Public Member Functions | |
| XmlWriter () | |
| constructor | |
| virtual | ~XmlWriter () |
| destructor | |
| void | clear () |
| clear; | |
| const XmlData * | getXmlData () const |
| get xml data | |
| virtual void | setEncoding (const std::string &encoding) |
| virtual void | changeTempo (double tempo) |
| change tempo | |
| virtual void | changeBeat (const Beat &beat) |
| change beat | |
| virtual void | changeDynamics (const Dynamics &dynamics) |
| change dynamics | |
| virtual void | changeKey (const Key &key) |
| change key | |
| virtual void | startCrescendo () |
| start crescendo | |
| virtual void | startDiminuendo () |
| start diminuendo | |
| virtual void | stopCrescendo () |
| stop crescendo | |
| virtual void | stopDiminuendo () |
| stop diminuendo | |
| virtual void | addNote (const Note ¬e) |
| add note | |
| bool | writeXml (WritableStrStream &stream) const |
| write xml to stream | |
| bool | writeXml (WritableStrStream &stream, const XmlData &origData_) |
| write xml to stream using original xml |
| void XmlWriter::clear | ( | ) |
clear;
clear
| void XmlWriter::setEncoding | ( | const std::string & | enc | ) | [virtual] |
set encoding
Implements sinsy::IScoreWritable.
| bool XmlWriter::writeXml | ( | WritableStrStream & | stream | ) | const |
write xml to stream
write xml to stream
| stream | output stream |
| bool XmlWriter::writeXml | ( | WritableStrStream & | stream, |
| const XmlData & | origData_ | ||
| ) |
write xml to stream using original xml
write xml to stream using original xml
| stream | output stream oroginal MusicXML |


@* * This template takes a single argument, a String containing a * message to display. *@ @(message: String, instances: List[Instance]) @* * Call the `main` template with two arguments. The first * argument is a `String` with the title of the page, the second * argument is an `Html` object containing the body of the page. *@ @main("ProdStock") { @* * Get an `Html` object by calling the built-in Play welcome * template and passing a `String` message. *@


--- layout: post date: 2011-08-27 15:06:00 +02:00 title: "Understanding and Optimizing 802.11n" ---
Lesetipp: Understanding and Optimizing 802.11n von Buffalo Technology.


Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more details on ...  Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more details on ... Read More


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Results of 2nd trial
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| HBASE-9607 |
Data loss after snapshot restore into cloned table |
Major |
snapshots |
Ted Yu |
Matteo Bertozzi |
| HBASE-9430 |
Memstore heapSize calculation - DEEP_OVERHEAD is incorrect |
Major |
. |
Anoop Sam John |
Anoop Sam John |
| HBASE-9649 |
HFilePrettyPrinter should not throw a NPE if FirstKey or LastKey is null. |
Major |
util |
Jean-Marc Spaggiari |
Jean-Marc Spaggiari |
| HBASE-9548 |
Cleanup SnapshotTestingUtils |
Trivial |
snapshots, test |
Matteo Bertozzi |
Matteo Bertozzi |
| HBASE-9504 |
Backport HBASE-1212 to 0.94 |
Major |
. |
Jean-Marc Spaggiari |
Jean-Marc Spaggiari |
| HBASE-8521 |
Cells cannot be overwritten with bulk loaded HFiles |
Major |
. |
Jonathan Natkins |
Jean-Marc Spaggiari |
| HBASE-9732 |
Static AtomicLong updated in StoreFileScanner every (re)seek |
Major |
. |
Lars Hofhansl |
Lars Hofhansl |
| HBASE-9731 |
updatesBlockedSeconds RegionServer metric should not be a histogram |
Major |
. |
Lars Hofhansl |
Lars Hofhansl |
| HBASE-9745 |
Append HBASE_CLASSPATH to end of Java classpath and use another env var for prefix |
Major |
scripts |
Aditya Kishore |
Aditya Kishore |
| HBASE-9751 |
Excessive readpoints checks in StoreFileScanner |
Major |
. |
Vladimir Rodionov |
Lars Hofhansl |
| HBASE-9753 |
Excessive readpoint checks in MemstoreScanner |
Major |
. |
Lars Hofhansl |
Ted Yu |
| HBASE-9789 |
Change logging for Coprocessor exec call to trace |
Major |
. |
Lars Hofhansl |
Lars Hofhansl |
| HBASE-9747 |
PrefixFilter with OR condition gives wrong results |
Major |
Filters |
Deepa Remesh |
Aditya Kishore |
| HBASE-9727 |
HBase Rest Server - DELETE scanner operation is a no-op |
Major |
REST |
Aditya Kishore |
Aditya Kishore |
| HBASE-9651 |
Backport HBASE-3890 'Scheduled tasks in distributed log splitting not in sync with ZK' to 0.94 |
Major |
. |
Ted Yu |
Ted Yu |
| HBASE-9783 |
o.a.h.h.r.HRegion.mutateRow() with non-existent CF cause NPE |
Minor |
regionserver |
Aditya Kishore |
Aditya Kishore |
| HBASE-9737 |
Corrupt HFile cause resource leak leading to Region Server OOM |
Critical |
HFile |
Aditya Kishore |
Aditya Kishore |
| HBASE-7600 |
TestAdmin.testCreateBadTables is failing occasionally |
Major |
. |
Lars Hofhansl |
Liu Shaohui |
| HBASE-9807 |
block encoder unnecessarily copies the key for each reseek |
Major |
. |
Lars Hofhansl |
Lars Hofhansl |
| HBASE-9847 |
HConnectionImplementation does not connect to new active master |
Major |
shell |
rajeshbabu |
Pankaj Kumar |
| HBASE-9842 |
Backport HBASE-9593 and HBASE-8667 to 0.94 |
Major |
. |
Lars Hofhansl |
rajeshbabu |


Coalescence is a choose-your-own-adventure style campout focused on celebrating nature through outdoor activities and fellowship.
Try something new or show off your skills by hiking, climbing, kayaking, mountain biking, swimming, or practicing yoga.
Over our three days together in the mountains, we can begin to reconnect with ourselves, each other, and with nature.
Join us as we decorate space and time through the intertwining of art, music and dance.
Leave your mark on the collaborative mural, then moonwalk over to the pavilion to boogie down with our live bands and DJs.
Stop by the swap meet and browse the wares of your fellow Coalescees on your way to the bonfire, where you can share your newest song or your passion for poetry at the drum circle talent show.

Like anything in life, Coalescence is what you make it.
We ask that every Coalescee contribute in some way – whether you’re leading an activity, picking up trash, helping coordinate a meal, organizing a gear exchange, or throwing a camp party, the true magic of Coalescence doesn’t happen without you!
As you prepare for the weekend, brainstorm how you can make the experience more special not only for yourself but for those you’ll be sharing it with.
Together, we coalesce.


Naveen Kumar
I'm a Full Stack Web Developer
About Me
I'm Naveen Kumar && Full Stack Web Developer!
Hi! my name is Naveen Kumar. I am a Full Stack Web Developer, and I'm good at java, servlets, REST API's, SPA's, Angular etc., Now a days iam working on developing open source projects, i would like to contribute more in future. I enjoy working with a team, and with good communication skills i can manage well.
Age : 21
Website : www.
Email : lakkaramnaveen4488
Degree : B-Tech
City : Hyderabad
Freelance : Available
Java
C
Python
Javascript
Html
Bootstrap
Education
2016 - 2020
B-Tech at BVRIT Narsapur
Graduated from Electronics and communication Engineering, Aggregate of 8.04 CGPA.
2014 - 2016
Inter
Narayana Junior College, MPC branch, Aggregate 9.6 CGPA.
2013 - 2014
10th
Vijay High School, Aggregate of 9.5 CGPA.
Experience
2020 -
Capgemini India
Currently working.


This simple Black Jack like game is intended as example for projects using SWI Prolog, its Pengines library and Tau-Prolog. Graphics is done with JS Processing variant p5js. This is no Casino game, there is nothing to win and no purpose. It's just a demo - for experimenting with. Soucecode is available at https://github.com/hnbeck/ecblackjack with no warranties. See license information at Github.
Click on the deck for drawing a card or click "Stand"-button to give the dealer the control. Do a page refresh for a new game.
Test / Debug area
The test below queries for a hard coded predicate .
Output for Tau Prolog queries. Output is done via callback of the pl.answer function of Tau Prolog.


