it primarily means that their API has not yet solidified enough in order to be considered frozen. You can help accelerating this process by giving feedback on these modules on our mailing list.
- akka-contrib – an assortment of contributions which may or may not be moved into core modules, see External Contributions for more details.
The filename of the actual JAR is for example akka-actor_2.11-2.4.11.jar (and analog for the other modules).
How to see the JARs dependencies of each Akka module is described in the Dependencies section.
Using a release distribution
Download the release you need from http://akka.io/downloads and unzip it.
Using a snapshot version
The Akka nightly snapshots are published to http://repo.akka.io/snapshots/ and are versioned with both SNAPSHOT and timestamps. You can choose a timestamped version to work with and can decide when to update to a newer version.
Warning
The use of Akka SNAPSHOTs, nightlies and milestone releases is discouraged unless you know what you are doing.
Using a build tool
Akka can be used with build tools that support Maven repositories.
Maven repositories
For Akka version 2.1-M2 and onwards:
For previous Akka versions:
Using Akka with Maven
The simplest way to get started with Akka and Maven is to check out the Lightbend Activator tutorial named Akka Main in Java.
Since Akka is published to Maven Central (for versions since 2.1-M2), it is enough to add the Akka dependencies to the POM. For example, here is the dependency for akka-actor:
<dependency>
<groupId>com.typesafe.akka</groupId>
<artifactId>akka-actor_2.11</artifactId>
<version>2.4.11</version>
</dependency>
For snapshot versions, the snapshot repository needs to be added as well:
<repositories>
<repository>
<id>akka-snapshots</id>
<snapshots>
<enabled>true</enabled>
</snapshots>
<url>http://repo.akka.io/snapshots/</url>
</repository>
</repositories>
Note: for snapshot versions both SNAPSHOT and timestamped versions are published.
Using Akka with SBT
The simplest way to get started with Akka and SBT is to use Lightbend Activator with one of the SBT templates.
Summary of the essential parts for using Akka with SBT:
SBT installation instructions on http://www.scala-sbt.org/release/tutorial/Setup.html
build.sbt file:
name := "My Project"
version := "1.0"
scalaVersion := "2.11.8"
libraryDependencies +=
"com.typesafe.akka" %% "akka-actor" % "2.4.11"
Note: the libraryDependencies setting above is specific to SBT v0.12.x and higher. If you are using an older version of SBT, the libraryDependencies should look like this:
libraryDependencies +=
"com.typesafe.akka" % "akka-actor_2.11" % "2.4.11"
For snapshot versions, the snapshot repository needs to be added as well:
resolvers += "Akka Snapshot Repository" at "http://repo.akka.io/snapshots/"
Using Akka with Gradle
Requires at least Gradle 1.4 Uses the Scala plugin
apply plugin: 'scala'
repositories {
mavenCentral()
}
dependencies {
compile 'org.scala-lang:scala-library:2.11.8'
}
tasks.withType(ScalaCompile) {
scalaCompileOptions.useAnt = false
}
dependencies {
compile group: 'com.typesafe.akka', name: 'akka-actor_2.11', version: '2.4.11'
compile group: 'org.scala-lang', name: 'scala-library', version: '2.11.8'
}
For snapshot versions, the snapshot repository needs to be added as well:
repositories {
mavenCentral()
maven {
url "http://repo.akka.io/snapshots/"
}
}
Using Akka with Eclipse
Setup SBT project and then use sbteclipse to generate an Eclipse project.
Using Akka with IntelliJ IDEA
Setup SBT project and then use sbt-idea to generate an IntelliJ IDEA project.
Using Akka with NetBeans
Setup SBT project and then use nbsbt to generate a NetBeans project.
You should also use nbscala for general scala support in the IDE.
Do not use -optimize Scala compiler flag
Warning
Akka has not been compiled or tested with -optimize Scala compiler flag. Strange behavior has been reported by users that have tried it.
Build from sources
Akka uses Git and is hosted at Github.
- Akka: clone the Akka repository from https://github.com/akka/akka
Continue reading the page on Building Akka
Need help?
If you have questions you can get help on the Akka Mailing List.
You can also ask for commercial support.
Thanks for being a part of the Akka community.
Contents


Galaxy Fit gets new watch faces, music control widget with latest update
Source: Android Central
What you need to know
- Samsung is rolling out a new software for the Galaxy Fit.
- The update adds new watch faces as well as a music control widget to the fitness band.
- You will need to update the Galaxy Fit Plugin app before you can download the new software update.
Samsung is adding a few new features to the Galaxy Fit with a new software update. As reported by TizenHelp, the small update brings new watch faces as well as a music control widget to the fitness band. Currently, the update is said to be available in the U.S., Italy, South Korea, India, and the UK.
The update includes 31 new watch faces, most of which are focused on showing useful information such as your heart rate, step count, and weather. Samsung had added 14 new watch faces to the fitness band in the previous update, which was rolled out in September.
Apart from the new watch faces, the update adds a feature that the Galaxy Fit should have offered right from day one – the ability to control music playback. The new music control widget will allow you to play, pause, resume and skip songs directly from your wrist. Additionally, some users have claimed that the update has made the Do Not Disturb feature more responsive than earlier.
To get the new update, you will first have to update the Galaxy Fit Plugin app from the Play Store. Once you have updated the Galaxy Fit Plugin, you will be able to download and install the latest R370XXU0ASK1 update from the Galaxy Wearable app.
Samsung Galaxy Fit
If you're looking for a lightweight yet durable new fitness band, the Galaxy Fit could be a great choice. The fitness band can track your daily steps, calories burned, water intake, monitor your heart rate, and more. It offers 5ATM water resistance and is also shock resistant with MIL-STD-810G certification.
We may earn a commission for purchases using our links. Learn more.


Dataset submission: {{ dataset_submission.identifier }}
{% if path %}Repository submissions may take a long time, particularly for large files. Click 'refresh' to see the current status of your submission. You will also receive a confirmation email when the process is complete (check with your administrator if you are unsure DataStage has your correct email address).
{% endif %}


Change keybind
Emacs key bindings [control+keys]
Emacs key bindings [option+keys]
Launcher Mode v3
- Change spacebar to left_shift.
-
Enter Launcher Mode by tapping the right_command key while left_shift is pressed.
(Leave Launcher Mode when the left_shift is released.)
-
Launcher Mode v3 keys
- tab: Mission Control
- q: Dictionary
- f: Finder
- a: Activity Monitor
- j: Alfred 3
- k: Emacs
- l: iTerm2
- c: Google Chrome
- etc.


