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عدد المساهمات : 19004 التقييم : 35512 تاريخ التسجيل : 01/07/2009 الدولة : مصر العمل : مدير منتدى هندسة الإنتاج والتصميم الميكانيكى
| موضوع: كتاب Python for MATLAB Development الأحد 22 مايو 2022, 1:41 am | |
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أخواني في الله أحضرت لكم كتاب Python for MATLAB Development Extend MATLAB with 300,000+ Modules from the Python Package Index Albert Danial
و المحتوى كما يلي :
Table of Contents Chapter 1: Introduction 1 1.1 Learn Python Through MATLAB Equivalents . 2 1.2 Is Python Really Free? . 4 1.3 What About Toolboxes? . 5 1.4 Why Python Won’t Replace MATLAB . 5 1.5 Contents at a Glance . 6 1.6 I Already Know Python. How Do I Call Python Functions in MATLAB? . 8 1.7 The Recipes Don’t Work! MATLAB Crashes! (and What to Do About It) . 8 Chapter 2: Installation 11 2.1 Downloads 11 2.1.1 Match Your Python and MATLAB Versions! . 12 2.1.2 Verify That Python Runs 12 2.2 Post-Install Configuration and Checkout . 12 2.3 Creating and Running a Python Program 14 2.4 The Curse of Choice 15 2.5 Virtual Environments . 15 2.5.1 matpy, the Virtual Environment Used in This Book . 16 2.5.2 Commands to Manage Virtual Environments 17 2.5.3 Keeping Your Virtual Environment Current 18 About the Author xxi About the Technical Reviewers xxiii Preface xxv Acknowledgments xxviivi 2.6 ipython, IDEs . 20 2.6.1 Autoload Modules When ipython Starts 20 2.7 Python and MATLAB Versions Used in This Book 21 Chapter 3: Language Basics 23 3.1 Assignment . 23 3.1.1 Assignment with = . 23 3.1.2 In-Place Updates with +=, -=, and Others . 25 3.1.3 Walrus Operator, = 26 3.2 Printing 27 3.3 Indentation 28 3.3.1 Tabs 30 3.4 Indexing 30 3.4.1 Brackets vs. Parentheses . 30 3.4.2 Zero-Based Indexing and Index Ranges . 30 3.4.3 Start, End, and Negative Indices . 31 3.4.4 Index Strides . 32 3.4.5 Index Chaining 32 3.5 for loops 33 3.5.1 Early Loop Exits 36 3.5.2 Exit from Nested Loops 36 3.6 while Loops . 37 3.7 if Statements . 38 3.7.1 Boolean Expressions and Operators . 39 3.7.2 Range Tests 39 3.8 Functions 40 3.8.1 Pass by Value and Pass by Reference 41 3.8.2 Variable Arguments 43 3.8.3 Keyword Arguments . 44 Table of ConTenTsvii 3.8.4 Decorators 46 3.8.5 Type Annotation and Argument Validation 47 3.8.6 Left-Hand Side Argument Count . 49 3.9 Generators 50 3.9.1 yield, next() . 50 3.9.2 range() 51 3.10 Scoping Rules and Global Variables 52 3.11 Comments . 54 3.11.1 Docstrings 54 3.12 Line Continuation 56 3.13 Exceptions . 56 3.14 Modules and Packages . 58 3.14.1 Namespace . 58 3.14.2 def main() . 60 3.14.3 Module Search Path . 61 3.14.4 Installing New Modules 62 3.14.5 Module Dependency Conflicts and Virtual Environments . 63 Chapter 4: Data Containers 65 4.1 NumPy Arrays 66 4.2 Strings . 68 4.2.1 Strings, Character Arrays, and Byte Arrays . 68 4.2.2 String Operations 70 4.2.3 Formatting 74 4.2.4 Separate a String into Words 75 4.2.5 Tests on Strings 76 4.2.6 String Searching, Replacing with Regular Expressions 77 4.2.7 String Templates . 80 4.3 Python Lists and MATLAB Cell Arrays . 