For I/O there is a need to give the size, displacement, and offset
into a file. These quantities can easily be larger than 32 bits which
can be the default size of a Fortran integer. To overcome this, these
quantities are declared to be
INTEGER (KIND=MPI_OFFSET_KIND) in
Fortran.
In C one uses MPI_Offset whereas in C++ one uses
MPI::Offset.
These types must have the same width and encode
address values in the same manner such that offset values in one
language may be passed directly to another language without
conversion.
Up: Data Types
Next: Language Binding
Previous: Addresses
Return to MPI-2.2 Standard Index
Return to MPI Forum Home Page
(Unofficial) MPI-2.2 of September 4, 2009
HTML Generated on September 10, 2009


GitHub
Java API
Development Standards (Base Document)
Software Requirements Specification (Base Document)
Youtube
GitHub
Java API
Development Standards (Base Document)
Software Requirements Specification (Base Document)
Youtube


{% extends "layout.html" %} {% block content %}
Oakland's Elementary Schools are as diverse as it's students.
By choosing from the options presented you can explore the relative achievement levels for each demographic or combination of demographics.


Blog | Zach Snyder{% endblock %}
{% block precontent %}
Blog
About the Blog
This is a place where I occasionally post things. Sometimes
just random thoughts. Other times more organized ones. I
guess I would call it a general purpose blog. Please enjoy.


Pick compound ID field
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Phone: +49 7627 970068
E-mail<EMAIL_ADDRESS>Homepage:
www.iScienceSearch.com
Dr. Alexander Kos
Austr. 26
D-79585 Steinen, Germany
Open ChemRPS search page


Encpsulation is responsible for:
1. Grouping methodes and properties in object.
2. Controlling of access should be done by obejct itself.
3. Using methodes get and set in objects to control dara flow in it.
4. Hiding implementation by object and giving access for other object with interface - which is public.
Encapsulation - example
Math.floor(2.22); // We do not care about implementtion and we do not have the access for it. The inrerface for an object math in an object method - floor in that case.
Not hidden data (minimal encapsulation connected with datas without hinding them) - example
const user = { age: 20 // the value is not protected - can be changed } // We can change the value of object user.age - 21; // value change.


[gecode-users] Configure fails on Gentoo Linux
Mikael Zayenz Lagerkvist
zayenz at gmail.com
Tue Sep 16 10:27:52 CEST 2008
Hi,
The configure files uses the path to the javac compiler to find the
JNI include files. In most cases (i.e., no repackaging of the JDK is
done), if javac is in the directory /some/path/bin/javac, then the JNI
include files are available in /some/path/include/. The macro that
checks for this is in gecodej.m4, and is called AC_JNI_INCLUDE_DIR.
Also, which JDK-version are you using? We only test and support the
Sun JDK for use with Gecode/J. If you are using any other JDK, then it
might not work.
Cheers,
Mikael
On Tue, Sep 16, 2008 at 9:59 AM, Vasilij Savin
<Vasilij.Savin.8691 at student.uu.se> wrote:
> Hello Andrew,
>
> JDK is on PATH, because "shell> javac" works just fine. The problem is
> that configure script fails to read it properly.
>
> Once I changed the to JAVAC=javac, it passed the failing step, but
> then failed later - while looking for libs and extensions, because the
> context is different.
> (usr/bin instead of /path/to/JDK)
>
> I am trying to hardcode the pathes for them and see how it works.
>
> Regards,
> Vasilij Savin
>
>
>
> _______________________________________________
> Gecode users mailing list
> users at gecode.org
> https://www.gecode.org/mailman/listinfo/gecode-users
>
--
Mikael Zayenz Lagerkvist, http://www.ict.kth.se/~zayenz/
More information about the gecode-users
mailing list


