Book Description
Thorough and accessible, this book presents the design principles of biological systems, and highlights the recurring circuit elements that make up biological networks. It provides a simple mathematical framework which can be used to understand and even design biological circuits. The text avoids specialist terms, focusing instead on several well-studied biological systems that concisely demonstrate key principles. An Introduction to Systems Biology: Design Principles of Biological Circuits builds a solid foundation for the intuitive understanding of general principles. It encourages the reader to ask why a system is designed in a particular way and then proceeds to answer with simplified models.
Customer Reviews:
Clear, rigorous, fascinating.......2007-01-20
I'm a Ph.D. student in biophysics. This is the best treatment of systems biology that I've encountered. It treats both the math and the biology with clarity, rigor, and respect. It simplifies without dumbing down. It's beautifully written. If you doubt that systems biology is a real scientific discipline, this book will change your mind.
Building Mathematical Models of Cells.......2006-09-25
The history of science over the past few centuries is to become ever more specialized. The physicists, becomming ever more concerned with the very large (stars, galaxies, the cosmos) or the very tiny (first atoms, then atomic components, now sub-components. The biologists on the other hand were studying much larger things, such as the cells that make up life. Both sciences developed techniques to facilitate their study.
In recent years, researchers have discovered that sometimes these specialized techniques can be used to develop greater insight into what is happening in other sciences.
In this book, Dr. Alon uses his training in physics to examine certain aspects of biology and to use the terminology and mathematics to describe the way these biological networks work.
The goal of the book is to begin the formulation of general laws that apply to biological networks. This is done by providing a mathematical framework in which some of the design principles of biological systems can help to understand biological networks. In looking at the results, an underlying simplicity not seen before appears in biological systems.
Great Job.......2006-09-09
A superb intro to the field. The math is moderate and helpful. Network concepts and their ties to examples and theory are clearly and succinctly presented. This is a textbook but reads easily like a book. Covers key elements while connecting them by at least mention to up-to-date further research. The basics and the grandeur of systems biology. I am trying to remember now anything on the negative side and cannot.
Book Description
Contains a wealth of topics to allow instructors flexibility in the choice of topics and depth of coverage: Examines
projective motion with and without realistic air resistance. Discusses planetary motion and the three-body problem. Explores
chaotic motion of the pendulum and waves on a string. Includes topics relating to fractal growth and stochastic systems.
Offers examples on statistical physics and quantum mechanics. Contains ample explanations of the necessary algorithms
students need to help them write original programs, and provides many example programs and calculations for reference.
Customer Reviews:
great book.......2001-03-06
This is a great book. I enjoy reading and using it quite a bit. The focus is realistic simulations, not just simulations. Also, this book has a wide scope: there are sections covering random systems, molecular dynamics, even earthqakes and self-organized criticality. I suspect a second edition might even expand on these topics to include, oh perhaps economic simulations? But as it is it's a superb book. The style is even engaging; just enough theory (but indeed the right amount of it) and some pointed results... Where else would you go to find three-body gravitational simulations and protein folding and the brain as a complex system, in the same book? Note: there are code examples and the programming language is True Basic for the Macintosh. If that's not your cup of tea, it should not be too hard to port that to, say, Matlab or something more universal. Perhaps again for the second edition...
good book for physicists who like to write simulations.......2001-03-04
This is a great book to get you started using you desktop for more than running your screen saver or surfin' the net. Some sections are dealing with elementary physics but most deal with intermediate to even advanced topics. What's also great about this book is that the author doesn't assume you necessarily remember all of your undergrad physics. You're gently reminded of the key concepts and the bottom line you need to remember and then it's off to the good stuff. I liked this book quite a bit; it's really a great book. Unpretentious and striking the right balance between the theory necessary to write realistic or meaningful simulations. Overall I'd say the word superb applies here. Next edition: expand on stochastic processes a bit more, then you get 5 stars...