lenstronomy.ImSim.MultiBand package¶
Submodules¶
lenstronomy.ImSim.MultiBand.joint_linear module¶
-
class
lenstronomy.ImSim.MultiBand.joint_linear.
JointLinear
(multi_band_list, kwargs_model, compute_bool=None, likelihood_mask_list=None)[source]¶ Bases:
lenstronomy.ImSim.MultiBand.multi_linear.MultiLinear
class to model multiple exposures in the same band and makes a constraint fit to all bands simultaneously with joint constraints on the surface brightness of the model. This model setting require the same surface brightness models to be called in all available images/bands
-
data_response
¶ returns the 1d array of the data element that is fitted for (including masking)
Returns: 1d numpy array
-
error_response
(kwargs_lens, kwargs_ps, kwargs_special=None)[source]¶ returns the 1d array of the error estimate corresponding to the data response
Returns: 1d numpy array of response, 2d array of additonal errors (e.g. point source uncertainties)
-
image_linear_solve
(kwargs_lens=None, kwargs_source=None, kwargs_lens_light=None, kwargs_ps=None, kwargs_extinction=None, kwargs_special=None, inv_bool=False)[source]¶ computes the image (lens and source surface brightness with a given lens model). The linear parameters are computed with a weighted linear least square optimization (i.e. flux normalization of the brightness profiles)
Parameters: - kwargs_lens – list of keyword arguments corresponding to the superposition of different lens profiles
- kwargs_source – list of keyword arguments corresponding to the superposition of different source light profiles
- kwargs_lens_light – list of keyword arguments corresponding to different lens light surface brightness profiles
- kwargs_ps – keyword arguments corresponding to “other” parameters, such as external shear and point source image positions
- inv_bool – if True, invert the full linear solver Matrix Ax = y for the purpose of the covariance matrix.
Returns: 1d array of surface brightness pixels of the optimal solution of the linear parameters to match the data
-
likelihood_data_given_model
(kwargs_lens=None, kwargs_source=None, kwargs_lens_light=None, kwargs_ps=None, kwargs_extinction=None, kwargs_special=None, source_marg=False, linear_prior=None, check_positive_flux=False)[source]¶ computes the likelihood of the data given a model This is specified with the non-linear parameters and a linear inversion and prior marginalisation.
Parameters: - kwargs_lens –
- kwargs_source –
- kwargs_lens_light –
- kwargs_ps –
- check_positive_flux – bool, if True, checks whether the linear inversion resulted in non-negative flux components and applies a punishment in the likelihood if so.
Returns: log likelihood (natural logarithm) (sum of the log likelihoods of the individual images)
-
linear_response_matrix
(kwargs_lens=None, kwargs_source=None, kwargs_lens_light=None, kwargs_ps=None, kwargs_extinction=None, kwargs_special=None)[source]¶ computes the linear response matrix (m x n), with n being the data size and m being the coefficients
Parameters: - kwargs_lens –
- kwargs_source –
- kwargs_lens_light –
- kwargs_ps –
Returns:
-
lenstronomy.ImSim.MultiBand.multi_data_base module¶
-
class
lenstronomy.ImSim.MultiBand.multi_data_base.
MultiDataBase
(imageModel_list, compute_bool=None)[source]¶ Bases:
object
Base class with definitions that are shared among all variations of modelling multiple data sets
-
num_bands
¶
-
num_data_evaluate
¶
-
num_param_linear
(kwargs_lens, kwargs_source, kwargs_lens_light, kwargs_ps)[source]¶ Parameters: compute_bool – Returns: number of linear coefficients to be solved for in the linear inversion
-
num_response_list
¶ list of number of data elements that are used in the minimization
Returns: list of integers
-
lenstronomy.ImSim.MultiBand.multi_linear module¶
-
class
lenstronomy.ImSim.MultiBand.multi_linear.
MultiLinear
(multi_band_list, kwargs_model, likelihood_mask_list=None, compute_bool=None, kwargs_pixelbased=None)[source]¶ Bases:
lenstronomy.ImSim.MultiBand.multi_data_base.MultiDataBase
class to simulate/reconstruct images in multi-band option. This class calls functions of image_model.py with different bands with joint non-linear parameters and decoupled linear parameters.
the class supports keyword arguments ‘index_lens_model_list’, ‘index_source_light_model_list’, ‘index_lens_light_model_list’, ‘index_point_source_model_list’, ‘index_optical_depth_model_list’ in kwargs_model These arguments should be lists of length the number of imaging bands available and each entry in the list is a list of integers specifying the model components being evaluated for the specific band.
E.g. there are two bands and you want to different light profiles being modeled. - you define two different light profiles lens_light_model_list = [‘SERSIC’, ‘SERSIC’] - set index_lens_light_model_list = [[0], [1]] - (optional) for now all the parameters between the two light profiles are independent in the model. You have the possibility to join a subset of model parameters (e.g. joint centroid). See the Param() class for documentation.
-
image_linear_solve
(kwargs_lens=None, kwargs_source=None, kwargs_lens_light=None, kwargs_ps=None, kwargs_extinction=None, kwargs_special=None, inv_bool=False)[source]¶ computes the image (lens and source surface brightness with a given lens model). The linear parameters are computed with a weighted linear least square optimization (i.e. flux normalization of the brightness profiles)
Parameters: - kwargs_lens – list of keyword arguments corresponding to the superposition of different lens profiles
- kwargs_source – list of keyword arguments corresponding to the superposition of different source light profiles
- kwargs_lens_light – list of keyword arguments corresponding to different lens light surface brightness profiles
- kwargs_ps – keyword arguments corresponding to “other” parameters, such as external shear and point source image positions
- inv_bool – if True, invert the full linear solver Matrix Ax = y for the purpose of the covariance matrix.
Returns: 1d array of surface brightness pixels of the optimal solution of the linear parameters to match the data
-
likelihood_data_given_model
(kwargs_lens=None, kwargs_source=None, kwargs_lens_light=None, kwargs_ps=None, kwargs_extinction=None, kwargs_special=None, source_marg=False, linear_prior=None, check_positive_flux=False)[source]¶ computes the likelihood of the data given a model This is specified with the non-linear parameters and a linear inversion and prior marginalisation.
Parameters: - kwargs_lens –
- kwargs_source –
- kwargs_lens_light –
- kwargs_ps –
- check_positive_flux – bool, if True, checks whether the linear inversion resulted in non-negative flux components and applies a punishment in the likelihood if so.
Returns: log likelihood (natural logarithm) (sum of the log likelihoods of the individual images)
-
lenstronomy.ImSim.MultiBand.single_band_multi_model module¶
-
class
lenstronomy.ImSim.MultiBand.single_band_multi_model.
SingleBandMultiModel
(multi_band_list, kwargs_model, likelihood_mask_list=None, band_index=0, kwargs_pixelbased=None)[source]¶ Bases:
lenstronomy.ImSim.image_linear_solve.ImageLinearFit
class to simulate/reconstruct images in multi-band option. This class calls functions of image_model.py with different bands with decoupled linear parameters and the option to pass/select different light models for the different bands
the class supports keyword arguments ‘index_lens_model_list’, ‘index_source_light_model_list’, ‘index_lens_light_model_list’, ‘index_point_source_model_list’, ‘index_optical_depth_model_list’ in kwargs_model These arguments should be lists of length the number of imaging bands available and each entry in the list is a list of integers specifying the model components being evaluated for the specific band.
E.g. there are two bands and you want to different light profiles being modeled. - you define two different light profiles lens_light_model_list = [‘SERSIC’, ‘SERSIC’] - set index_lens_light_model_list = [[0], [1]] - (optional) for now all the parameters between the two light profiles are independent in the model. You have the possibility to join a subset of model parameters (e.g. joint centroid). See the Param() class for documentation.
-
error_map_source
(kwargs_source, x_grid, y_grid, cov_param, model_index_select=True)[source]¶ variance of the linear source reconstruction in the source plane coordinates, computed by the diagonal elements of the covariance matrix of the source reconstruction as a sum of the errors of the basis set.
Parameters: - kwargs_source – keyword arguments of source model
- x_grid – x-axis of positions to compute error map
- y_grid – y-axis of positions to compute error map
- cov_param – covariance matrix of liner inversion parameters
- model_index_select – boolean, if True, selects the model components of this band (default). If False, assumes input kwargs_source is already selected list.
Returns: diagonal covariance errors at the positions (x_grid, y_grid)
-
image_linear_solve
(kwargs_lens=None, kwargs_source=None, kwargs_lens_light=None, kwargs_ps=None, kwargs_extinction=None, kwargs_special=None, inv_bool=False)[source]¶ computes the image (lens and source surface brightness with a given lens model). The linear parameters are computed with a weighted linear least square optimization (i.e. flux normalization of the brightness profiles) :param kwargs_lens: list of keyword arguments corresponding to the superposition of different lens profiles :param kwargs_source: list of keyword arguments corresponding to the superposition of different source light profiles :param kwargs_lens_light: list of keyword arguments corresponding to different lens light surface brightness profiles :param kwargs_ps: keyword arguments corresponding to “other” parameters, such as external shear and point source image positions :param inv_bool: if True, invert the full linear solver Matrix Ax = y for the purpose of the covariance matrix. :return: 1d array of surface brightness pixels of the optimal solution of the linear parameters to match the data
-
likelihood_data_given_model
(kwargs_lens=None, kwargs_source=None, kwargs_lens_light=None, kwargs_ps=None, kwargs_extinction=None, kwargs_special=None, source_marg=False, linear_prior=None, check_positive_flux=False)[source]¶ computes the likelihood of the data given a model This is specified with the non-linear parameters and a linear inversion and prior marginalisation.
Parameters: - kwargs_lens –
- kwargs_source –
- kwargs_lens_light –
- kwargs_ps –
- check_positive_flux – bool, if True, checks whether the linear inversion resulted in non-negative flux components and applies a punishment in the likelihood if so.
Returns: log likelihood (natural logarithm) (sum of the log likelihoods of the individual images)
-
linear_response_matrix
(kwargs_lens=None, kwargs_source=None, kwargs_lens_light=None, kwargs_ps=None, kwargs_extinction=None, kwargs_special=None)[source]¶ computes the linear response matrix (m x n), with n beeing the data size and m being the coefficients
Parameters: - kwargs_lens –
- kwargs_source –
- kwargs_lens_light –
- kwargs_ps –
Returns:
-