Class BundleAdjustment
- java.lang.Object
-
- algorithms.imageProcessing.transform.BundleAdjustment
-
public class BundleAdjustment extends java.lang.Object
given intrinsic and extrinsic camera parameters, coordinates for points in a world reference frame, and observations of those points in one or more camera, return data structures needed by Levenberg-Marquardt algorithm in refinement of the intrinsic and extrinsic camera parameters. BundleAdjustment calculates partial derivatives of the parameters and calculates the re-projection error to form the parameter update steps, the gradient covector, and the evaluation of the objective (sum of squares of the re-projection error). From Triggs et al. 2000, "Bundle Adjustment - A Modern Synthesis" "Bundle adjustment is the problem of refining a visual reconstruction to produce jointly optimal 3D structure and viewing parameter (camera pose and/or calibration) estimates. Optimal means that the parameter estimates are found by minimizing some cost function that quantifies the model fitting error, and jointly that the solution is simultaneously optimal with respect to both structure and camera variations. The name refers to the ‘bundles’ of light rays leaving each 3D feature and converging on each camera centre, which are ‘adjusted’ optimally with respect to both feature and camera positions. Equivalently — unlike independent model methods, which merge partial reconstructions without up- dating their internal structure — all of the structure and camera parameters are adjusted together ‘in one bundle’." This version of Bundle-Adjustment uses Levenberg-Marquardt Algorithm (LMA) step in each iteration solved by dense Cholesky decomposition (LMA-CD). TODO: consider implementing or finding an implementation of Jakob Engel, Vladlen Koltun, and Daniel Cremers. "Direct sparse odometry". IEEE transactions on pattern analysis and machine intelligence, 40(3):611–625, 2018. TODO: find errors leading to such large parameter steps (dC and dP). TODO: add gauge fix. And related to that, consider adding constraints suggested in Seliski 2010: u_0 and v_0 are close to half the image lengths and widths, respectively. the angle between 2 image axes is close to 90. the focal lengths along both axes are greater than 0. TODO: consider implementing the "reduced structure system" for the cases where (9^3)*mImages > (3^3)*nFeatures, The "reduced camera system" is currently implemented.for a bigger picture summary, see Section "Objective functions for estimating epipolar geometry" on page 169 of MASKS (Ma, Soatto, Kosecká, and Sastry 2012, "An Invitation to 3-D Vision"). Also see Chap 5.2, pp 127-128 of MASKS for constrained optimization.
- Author:
- nichole
-
-
Nested Class Summary
Nested Classes Modifier and Type Class Description (package private) static class
BundleAdjustment.AuxiliaryArrays
-
Constructor Summary
Constructors Constructor Description BundleAdjustment()
-
Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description (package private) void
aIJBIJ(double[] xWI, double[] xWCI, double[][] intr, double k1, double k2, double[] rotAngles, double[][] rot, double[] trans, BundleAdjustment.AuxiliaryArrays aa, double[][] outAIJ, double[][] outBIJ)
NOTE: there may be a problem if using the homography matrix [r0 r1 t] to transform world scene to camera coordinates as the partial derivatives here are assuming the use of the 3nd column of rotation too, that is R * T.protected void
calculateLMVectorsSparsely(double[][] coordsI, double[][] coordsW, gnu.trove.map.TIntObjectMap<gnu.trove.set.TIntSet> imageFeaturesMap, algorithms.matrix.BlockMatrixIsometric intr, double[][] extrRotThetas, double[][] extrTrans, double[][] kRadials, boolean useR2R4, double[] outDP, double[] outDC, double[] outGradP, double[] outGradC, double[] outFSqSum, double lambda, double[] outInitLambda)
NOT YET TESTED.(package private) void
pdCIJXWIJ(double[] xWCI, double[][] out)
the partial derivative of the 2D coordinates of perspective projection of the i-th feature point normalized, w.r.t.(package private) void
pdCpIJCIJ(double[] xWCNI, double[][] intr, double k1, double k2, double[][] out)
the partial derivative of the final 2D re-projected coordinates of the i-th feature point w.r.t.(package private) void
pdCpIJYJ(double[] xWCNI, double[][] intr, double k1, double k2, double[][] out)
the partial derivative of the final 2D re-projected coordinates of the i-th feature point w.r.t.(package private) void
pdXWIJPhiJ(double[] xWI, double[] phi, double[][] out)
the partial derivative of the final 2D re-projected coordinates of the i-th feature point w.r.t.(package private) void
populateCameraProjectionHomography(double[][] rot, double[] translation, double[][] outH)
populate the homography matrix to transform world screen coordinates to projected 2D coordinates in the camera reference frame.(package private) void
populateCameraProjectionHomography(double[][] rot, double[] translation, double[] outH, boolean useLeftHanded)
populate the homography matrix to transform world screen coordinates to projected 2D coordinates in the camera reference frame.void
setUseHomography()
setting to use the homography matrix in the WCS projection to camera 2-D reference frame.void
solveSparsely(double[][] coordsI, double[][] coordsW, gnu.trove.map.TIntObjectMap<gnu.trove.set.TIntSet> imageFeaturesMap, algorithms.matrix.BlockMatrixIsometric intr, double[][] extrRotThetas, double[][] extrTrans, double[][] kRadials, int nMaxIter, boolean useR2R4)
given world scene features, the features observed in images, initial camera calibration and extrinsic parameters, use the iterative non-linear Levenberg-Marquardt (L-M) algorithm to minimize the re-projection error by refining the values of coordsW, intrinsic, and extrinsic camera parameters.
-
-
-
Method Detail
-
setUseHomography
public void setUseHomography()
setting to use the homography matrix in the WCS projection to camera 2-D reference frame. The homography matrix is the first 2 columns of the rotation matrix and the translation vector as the 3rd column in the homography. The default uses, instead, the full projection of Rotation * x_WCS + translation. Note that the partial derivatives calculated in making the Jacobian are derived from the full projection, not the homography, so there will be inconsistencies until that is fixed for the homography derivatives.
-
solveSparsely
public void solveSparsely(double[][] coordsI, double[][] coordsW, gnu.trove.map.TIntObjectMap<gnu.trove.set.TIntSet> imageFeaturesMap, algorithms.matrix.BlockMatrixIsometric intr, double[][] extrRotThetas, double[][] extrTrans, double[][] kRadials, int nMaxIter, boolean useR2R4) throws no.uib.cipr.matrix.NotConvergedException, java.io.IOException
given world scene features, the features observed in images, initial camera calibration and extrinsic parameters, use the iterative non-linear Levenberg-Marquardt (L-M) algorithm to minimize the re-projection error by refining the values of coordsW, intrinsic, and extrinsic camera parameters. The L-M is an iterative non-linear optimization to minimize the objective. For bundle adjustment, the objective is the re-projection error. L-M is guaranteed to converge to eventually find an improvement, because an update with a sufficiently small magnitude and a negative scalar product with the gradient is guaranteed to do so. This method exploits some of the properties of sparse matrices in the block structure of the Jacobian by using the Schur complement to form reduced camera matrices which can be solved by Cholesky factoring and forward and backward substitution (halving the computation time for the parameter vector). Regarding the bundle adjustment as refinement for extrinsic parameters:However, several researchers have noted (Fitzgibbon and Zisserman, 1998, Nistér, 2001, Pollefeys, 1999) that in the application of camera tracking, performing bundle adjustment each time a new frame has been added to the estimation can prevent the tracking process from failing over time. Thus, bundle adjustment can over time in a sequential estimation process have a much more dramatic impact than mere accuracy improvement, since it improves the initialization for future estimates, which can ultimately enable success in cases that would otherwise miserably fail.