Average customer rating:
- great book for MD basics
- Old fashioned fortran, strong bias on Monte Carlo
- Excellent text for beginners in simulation
- Perfect for New Grad Students
- A nice disappointment
|
Understanding Molecular Simulation (Computational Science Series, Vol 1)
Daan Frenkel , and
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Similar Items:
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Computer Simulation of Liquids
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The Art of Molecular Dynamics Simulation
-
Molecular Modelling: Principles and Applications (2nd Edition)
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An Introduction to Statistical Thermodynamics
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Introduction to Modern Statistical Mechanics
ASIN: 0122673514 |
Book Description
Understanding Molecular Simulation: From Algorithms to Applications explains the physics behind the "recipes" of molecular simulation for materials science. Computer simulators are continuously confronted with questions concerning the choice of a particular technique for a given application. A wide variety of tools exist, so the choice of technique requires a good understanding of the basic principles. More importantly, such understanding may greatly improve the efficiency of a simulation program. The implementation of simulation methods is illustrated in pseudocodes and their practical use in the case studies used in the text.
Since the first edition only five years ago, the simulation world has changed significantly -- current techniques have matured and new ones have appeared. This new edition deals with these new developments; in particular, there are sections on:
· Transition path sampling and diffusive barrier crossing to simulaterare events
· Dissipative particle dynamic as a course-grained simulation technique
· Novel schemes to compute the long-ranged forces
· Hamiltonian and non-Hamiltonian dynamics in the context constant-temperature and constant-pressure molecular dynamics simulations
· Multiple-time step algorithms as an alternative for constraints
· Defects in solids
· The pruned-enriched Rosenbluth sampling, recoil-growth, and concerted rotations for complex molecules
· Parallel tempering for glassy Hamiltonians
Examples are included that highlight current applications and the codes of case studies are available on the World Wide Web. Several new examples have been added since the first edition to illustrate recent applications. Questions are included in this new edition. No prior knowledge of computer simulation is assumed.
Customer Reviews:
great book for MD basics.......2007-05-07
I was especially delighted about the Monte Carlo methods and the free energy calculation techniques.
Old fashioned fortran, strong bias on Monte Carlo.......2006-06-19
There is a very strong bias to MC methods in the book. What they have to say about Molecular Dynamics methods is not really new, most of it is virtually copied from the classic by Allan/Tildesley, and many MD techniques which they consider "advanced" (such as cell list methods, verlet tables, etc.) are shifted to one of the many appendices. They do not talk about ghostparticles for instance or give a detailed account of parallelized algorithms which is really state-of-the art today.
The code examples for download for the exercises, contain subtle errors, are not optimized for performance (which is THE most important thing in simulation business) and worst of all, are written in Fortran. The fact that they publish Fortran code must reflect the fact that at the time they learned how to program a computer there was no C, C++, JAVA, etc. and no object orientation in sight. Nowadays, probably no expert in programming would start a scientific and readable code in fortran. Also their definition of an algorithm is simply technically wrong. The authors are very sloppy here, have obviously no training in theoretical computer science and are obviously no experts for writing optimal code.
Scientifically, as far as physics is concerned, the book is sound, they give good arguments pro and against certain methods, but when you have already worked with Allan/Tildesley or Rappaport for many years you have the eery impression that they simply repeat many arguments from these books or from other research articles (They keep citing Allan/Tildesley a lot) Those things that are not more or less copied from other sources seems to reflect their own experience in this field which seems to be strongly limited to MC methods.
Although this book is sometimes praised I cannot really recommend it. Allan/Tildesley, and in particular the book by Rappaport are superior in stlye and in particluar as code examples are concerned. With Rappaport you get working code right away in proper C (albeit in Fortran-Style C -- again, the reason for this being the fact, that all these authors of Simulation books learned programming probably in the late 70's when Fortran was state-of-the-art). I nevertheless would recommend Rappaports book instead. The authors even offer scientific workshops based on their book (and probably make a lot of money with that). One can only hope that those are better than the coding examples of the exercises. Therefore only 2 stars.
Excellent text for beginners in simulation.......2004-11-20
Its an excellent book for those who are just beginners in MC & MD simulations. everything is very clearly explained with lot of examples and some related unsolved problems. the text explores this topic indetails with advanced chapters in later sections. Good for anybody int hsi field be it in materials science, physics or related fields.
Perfect for New Grad Students.......2002-11-24
This book is how I bootstrapped my way into being a molecular simulationist. Anyone who can program in some language can get started writing simple routines for the basic MD and MC simulations.
I do Monte Carlo simulations at Princeton, and found this book to be the most helpful available for getting my research started. It is my most common reference, and is used extensively in writing background information for various research documents.
However, after you have written your first few codes, you will pass the level of this book and need to move on. I use it less now than I did my first year.
Every student in my group (Panagiotopoulos) has this book I think. And like me, they started with it, but moved on.