--- layout: default title: Panobloc permalink: /panobloc/ image: panobloc-background.jpg --- {% include top-section.html %}
This year silver sponsor is Panobloc, a company located in Marbella which offers a panoramic design bloc. This layout is meant to be laid just below your keyboard, so it will not annoy you while writting code, designing or just using your computer. It also has a 5 mm points grid to facilitate the drawing of sketches.
They currently have an online shop where you can find all their products, see offers and find more informations about the characteristics of Panobloc.


|
shared_memory
|
All templated types in this namespaces are elementary types: int, double, float, char*, ... More...
Classes | |
| class | Allocation_exception |
| class | array |
| Implement a shared array stored on a shared memory segment. More... | |
| class | ConditionVariable |
| class | Exchange_manager_consumer |
| class | Exchange_manager_producer |
| class | Four_int_values |
| Example of an instance that can be serialized. More... | |
| class | Item |
| class | Lock |
| A scope lock object for locking a shared memory mutex, to use for example with a shared memory condition variable. More... | |
| class | LockedConditionVariable |
| The LockedConditionVariable class is here as a anonymous layer on top of the boost intersprocess condition variable labrary. More... | |
| class | Memory_overflow_exception |
| class | Mutex |
| class | Non_existing_segment_exception |
| class | Not_consumed_exception |
| class | SegmentInfo |
| encapsulate information related to a shared memory segment More... | |
| class | Serializable_exchange |
| class | Serializer |
| class | SharedMemorySegment |
| The SharedMemorySegment contains the pointers of the shared objects in on shared memrory segment. More... | |
| struct | ShmTypeHelper |
| ShmTypeHelper is a small struct that allow the definition of templated typedef. More... | |
| class | Unexpected_map_key |
| class | Unexpected_size_exception |
Typedefs | |
| typedef boost::interprocess::named_condition | SHMCondition |
| typedef boost::interprocess::scoped_lock< SHMMutex > | SHMScopeLock |
| typedef boost::interprocess::interprocess_mutex | UnamedSHMMutex |
| typedef boost::interprocess::interprocess_condition | UnamedSHMCondition |
| typedef boost::interprocess::scoped_lock< UnamedSHMMutex > | UnamedSHMLock |
| typedef boost::interprocess::named_mutex | SHMMutex |
| typedef cereal::access | private_serialization |
| typedef std::map< std::string, std::pair< void *, std::size_t > > | ShmObjects |
| ShmObjects typedef is a simple renaming that ease the for loop writting. | |
| typedef ShmTypeHelper< char >::ElemTypeAllocator | ShmCharAllocator |
| Create a char allocator to ease the creation of strings. | |
| typedef std::basic_string< char, std::char_traits< char >, ShmCharAllocator > | ShmString |
| Create a basic_string type for the Shared Memory. | |
| typedef std::map< std::string, std::unique_ptr< SharedMemorySegment > > | SegmentMap |
| SegmentMap typedef is a simple short cut to the GLOBAL_SHM_SEGMENTS type. | |
Functions | |
| void | clear_array (std::string segment_id) |
| wipe the shared memory segment created by an instance of shared_memory::array, including mutexes, if any. More... | |
| static uint | get_segment_size (size_t size_array, size_t size_item) |
| void | set_segment_sizes (uint multiplier_1025) |
| sets the size of the segments that will be newly created via the set methods. More... | |
| void | set_default_segment_sizes () |
| set the size of segment newly created to the default size value of 65536 | |
| SharedMemorySegment & | get_segment (const std::string &segment_id, const bool clear_upon_destruction=false, const bool create=true) |
| get_segment creates or give back a pointer to a SharedMemorySegment object. More... | |
| SegmentInfo | get_segment_info (const std::string &segment_id) |
| performs introspection on the segment and return related information. More... | |
| bool | segment_exists (const std::string &segment_id) |
| returns true if a segment exists under this id More... | |
| void | delete_segment (const std::string &segment_id) |
| delete_segment deletes the segment of existing shared memory. More... | |
| void | delete_all_segment () |
| delete_all_segment delete all mapping to the shared memory used during the current process | |
| template<typename ElemType > | |
| bool | delete_object (const std::string &segment_id, const std::string &object_id) |
| delete_object deletes a particular object in the shared memory segment More... | |
| boost::interprocess::interprocess_mutex & | get_segment_mutex (const std::string segment_id) |
| get_sgement_mutex aquiere a reference to the semgent global mutex. More... | |
| void | clear_shared_memory (const std::string &segment_id) |
| clear_shared_memory_segment destroys the shared memory More... | |
| template<typename ElemType > | |
| void | set (const std::string &segment_id, const std::string &object_id, const ElemType &set_) |
| set instanciates or get pointer to any elementary types in the shared memory. More... | |
| template<typename ElemType > | |
| void | set (const std::string &segment_id, const std::string &object_id, const ElemType *set_, const std::size_t size) |
| set instanciates or get pointer to a fixed sized array of the templated type "T" in the shared memory. More... | |
| void | set (const std::string &segment_id, const std::string &object_id, const std::string &set_) |
| set instanciates or get pointer to a string in the shared memory. More... | |
| template<typename ElemType > | |
| void | set (const std::string &segment_id, const std::string &object_id, const std::vector< ElemType > &set_) |
| set instanciates or get pointer to a std::vector<ElemType> in the shared memory. More... | |
| template<typename ElemType > | |
| void | set (const std::string &segment_id, const std::string &object_id, const Eigen::Matrix< ElemType, Eigen::Dynamic, 1 > &set_) |
| set instanciates or get pointer to a Eigen::Matrix<ElemType, Eigen::Dynamic, 1> in the shared memory. More... | |
| template<typename FirstType , typename SecondType > | |
| void | set (const std::string &segment_id, const std::string &object_id, const std::pair< FirstType, SecondType > &set_) |
| set instanciates or get pointer to a std::pair<FirstType, SecondType> in the shared memory. More... | |
| template<typename KeyType , typename ValueType > | |
| void | set (const std::string &segment_id, const std::string &object_id, const std::map< KeyType, ValueType > &set_) |
| set instanciates or get pointer to a std::vector<ElemType> or an Eigen::Matrix<ElemType, any, any> in the shared memory. More... | |
| template<typename ElemType > | |
| void | get (const std::string &segment_id, const std::string &object_id, ElemType &get_, bool create=true) |
| get gets a pointer to any elementary types in the shared memory. More... | |
| template<typename ElemType > | |
| void | get (const std::string &segment_id, const std::string &object_id, ElemType *get_, const std::size_t expected_size, bool create=true) |
| get gets a pointer to a fixed sized array of the templated type "T" in the shared memory. More... | |
| void | get (const std::string &segment_id, const std::string &object_id, std::string &get_, bool create=true) |
| get gets a pointer to a string in the shared memory. More... | |
| template<typename ElemType > | |
| void | get (const std::string &segment_id, const std::string &object_id, std::vector< ElemType > &get_, bool create=true) |
| get gets a pointer to a std::vector<ElemType> in the shared memory. More... | |
| template<typename ElemType > | |
| void | get (const std::string &segment_id, const std::string &object_id, Eigen::Matrix< ElemType, Eigen::Dynamic, 1 > &get_, bool create=true) |
| get gets a pointer to a Eigen::Matrix<ElemType, Eigen::Dynamic, 1> in the shared memory. More... | |
| template<typename FirstType , typename SecondType > | |
| void | get (const std::string &segment_id, const std::string &object_id, std::pair< FirstType, SecondType > &get_, bool create=true) |
| get instanciates or get pointer to a std::pair<FirstType, SecondType> in the shared memory. More... | |
| template<typename KeyType , typename ValueType > | |
| void | get (const std::string &segment_id, const std::string &object_id, std::map< KeyType, ValueType > &get_, bool create=true) |
| get gets a pointer to a std::vector<ElemType> or an Eigen::Matrix<ElemType, any, any> in the shared memory. More... | |
| template<class Serializable > | |
| void | serialize (const std::string &segment, const std::string &object, const Serializable &serializable) |
| Serialize the instance into a string which is written in the shared memory. More... | |
| template<class Serializable > | |
| void | deserialize (const std::string &segment, const std::string &object, Serializable &serializable) |
| Read from the memory a string that is deserialized into the passed instance of Serializable. More... | |
| void | set_verbose (bool mode) |
| if verbose mode set to true (starting default is false), informaton about newly created objects will be displayed in the terminal. More... | |
| bool | wait_for_segment (const std::string &segment_id, int timeout_ms=-1) |
| wait until the segment is created either via call to a get or set function. More... | |
| template<typename VectorType , typename ElemType > | |
| void | set (const std::string &segment_id, const std::string &object_id, const VectorType &set_) |
| static std::chrono::milliseconds | time_now () |
Variables | |
| bool | VERBOSE = false |
| static SegmentMap | GLOBAL_SHM_SEGMENTS |
| GLOBAL_SHARED_MEMORY_SEGMENT is global variable that acts as a a shared memory manager. More... | |
| static uint | SEGMENT_SIZE = DEFAULT_SHARED_MEMORY_SIZE |
| static std::mutex | SEGMENT_SIZE_MUTEX |
All templated types in this namespaces are elementary types: int, double, float, char*, ...
| void shared_memory::clear_array | ( | std::string | segment_id | ) |
wipe the shared memory segment created by an instance of shared_memory::array, including mutexes, if any.
If there are no memory segment of this id, there will be no effect. If shared_memory::array instances are pointing to the wiped out segment, their get and set functions may hang indefinitely.
| void shared_memory::clear_shared_memory | ( | const std::string & | segment_id | ) |
clear_shared_memory_segment destroys the shared memory
| [in] | segment_id | is the name of the shared memory segment. |
| bool shared_memory::delete_object | ( | const std::string & | segment_id, |
| const std::string & | object_id | ||
| ) |
delete_object deletes a particular object in the shared memory segment
| [in] | segment_id | is the name of the shared memory segment. |
| void shared_memory::delete_segment | ( | const std::string & | segment_id | ) |
delete_segment deletes the segment of existing shared memory.
it makes sure that all element created in it is destroyed first. (is this needed? I do not know.)
| segment_id | is the name of the shared memory segment. |
| void shared_memory::deserialize | ( | const std::string & | segment, |
| const std::string & | object, | ||
| Serializable & | serializable | ||
| ) |
Read from the memory a string that is deserialized into the passed instance of Serializable.
This assumes the serialization and writting in the shared memory has been performed using the serialize function.
| [in] | segment_id | is the name of the shared memory segment. |
| [in] | object_id | is the name of the shared memory object to set. |
| [in] | serializable | is the instance in which the string will be deserialized |
| void shared_memory::get | ( | const std::string & | segment_id, |
| const std::string & | object_id, | ||
| ElemType & | get_, | ||
| bool | create = true |
||
| ) |
get gets a pointer to any elementary types in the shared memory.