References: http://users.ics.forth.gr/~lourakis/sba/PRCV_colloq.pdf lecture by Lourakis “Bundle adjustment gone public” Zhongnan Qu's master thesis, "Efficient Optimization for Robust Bundle Adjustment", 2018 Technical University of Munich Chen, Chen, & Wang 2019, "Bundle Adjustment Revisited" Engels, Stewenius, Nister 2006, “Bundle Adjustment Rules” Bill Triggs, Philip Mclauchlan, Richard Hartley, Andrew Fitzgibbon. Bundle Adjustment – A Modern Synthesis. International Workshop on Vision Algorithms, Sep 2000, Corfu, Greece. pp.298–372, 10.1007/3-540-44480-7_21 . inria-00548290 T. Barfoot, et al., "Pose estimation using linearized rotations and quaternion algebra", Acta Astronautica (2010), doi:10.1016/j.actaastro.2010.06.049 -- using the rotation and translation update details. -- one of the 2 examples is interesting for the problem of pose for a pair of stereo-images. it also uses cholesky factoring of block sparse matrix structure. Tomasi 2007,CPS 296.1 Supplementary Lectur Notes, Duke University graph partioning: https://cseweb.ucsd.edu/classes/fa04/cse252c/manmohan1.pdf recursive partitioning w/ elimination graph and vertex cut. Triggs et al. 2000, "Bundle Adjustment – A Modern Synthesis", Section 6 Skeletal graphs for efficient structure from motion N Snavely, SM Seitz, R Szeliski - 2008 Graph partitioning in this project: NormalizedCuts.java which uses the Fiedler vector of the Laplacian. UnweightedGraphCommunityFinder.java
- Parameters:
coordsI
- the features observed in different images (in coordinates of the image reference frame). The format of coordsI is 3 X (nFeatures*nImages). Each row should have nFeatures of one image, followed by nFeatures of the next image, etc. The first dimension is for the x,y, and z axes. Note that if a feature is not present in the image, that should be an entry in imageMissingFeatureMap.coordsW
- the features in a world coordinate system. The format is 3 X nFeatures. The first dimension is for the x,y, and z axes.imageFeaturesMap
- an associative array holding the features in each image. They key is the image number in coordsI which is j/nFeatures where j is the index of the 2nd dimension, that is coordsI[j]. The value is a set of feature numbers which are missing from the image. The feature numbers correspond to the 2nd dimension indexes in coordsW.intr
- the intrinsic camera parameter matrices stacked along rows to make a tall double array of size [(mImages*3) X 3] where each image block is size 3X3. Note that only the focus parameter is refined in this method.extrRotThetas
- the extrinsic camera parameter rotation euler angles stacked along the 3 columns, that is the size is [mImages X 3]. each image block is size 1X3.extrTrans
- the extrinsic camera parameter translation vectors stacked along the 3 columns, that is the size is [nImages X 3] where nImages is coordsI[0].length/coordsW[0].length. each array is size 1X3.kRadials
- a double array wherein each row holds the radial distortion coefficients k1 and k2 for an image. NOTE: current implementation accepts values of 0 for k1 and k2.useR2R4
- useR2R4 use radial distortion function from Ma et al. 2004 for model #4 in Table 2, f(r) = 1 +k1*r^2 + k2*r^4 if true, else use model #3 f(r) = 1 +k1*r + k2*r^2.nMaxIter
-- Throws:
no.uib.cipr.matrix.NotConvergedException
java.io.IOException
-
calculateLMVectorsSparsely
protected void calculateLMVectorsSparsely(double[][] coordsI, double[][] coordsW, gnu.trove.map.TIntObjectMap<gnu.trove.set.TIntSet> imageFeaturesMap, algorithms.matrix.BlockMatrixIsometric intr, double[][] extrRotThetas, double[][] extrTrans, double[][] kRadials, boolean useR2R4, double[] outDP, double[] outDC, double[] outGradP, double[] outGradC, double[] outFSqSum, double lambda, double[] outInitLambda) throws no.uib.cipr.matrix.NotConvergedException, java.io.IOException, NaNException
NOT YET TESTED. solve for bundle adjustment data structures needed by the Levenberg-Marquardt algorithm to refine the intrinsic and extrinsic camera parameters. The algorithms uses the sparse structure of the jacobian to reduce the computation time and memory needed. The code needs initial parameter estimates of intrinsic and extrinsic camera parameters (in intr, extrRot, kRadial, and extrTrans). The code returns results in outGradP, outGradC, outFSqSum, outDP, outDC for refined parameters and the gradient, objective and parameter update steps needed by code such as Levenberg-Marquardt. NOTE: the code does not update the intrinsic and extrinsic camera parameters, allowing the L-M algorithm to handle that. The runtime complexity is ~ O(nFeatures * mImages^2). Assumptions used in forming the partial derivatives of the intrinsic camera parameters are no skew, focal length along x is the same as focal length along y, square pixels. Cholesky decomposition is used with forward and back substitution to avoid inverting the reduced camera matrix and to half the runtime compared to L-U decomposition. Note that there can be more than one camera and should be 6 of more features per image (3 for rot, 3 for trans) and among those, need 3 per camera for the intrinsic parameters and 2 or more vantage points for the point parameters (no reference for these numbers, just a rough estimate from counting the number of unknowns). Also note that the code uses the Jacobian J = [J_P J_C] following Engels et al., which is reversed from the Lourakis Jacobian J = [J_c J_P]. Qu Jacobian (and hence reduced camera matrix are consistent with Lourakis. See details in doc/bundle_adjustment.pdfReferences: additional information is present in directory doc as "bundle_adjustment.pdf" and "Levenberg-Marquardt_notes.pdf" http://users.ics.forth.gr/~lourakis/sba/PRCV_colloq.pdf lecture by Lourakis “Bundle adjustment gone public” Engels, Stewenius, Nister 2006, “Bundle Adjustment Rules” Bill Triggs, Philip Mclauchlan, Richard Hartley, Andrew Fitzgibbon. Bundle Adjustment – A Modern Synthesis. International Workshop on Vision Algorithms, Sep 2000, Corfu, Greece. pp.298–372, 10.1007/3-540-44480-7_21 . inria-00548290 Zhongnan Qu's master thesis, "Efficient Optimization for Robust Bundle Adjustment", 2018 Technical University of Munich Chen, Chen, & Wang 2019, "Bundle Adjustment Revisited" T. Barfoot, et al., "Pose estimation using linearized rotations and quaternion algebra", Acta Astronautica (2010), doi:10.1016/j.actaastro.2010.06.049 -- using the rotation and translation update details. -- one of the 2 examples is interesting for the problem of pose for a pair of stereo-images. it also uses cholesky factoring of block sparse matrix structure.
- Parameters:
coordsI
- the features observed in different images (in coordinates of the image reference frame). The different images may or may not be from the same camera. The format of coordsI is 3 X (nFeatures*nImages). Each row should have nFeatures of one image, followed by nFeatures of the next image, etc. The first dimension is for the x,y, and z axes. Note that if a feature is not present in the image, that should be an entry in imageMissingFeatureMap.coordsW