A nice disappointment.......2001-08-30
The title of the book is overly ambitious and falls short on its promises. The book is a good introduction to Molecular Mechanics (MM), Molecular Dynamics (MD) and Monte Carlo (MC) methods, with detailed descriptions of the methods used and FORTRAN (pseudo)code, covering from the basics to some middle-level and some advanced algorithms.
But it does NOT cover all the fields of Molecular Modelling, just the three mentioned (MM, MD and MC), there's no coverage of quantum mechanics methods, nor QSAR or other technologies. And, while it described the algorithms, I can't think of it going all the way through up to building applications. For this, Rapaport's makes a better job, and for a general intro to Molecular Modelling, Grant & Richards' Computational Chemistry is more comprehensive (albeit at a more superficial level). Nor does it provide much detail on the methods used in modelling biological macromolecules, an increasing application field for the methods discussed in the book.
All in all, this book fails to satisfy its cover title, it won't introduce to the whole field (just the areas of MM, MD and MC) nor does it go up to application level. But it IS a REAL GOOD introduction to the subjects covered and their basic algorithms,
with sample code, detailed descriptions and plenty of references to specialized articles, texts and resources.
Book Description
This extensively revised and expanded third edition of the Artech House bestseller, Computational Electrodynamics: The Finite-Difference Time-Domain Method, offers you the most up-to-date and definitive resource on this critical method for solving Maxwell's equations. There has been considerable advancement in FDTD computational technology over the past few years, and this new edition brings you the very latest details with four new invited chapters on advanced techniques for PSTD, unconditional stability, provably stable FDTD-FETD hybrids, and hardware acceleration. Moreover, you find many completely new sections throughout the book, including major updates on convolutional PML ABCs; dispersive, nonlinear, classical-gain, and quantum-gain materials; and micro-, nano-, and bio- photonics.
This single resource provides complete guidance on FDTD techniques and applications, from basic concepts, to the current state-of-the-art. It enables you to more efficiently and effectively design and analyze key electronics and photonics technologies, including wireless communications devices, high-speed digital and microwave circuits, and integrated optics. You find sample FDTD codes written in Matlab® that serve as a self-guided refresher, and examples of how to use the FDTD method on a wide range of projects in the field. What's more, to supplement the third edition, the authors and publisher have created a Website where you can find solutions to the problems, sample FDTD PML codes, text updates/errata, and downloadable color graphics and videos. Consequently, this new edition is the ideal textbook for both a senior-year undergraduate elective course and a graduate course in computational electrodynamics.
Customer Reviews:
Brilliant textbook on computational EM.......2007-02-04
This is THE STANDARD reference on FDTD methods in computational electrodynamics. Moreover, even if time-domain is not your main thing but you still work with computational EM, add this to your library. It is wonderfully written, simultaneously easy to read and deeply comprehensive. You can get your own codes going by reading this book. After applying the things you learn here you will have a renewed inspiration in Maxwell's equations and E&M.
The book for FDTD.......2005-11-09
This book is an excellent and thoroughly enjoyable reference/tutorial. The book is suitable for use in an advanced undergraduate/first-year graduate class with a prerequisite of one semester of undergraduate E&M. (The authors' preface indicates that this prerequisite is not entirely necessary, but I don't see how you could understand what is going on without it.)
The book can also be used for self-study. In this vein, the book's website contains 1d-, 2d-, and 3d-matlab scripts that are excellent for learning how to actually implement all of this stuff. The third edition weighs in at just over 1000 pages with a price tag of $139, which is $10 cheaper than the 2nd edition was when it came out.
Allen Taflove is, perhaps, the leader in the development and use of this technique. Allen is now at Northwestern. Susan Hagness was a recent PhD student of his (1998) and is now an associate professor in the Electrical and Computer Engineering department at the University of Wisconsin. The authors are at the forefront in the development of applications.
The third edition is significantly larger than the 2nd edition and includes several applications chapters that were cowritten with the major researchers in the field. The extraordinary explosion of application areas for FDTD is captured in the later chapters, and these chapters give students and new researchers a clear flavor of the vitality and interest in the field which extends from the detection of breast cancer to ELF pulses produced by earthquakes. It is refreshing to find authors who so readily give credit to others in their field. Taflove and Hagness have been very gracious in this regard, and as a consequence have a much better book and a very detailed and useful bibliography.