All set functions make sure that the pointer is uniquely created to avoid useless computation time consumption.
| [in] | segment_id | is the name of the shared memory segment. |
| [in] | object_id | is the name of the shared memory object to set. |
| [in] | get_ | is the string to be created in the shared memory |
| void shared_memory::get | ( | const std::string & | segment_id, |
| const std::string & | object_id, | ||
| ElemType * | get_, | ||
| const std::size_t | expected_size, | ||
| bool | create = true |
||
| ) |
get gets a pointer to a fixed sized array of the templated type "T" in the shared memory.
All set functions make sure that the pointer is uniquely created to avoid useless computation time consumption.
| [in] | segment_id | is the name of the shared memory segment. |
| [in] | object_id | is the name of the shared memory object to set. |
| [in] | get_ | is the pointer to the array of objects to set in the memory. |
| [in] | size | is the array size. |
| [in] | create | : if false, raise a Non_existing_segment_exception if the segment does not already exist |
| void shared_memory::get | ( | const std::string & | segment_id, |
| const std::string & | object_id, | ||
| std::string & | get_, | ||
| bool | create = true |
||
| ) |
get gets a pointer to a string in the shared memory.
All set functions make sure that the pointer is uniquely created to avoid useless computation time consumption.
| [in] | segment_id | is the name of the shared memory segment. |
| [in] | object_id | is the name of the shared memory object to set. |
| [in] | get_ | is the string to be created in the shared memory |
| [in] | create | : if false, raise a Non_existing_segment_exception if the segment does not already exist |
| void shared_memory::get | ( | const std::string & | segment_id, |
| const std::string & | object_id, | ||
| std::vector< ElemType > & | get_, | ||
| bool | create = true |
||
| ) |
get gets a pointer to a std::vector<ElemType> in the shared memory.
This will translated as a fixed sized array in the shared memory
All set functions make sure that the pointer is uniquely created to avoid useless computation time consumption.
| [in] | segment_id | is the name of the shared memory segment. |
| [in] | object_id | is the name of the shared memory object to set. |
| [in] | set_ | is the string to be created in the shared memory |
| [in] | create | : if false, raise a Non_existing_segment_exception if the segment does not already exist |
| void shared_memory::get | ( | const std::string & | segment_id, |
| const std::string & | object_id, | ||
| Eigen::Matrix< ElemType, Eigen::Dynamic, 1 > & | get_, | ||
| bool | create = true |
||
| ) |
get gets a pointer to a Eigen::Matrix<ElemType, Eigen::Dynamic, 1> in the shared memory.
This will translated as a fixed sized array in the shared memory
All set functions make sure that the pointer is uniquely created to avoid useless computation time consumption.
| [in] | segment_id | is the name of the shared memory segment. |
| [in] | object_id | is the name of the shared memory object to set. |
| [in] | set_ | is the string to be created in the shared memory |
| [in] | create | : if false, raise a Non_existing_segment_exception if the segment does not already exist |
| void shared_memory::get | ( | const std::string & | segment_id, |
| const std::string & | object_id, | ||
| std::pair< FirstType, SecondType > & | get_, | ||
| bool | create = true |
||
| ) |
get instanciates or get pointer to a std::pair<FirstType, SecondType> in the shared memory.
This is very usefull to dump maps in the shared memory
All set functions make sure that the pointer is uniquely created to avoid useless computation time consumption.
| [in] | segment_id | is the name of the shared memory segment. |
| [in] | object_id | is the name of the shared memory object to set. |
| [in] | get_ | is the string to be created in the shared memory |
| [in] | create | : if false, raise a Non_existing_segment_exception if the segment does not already exist |
| void shared_memory::get | ( | const std::string & | segment_id, |
| const std::string & | object_id, | ||
| std::map< KeyType, ValueType > & | get_, | ||
| bool | create = true |
||
| ) |
get gets a pointer to a std::vector<ElemType> or an Eigen::Matrix<ElemType, any, any> in the shared memory.
This will translated as a fixed sized array in the shared memory
All set functions make sure that the pointer is uniquely created to avoid useless computation time consumption.
| [in] | segment_id | is the name of the shared memory segment. |
| [in] | object_id | is the name of the shared memory object to set. |
| [in] | get_ | is the string to be created in the shared memory |
| [in] | create | : if false, raise a Non_existing_segment_exception if the segment does not already exist |
| SharedMemorySegment & shared_memory::get_segment | ( | const std::string & | segment_id, |
| const bool | clear_upon_destruction = false , |
||
| const bool | create = true |
||
| ) |
get_segment creates or give back a pointer to a SharedMemorySegment object.
| segment_id | is the name of the shared memory segment. |
| SegmentInfo shared_memory::get_segment_info | ( | const std::string & | segment_id | ) |
performs introspection on the segment and return related information.
If the segment does not exists, creates it first.
| boost::interprocess::interprocess_mutex & shared_memory::get_segment_mutex | ( | const std::string | segment_id | ) |
get_sgement_mutex aquiere a reference to the semgent global mutex.
| [in] | segment_id | is the name of the shared memory segment. |
| bool shared_memory::segment_exists | ( | const std::string & | segment_id | ) |
returns true if a segment exists under this id
| segment_id | is the name of the shared memory segment. |
| void shared_memory::serialize | ( | const std::string & | segment, |
| const std::string & | object, | ||
| const Serializable & | serializable | ||
| ) |
Serialize the instance into a string which is written in the shared memory.
This uses cereal for serialization, and Serializable must implement a serialize function, see: https://uscilab.github.io/cereal/
| [in] | segment_id | is the name of the shared memory segment. |
| [in] | object_id | is the name of the shared memory object to set. |
| [in] | serializable | is the instance to serialize |
| void shared_memory::set | ( | const std::string & | segment_id, |
| const std::string & | object_id, | ||
| const ElemType & | set_ | ||
| ) |
set instanciates or get pointer to any elementary types in the shared memory.
All set functions make sure that the pointer is uniquely created to avoid useless computation time consumption.
| [in] | segment_id | is the name of the shared memory segment. |
| [in] | object_id | is the name of the shared memory object to set. |
| [in] | set_ | is the string to be created in the shared memory |
| void shared_memory::set | ( | const std::string & | segment_id, |
| const std::string & | object_id, | ||
| const ElemType * | set_, | ||
| const std::size_t | size | ||
| ) |
set instanciates or get pointer to a fixed sized array of the templated type "T" in the shared memory.
All set functions make sure that the pointer is uniquely created to avoid useless computation time consumption.
| [in] | segment_id | is the name of the shared memory segment. |
| [in] | object_id | is the name of the shared memory object to set. |
| [in] | set_ | is the pointer to the array of objects to set in the memory. |
| [in] | size | is the array size. |
| void shared_memory::set | ( | const std::string & | segment_id, |
| const std::string & | object_id, | ||
| const std::string & | set_ | ||
| ) |
set instanciates or get pointer to a string in the shared memory.
All set functions make sure that the pointer is uniquely created to avoid useless computation time consumption.
| [in] | segment_id | is the name of the shared memory segment. |
| [in] | object_id | is the name of the shared memory object to set. |
| [in] | set_ | is the string to be created in the shared memory |
| void shared_memory::set | ( | const std::string & | segment_id, |
| const std::string & | object_id, | ||
| const std::vector< ElemType > & | set_ | ||
| ) |
set instanciates or get pointer to a std::vector<ElemType> in the shared memory.
This will translated as a fixed sized array in the shared memory
All set functions make sure that the pointer is uniquely created to avoid useless computation time consumption.
| [in] | segment_id | is the name of the shared memory segment. |
| [in] | object_id | is the name of the shared memory object to set. |
| [in] | set_ | is the string to be created in the shared memory |
| void shared_memory::set | ( | const std::string & | segment_id, |
| const std::string & | object_id, | ||
| const Eigen::Matrix< ElemType, Eigen::Dynamic, 1 > & | set_ | ||
| ) |
set instanciates or get pointer to a Eigen::Matrix<ElemType, Eigen::Dynamic, 1> in the shared memory.
This will translated as a fixed sized array in the shared memory
All set functions make sure that the pointer is uniquely created to avoid useless computation time consumption.
| [in] | segment_id | is the name of the shared memory segment. |
| [in] | object_id | is the name of the shared memory object to set. |
| [in] | set_ | is the string to be created in the shared memory |
| void shared_memory::set | ( | const std::string & | segment_id, |
| const std::string & | object_id, | ||
| const std::pair< FirstType, SecondType > & | set_ | ||
| ) |
set instanciates or get pointer to a std::pair<FirstType, SecondType> in the shared memory.
This is very usefull to dump maps in the shared memory
All set functions make sure that the pointer is uniquely created to avoid useless computation time consumption.
| [in] | segment_id | is the name of the shared memory segment. |
| [in] | object_id | is the name of the shared memory object to set. |
| [in] | set_ | is the string to be created in the shared memory |
| void shared_memory::set | ( | const std::string & | segment_id, |
| const std::string & | object_id, | ||
| const std::map< KeyType, ValueType > & | set_ | ||
| ) |
set instanciates or get pointer to a std::vector<ElemType> or an Eigen::Matrix<ElemType, any, any> in the shared memory.
This will translated as a fixed sized array in the shared memory
All set functions make sure that the pointer is uniquely created to avoid useless computation time consumption.
| [in] | segment_id | is the name of the shared memory segment. |
| [in] | object_id | is the name of the shared memory object to set. |
| [in] | set_ | is the string to be created in the shared memory |
| void shared_memory::set_segment_sizes | ( | uint | multiplier_1025 | ) |
sets the size of the segments that will be newly created via the set methods.
Until this function is called, segments are created with a size of 65536 bytes. This function is not interprocess : it will set the size of segments created in the current process
| multiplier_1025 | the size of create segment will be multiplier_1025 * 1025 bytes (because memory segment sizes have to be a multiple of 1025) |
| void shared_memory::set_verbose | ( | bool | mode | ) |
if verbose mode set to true (starting default is false), informaton about newly created objects will be displayed in the terminal.
Call to this function will change the verbose mode only for the current process.
| bool shared_memory::wait_for_segment | ( | const std::string & | segment_id, |
| int | timeout_ms = -1 |
||
| ) |
wait until the segment is created either via call to a get or set function.
| [in] | segment_id | is the name of the shared memory segment. |
| [in] | timeout_ms | is a timeout in ms |
|
static |
GLOBAL_SHARED_MEMORY_SEGMENT is global variable that acts as a a shared memory manager.
The use of the std::unique_ptr allows to delete the object and re-create at will.