- the features in a world coordinate system. The format is 3 X nFeatures. The first dimension is for the x,y, and z axes.imageFeaturesMap
- an associative array holding the features present in each image. They key is the image number in coordsI which is j/nFeatures where j is the index of the 2nd dimension, that is coordsI[j]. The value is a set of feature numbers which are missing from the image. The feature numbers correspond to the 2nd dimension indexes in coordsW.intr
- the intrinsic camera parameter matrices stacked along rows to make a tall double array of size [(mImages*3) X 3] where each block is size 3X3. Note that only the focus parameter is refined in this class.extrRotThetas
- the extrinsic camera parameter rotation euler angles stacked along the 3 columns, that is the size is nImages X 3 where nImages is coordsI[0].length/coordsW[0].length. each array is size 1X3.extrTrans
- the extrinsic camera parameter translation vectors stacked along the 3 columns, that is the size is nImages X 3 where nImages is coordsI[0].length/coordsW[0].length. each array is size 1X3.kRadials
- a double array wherein each row holds the radial distortion coefficients k1 and k2 for an image, so the total size is [nCameras X 2]. NOTE: current implementation accepts values of 0 for k1 and k2.useR2R4
- useR2R4 use radial distortion function from Ma et al. 2004 for model #4 in Table 2, f(r) = 1 +k1*r^2 + k2*r^4 if true, else use model #3 f(r) = 1 +k1*r + k2*r^2.outDP
- an output array holding the update values for the point parameters. The length should be 3*nFeatures.outDC
- an output array holding the update values for the camera parameters. The length should be 9*mImages.outGradP
- an output array holding the gradient covector for point parameters (-J_P^T*(x-x_hat) as the summation of bij^T*fij). The length should be 3 * number of features. This is used by the L-M algorithm to calculate the gain ratio and evaluate stopping criteria.outGradC
- an output array holding the gradient covector for camera parameters (-J_C^T*(x-x_hat) as the summation of aij^T*fij). The length should be 9 times the number of images. This is used by the L-M algorithm to calculate the gain ratio and evaluate stopping criteria.outFSqSum
- an output array holding the evaluation of the objective, that is the sum of squares of the observed feature - projected feature. It's the re-projection error. NOTE that this evaluation is for the given parameters, not the given parameters plus the returned update steps (outDC and outDP). The length should be 1.lambda
- the damping parameter. upon first use, this is 0 and outInitLambda is not null so that the sparse Hessian is calculated without the damping term and is used to find the initial value of lambda which it places in outInitLambda. upon all subsequent uses of this method, it's expected that lambda > 0 and outInitLambda is null.outInitLambda
- when not null this is the output parameter holding the maximum of the diagonal of j^T*J. the array has length 1.- Throws:
no.uib.cipr.matrix.NotConvergedException
java.io.IOException
NaNException
-
pdCpIJCIJ
void pdCpIJCIJ(double[] xWCNI, double[][] intr, double k1, double k2, double[][] out)
the partial derivative of the final 2D re-projected coordinates of the i-th feature point w.r.t. 2D coordinates of perspective projection of the i-th feature point. Defined in Qu 2018 eqn (3.12).- Parameters:
xWCNI
- a world point projected to the camera reference frame and normalized by it's last coordinate. xWCI = column i of coordsW transformed to camera coordinates; xWCNI = xWCI/xWCI[2];intr
-k1
- radial distortion coefficient 1k2
- radial distortion coefficient 2out
- output array of size [2X2]
-
pdCIJXWIJ
void pdCIJXWIJ(double[] xWCI, double[][] out)
the partial derivative of the 2D coordinates of perspective projection of the i-th feature point normalized, w.r.t. to the same not normalized. Defined in Qu 2018 eqn (3.16).- Parameters:
xWCI
- a world point projected to the camera reference frame. xWCI = column i of coordsW transformed to camera coordinates;out
- output array of size [2X3]
-
pdCpIJYJ
void pdCpIJYJ(double[] xWCNI, double[][] intr, double k1, double k2, double[][] out)
the partial derivative of the final 2D re-projected coordinates of the i-th feature point w.r.t. the intrinsic camera parameters. Defined in Qu 2018 eqn (3.10).- Parameters:
xWCNI
- a world point projected to the camera reference frame and normalized by it's last coordinate. xWCI = column i of coordsW transformed to camera coordinates; xWCNI = xWCI/xWCI[2];intr
-k1
- radial distortion coefficient 1k2
- radial distortion coefficient 2out
- output array of size [2X3]
-
pdXWIJPhiJ
void pdXWIJPhiJ(double[] xWI, double[] phi, double[][] out)
the partial derivative of the final 2D re-projected coordinates of the i-th feature point w.r.t. 2D coordinates of perspective projection of the i-th feature point. Defined in Qu 2018 eqns (3.28 - 3.33).- Parameters:
xWI
- the 3-D coordinates of a world scene feature.phi
- rotation angle vector of length 3 in units of radiansout
- output array of size [3X3]
-
aIJBIJ
void aIJBIJ(double[] xWI, double[] xWCI, double[][] intr, double k1, double k2, double[] rotAngles, double[][] rot, double[] trans, BundleAdjustment.AuxiliaryArrays aa, double[][] outAIJ, double[][] outBIJ)
NOTE: there may be a problem if using the homography matrix [r0 r1 t] to transform world scene to camera coordinates as the partial derivatives here are assuming the use of the 3nd column of rotation too, that is R * T. for aIJ creates dF/dCameraParams which are the 9 parameters of extrinsic and intrinsic, where the 9 parameters are the Qu notation for the variables phi_j, t_j, y_j. for each image = 9*nImages elements (j index is used for images). for bIJ creates dF/dPointParams which are the 3 parameters of the world point position. for each feature = 3 * mFeatures elements (i index is used for features) Defined in Lourakis lecture slide 10.- Parameters:
xWI
- a world scene feature. xWI = column i of coordsWxWCI
- xWI projected to the camera reference frame. xWCI = column i of coordsW transformed to camera coordinates, but not normalize;intr
-k1
- radial distortion coefficient 1k2
- radial distortion coefficient 2 //@param rot extrinsic camera parameter rotation matrix.rotAngles
- [1 X 3] array holding euler rotation angles.rot
- [3 X 3] rotation matrix which was created with Rotation.createRotationZYX(rotAngles...);trans
- extrinsic camera parameter translation vector.aa
- a group of arrays passed in by invoking code, re-used to avoid constructing more objects. AuxiliaryArrays aa = AuxiliaryArrays().outAIJ
- output array of size [2X9]outBIJ
- output array of size [2X3]
-
populateCameraProjectionHomography
void populateCameraProjectionHomography(double[][] rot, double[] translation, double[][] outH)
populate the homography matrix to transform world screen coordinates to projected 2D coordinates in the camera reference frame.- Parameters:
rot
-translation
-outH
-
-
populateCameraProjectionHomography
void populateCameraProjectionHomography(double[][] rot, double[] translation, double[] outH, boolean useLeftHanded)
populate the homography matrix to transform world screen coordinates to projected 2D coordinates in the camera reference frame. method follows Wetzstein, eqn 19.- Parameters:
rot
-translation
-outH
-
-
-