81 4.3.1 Initialize an Empty List . 82 4.3.2 Create a List with Given Values 83 Table of ConTenTsviii 4.3.3 Get the Length of a List 83 4.3.4 Index a List Item . 84 4.3.5 Extract a Range of Items 85 4.3.6 Warning—Python Index Ranges Are Not Checked! 87 4.3.7 Append an Item 90 4.3.8 Append Another List . 91 4.3.9 Preallocate an Empty List . 92 4.3.10 Insert to the Beginning (or Any Other Position) of a List . 93 4.3.11 Indexing Nested Containers 93 4.3.12 Membership Test: Does an Item Exist in a List? . 94 4.3.13 Find the Index of an Item 95 4.3.14 Apply an Operation to All Items (List Comprehension) 97 4.3.15 Select a Subset of Items Based on a Condition 98 4.3.16 How Many Times Does an Item Occur? 99 4.3.17 Remove the First or Last (or Any Intermediate) List Item . 99 4.3.18 Remove an Item by Value . 100 4.3.19 Merging Multiple Lists 101 4.3.20 Unmerging Combined Lists 103 4.3.21 Sort a List . 105 4.3.22 Reverse a List . 106 4.4 Python Tuples 106 4.5 Python Sets and MATLAB Set Operations . 109 4.6 Python Dictionaries and MATLAB Maps 111 4.6.1 Iterating over Keys 112 4.6.2 Testing for Key Existence 113 4.6.3 Iterating over Keys, Sorting by Key . 115 4.6.4 Iterating over Keys, Sorting by Value 117 4.6.5 Tuples As Keys 119 4.6.6 List Values 120 Table of ConTenTsix 4.7 Structured Data . 120 4.7.1 Method 1: namedtuple 121 4.7.2 Method 2: SimpleNamespace . 121 4.7.3 Method 3: Classes 122 4.7.4 Method 4: Data Classes 124 4.7.5 Enumerations . 132 4.8 Caveat: “=” Copies a Reference for Nonscalars! 134 Chapter 5: Dates and Times 137 5.1 Time 137 5.1.1 Current Time . 137 5.1.2 Time String Formats . 138 5.1.3 tic, toc; %timeit . 140 5.2 Dates . 141 5.2.1 datetime Objects to and from Strings . 141 5.2.2 Time Deltas . 142 5.3 Timezones . 144 5.3.1 UTC vs. Local Time . 146 5.4 Time Conversions to and from datetime Objects 148 5.4.1 Unix Epoch Seconds . 148 5.4.2 ISO 8601 Time String 149 5.4.3 Julian Date; Modified Julian Date; GPS Time . 150 5.5 zoneinfo in Python >= 3.9 151 5.5.1 List Available Timezones . 152 5.5.2 Date Increments Across Daylight Savings Transition 152 5.6 References 153 Chapter 6: Call Python Functions from MATLAB 155 6.1 Configure MATLAB to Recognize Python . 155 6.2 Does It Work? 157 6.3 Importing (and Reloading) Python Modules 159 6.4 Configure startup.m for Python Work 159 Table of ConTenTsx 6.5 Create Python Variables and Call Python Functions in MATLAB 161 6.5.1 Scalars 161 6.5.2 Lists and Cell Arrays . 163 6.5.3 Tuples . 165 6.5.4 Numeric Arrays . 166 6.5.5 Dictionaries and Structs . 168 6.5.6 Keyword Arguments . 171 6.5.7 Python-to-MATLAB and MATLAB-to-Python Variable Converters . 172 6.5.8 Traversing Generators . 172 6.5.9 Traversing zip() . 174 6.6 Modifying the Python Search Path Within MATLAB . 174 6.6.1 Extending sys.path with an Alias 175 6.6.2 Extending sys.path with insert() . 175 6.6.3 Extending sys.path with append() 176 6.7 Python Bridge Modules . 177 6.8 Debugging Python Code Called by MATLAB 178 6.9 Summary of Steps to Calling Python Code from MATLAB . 181 6.10 Call MATLAB from Python . 