The rapid development of NGS technologies enables the investigation of the transcriptome of thousands of cells in a single experiment. scRNA-seq allows to identify rare cell types and populations, to uncover gene regulatory networks, and to track the trajectories of distinct cell lineages in development. The extension i2dash.scrnaseq enables an enhanced user interactivity and contains simple but effective tools for the creation of an i2dashboard with focus on scRNA-seq data visualization and exploration. Read further information of the core i2dash package here.
The ability of i2dash to generate R Markdown code can be extended with additional packages. The figure below demonstrates the concept of extensibility. In order to develop a component or a page with a pre-defined layout and specific composition of components as an extension, the developer needs to provide a method and an R Markdown template. The method takes the i2dashboard object and the data relevant for the component. It validates and stores the data in a suitable data structure in a file (e.g. RDS file). Furthermore the method generates an R Markdown string based on a template for the component or page and extends the i2dashboard object. This package follows the concept of extensibility described in this i2dash vignette.
# if i2dash is not installed: install.packages("i2dash") install.packages("devtools") devtools::install_github("loosolab/i2dash.scrnaseq", dependencies=c("Depends", "Imports", "LinkingTo"))
Based on three common use-cases for single-cell data analysis you can explore the possibilities and features of the i2dash.scrnaseq extension. Note: The use-cases show an increasing degree of difficulty and complexity.
This use-case shows how to build a SingleCellExperiment object from a count-matrix, calculate quality metrics and create a simple dashboard to visualize different quality aspects of an scRNA-seq dataset. Demo
The second use-case demonstrates how to build a dashboard, which enables the exploration of gene expression values and metadata coupled with reduced dimension plots. Mainly native tools and pre-defined pages from the i2dash.scrnaseq package are used. Demo
Visual parameter selection for experts
The third use-case provides tools of i2dash.scrnaseq, which are useful during the process of data analysis but are not reasonable for the final report. The pre-defined pages enable the selection of features, the inspection of the normalisazion and the selection of optimal paramters for a dimensionality reduction. Demo
Documentation This page gives you an overview over all features containing in the i2dash.scrnaseq package.
Developer guide This tutorial explains how to build a customized componentor a pre-defined page from scratch and how to link the components of your page together.
If you use i2dash or i2dash.scrnaseq in your work, please cite:
Ustjanzew A., Preussner J., Bentsen M., Kuenne C., and Looso M. i2dash: creation of flexible, interactive and web-based dashboards for visualization of omics-pipeline results. tba (2020)
| Visualization | Data manipulation | Further |
|---|---|---|
| ComplexHeatmap | stringi | i2dash |
| plotly | methods | magrittr |
| ggplot2 | rlist | assertive.sets |
| shiny | data.table | assertive.types |
| shinyWidgets | tidyr | assertive.properties |
| ComplexHeatmap | dplyr | htmltools |
| knitr | tibble | |
| multipanelfigure | scran | |
| DT | scater | |
| kableExtra | SingleCellExperiment |