@BobMcElrath @_tessr There were public discussions after 2009 fin crisis, 2010 Greek crisis, 2011 MF Global collapse. Tri-party repo, securities lending and rehypo of collateral are necessary for the functioning of the financial system, per Bill Dudley (former NYFed). http...


We often talk about developers working in “isolation” or use the term “sandbox” to describe an environment that cuts ourselves off from the outside world. But what exactly do we mean by these terms – what is on the inside and what is on the outside? There are often many different sandboxes in the development process too, for example the build pipeline and the various test environments. Some of these are “larger” than others, where size could be measured in terms of the number of processes, machines and network paths collaborating together.
The aim of this article is to look at various different sizes of development-level sandboxes and explain what problems I’ve commonly encountered when using them. As will become apparent later you’ll see what I personally consider is the ideal sandbox for day-to-day, user-story development work. That last qualification is important because when I’m doing support or localised system-level testing I probably need to loosen the sandbox constraints to bring in some external dependencies, but ideally under tightly controlled conditions [1].
To be doubly clear this is not about unit tests – it’s about developing and running component, integration and acceptance level tests. Unit tests naturally have no dependencies but once we have run those and our confidence starts to build it’s nice to start bringing in fast running tests that talk to real dependencies to start gaining further confidence that all the units have been assembled correctly and are still working together as intended.
The kinds of services I’ve been developing in recent years have been developed outside-in, starting with a failing acceptance test and then moving inside the service, sometimes leading to writing a combination of integration, component and/or unit tests before “unwinding the stack”. Whilst they often have a real (e.g. out-of-process) database and messaging service in play for the acceptance tests they all still run to completion within a couple of minutes. Even so they exercise the majority of code paths which leads to high degree of confidence in the functional aspects of any change before it is committed by the developer.
Hence this article is about where those “heavier” 3rd party dependencies live and how we can cope with the potential disruptions they have a habit of producing. Once we leave the simplicity and beauty of the in-memory sandbox that unit testing provides we enter a realm where side-effects can become persistent. If we’re not careful we start chasing our own tails due to test failures outside our control, or worse, start to ignore test failures we believe our changes could never have caused; that is the start of a very slippery slope.
At the extreme our degree of isolation might only be to avoid us affecting the production system. More typically we create named environments, such as DEV and UAT, which are usually partitioned on a (virtual) machine-wide basis.
From a developer’s perspective this kind of environment means there is some form of shared infrastructure in use, such as a database, file share or message bus. Once we have any form of shared resource we start to bring in the possibility of noise to the development process, which, as mentioned earlier can manifest itself as test failures outside our control. Nothing kills a state of “flow” more readily than an unexpected test failure and shared resources increase the likelihood of that happening.
When any test fails my immediate reaction is that it’s my fault – I’m always guilty until proven innocent. Not every line of code (production or test) I come across is easy to reason about and so I have to assume the worst. Tolerating transient test failures just leads to distrust and an eventual “blindness” whereby the test provides no value because its failure is ignored. Eventually someone will get fed up and just comment the test out altogether or add the “ignore” attribute so that it never runs. Now the test is just an illusion that buys us false hope.
Years ago the need to share infrastructure was borne out of cost – not every developer could afford to have an instance of SQL Server or Oracle on their machine due to the high licensing costs. In today’s world there are “developer” editions of the big iron products which help to alleviate this cost. The NOSQL databases are usually free and only come with the kind of limitations a developer would never breach as part of their normal development cycle anyway. The same goes for web servers and message queuing products too. What is more likely to make this set-up unusable is either a draconian usage policy [2], where you have no rights to install anything, or the machine is woefully underpowered and couldn’t take the extra strain of additional services in tandem.
Putting aside these reasons why you might have to suffer the sharing of services another problem they create is that it can make remote working even more painful. If the organisation does not provide a VPN or some form of remote desktop then you cannot easily work outside the confines of the office. Even with a decent broadband connection I’ve seen test suites take an order of magnitude longer to run because of the latency that starts to dominate on all the underlying remote service connections created during the test runs. In some cases the firewall covering the VPN may only be configured for the “standard” network traffic (think SharePoint) and so you might be blocked from accessing your modern NOSQL database due to its use of unusual port numbers. As for working on the train during your daily commute or business trip, that would just be a non-starter.
The usual technique for dealing with shared infrastructure is to partition either at the schema-level or data-level. For databases you can have your own named database within an instance and for message queues the queue name could encompass some derivable prefix or suffix, such as your login or developer machine. These values work nicely for an out-of-the-box configuration option but as we shall see later being able to easily override them, such as through a defaulted environment variable, is often desirable anyway [1].
At least with this kind of partitioning you are only really sharing the service itself with other developers. Hopefully the product is reliable, which is presumably why you picked it, the data volumes are low, and so the chances of failure are mostly down to hardware issues of some description. The use of virtual servers would make this kind of problem largely a thing of the past if it wasn’t for all the bureaucracy that can be required to get the VM up and running again on another host. The security patching cycle that goes on every month has also been known to take down a crucial development server or two in the past so it’s not all plain sailing.
The second option is to partition at the data level. This usually involves adding prefixes and/or suffixes to the data in such a way that you can uniquely identify your own test data to distinguish it from your colleague’s. This can be a useful technique but it starts to have an impact on both your production and test code as your design inherently has to acquire the ability to pre and post-process data down in the stack. If you’re lucky this will already be a required part of the design and the application of some classic design patterns, such as Decorator, will minimise the impact. If not you’re adding complexity to the code which might be avoidable via other means. Granted it may not be a huge leap in complexity, but it is still something which differs (code wise) between what you run in development and what is actually running in production.
Due to the potentially low-level nature of trying to work this way, it also affects the way you write your tests. Now you have to be mindful of other developers and so can’t just truncate a data table or purge a message queue. Instead you have to delete only your own data from a table or carefully drain the message queue without disturbing the order of other messages. I’m not even sure the latter is entirely possible (I’ve only seen teams take the hit on the disruption when tests are run concurrently, i.e. just keep running them until they do pass).
Sometimes you are not in complete control of all the data which is generated – database identity columns are a case in point. If you rely on them to generate the IDs for your entities you either have to write a different query to identify your data or make sure you capture the identity values in some way so you can refer to them later. Identity columns might not partake in transactions so you can’t assume that N inserts will result in rows with N consecutive identity values when run concurrently with other tests.
Aside from server failures the other big disruption to using shared relational databases with data-level partitioning is schema changes. If another developer needs to change the schema or some shared code, such as a stored procedure, it affects everyone. This also implies that the database must always be running the latest code – reverting the database back to match the current production schema is out of the question without interfering with the rest of the team. Whilst NOSQL databases are inherently schema-less this does not mean schema problems do not happen. On a fast moving codebase with heavy refactoring the schema may be changing rapidly without formally bumping any internal “schema version number” such that breaks in serialization occur. They should be infrequent, but it’s important to be aware that it’s still possible when sharing infrastructure.
Being able to work isolated from the rest of the team (infrastructure wise) is a useful step up. Once you remove what’s going on around you from the potential sources of noise you then only have yourself to blame when something goes wrong; although maybe a group policy update or security patch will still catch you unawares every now and then.
 Want to restart your database, IIS, or the messaging service to blow away the cobwebs? No problem, just do it as there’s no need to coordinate this kind of activity with everyone else.
This doesn’t mean that your setup can be entirely ad-hoc though. Although you can assume that the service name will be “localhost” in any configuration it helps if developers stick to a consistent set of port numbers, etc. so that the default configuration stored in the version control system should just work on any developer’s machine. This is especially useful for getting a new joiner up and running quickly.
Exactly because everything is running locally on every developer’s machine you don’t have to play games with the names of databases or message queues as you can all use the same name. The ability to easily configure such settings is useful for other test environments or scenarios, but for the common case – developing user stories on the default integration branch (e.g. trunk) – it should just work as is.
Whilst this set-up is more stable than having to share infrastructure it does not come without it a few of its own problems. Sometimes you might feel like a part-time system administrator, which is A Good Thing from a DevOps perspective, but can be a distraction when you really just want to get your story finished. For example IIS and IIS Express play games in the background that can leave your test failing, despite you putting in the working implementation, only to find it was still using the old, cached failing implementation. User rights are another area of contention as services tend to run under privileged accounts which makes debugging harder. Being forced to develop as an administrator is not a good habit and is probably what makes some companies nervous enough to disallow any local administrative rights altogether [2].
Not sharing services also implies that there are many more copies of that service around, which means that there will likely be different variations as each developer upgrades his or her machine at different times. Whilst “it works on my machine and the build server” is great for your confidence, you might still end up helping out the one colleague who can’t get it working on their machine because of some weird issue related to them having a different version of a product or driver. Of course this kind of problem can be easily mitigated by having some notes on a wiki or a set of scripts that ensure everyone gets to install the same version at each upgrade. This also ensures that those who may be inclined to always get the latest and greatest beta directly from the vendor are also in sync.
3rd party products are, or
should be, fairly stable. Aside from bug fixes one doesn’t tend to switch major
versions of a database on a whim so the problems cited above are probably a
little over dramatic. Where this problem can start to creep in is with internal
(i.e. the business’s) services which you’d hope would evolve more rapidly as the
company’s priorities change. If you work on a team that is responsible for developing
a number of small, independently deployable services, then you will have to
decide how much coupling you want to take-on to balance detecting
When the team develops a number of services that are dependent on one another, even if they’re independently deployed, there is a temptation to either include them all in the same solution, or try and reuse them for integration and acceptance testing. Doing this in the build pipeline makes perfect sense as you are usually interested in building layers of trust by integrating more services to ensure they still work together. However, I’m not convinced that this set-up is quite so desirable on a developer’s workstation.
If you’re working on the interface between the two services then you’re probably interested in those problems showing up. The majority of the time however is unlikely to be spent that way and other features will should not be directly dependent either as that would be a sign of unnecessarily tight coupling. If those services are not mocked locally within the solution, then, any time you integrate upstream changes for the solution you’re working on, you need to update the dependent solutions too, lest you run the chance of an “impedance mismatch” occurring when running unrelated tests.
Part of the motivation for moving to much smaller services with more well defined contracts is to decouple their evolutions and that has a knock-on effect into the amount of isolation you can afford to take on. This is especially true when you have a build pipeline that can easily verify each service in isolation and then deploy the services together and verify their respective contracts are being honoured by their consumers.
One of the key concepts that the rise in Functional Programming is bringing to the forefront is the notion of side-effects, and that is exactly what makes testing noisier than it should be. Most of the problems mentioned above are the result of side-effects – the output of binaries and test run data that leaks outside the (supposedly transient) test environment. This leaked state then pollutes further test runs for ourselves and potentially others until we can revert back to a known good state.
Whilst isolation at the machine-level generally provides us with our biggest bang-for-buck it’s possible to strive to eliminate even the use of shared local services so that each source folder becomes an independent test environment. Some of the systems I’ve worked on have been able to have two source folders of two different revisions of the same product be built and tested concurrently. This then easily leads to an ability to run them side-by-side too which has been very useful for investigating unintended differences not picked up by the automated tests.
What makes this finer-grained sandbox achievable is the ability to host more of the dependent services in-process, or if out-of-process, then it should be configured, started and managed by the test suite itself rather than being a classic machine-wide daemon. For databases this could be done using an in-process version like SQL Server Compact Edition or SQLite [3], or an out-of-process mock such as CouchbaseMock [4]. With .Net based web APIs the newer OWIN stack is designed to support hosting multiple APIs in the same process, albeit under different app domains. Even the traditional TIBCO messaging service can be started on-the-fly.
Naturally this implies that for a distributed system you are not running exactly the same versions of the those services, but the point of the exercise is not to replicate the production environment, but to trade-off ease of development with the ability to pick up fundamental bugs caused by simple integration mistakes. It’s always easier to debug on your local machine as you have your entire toolbox at your disposal.
Running two codelines [5] side-by-side where there are services that listen on network ports likely won’t work out-of-the-box as it’s often easier to fix the port numbers to create a more deterministic configuration. However, as was mentioned earlier, it helps if key settings such as these can be easily tweaked, perhaps through the use of environment variables, to make it painless to expand the sandbox as needed.
I once started a new job and was presented with a 50-page document describing what I needed to do to set-up my development machine. Admittedly it covered a few other things as well, but even so the process seemed far too convoluted just to get into the code.
Nowadays I’d expect to install the core language toolset and the version control client and pretty much be done, at least, to get started that is. From this meagre configuration I should then be able to create a working copy of the latest source code from the repo, build it and run the core test suites to verify that I’m all set up. At this point I should now be in a position to start making most normal code changes that could be pushed to production via the standard build pipeline. The only scenarios initially out of my reach would require me to know more about a production-like set-up, but that will come in due course.
It’s not always possible to create and develop in the sandbox of your own choosing but where possible I’ve found it well worth the effort to strive to remove as much noise as possible from sources outside my control. The more constrained you make your sandbox the more confident you feel about exploring the codebase and the system without constantly looking over your shoulder to see if any of your meddling has disturbed your team mates.
[1] Testing Drives the Need for Flexible Configuration, Chris Oldwood, Overload 124
[2] Developer Freedom, Chris Oldwood, C Vu 26-1
[4] https://github.com/couchbase/CouchbaseMock
[5]
12 March 2015
Bio
Chris is a freelance developer who started out as a bedroom coder in the 80’s writing assembler on 8-bit micros; these days it’s C++ and C#. He also commentates on the Godmanchester duck race and can be contacted via<EMAIL_ADDRESS>or @chrisoldwood.