182 6.10.1 Install matlab.engine 182 6.10.2 Call Functions in a New MATLAB Session 183 6.10.3 Call Functions in an Existing MATLAB Session . 184 6.11 Other Mechanisms for MATLAB/Python Interaction 186 6.11.1 System Calls and File I/O 186 6.11.2 TCP/IP Exchange . 188 Chapter 7: Input and Output 189 7.1 Text Files . 189 7.1.1 Reading Corrupted Text Files with pathlib 191 7.1.2 Reading and Writing Numeric Data 192 7.1.3 I/O Exceptions . 192 7.1.4 Parsing Text 193 Table of ConTenTsxi 7.1.5 csv 199 7.1.6 XML . 203 7.1.7 YAML . 212 7.1.8 JSON . 213 7.1.9 ini 214 7.2 Recipe 7-1: Read YAML Files . 216 7.3 Recipe 7-2: Write YAML Files 217 7.4 Recipe 7-3: Read an ini File 218 7.5 Recipe 7-4: Write an ini File 220 7.6 Binary Files . 222 7.7 Excel .xls, .xlsx 225 7.7.1 Reading .xls and .xlsx Files 226 7.7.2 Writing .xlsx Files . 231 7.8 Recipe 7-5: Write an .xlsx File . 234 7.9 HDF5 . 237 7.9.1 Reading an HDF5 File . 237 7.9.2 Writing an HDF5 File . 239 7.9.3 Reading and Writing HDF5 Dataset Attributes 243 7.9.4 Iterating over All HDF5 Datasets . 244 7.10 NetCDF4 246 7.10.1 Reading a NetCDF4 File 246 7.11 SQLite 249 7.12 Recipe 7-6: CRUD with an SQLite Database 252 7.13 Pickle Files 255 7.14 MATLAB .mat Files 257 7.14.1 Inspecting the Contents of a .mat File 258 7.14.2 Reading a .mat File . 260 7.14.3 Writing a .mat File 262 7.14.4 mat Version 7.3 . 267 Table of ConTenTsxii 7.15 Command-Line Input 268 7.15.1 Python: sys.argv . 269 7.15.2 MATLAB: Function Arguments; varargin . 270 7.15.3 Python: argparse 271 7.16 Interactive Input 275 7.17 Receiving and Sending over a Network 276 7.17.1 HTTP, HTTPS 276 7.17.2 Python As a Web Server . 278 7.17.3 TCP/IP . 280 7.18 Recipe 7-7: TCP Server . 284 7.19 Interacting with Databases . 286 7.19.1 PostgreSQL . 286 7.19.2 MongoDB 290 7.20 Recipe 7-8: CRUD with a PostgreSQL Database . 293 7.21 Recipe 7-9: CRUD with a MongoDB Database . 296 7.21.1 Read . 298 7.21.2 Update 300 7.21.3 Delete . 300 7.22 Recipe 7-10: Interact with Redis . 300 7.23 Reference 305 Chapter 8: Interacting with the File System 307 8.1 Reading Directory Contents 308 8.2 Finding Files 309 8.3 Deleting Files 309 8.4 Creating Directories 310 8.5 Deleting Directories 310 8.6 Walking Directory Trees 311 Table of ConTenTsxiii Chapter 9: Interacting with the Operating System and External Executables 315 9.1 Reading, Setting Environment Variables . 315 9.2 Calling External Executables 317 9.2.1 Checking for Failures 319 9.2.2 A Bytes-Like Object Is Required . 321 9.3 Inspecting the Process Table and Process Resources 322 Chapter 10: Object-Oriented Programming 327 10.1 Classes 327 10.1.1 Private vs. Public 329 10.1.2 Custom Printers 330 10.1.3 Custom Exceptions . 331 10.2 Performance Implications . 333 Chapter 11: NumPy and SciPy 335 11.1 NumPy Arrays 335 11.1.1 Formatting NumPy Array Values . 336 11.1.2 Differences Between NumPy Arrays and MATLAB Matrices . 338 11.1.3 NumPy Data Types 341 11.1.4 Typecasting Scalars and Arrays 343 11.1.5 Hex, Binary, and Decimal Representations . 344 11.1.6 Creating Arrays . 345 11.1.7 Complex Scalars and Arrays . 355 11.1.8 Linear Indexing . 