I very heartily recommend this book to anyone who wishes to use FDTD techniques.
Agree with Prior Reviewer.......2002-09-21
I cannot quite honestly give this book (*first* edition, not second) a full five-point-zero stars because it somewhat comes apart the closer one gets to the final chapters. I read this book a few years ago, so I apologize for lack of specificity. However, I completely agree with the prior reviewer who stated that this book is better than Kunz's and Luebbers' book, which I appears to be a slightly edited compilation of previous publications --- even if that is completely untrue. In fact, in my opinion, Taflove's book (again, first edition) is a *much* better textbook than Kunz and Luebbers.
The Book News review is somewhat misleading. Taflove derives the difference equations in full, painstaking detail. (Perhaps the Book News reviewer fell asleep during that portion.) For me, this was the most valuable and educational portion of the book. Example applications have their place, but only after understanding the basic principles. Taflove did an excellent job in describing these principles, which go far beyond the basic Yee algorithm (e.g. extrapolation techniques and incorporation of BC's). Those readers familiar with other FD books should understand what I'm saying here: Anyone who reads this book and understands it will not only be conversant about FDTD but should also be able to write solid working codes. With the K&L book, this is very questionable.
A good overview of FD-TD method.......2000-05-25
A good intro book for the FD-TD method with many applications. The list of references at the end of each chapter is also very useful. Some of the material is now outdated and needs corrections, but otherwise a great reference for CEM. I would recommend this book over the Kunz & Luebbers FD-TD book.
Book Description
Computational science is a quickly emerging field at the intersection of the sciences, computer science, and mathematics because much scientific investigation now involves computing as well as theory and experiment. However, limited educational materials exist in this field. Introduction to Computational Science fills this void with a flexible, readable textbook that assumes only a background in high school algebra and enables instructors to follow tailored pathways through the material. It is the first textbook designed specifically for an introductory course in the computational science and engineering curriculum.
The text embraces two major approaches to computational science problems: System dynamics models with their global views of major systems that change with time; and cellular automaton simulations with their local views of how individuals affect individuals. While the text is generic, an extensive author-generated Web-site contains tutorials and files in a variety of software packages to accompany the text.
- Generic software approach in the text
- Web site with tutorials and files in a variety of software packages
- Engaging examples, exercises, and projects that explore science
- Additional, substantial projects for students to develop individually or in teams
- Consistent application of the modeling process
- Quick review questions and answers
- Projects for students to develop individually or in teams
- Reference sections for most modules, as well as a glossary
- Online instructor's manual with a test bank and solutions
Book Description
C++ is rapidly becoming the programming language of choice for science and engineering applications because of its rich object-oriented features. Intended for beginning and intermediate programmers, this book surveys the application of C++ to technical problems. Modern object-oriented software engineering tools are employed to simplify the presentation and all aspects of modern C++ programming practices of relevance to scientific programming are surveyed.
Customer Reviews:
the best.......2005-07-13
This is a very good book, the codes are clear and
written from a computational point of view. It is easy
to set up the software. I agree with the authors self
remraks except that he should wirte up some harder examples
in the end. But still, the best.
From the Author:.......2005-05-19
This book was developed during many years of teaching scientific programming to engineers and scientists in both electrical engineering and physics courses. About 1/3 of the text is accessible to beginning programmers even at a high-school level, while the last part of the book can serve as a second-term undergraduate scientific programming course or as a reference text. While the title indicates that a major focus of the text is computational physics, the book contains problems and examples from numerous scientific and engineering disciplines and can be employed across a wide variety of course offerings.
Because of the practical difficulties faced by beginning students, a first course in scientific programming generally requires very significant personal intervention by the instructor or laboratory assistant. This book effectively removes this issue by providing a common base of free Windows software on CD-ROM that is meticulously documented in the text (the software is also available for Linux). The reader is introduced to programming through numerous assignments containing real-world technical problems. The assignments at first contain nearly the entire program to be developed; as the book develops, however, fewer code sections are provided. This method allows the user to absorb proper program structure while avoiding frustrating and confusing stylistic traps. A solution manual is made available to instructors through Cambridge University Press (see their website for errata) while the CD-ROM also contains copies of all programs presented in the text.