{% extends "global/Page.html" %} {% load otree %} {% block title %} Thank you {% endblock %} {% block content %}
Please remain seated until your number is called. Then take your number card, and proceed to the cashier.


my passion about coding started when I was around twelve years old
After I got completely intrested
i decided to watch some YouTube tutorials so that I can learn how to code perfectly. Unfortunately i was overwhellmed by the volumes of information.
So i heard of Moringa School which was doing coding and it was a very short so in decided to join Moringa and learn how to code
I also developed a hobby about photography
here are some if the images
Though I have not yet started professionally i will start so soon.


|
keigeki
1.0.0
傾撃
|
Files | |
| file | base64.c |
| file | base64.h [code] |
| file | CCArray.h [code] |
| file | CCArray.m |
| file | ccCArray.h [code] |
| file | ccCArray.m |
| file | CCFileUtils.h [code] |
| file | CCFileUtils.m |
| file | CCProfiling.h [code] |
| file | CCProfiling.m |
| file | ccUtils.c |
| file | ccUtils.h [code] |
| file | CCVertex.h [code] |
| file | CCVertex.m |
| file | CGPointExtension.h [code] |
| file | CGPointExtension.m |
| file | NSThread+performBlock.h [code] |
| file | NSThread+performBlock.m |
| file | OpenGL_Internal.h [code] |
| file | TGAlib.h [code] |
| file | TGAlib.m |
| file | TransformUtils.h [code] |
| file | TransformUtils.m |
| file | uthash.h [code] |
| file | utlist.h [code] |
| file | ZipUtils.h [code] |
| file | ZipUtils.m |


--- layout: default feijoa: true title: B A short dictionary of dimension-based GIS terms | Thesis file: thesis/dictionary.html lang: en mathjax: true locale_es: /en/thesis/resumen.html ---
ambient space the space in which objects are embedded.
area 1. measure of the 2D extent of an object; 2. 2D combinatorial element; 3. 2D geometric object.
ball 1. (\(\rightarrow\) same as 3-ball) topological definition of the space within a 2-sphere (i.e. a sphere), often defined as the space within a certain distance (the radius) from a point in \(\mathbb{R}^3\) (the centre); 2. (\(\rightarrow\) often \(n\)-ball) topological definition of the space within an \((n-1)\)-sphere, often defined as the space within a certain distance (the radius) from a point in \(\mathbb{R}^n\) (the centre); 3. geometric definition of a perfectly round filled 3D object.
body \(n\)-dimensional combinatorial element in an \(n\)D context.
box 1. cuboid; 2. orthotope of any dimension.
cavity 3D hole.
cell 1. (\(\rightarrow\) sometimes \(n\)-cell) \(n\)D combinatorial element; 2. 3D combinatorial element.
cell complex topological space formed by a set of cells glued along common faces, all faces of a cell in the complex should be in the complex.
circle 1. topological definition of the space at a certain distance (the radius) from a point in \(\mathbb{R}^2\) (the centre); 2. geometric definition of a perfectly round hollow 2D object.
closed 1. topological definition of an object that includes its boundary; 2. geometric definition of an object in \(n\)D, usually defined using boundary representation, that encloses an \(n\)D subspace.
congruent having the same shape and size.
cube 1. (\(\rightarrow\) same as \(3\)-cube) 3D polyhedron with 6 square facets; 2. (\(\rightarrow\) usually \(n\)-cube) \(n\)-orthotope with identical \((n-1)\)-cube facets, akin to a square in 2D and a cube in 3D.
cuboid 1. box-shaped 3D polyhedron with 6 rectangular facets, its opposite facets are congruent and parallel; 2. parallelotope.
curve 1. 1D geometric object, often with a non-linear geometry; 2. 1D combinatorial element; 3. 1-manifold.
cut-line degenerate part of a 2D shape forming a curve and protruding inwards from its boundary.
disk topological definition of the space within a circle, often defined as the space within a certain distance (the radius) from a point in \(\mathbb{R}^2\) (the centre).
edge 1D combinatorial element.
face 1. 2D combinatorial element; 2. (\(\rightarrow\) sometimes \(n\)-face of \(X\)) \(n\)D combinatorial element on the boundary of \(X\); 3. (\(\rightarrow\) usually face of \(X\)) \((n-1)\)D combinatorial element on the boundary of an \(n\)D combinatorial element \(X\).
facet 1. \((n-1)\)D combinatorial element in an \(n\)D context; 2. (\(\rightarrow\) often facet of \(X\)) \((n-1)\)D combinatorial element on the boundary of an \(n\)D combinatorial element \(X\); 3. 2D combinatorial element.
flat unbounded geometric object with linear geometry of any dimension, such as a point, line or plane.
hole 1. 2D void region; 2. \(n\)D void region.
hyperball higher-dimensional ball.
hypercell 1. higher-dimensional combinatorial element; 2. 4D combinatorial element.
hypercube 1. higher-dimensional cube; 2. 4-cube.
hyperplane 1. \((n-1)\)D linear subspace in an \(n\)D context; 2. plane in a higher-dimensional context.
hyperrectangle higher-dimensional orthotope.
hypersphere higher-dimensional sphere.
hypersurface \((n-1)\)D subspace in an \(n\)D context, often curved;
interval topological definition of the space between two points in \(\mathbb{R}\) (the endpoints).
Lebesgue measure measure of the \(n\)D extent of an object, akin to length in 1D, area in 2D and volume in 3D.
length measure of the 1D extent of an object.
line segment 1D geometric object.
manifold (\(\rightarrow\) sometimes \(n\)-manifold) topological space that resembles \(\mathbb{R}^n\) at every point.
manifold with boundary (\(\rightarrow\) sometimes \(n\)-manifold with boundary) topological space that resembles \(\mathbb{R}^n\) at every point in its interior.
node 0D combinatorial element.
open 1. topological definition of an object that does not include its boundary; 2. geometric definition of an object in \(n\)D, usually defined using boundary representation, that does not enclose any \(n\)D subspace.
orthotope (\(\rightarrow\) sometimes \(n\)-orthotope) \(n\)-polytope with congruent parallel facets forming right angles to each other, akin to a rectangle in 2D and a cuboid in 3D.
parallelepiped 3D polyhedron bounded by 6 parallelogram-shaped 2D faces.
parallelogram polygon bounded by 4 parallel and have the same shape.
parallelotope a polytope whose opposite facets are parallel and have the same shape, akin to a parallelogram in 2D and a parallelepiped in 3D.
peak 1. \((n-3)\)D combinatorial element in an \(n\)D context; 2. (\(\rightarrow\) peak of \(X\)) \((n-3)\)D combinatorial element on the boundary of an \(n\)D combinatorial element \(X\);
plane 2D unbounded linear subspace.
point 1. 0D geometric element; 2. topological definition of the space at one location.
polychoron 4D geometric object with linear geometry.
polygon 2D geometric object with linear geometry, possibly with holes.
polygonal curve curve formed by a sequence of line segments joined at their endpoints.
polyhedron 1. 3D geometric object with linear geometry, possibly with holes; 2. an \(n\)D geometric object with linear geometry.
polyline curve formed by a sequence of line segments joined at their endpoints.
polyteron 5D geometric object with linear geometry.
polytope \(n\)D geometric object with linear geometry.
puncture 0D (point) hole, often formed from a degenerate polyline or polygon.
ridge 1. \((n-2)\)D combinatorial element in an \(n\)D context; 2. (\(\rightarrow\) ridge of \(X\)) \((n-2)\)D combinatorial element on the boundary of an \(n\)D combinatorial element \(X\).
line string curve formed by joining a sequence of vertices by straight line segments, represented by these vertices.
linear ring 2D geometric object with linear geometry represented as a sequence of vertices.
ring 2D combinatorial element represented by its 1D boundary.
subfacet 1. \((n-2)\)D combinatorial element in an \(n\)D context; 2. (\(\rightarrow\) subfacet of \(X\)) \((n-2)\)D combinatorial element on the boundary of an \(n\)D combinatorial element \(X\).
shell 3D geometric object with linear geometry without 3D holes, usually defined as the volume enclosed by its 2D boundary, often represented as a set of 2D faces.
simplex 1. (\(\rightarrow\) sometimes \(n\)-simplex) combinatorial element with \(n+1\) vertices and \(n+1\) facets; 2. (\(\rightarrow\) sometimes \(n\)-simplex) geometric object based on \(n+1\) affinely independent vertices, akin to a point in 0D, a line segment in 1D, a triangle in 2D, or a tetrahedron in 3D.
simplicial complex 1. (\(\rightarrow\) sometimes abstract simplicial complex) topological space formed by a set of simplices glued along common faces, all faces of a simplex in the complex should be in the complex; 2. (\(\rightarrow\) sometimes geometric simplicial complex) abstract simplicial complex where simplices are embedded into Euclidean space, their interiors should not intersect geometrically.
solid 1. 3D geometric object with linear geometry, possibly with 3D holes, often represented as a set of shells; 2. object defined based on solid modelling, often as opposed one based on boundary representation; 3. an object containing its interior (as opposed to hollow).
spike degenerate part of a 2D shape forming a curve, often protruding outwards from its boundary.
sphere 1. (\(\rightarrow\) same as \(2\)-sphere) topological definition of the space at a certain distance (the radius) from a point in \(\mathbb{R}^3\) (the centre); 2. (\(\rightarrow\) often \(n\)-sphere) topological definition of the space at a certain distance (the radius) from a point in \(\mathbb{R}^{n+1}\) (the centre); 3. geometric definition of a perfectly round hollow 3D object.
surface 1. 2-manifold; 2. 2D combinatorial element.
tesseract 4-cube: polychoron with 8 cubical facets.
vertex 0D combinatorial element.
volume 1. measure of the 3D extent of an object; 2. 3D combinatorial element.
wire 2D combinatorial element represented by its 1D boundary.