357 11.1.9 Reading/Writing Arrays to/from Text Files 359 11.1.10 Reading/Writing Arrays to/from Binary Files 360 11.1.11 Primitive Array Operations 368 11.1.12 Adding Dimensions . 371 11.1.13 Array Broadcasting . 373 11.1.14 Index Masks . 377 11.1.15 Extracting and Updating Submatrices 380 Table of ConTenTsxiv 11.1.16 Finding Terms of Interest 383 11.1.17 Object-Oriented Programming and Computational Performance . 388 11.2 Linear Algebra . 394 11.2.1 Linear Equations . 395 11.2.2 Singular Value Decomposition 397 11.2.3 Eigenvalue Problems 398 11.3 Sparse Matrices 401 11.3.1 Sparse Matrix Creation with COO, CSC, CSR . 401 11.3.2 Sparse Matrix Creation with LIL, DOK . 408 11.3.3 Sparse Matrix Creation with BSR, DIA 411 11.3.4 Test Matrices 413 11.3.5 Sparse Matrix I/O 415 11.3.6 Linear Algebra 418 11.3.7 Summary of Sparse Formats and Capabilities; Recommendations . 424 11.4 Interpolation 426 11.4.1 One-Dimensional Interpolation . 426 11.4.2 Two-Dimensional Interpolation . 429 11.4.3 Two-Dimensional Interpolation on a Grid 435 11.5 Curve Fitting 437 11.5.1 Linear Regression . 437 11.5.2 Fitting Higher-Order Polynomials . 438 11.5.3 Fitting to Models . 439 11.6 Recipe 11-1: Curve Fitting with differential_evolution() . 447 11.7 Regression 449 11.7.1 Ordinary Least Squares 449 11.7.2 Weighted Least Squares . 452 11.7.3 Confidence and Prediction Intervals . 453 11.8 Recipe 11-2: Weighted Least Squares in MATLAB 457 11.9 Recipe 11-3: Confidence and Prediction Intervals in MATLAB 460 Table of ConTenTsxv 11.10 Finding Roots 463 11.10.1 Univariate . 463 11.10.2 Multivariate . 465 11.11 Recipe 11-4: Solving Simultaneous Nonlinear Equations . 466 11.12 Optimization 467 11.12.1 Linear Programming . 468 11.12.2 Simulated Annealing . 474 11.13 Differential Equations 479 11.14 Symbolic Mathematics 481 11.14.1 Defining Symbolic Variables . 482 11.14.2 Derivatives 482 11.14.3 Integrals . 483 11.14.4 Solving Equations . 484 11.14.5 Linear Algebra 484 11.14.6 Series . 486 11.15 Recipe 11-5: Using SymPy in MATLAB 486 11.16 Recipe 11-6: Compute Laplace Transforms 487 11.17 Unit Systems . 488 11.17.1 Defining Units in pint 489 11.18 Recipe 11-7: Using pint in MATLAB . 491 11.19 References 492 Chapter 12: Plotting 493 12.1 Point and Line Plots 493 12.1.1 Saving Plots to Files . 496 12.1.2 Multiple Plots per Figure 497 12.1.3 Date and Time on the X Axis . 499 12.1.4 Double Y Axes . 500 12.1.5 Histograms . 502 12.1.6 Stack Plots 504 Table of ConTenTsxvi 12.2 Area Plots 505 12.2.1 imshow() . 505 12.3 Animations 510 12.4 Plotting on Maps with Cartopy 514 12.4.1 Points 514 12.4.2 Lines . 517 12.4.3 Area 519 12.4.4 MATLAB and Cartopy 527 12.4.5 Avoid matplotlib’s Qt Backend in MATLAB! . 529 12.5 Recipe 12-1: Drawing Lines on Maps with Cartopy 529 12.6 Recipe 12-2: Overlay Contours on Globe with Cartopy . 531 12.7 Recipe 12-3: Shade Map Regions by Value with Cartopy . 532 12.8 Plotting on Maps with GeoPandas 535 12.9 Making Plots in Batch Mode . 535 12.10 Interactive Plot Editing 536 Chapter 13: Tables and Dataframes 539 13.1 Loading Tables from Files . 