This book presents a compact but completely unified picture of modern programming practice as it applies to scientific programming. The fundamental, underlying principles of the C++ language and scientific programming are stressed in order to simplify retention of complex C++ syntax and of the mathematical and physical content. More involved topics in numerical analysis, scientific programming methods and C++ are presented in an intuitive and easily-understood manner. Examples of the subjects covered are: software engineering principles (UML), numerical analysis, scientific graphics programming, the Standard Template Library (STL), Monte-Carlo methods including the Metropolis and multicanonical techniques, partial differential equation solvers, calling Fortran from C++, C++ program optimization.
not as abstract as a pure physics text.......2005-04-11
This book can serve several audiences. It teaches both computational physics and the use of C++ in writing object oriented code. Clearly, if you are already know one of these topics, but not the other, then the book is a natural fit. You can concentrate on what is essentially half the book.
The more challenging task is if you are unfamiliar with both. Well, it is reasonable to assume that you know some physics, say at the first year undergraduate level. And perhaps you have done some programming, in a procedural language like Fortran or Basic.
The amount of abstractions, or rather the level of difficulty in this, is less than in a typical physics text that is explaining Maxwell's Equations or Einstein's Special Relativity. The physics in the book revolves around trying to compute certain numbers in an efficient manner.
While from a programming standpoint, computational physics examples are given as an important use case, to help the student grasp the OO concepts.
Book Description
Help students master real-world problems as they develop new insight into the physical sciences
Problems in the physical sciences that once baffled and frustrated scientists can now be solved easily with the aid of a computer. Computers can quickly complete complex calculations, provide numerical simulations of natural systems, and explore the unknown. Computational Physics shows students how to use computers to solve scientific problems and understand systems at a level previously possible only in a research environment. Adaptable to a ten-week class or a full-year course, it provides C and Fortran programs that can be modified and rewritten as needed to implement a wide range of computational projects.
Light on theory, heavy on applications, this practical, easy-to-understand guide
* Presents material from a problem-oriented perspective
* Integrates physics, computer science, and numerical methods and statistics
* Encourages creative thinking and an object-oriented view of problem solving
* Provides C and Fortran programs for implementing most of the projects
* Provides samples of problems actually solved in two ten-week quarters
* Includes a 3.5'' floppy disk containing the codes featured in the text
* Offers multimedia demonstrations and updates on a complementary Web site
With this engaging book as a guide, advanced undergraduates and first-year graduate students will gain confidence in their abilities and develop new insight into the physical sciences as they use their computers to address challenging and stimulating problems.
Customer Reviews:
This book is for advanced physics.......2000-10-13
The number of stars I gave the book is basically irrelevant.
I'm writing the review to point out that the book should be called: "computations for *advanced* physics".
Most of the topics covered in the book are for second year physics, or advanced topics. That's neither good nor bad, it just depends what you're looking for. If you want to find ways to apply computer programs in a first-years course -- this ain't it. There are probably only a few cases in which the topics are close enough to first-year physics to be relevant (multiple waves on a string; contrasting an idealized model of a pendulum with a "real-one").
Having said that, I give the book some pluses for covering a wide range of physics and mathematical topics, and a bit of a minus for writing that can be fairly opaque.
Average customer rating:
- strong computational emphasis
- Great Suppliment to Numerical methods
- Python for Science Academics and Engineers, NOT programmers
- Convincing demonstration of Python's value in science
|
Python Scripting for Computational Science (Texts in Computational Science and Engineering)
Hans Petter Langtangen
Manufacturer: Springer
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ASIN: 3540294155 |
Book Description
The goal of this book is to teach computational scientists how to develop tailored, flexible, and human-efficient working environments built from small programs (scripts) written in the easy-to-learn, high-level language Python. The focus is on examples and applications of relevance to computational scientists: gluing existing applications and tools, e.g. for automating simulation, data analysis, and visualization; steering simulations and computational experiments; equipping old programs with graphical user interfaces; making computational Web applications; and creating interactive interfaces with a Maple/Matlab-like syntax to numerical applications in C/C++ or Fortran. In short, scripting with Python makes you much more productive, increases the reliability of your scientific work and lets you have more fun - on Unix, Windows and Macintosh. All the tools and examples in this book are open source codes. The third edition is compatible with the new NumPy implementation and features updated information, correction of errors, and improved associated software tools.
Customer Reviews:
strong computational emphasis.......2006-11-13
Langtangen's emphasis here is on a reader who comes from a strong background in engineering or science, and is familiar with common computational ideas and has done some programming, but not necessarily in Python. The typical book on Python is aimed at a general programming reader, and the examples in such a book usually are quite elementary, from a computational viewpoint.