Lab #5:
The Secret of
The French Bulldogs
INSTRUCTIONS
There are 7 boxes, corresponding to 7 game levels.
Each box contains two multiple choice questions.
You must correctly answer both questions in a box to unlock the next box.
Each correct answer is worth 1 point.
If you choose an incorrect answer, you will be given chances to try again until you answer correctly.
If you answer correctly on the first try, you will receive 2 bonus points, and 1 bonus point on the second try.
Unlock and complete all 7 boxes to become a Mini Box Champion!
Play Mini Boxes!
Click on an unlocked box to play!
Points:
Points:
Next Question
Back to Boxes


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mkdoc - Source code documentation extractor/converter application
This document describes mkdoc, an application to extract documentation embedded in source code files, be they ".tcl", or other.
The application prints a short help to standard output and exits.
The application prints its version number to standard output and exits.
The application prints its license to standard output and exits.
The application reads the input file, extracts the embedded documentation, and writes it to the output file.
If the output file is not a ".md" file the extracted documentation is converted to HTML before being written.
When generating and writing HTML the default CSS stylesheet can be overridden by specifying the path to a custom stylesheet via option --css.
If the input file is a ".md" file it is expected to contain Markdown as-is, instead of Markdown embedded into code.
On the other side, when the file is considered code then the documentation is expected to be contained in all lines starting with the marker #'. For script languages like Tcl the # character of this marker means that the documentation is contained in the so-flagged comments. For other languages the marker and documentation may have to be embedded into multi-line comments.
# Create HTML manual for a CPP file using a custom style sheet mkdoc sample.cpp sample.html --css manual.css # Extract the documentation from code as simple Markdown, ready to be processed # further, for example with pandoc, or similar mkdoc sample.cpp sample.md # Convert a Markdown file to HTML mkdoc sample.md sample.html
This document, and the package it describes, will undoubtedly contain bugs and other problems. Please report such to the author of this package. Please also report any ideas for enhancements you may have for either package and/or documentation.
BSD License type:
The following terms apply to all files a ssociated with the software unless explicitly disclaimed in individual files.
The authors hereby grant permission to use, copy, modify, distribute, and license this software and its documentation for any purpose, provided that existing copyright notices are retained in all copies and that this notice is included verbatim in any distributions. No written agreement, license, or royalty fee is required for any of the authorized uses. Modifications to this software may be copyrighted by their authors and need not follow the licensing terms described here, provided that the new terms are clearly indicated on the first page of each file where they apply.
In no event shall the authors or distributors be liable to any party for direct, indirect, special, incidental, or consequential damages arising out of the use of this software, its documentation, or any derivatives thereof, even if the authors have been advised of the possibility of such damage.
The authors and distributors specifically disclaim any warranties, including, but not limited to, the implied warranties of merchantability, fitness for a particular purpose, and non-infringement. This software is provided on an "as is" basis, and the authors and distributors have no obligation to provide maintenance, support, updates, enhancements, or modifications.
RESTRICTED RIGHTS: Use, duplication or disclosure by the government is subject to the restrictions as set forth in subparagraph (c) (1) (ii) of the Rights in Technical Data and Computer Software Clause as DFARS<PHONE_NUMBER> and FAR 52.227-19.
Text processing
Copyright © 2019-2022, Detlef Groth <detlef(at)dgroth(dot)de>


| HOME | DOWNLOAD | DOCUMENTATION | FAQ |
> Home > Documentation
Using SHTOOLS with Python
To access the SHTOOLS routines from Python, it is necessary that the pyshtools directory be in the Python search path. From within Python, enter
import sys
sys.path.append('/path-to-pyshtools')
where /path-to-pyshtools should be /usr/local/lib/python2.7/site-packages after a full installation. After setting the path, it is then only necessary to execute the statement
import pyshtools as shtools
to load the routines and documentation. If you are using iPython, which adds improved functionality to Python, the available shtools routines can be explored by typing
shtools.[tab]
where [tab] is the tab key.
To explore the list of predefined constants used by SHTOOLS, enter
shtools.constant.[tab]
Documentation
To read the documentation of a routine in iPython, such as PlmBar, enter
shtools.PlmBar?
Documentation for the Python functions used in SHTOOLS can also be accessed by their unix man pages, appending py to the name and using all lower case letters. As an example, to access the MakeGridDH man page, use
man pymakegriddh
Alternatively, the man pages can be accessed from the documentation link on this web site.
> Home > Documentation
| Institut de Physique du Globe de Paris | University of Sorbonne Paris Cité | © 2016 SHTOOLS |


|
lubyk
0.5
|
#include <Box2D/Common/b2Math.h>
#include <climits>
Go to the source code of this file.
Classes | |
| struct | b2ContactFeature |
| union | b2ContactID |
| Contact ids to facilitate warm starting. More... | |
| struct | b2ManifoldPoint |
| struct | b2Manifold |
| struct | b2WorldManifold |
| This is used to compute the current state of a contact manifold. More... | |
| struct | b2ClipVertex |
| Used for computing contact manifolds. More... | |
| struct | b2RayCastInput |
| Ray-cast input data. The ray extends from p1 to p1 + maxFraction * (p2 - p1). More... | |
| struct | b2RayCastOutput |
| struct | b2AABB |
| An axis aligned bounding box. More... | |
Enumerations | |
| enum | b2PointState { b2_nullState, b2_addState, b2_persistState, b2_removeState } |
| This is used for determining the state of contact points. More... | |
Functions | |
| void | b2GetPointStates (b2PointState state1[b2_maxManifoldPoints], b2PointState state2[b2_maxManifoldPoints], const b2Manifold *manifold1, const b2Manifold *manifold2) |
| void | b2CollideCircles (b2Manifold *manifold, const b2CircleShape *circleA, const b2Transform &xfA, const b2CircleShape *circleB, const b2Transform &xfB) |
| Compute the collision manifold between two circles. | |
| void | b2CollidePolygonAndCircle (b2Manifold *manifold, const b2PolygonShape *polygonA, const b2Transform &xfA, const b2CircleShape *circleB, const b2Transform &xfB) |
| Compute the collision manifold between a polygon and a circle. | |
| void | b2CollidePolygons (b2Manifold *manifold, const b2PolygonShape *polygonA, const b2Transform &xfA, const b2PolygonShape *polygonB, const b2Transform &xfB) |
| Compute the collision manifold between two polygons. | |
| void | b2CollideEdgeAndCircle (b2Manifold *manifold, const b2EdgeShape *polygonA, const b2Transform &xfA, const b2CircleShape *circleB, const b2Transform &xfB) |
| Compute the collision manifold between an edge and a circle. | |
| void | b2CollideEdgeAndPolygon (b2Manifold *manifold, const b2EdgeShape *edgeA, const b2Transform &xfA, const b2PolygonShape *circleB, const b2Transform &xfB) |
| Compute the collision manifold between an edge and a circle. | |
| int32 | b2ClipSegmentToLine (b2ClipVertex vOut[2], const b2ClipVertex vIn[2], const b2Vec2 &normal, float32 offset, int32 vertexIndexA) |
| Clipping for contact manifolds. | |
| bool | b2TestOverlap (const b2Shape *shapeA, int32 indexA, const b2Shape *shapeB, int32 indexB, const b2Transform &xfA, const b2Transform &xfB) |
| Determine if two generic shapes overlap. | |
| bool | b2TestOverlap (const b2AABB &a, const b2AABB &b) |
Variables | |
| const uint8 | b2_nullFeature = UCHAR_MAX |
Structures and functions used for computing contact points, distance queries, and TOI queries.
Definition in file b2Collision.h.
| enum b2PointState |
This is used for determining the state of contact points.
| b2_nullState |
point does not exist |
| b2_addState |
point was added in the update |
| b2_persistState |
point persisted across the update |
| b2_removeState |
point was removed in the update |
Definition at line 125 of file b2Collision.h.
| int32 b2ClipSegmentToLine | ( | b2ClipVertex | vOut[2], |
| const b2ClipVertex | vIn[2], | ||
| const b2Vec2 & | normal, | ||
| float32 | offset, | ||
| int32 | vertexIndexA | ||
| ) |
Clipping for contact manifolds.
| void b2CollideCircles | ( | b2Manifold * | manifold, |
| const b2CircleShape * | circleA, | ||
| const b2Transform & | xfA, | ||
| const b2CircleShape * | circleB, | ||
| const b2Transform & | xfB | ||
| ) |
Compute the collision manifold between two circles.
| void b2CollideEdgeAndCircle | ( | b2Manifold * | manifold, |
| const b2EdgeShape * | polygonA, | ||
| const b2Transform & | xfA, | ||
| const b2CircleShape * | circleB, | ||
| const b2Transform & | xfB | ||
| ) |
Compute the collision manifold between an edge and a circle.
| void b2CollideEdgeAndPolygon | ( | b2Manifold * | manifold, |
| const b2EdgeShape * | edgeA, | ||
| const b2Transform & | xfA, | ||
| const b2PolygonShape * | circleB, | ||
| const b2Transform & | xfB | ||
| ) |
Compute the collision manifold between an edge and a circle.
| void b2CollidePolygonAndCircle | ( | b2Manifold * | manifold, |
| const b2PolygonShape * | polygonA, | ||
| const b2Transform & | xfA, | ||
| const b2CircleShape * | circleB, | ||
| const b2Transform & | xfB | ||
| ) |
Compute the collision manifold between a polygon and a circle.
| void b2CollidePolygons | ( | b2Manifold * | manifold, |
| const b2PolygonShape * | polygonA, | ||
| const b2Transform & | xfA, | ||
| const b2PolygonShape * | polygonB, | ||
| const b2Transform & | xfB | ||
| ) |
Compute the collision manifold between two polygons.
| void b2GetPointStates | ( | b2PointState | state1[b2_maxManifoldPoints], |
| b2PointState | state2[b2_maxManifoldPoints], | ||
| const b2Manifold * | manifold1, | ||
| const b2Manifold * | manifold2 | ||
| ) |
Compute the point states given two manifolds. The states pertain to the transition from manifold1 to manifold2. So state1 is either persist or remove while state2 is either add or persist.
| bool b2TestOverlap | ( | const b2Shape * | shapeA, |
| int32 | indexA, | ||
| const b2Shape * | shapeB, | ||
| int32 | indexB, | ||
| const b2Transform & | xfA, | ||
| const b2Transform & | xfB | ||
| ) |
Determine if two generic shapes overlap.
Referenced by b2DynamicTree::Query(), b2DynamicTree::RayCast(), and b2BroadPhase::TestOverlap().
Definition at line 261 of file b2Collision.h.
References b2AABB::lowerBound, b2AABB::upperBound, b2Vec2::x, and b2Vec2::y.
| const uint8 b2_nullFeature = UCHAR_MAX |
Definition at line 34 of file b2Collision.h.