540 13.2 Table Summaries 543 13.2.1 Table Size, Column Names, Column Types 543 13.2.2 summary() and .info()/.describe() . 545 13.2.3 groupsummary() and .value_counts() . 546 13.2.4 head() and tail() 546 13.3 Cleaning Data 547 13.3.1 Renaming Columns 547 13.3.2 Changing Column Data Types . 548 13.3.3 Changing Column Data . 549 13.3.4 Making Timestamps from Strings 550 13.4 Creating Tables Programmatically 550 13.5 Sorting Rows . 551 Table of ConTenTsxvii 13.6 Table Subsets 552 13.6.1 All Rows, Selected Columns . 552 13.6.2 All Columns, Selected Rows . 553 13.6.3 Selected Rows, Selected Columns . 553 13.6.4 Filter Rows by Conditional Operations 555 13.7 Iterating over Rows . 555 13.8 Pivot Tables . 556 13.8.1 Single-Level Aggregation . 556 13.8.2 Multilevel Aggregation 558 13.9 Adding Columns 558 13.10 Deleting Columns 560 13.11 Joins Across Tables . 561 13.12 GeoPandas 564 13.13 Recipe 13-1: Maps with GeoPandas . 569 13.14 References 573 Chapter 14: High Performance Computing 575 14.1 Paths to Faster Python Code . 576 14.2 Reference Problems 577 14.2.1 The Mandelbrot Set 577 14.2.2 A 2D Finite Element Solver . 579 14.3 Reference Hardware and OS . 581 14.4 Baseline Performance . 582 14.4.1 Mandelbrot Set Performance . 582 14.4.2 FE Solver Performance . 582 14.5 Profiling Python Code 583 14.5.1 Scalene . 584 14.5.2 Austin and FlameGraph 586 14.6 Multicore Computation with multiprocessing . 589 14.7 Vectorization . 591 Table of ConTenTsxviii 14.8 Cython . 594 14.8.1 Python Compiled with Cython . 595 14.8.2 Parallel for Loops with Cython 598 14.8.3 Cython Performance . 599 14.9 Pythran 599 14.9.1 Examples of Signature Comments . 600 14.9.2 Python Compiled with Pythran; Parallel for Loops 601 14.9.3 Pythran Performance 603 14.10 Numba . 604 14.10.1 Parallel for Loops with Numba . 606 14.10.2 Numba Keyword Arguments nopython, fastmath . 607 14.10.3 Numba Performance 607 14.10.4 Numba Limitations . 607 14.11 f2py . 608 14.12 Recipe 14-1: Accelerating MATLAB with Python on a Single Computer 612 14.12.1 Compile Python Modules in a MATLAB-Friendly Virtual Environment 612 14.12.2 MATLAB + Cython . 612 14.12.3 MATLAB + Pythran 613 14.12.4 MATLAB + Numba 613 14.12.5 MATLAB + f2py . 614 14.12.6 MATLAB + Python Performance Results . 614 14.13 Distributed Memory Parallel Processing with Dask 615 14.13.1 Parallel MATLAB . 616 14.13.2 Dask Execution Paradigm and Performance Expectations . 617 14.13.3 Example 1: Sum of Prime Factors on One Computer 618 14.13.4 Setting Up a Dask Cluster on Multiple Computers 625 14.13.5 Example 2: Sum of Prime Factors on Multiple Computers . 626 14.13.6 Example 3: A Gigapixel Mandelbrot Image . 628 14.13.7 Example 4: Finite Element Frequency Domain Response . 