The merit of Langtangen's book is that he gets into a lot of computational ideas. This is not a trivial book. Aspects like parsing data in files, connecting to local and remote hosts, and interacting with programs written in other languages are covered. For the latter, the important cases of Fortran and C programs are explained. The choices of these languages is deliberate. In science and engineering, they are the dominant languages for raw computation. And you are likely to have legacy code written in these, that you cannot abandon while using Python.
Great Suppliment to Numerical methods.......2006-07-25
When I first got ahold of this book I had just finished learning all the gory details of good numerical codes. But when developing tests for simple cases I found that development went way too slow, so someone suggested I learn Python. This book provides a great demonstration of how python can supplement your existing codes. Either by organizing the tests, formatting output, or just adding pretty interfaces.
This book contains a lot of the necessary extras that a scientist or engineer must do to get his work going or finished, which is too pedantic to be taught in most courses. It shows the power of Python over some other scripting languages for this purpose. It is definitely one of the best references on my book shelf.
Python for Science Academics and Engineers, NOT programmers.......2005-06-03
I bought this book as an experienced programmer and Unix user expecting more of a "Numerical Recepies in Python" emphasis on the efficient implementation of algorithms which happen to be in Python. I should have paid more attention to the description.
This book is really more of a "Grad Student's Guide to Everyday Python Usage". I imagine it would be very valuable to a mathematics Grad student without too much programming or shell experience, looking for an alternative to Matlab. However, there is very little "Computational Science" in this book. Do NOT expect a cookbook of high performance algorithm implementations.
The book is a very verbose 700+ pages, all in an unexciting academic LaTeX format. The author works through idiom after idiom for accomplishing different tasks in fairly stand-alone sub-sections without much of a feeling of conceptual "flow" between them. It sort of feels like reading through the author's personal lab notes that he took everytime he learned a new language feature or trick.
If you are an experienced programmer, you will quickly get impatient with the verbose presentation that emphasizes idioms and examples instead of fundamental concepts and syntax reference tables. But, if you are an experienced programmer, you are not the target audience for this book.
Braddock Gaskill
Convincing demonstration of Python's value in science.......2004-10-15
The author has 2 main goals:
1) To improve the productivity of scientists familiar with specific software systems (especially Matlab, Maple, and Mathematica) by teaching them to "glue" applications together.
2) To advocate Python as the preferred "glue" language. In his own words, "I hope to convince computational scientists having experience with Perl that Python is a preferable alternative, especially for large long-term projects."
He has certainly done a creditable job. As an expert in computational differential equations, he neglects neither efficiency nor correctness, while stressing both simplicity and reliability. In this sense, he has done a great service to the Python community.
The question is: What justifies the purchase of his book?
The answer is: Chapters 4, 9, and 10.
Contents:
1. Introduction--26pp
Very convincing arguments.
2. Getting Started With Python Scripting--38pp
Interesting examples.
3. Basic Python--56pp
A too-quick tutorial. Go to python dot org instead.
4. Numerical Computing in Python--48pp
Stellar explanations of vectorized array operations.
5. Combining Python with Fortran, C, and C++--36pp
Details use of Fortran2Py and SWIG. Mentions many alternatives.
6. Introduction to GUI Programming--70pp
Useful examples of Tkinter/pmw widgets.
7. Web Interfaces and CGI Programming--24pp
Good source of ideas.
8. Advanced Python--132pp
Deep and extensive. Includes: option parsing, regular expressions, data persistence and compression, object-oriented programming, exceptions, generic programming, efficiency.
9. Fortran Programming with NumPy Arrays--32pp
All about efficiency and re-use.
10. C and C++ Programming with NumPy Arrays--40pp
More about efficiency. NumPy C API, C++ objects, and SCXX.
11. More Advanced GUI Programming--73pp
Tedious discussion of both Web and standalone GUIs. BLT, canvas, cgi.
12. Tools and Examples--70pp
Excellent examples of PDE solvers, with a powerful GUI, but quite long and tedious.
A. Setting up the Required Software Environment--16pp
Wonderfully specific installation instructions!
B. Elements of Software Engineering--50pp
Python's strength! Very practical advice on modularity, documentation, coding style, regression-testing, version-control.