See: Description
| Class | Description |
|---|---|
| BatchEtlExecutorBean |
Batched implementation to run
ETL executors for Spring IoC container. |
| Driver |
Scriptella driver for The Spring Framework
Bean Factory(or Application Context) registered datasources.
|
| EtlExecutorBean |
Implementation of
EtlExecutor for Spring IoC container. |
| Exception | Description |
|---|---|
| SpringProviderException |
Thrown to indicate Spring provider failure.
|
This driver allows working in The Spring Framework environment and provides an ability to locate Spring-managed data sources.
This driver acts as a proxy and relies on JDBC Bridge.
Important:
The driver requires EtlExecutorBean to operate, see examples below.| Driver class: | scriptella.driver.spring.Driver |
| URL: | Name of the DataSource bean specified in the bean factory/application context |
| Runtime dependencies: | Spring Framework |
| Name | Description | Required |
|---|
Spring Application Context
Spring application context declares a datasource and an executor. Additional properties and dependencies like progress indicator may also be injected.
<beans>
<bean id="datasource" class="org.springframework.jdbc.datasource.DriverManagerDataSource">
<property name="driverClassName"><value>org.hsqldb.jdbcDriver</value></property>
<property name="url"><value>jdbc:hsqldb:mem:spring</value></property>
<property name="username"><value>sa</value></property>
<property name="password"><value></value></property>
</bean>
<bean id="progress" class="scriptella.interactive.ConsoleProgressIndicator"/>
<bean id="executor" class="scriptella.driver.spring.EtlExecutorBean">
<property name="configLocation"><value>etl.xml</value></property>
<property name="progressIndicator"><ref local="progress"/></property>
<property name="properties"><map>
<entry key="tableName"><value>Spring_Table</value></entry>
</map>
</property>
</bean>
</beans>
ETL file etl.xml
<etl>
<connection driver="spring" url="datasource"/>
<script>
CREATE TABLE ${tableName} (
ID INT
)
</script>
</etl>
The usage of executor
is straightforward:
EtlExecutor exec = (EtlExecutor) beanFactory.getBean("executor");
exec.execute();
Additionally you can use java.util.concurrent.Callable
or java.lang.Runnable
invocation interface to avoid unnecessary dependency on Scriptella in application code:
Callable exec = (Callable) beanFactory.getBean("executor");
exec.call();
BatchEtlExecutorBean
provides an API
to execute ETL files in a batch.Copyright © Copyright 2006-2019 The Scriptella Project Team.


This is not a fully-featured operating system. It's just a quick fun thing based on what I have done already.
This window also show scrolling which is fun I guess.
This is not a fully-featured operating system. It's just a quick fun thing based on what I have done already.
This window also show scrolling which is fun I guess.


Before You Throw Those Items Away, Think About How They Can Be REUSED.
By Reducing or Eliminating The Generation of Harmful And Persistent Wastes, Waste Minimisation Supports Efforts To Promote a More Sustainable Society.
When You Put The Whole Picture Together, Recycling is The Right Thing To Do.
Freshly Herbs, Fruits, or Vegetables YOU DECIDE!.
Login As Vendor To Find Where You Can Get Our Products!
You Can Customized Our Product To Fit You!


GLAM combines the power of WebGL with a set of easy-to-use markup tags and style properties. With GLAM, 3D authoring is like any other web authoring. To make 3D, you create elements, set their attributes, add event listeners, and define styles. Just like DOM used to make! Content is easy to animate: keyframes and tweens can be defined in a compact set of markup tags, or as standard CSS3 animations or transitions.
GLAM is also fully extensible: to add custom behavior, write JavaScript event handlers. If you want fancy shading written in GLSL, simply specify your vertex and fragment shaders as properties of the object's style. GLAM renders with WebGL, using Three.js, and adds behaviors, interaction and lots of easy-to-use features on top. But most importantly, GLAM defines a markup language and set of stylesheet extensions that make 3D programming a snap.
Take a look at the code in the Github repo, and if you'd like to help out, check out issues page, fork the repo and let's get to work!


This plugin has not been released yet. Hopefully released by the end of 2013.
Plugin Information |
|---|
No information for the plugin 'job-run-uuid-plugin' is available. It may have been removed from distribution. |
This plugin allows for tracking multiple executions of a job remotely.
Introduction
This plugin has been created to allow you to handle large numbers of multiple executions of a job more easily.
Each build is tagged with a UUID immediately on creation - allowing you to identify a build even before it leaves the queue and is given a "Run Id".
You invoke the API as follows...
<jenkins>/job/<your-job>/buildId/execute
And it will respond with...
"attempts":0,"buildId":7,"building":true,"delay":0,"errorCode":0,"errorDesc":"OK","format":"json","responseCode":200,"uuid":"18712488-5a40-4ce7-bf6c-a05147a743ed"
You can then request the status of the job by calling...
<jenkins>/job/<your-job>/buildId/findBuild?uuid=18712488-5a40-4ce7-bf6c-a05147a743ed
It becomes very useful when you invoke jobs than there are executors as you can track an invocation even if it does not have a buildId yet. The response from /execute looks like this
Example
Say, for example, you wanted to send out a customised release note to each of your clients. You know which clients are particularly interested in a feature/bug fix as they mark it as "watched" in JIRA so you'd like to prepare a release note thanking them for their continued support and to list the bugs they are most concerned about at the top of the information you send out.
You have over 50 clients though - oh-no! - and your infrastructure can only take 6 executing jobs at once. This could take forever...
By utilising this plugin, you can kick off all 50 builds and then use the plugin to track them to completion.
<jenkins>/job/release-notes/buildId/execute?client_name=Barbara&client_company=Foobar
<jenkins>/job/release-notes/buildId/execute?client_name=Jeff&client_company=Snafulle
<jenkins>/job/release-notes/buildId/execute?client_name=Fred&client_company=Mixsticks
...