634 Table of ConTen Index A Altair, 493 Anaconda, 203 Animations ball bouncing, 511–513 key elements, 510, 511 matplotlib, 510 Application program interface (API), 276 arange() function, 52 Area plots imagesc(), 506 imshow(), 506, 507 bilinear interpolation, 507, 508 prefixes, 508, 509 astimezone() method, 150 Austin, 586–589 B Basic linear algebra subroutines (BLAS), 602 Block compressed row (BSR), 411 Bokeh, 493 Bridge modules, 177 built-in scope, 52 C Cartopy cartographic transformation, 514 drawing lines, map, 529, 530 MATLAB, 527, 528 overlay contours, globe, 531, 532 projection functions, 514 shade map regions, value, 532–534 Cell arrays, 163, 165 Class circle, 327 constructor method, 329 custom exceptions, 331, 333 custom printers, 330 __init__() function, 328 instances, 329 private vs. public, 329, 330 variables, 327 Cloud service, 644 Coiled’s cloud performance, 644, 645 running, 644 Command-line input argparse, 271, 273 function arguments, 270 sys module, 269, 270 Comma-separated value (CSV), 199, 539 Comments block comment, 54 definition, 54 docstrings, 54 Communication-intensive parallel program, 576 Compressed Sparse Column (CSC), 406 Compressed Sparse Row (CSR), 406 Computer Algebra System (CAS), 481 conda package manager, 62 Conda environment, 612 conda-meta directory, 19 conda update, 12 Converters, 172 create_dataset() function, 239, 240 Create, read, update, delete (CRUD), 252, 254, 255 Curve fitting differential_evolution() bridge module, 447 compute_ABCD() function, 448 cost function, 447 matlab.engine, 447 py module, 447 solution, 449 fit models curve_fit(), 442–444 differential_evolution(), 446 differential_evolution(), 446 r2_score() function, 442 scipy.optimize module, 440 scipy.optimize.curve_fit(), 440 test data, 441 linear regression, 437 polynomials, 438, 439 Cython, 594 MATLAB, 612 parallel for loop, 598 performance, 599 Python, 595, 597, 598 D Dask, 615 execution paradigm, 617, 618, 620 Mandelbrot set, 628, 633 multiple computer, 625–627 parallel MATLAB, 616 prime factor, 623 scheduler, 622, 639 single computer, 625 Data cleaning, 547 columns changing, 549, 550 data types, 548 renaming, 547 timestamps, 550 Data classes convenience mechanism, 124 dynamic modification, 128, 129 entity relationship, 127 field values, 125, 126 calling mag(), 125 MATLAB vs. Python, 124 point, 124 traversing, 130 type enforcement, 124 type validation, Pydantic, 131, 132 Data containers, 6 MATLAB, 65 nonscalars, 134, 135 Python, 65 Dataframes., see Tables Dates datetime, 141 string, 141 time deltas, 142, 143 datestr() function, 138 datetime functions, 147 datetime module, 141 datetime object definition, 148 ISO 8601 time string, 149, 150 Julian date, 150, 151 Unix epoch seconds, 148, 149 INDEX689 Debugging Python code diary mode, 180, 181 do_work(), 179, 180 functions, 178, 179 logging, 178 steps, 181, 182 trace module, 178 deepcopy() function, 658 Dictionaries add keys, 170, 171 creation, 170 datasets, 111 iterating over keys for key in dict, 112 sorting by key, 115–117 sorting by values, 117–119 key existence .get() method, 113, 114 .get() method, 114 key collision, 115 KeyError, 113 .setdefault() method, 113, 114 test_key, 113 limitation, 170 vs. lists, 112 Python country-to-capital city relationship, 112 subscript, 112 struct, 169 tuples, 119 values, 120 Dictionary of keys (DOK), 408 Differential equations, 479, 480 Direct frequency, 652, 654 Directories contents, 308 creation, 310 deletion, 310 expressions, 308 trees .csv files, 311 dir(), 311 