Strengths:
+ Downloadable py4cs package, esp. numpytools module
+ Great advice everywhere, e.g. CGI checklist, Pythonic programming, and trouble-shooting.
+ Concrete evidence for most assertions.
+ Very attractive presentation. Sturdy, high-quality cover, binding and pages. Brief, elegant code fragments (except in Chapter 12). Readable prose. No wasted space.
+ Available as 5MB pdf file, after purchase of hardcopy. Very nice.
+ Slides, installation instructions, and errata also at web site. Very professional.
My peeves:
- Not enough tables to be a useful manual.
- On p.428(#7) he points out that handling a raised exception is very slow. However, when I time his example with a positive argument, the try-except version is 20% faster (b/c the if clause is skipped), so he is actually giving bad advice for the general case. Luckily, he contradicts himself later, on page 685: "Exceptions should be used instead of if-else tests." The best advice: Avoid common exceptions in inner loops.
- The 10-page index is not as great as it at first seems. (See Martelli's Python in a Nutshell for a better one.)
- Pure interface functions should 'raise NotImplementedError', rather than 'return'.
- Exceptions should never be trapped mindlessly with 'except:'. That would hide your own SyntaxErrors!
- Too many exercises. (It's published as a textbook.) Since there are no answers, the exercises are useless for non-students. (See Lutz's Learning Python for effective exercises with answers.)
Overall rating:
This contains the best information on numerical programming in Python that I've seen. Though expensive, it could easily be your only Python book, given the excellent online documenation already available.
Average customer rating:
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Protein Geometry, Classification, Topology and Symmetry: A Computational Analysis of Structure (Series in Biophysics)
William R. Taylor , and
Andras Aszodi
Manufacturer: Taylor & Francis
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ASIN: 0750309857 |
Book Description
Using a geometric perspective, Protein Geometry, Classification, Topology, and Symmetry reviews and analyzes the structural principals of proteins with the goal of revealing the underlying regularities in their construction. It also reviews computer methods for structure analysis and the automatic comparison and classification of these structures with an analysis of the statistical significance of comparing different shapes. Following an analysis of the current state of protein classification, the authors explore more abstract geometric and topological representations, including the occurrence of knotted topologies. The book concludes with a consideration of the origin of higher-level symmetries in protein structure. The authors focus on simple geometric methods that are deterministic rather than probabilistic and on the more abstract simplifications of protein structure that allow a better understanding of the overall fold of the structure. Most of the methods described in this book have corresponding computer programs. These can be found (as C source code) at the ftp site of the Division of Mathematical Biology at the National Institute for Medical Research. This collection of ideas contains pedagogical material that make it ideal for post-graduate courses as well as new ideas and results essential for researchers investigating protein structures.
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Principles of Computational Fluid Dynamics
Pieter Wesseling
Manufacturer: Springer
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Similar Items:
-
Computational Methods for Fluid Dynamics
-
An Introduction to Computational Fluid Dynamics: The Finite Volume Method (2nd Edition)
-
What is Lean Six Sigma
Accessories:
-
Random Number Generation and Monte Carlo Methods (Statistics and Computing)
-
Symbolic-Numeric Computation (Trends in Mathematics)
-
Numerical Mathematics (Texts in Applied Mathematics)
ASIN: 3540678530 |
Book Description
The book is aimed at graduate students, researchers, engineers and physicists involved in fluid computations. An up-to-date account is given of the present state of the art of numerical methods employed in computational fluid dynamics. The underlying numerical principles are treated with a fair amount of detail, using elementary methods. Attention is given to the difficulties arising from geometric complexity of the flow domain. Uniform accuracy for singular perturbation problems is studied, pointing the way to accurate computation of flows at high Reynolds number. Unified methods for compressible and incompressible flows are discussed. A treatment of the shallow-water equations is included. A basic introduction is given to efficient iterative solution methods. Many pointers are given to the current literature, facilitating further study.
Customer Reviews:
good for the experienced.......2002-09-18
hi all,
this book is not appropriate for the beginners to CFD so i don't recommend it for the instructors who are looking for a introduction book. The tensor notation is also not easy to grasp for the not experienced. Besides the language of the book is not clear and not enough to let the reader apply without referring to another book. This is probably because the book has covered a lot of CFD concepts so deep explanation on every item is not provided.
However I would recommend this book for experienced CFD'ers since it covers many concepts and it can be used as a good referring material.
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