Data Scientist with a background in mathematics and 4+ of experience in analytical roles in the media & entertainment industry. Experience building data services in Python and working with SQL and Hadoop databases with over 100M users. My data projects includes the use of analytics, hypothesis testing, and machine learning to model human behavior.
I work on the team which specializes in getting to know our players as best as we can. We model user journey throughout our ecosystem and use segmentation techniques to build organic audiences of players to serve as marketing profiles. Some highlights of my work include:
Create educational content on the topic of data science and marketing analytics for a variety of clients. The content is primarily tailored for field newcomers and outsiders who want to learn more about data science.
Completed five end-to-end projects in a rigorous, project-centered data science program, covering statistics, data acquisition, machine learning, visualization, and presentation. Projects can be found under the "Projects" section.
Capitalized on using analytics tools to interpret video data and identify key topics for content creation, resulting in an increase of viewership. Took ownership of video production end-to-end: script writing, footage capture, editing, post-production tasks.
Compiled and analyzed page view data from different communities to identify popular trends in pop culture and entertainment. Aggregated user feedback on site features and reported results to the product team. Defined KPIs for community growth and managed a group of volunteer contributors.


nips nips2011 nips2011-55 nips2011-55-reference knowledge-graph by maker-knowledge-mining
Source: pdf
Author: Daniel R. Sheldon, Thomas G. Dietterich
Abstract: There are many settings in which we wish to ﬁt a model of the behavior of individuals but where our data consist only of aggregate information (counts or low-dimensional contingency tables). This paper introduces Collective Graphical Models—a framework for modeling and probabilistic inference that operates directly on the sufﬁcient statistics of the individual model. We derive a highlyefﬁcient Gibbs sampling algorithm for sampling from the posterior distribution of the sufﬁcient statistics conditioned on noisy aggregate observations, prove its correctness, and demonstrate its effectiveness experimentally. 1
[1] D. Sheldon, M. A. S. Elmohamed, and D. Kozen. Collective inference on Markov models for modeling bird migration. In Advances in Neural Information Processing Systems (NIPS 2007), pages 1321–1328, Cambridge, MA, 2008. MIT Press.
[2] Daniel Sheldon. Manipulation of PageRank and Collective Hidden Markov Models. PhD thesis, Cornell University, 2009.
[3] L. Devroye. A simple generator for discrete log-concave distributions. Computing, 39(1): 87–91, 1987.
[4] A. Agresti. A survey of exact inference for contingency tables. Statistical Science, 7(1):131– 153, 1992.
[5] P. Diaconis and B. Sturmfels. Algebraic algorithms for sampling from conditional distributions. The Annals of statistics, 26(1):363–397, 1998. ISSN 0090-5364.
[6] A. Dobra. Markov bases for decomposable graphical models. Bernoulli, 9(6):1093–1108, 2003. ISSN 1350-7265.
[7] S.L. Lauritzen. Graphical models. Oxford University Press, USA, 1996.
[8] D. Poole. First-order probabilistic inference. In Proc. IJCAI, volume 18, pages 985–991, 2003.
[9] R. de Salvo Braz, E. Amir, and D. Roth. Lifted ﬁrst-order probabilistic inference. Introduction to Statistical Relational Learning, page 433, 2007.
[10] B. Milch, L.S. Zettlemoyer, K. Kersting, M. Haimes, and L.P. Kaelbling. Lifted probabilistic inference with counting formulas. Proc. 23rd AAAI, pages 1062–1068, 2008.
[11] P. Sen, A. Deshpande, and L. Getoor. Bisimulation-based approximate lifted inference. In Proceedings of the Twenty-Fifth Conference on Uncertainty in Artiﬁcial Intelligence, pages 496–505. AUAI Press, 2009.
[12] J. Kisynski and D. Poole. Lifted aggregation in directed ﬁrst-order probabilistic models. In Proc. IJCAI, volume 9, pages 1922–1929, 2009.
[13] Udi Apsel and Ronen Brafman. Extended lifted inference with joint formulas. In Proceedings of the Proceedings of the Twenty-Seventh Conference Annual Conference on Uncertainty in Artiﬁcial Intelligence (UAI-11), pages 11–18, Corvallis, Oregon, 2011. AUAI Press.
[14] R. Sundberg. Some results about decomposable (or Markov-type) models for multidimensional contingency tables: distribution of marginals and partitioning of tests. Scandinavian Journal of Statistics, 2(2):71–79, 1975.
[15] M.J. Wainwright and M.I. Jordan. Graphical models, exponential families, and variational inference. Foundations and Trends in Machine Learning, 1(1-2):1–305, 2008.
[16] P. Diaconis, S. Holmes, and R.M. Neal. Analysis of a nonreversible Markov chain sampler. The Annals of Applied Probability, 10(3):726–752, 2000.
[17] W.R. Gilks and P. Wild. Adaptive Rejection sampling for Gibbs Sampling. Journal of the Royal Statistical Society. Series C (Applied Statistics), 41(2):337–348, 1992. ISSN 0035-9254.
[18] K. Murphy. The Bayes net toolbox for MATLAB. Computing science and statistics, 33(2): 1024–1034, 2001. 9


You will have 100 seconds to complete this quiz. Every wrong answer will deduct 10 seconds from you time. Your remaining time is your score! Good luck!


Gaurav Hooda
Web Developer
I am a student of California State University East Bay pursuing Masters degree in Computer Science department and actively looking for Summer Internship 2017 in Web App Development.
A student having good knowledge of C, C++, Core Java, SQL Server, Oracle 10g, JavaScript, HTML5, CSS3, Bootstrap, and with a good understanding of OOP Concepts.


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Tags
Tags are major part of HTML. A tag directs the browser on how it should show the different content of a website.
Like Text formatting or showing images.
Tags have the general format of
<
TagLettersOrComand>
Content/Text<
/TagLettersOrComand>
There are two different syntax from the standard tags;
- Void
Void tags don't require a closing, example the break line tag
<br>
doesn't require:
</br>
Attributes
Attribute defines extra options for the tag or provide needed information.
Some attributes are Mandatory (required) & some are Optional.
<
Tag attribute="value">
Content
<
/Tag>
There are two types of tags
- Inline
- Block
Inline Tag Keeps the text on same line. It doesn't add extra white spaces.
It's best understood when compared with the Block type.
Block Tag It has the effect of surrounding the tagged text with invisible box
that has width and height. It separate the text from surrounding text by providing white space
through the borders of the invisible box.
Source: www.impressivewebs.com
Two famous tags, DIV and SPAN, are used as containers for other HTML elements.
They are used mostly with CSS.
DIV is a Block tag.
SPAN is an inline tag.
Trivia:
These are from personal experience and might be wrong.
- Many Inline Tags have corresponding Block Tags. Examples:
Span, Div
br, p
code, pre
-
If you forgot to close a formatting tag like b or em all the text after the starting tag will be formatted!
-
Inline! Block! Why we shall know the diffence between them .. as per my research they are very useful in styling with CSS
-
There is third secret type of tags that is usually sorted as inline (but not exactly inline); it is called Replaced Elements: img is one of them!
World Wide Web
The world Wide Web (www) is a collection of HyperText Markup Language pages (HTML) on millions of computers.
To connect to the net you need a browser (like Chrome or Firefox) which interpret and show HTML pages properly and formatted. The browser communicate with servers through out the world through Hypertext Transfer Protocol (HTTP); which is a simple protocol for HTML transfer. The servers deliver back to your browser the requested page and information.
Programmers 5 ways of thinking:
Procedural Thinking:
What are the procedures that need to be followed to achieve a certain task.
Like for hand to pick up a pencil and write with it, though it looks simple
it requires a lot of procedures: finding the pencil, coordinate the eye with
hands to get the pencil, holding the pencil with proper force, identifying
its shape (tip, end, length), rotating the pencil in a certain way, finding
papers, finding starting point of writing, applying proper pressure on
thetip … etc
Abstract Thinking:
To see similarities in things allowing some tools to be reused rather than
re-inventing the wheel. Abstract thinking is clear in websites designs
through CSS.
System thinking:
Is linking the ideas (like the procedures) in an organised way to know how
to go about it, where to start and what to do next… I feel it is like a project plan.
Machine Empathy:
To understand how the computer work. How the computer interpret the commands.
What is its capabilities language wise.
Debugging:
To have a systematic way to find mistakes and toggle bugs.
Usually it contains these steps:
- What is the symptoms of the mistake; the actions, messages, behavior it is creating.
- In what stage it happen (approximate location if possible).
- Putting theories about how this happen.
- Testing the theories.
- Fixing the mistake


Specific services in search and exploration, exploration, exploitation and closure of the mine
We carry out activities for the use of reserves with the mineralogical characterization of minerals and the evaluation of their metallurgical response
JaliscMinc provides your company with a comprehensive management of your resources, allowing you to focus all efforts on the exploitation of the mines and the activities derived from such exploitation.


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