Uses of Interface
org.apache.qpid.protonj2.engine.Session
-
Uses of Session in org.apache.qpid.protonj2.engine
Modifier and TypeMethodDescriptionSession.deliveryReadHandler
(EventHandler<IncomingDelivery> delivery) Allows monitoring of incoming deliveries to receivers attached to thisSession
.Link.getParent()
Link.getSession()
Session.receiverOpenHandler
(EventHandler<Receiver> remoteReceiverOpenEventHandler) Sets aEventHandler
for when an AMQP Attach frame is received from the remote peer for a receiving link.Session.senderOpenHandler
(EventHandler<Sender> remoteSenderOpenEventHandler) Sets aEventHandler
for when an AMQP Attach frame is received from the remote peer for a sending link.Connection.session()
Creates a new Session linked to this ConnectionSession.setHandleMax
(long handleMax) Set the handle max value for this Session.Session.setIncomingCapacity
(int incomingCapacity) Sets the maximum number of bytes this session can be sent from the remote.Session.setOutgoingCapacity
(int outgoingCapacity) Sets the maximum number of bytes this session can be write before blocking additional sends until the written bytes are known to have been flushed to the write.Session.transactionManagerOpenHandler
(EventHandler<TransactionManager> remoteTxnManagerOpenEventHandler) Sets aEventHandler
for when an AMQP Attach frame is received from the remote peer for a transaction coordination link.Modifier and TypeMethodDescriptionConnection.sessions()
Returns an unmodifiableSet
of Sessions that are tracked by the Connection.Modifier and TypeMethodDescriptionConnection.sessionOpenHandler
(EventHandler<Session> remoteSessionOpenEventHandler) Sets aEventHandler
for when an AMQP Begin frame is received from the remote peer. -
Uses of Session in org.apache.qpid.protonj2.engine.impl
Modifier and TypeMethodDescriptionProtonSession.setHandleMax
(long handleMax) ProtonSession.setIncomingCapacity
(int incomingCapacity) ProtonSession.setOutgoingCapacity
(int outgoingCapacity) Modifier and TypeMethodDescriptionProtonConnection.sessionOpenHandler
(EventHandler<Session> remoteSessionOpenEventHandler)


| File | Statements | Branches | Functions | Lines | |||||
|---|---|---|---|---|---|---|---|---|---|
| Card.js | 29.63% | 8/27 | 7.14% | 1/14 | 60% | 3/5 | 29.63% | 8/27 | |
| Container.js | 34.29% | 12/35 | 11.11% | 2/18 | 100% | 5/5 | 34.29% | 12/35 | |
| Delete.js | 61.54% | 8/13 | 25% | 2/8 | 100% | 2/2 | 61.54% | 8/13 | |
| FromExample.js | 64.29% | 9/14 | 50% | 3/6 | 60% | 3/5 | 81.82% | 9/11 | |
| Modal.js | 40% | 4/10 | 100% | 0/0 | 28.57% | 2/7 | 44.44% | 4/9 |


| Methods | Pros | Cons |
|---|---|---|
| Radio-Surgery | ||
| Chemos | ||
| Radiation Therapy (RT) |
| Results | Solution drawbacks |
|---|---|
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|
Problem Statement: Given the continuous-valued state of the measurements, statistically model how the observations from each sensor change over time.
where $\textbf{F}(k) \in \mathbb{R}^{2\times 2}$ is the state transition matrix given by \begin{equation} \textbf{F} = \begin{bmatrix} 1 & \Delta T \\ 0 & 1 \end{bmatrix} \end{equation}
$\textbf{u}(k) \in \mathbb{R}^2$ is the control input, $\textbf{B}(k)$ is the control input matrix that maps inputs to system states, $\textbf{G}(k) \in \mathbb{R}^{ 2 \times 2}$ is the process noise matrix, and $\textbf{w}(k) \in \mathbb{R}^2$ is a random variable that models the state uncertainty
\begin{align}\label{eq.accelmodel} \textbf{x}_k = \textbf{F}_k \textbf{x}_{k-1}+ \textbf{G}_k \textbf{w}_k \end{align}
$ \textbf{w}_k$ is the effect of an unknown input causing an acceleration $a_k$ in the head position and $ \textbf{G}_k$ applies that effect to the state vector, $ \textbf{x}_k$
setting $\textbf{G}_k$ to identity and set $\textbf{w}(k) \sim \mathcal{N}(0, \textbf{Q}(k))$,
the covariance matrix $\textbf{Q}(k)$ to a random walk sequence defined as $\textbf{W}_k={[\frac{{\Delta T}^2}{2}, \Delta T ]}^T$
\begin{equation}\label{eq:sensors_obs} {z}_s= \textbf{H}_s(k)\textbf{x}(k)+{v}_s(k) \qquad \qquad s = 1,2 \end{equation}
set $\textbf{H}_s(k) ={\begin{bmatrix} 1 & 0 \end{bmatrix} }^T$ maps the system's state space into the observation space
${v}_s(k) \in \mathbb{R}$ is a normally distributed random variable that models the sensors uncertainty with zero mean and variance $\sigma_{rs}^2$
\begin{equation} \label{eqn:Riccati} \begin{split} A^T P A \mbox{-}(A^T P B \mbox{+} N)(R \mbox{+} B^T P B)^{-1}(B^T P A \mbox{+} N) \mbox{+} & Q, \end{split} \end{equation}
allows us to solve for the optimal control law through a minimization of the resulting LQ problem\begin{align} Q = \begin{bmatrix} 1.0566 & 0 \\ 0 & 1.0566 \end{bmatrix} \hspace{0.4em} R = \begin{bmatrix} 0.058006 \end{bmatrix} \end{align}
full online state estimator with noise processes assumed to be independednt, white Gaussian
Slides available at the author's website.


RT @darinrs: We are not entirely sure what will be live streamed next from #railsConf…but will be on the big screens @newrelic! Come join u…
4/29/2013, 11:26:06 AM
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RT @darinrs: We are not entirely sure what will be live streamed next from #railsConf…but will be on the big screens @newrelic! Come join u…
4/29/2013, 11:26:06 AM
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link


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Before this incident, you did not believe in traveling to other worlds. But everything happens for the first time. You have one hope - to live as many days as possible.


YUKO BERGER
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