find() functions, 313 generators, 313 os.walk(), 311 output, 312 printing, 312 traversing, 311 .xlsx files, 311, 313 Duffing oscillator equation, 479 E eig() eigenvalue function, 49 enclosing scope, 52 enumerate() function, 35 Enumerations, 132, 133 env command, 14 Excel .xls, .xlsx definition, 225 extract columns, 229 extract rectangular block, 230, 231 extract rows, 228, 229 get worksheet names, 227 reading files, 226, 227 writing, 231, 233 writing file, 233–236 Exceptions, 56, 57 executemany() function, 252 External executables bytes-Like Object, 321 CalledProcessError, 319 ffmpeg, 319 os.environ object, 317 INDEX690 Result, 318 Result.returncode, 319 Status, 318 subprocess module, 317 subprocess.CalledProcessError, 321 subprocess.run(), 317, 319, 321 subsystem.run(), 319 system() function, 317 F f2py command, 608, 610, 614 File system deletion, 309, 310 finding, 309 MATLAB, 307, 308 Python, 307, 308 Finite element (FE), 579, 634 FlameGraphs, 587–589 For loops definition, 33 examples, 34 exits, 36 nested loops, 36, 37 variables, 34 Fortran-compiled module, 611 Functions comparison operators, 39 decorators, 46 keyword arguments, 44, 45 left-hand side argument count, 49 lists/dicts/arrays, 42, 43 pass by values/pass by reference, 41 type annotation/argument validation, 47, 48 variable arguments, 43 G Generators definition, 50 range(), 51, 52 yield, next(), 50 geo* functions, 514 GeoPandas create plot, 566 dataframes, 565 data type, 566 geographic data, 564 join, 566 maps bridge functions, 571, 572 bridge module, 569 issues, 573 iterrows(), 570, 571 plotting, 535 read_file() function, 565 shapefile, 565 Zillow research, 564 zip code, 567, 568 global keyword, 52 global scope, 52 H h5dump command-line utility, 241 HDF5 datasets, 244 netcdf4, 246, 248 reading files, 237, 239 reading/writing dataset attributes, 243 writing files, 239–243 Hierarchical Data File (HDF), 237 High performance computing (HPC), 7, 575 External executables (cont.) INDEX691 baseline performance FE, 582, 583 Mandelbrot set, 582 multiprocessing, 589 profiling tools austin, 586–589 drawbacks, 584 flameGraphs, 587–589 scalene, 584, 586 reference hardware/OS, 581 reference problems, 577 FE, 579, 580 Mandelbrot set, 577 I If statements Boolean expressions/operators, 39 range tests, 39 variables, 38 imshow() function, 505 Indentation brackets/parentheses, 30 index chaining, 32 indexing methods, 30 index strides, 32 MATLAB and Python, 29 start/end/negative indices, 31 Tabs, 30 zero-based indexing/index ranges, 30 Index masks creation, 378, 379 mathematical operations, 377, 378 uses, 379 input() function, 275 Installation, MATLAB creating/running Python program, 14 downloads, 11, 12 package, 11 post-install configuration/ checkout, 12, 13 toolboxes, 15 Interpolation one-dimensional extrapolation, 426 linear, 426, 427 spline, 427, 428 two-dimensional cubic/linear methods, 434 evaluation, 432, 433 function, 429 grid, 435–437 griddata(), 430 meshgrid(), 430 np.meshgrid(), 431, 432 testing, 429 values, 429 Ints, 223 ipython, IDEs application navigator, 20 autoload modules, 20 version, 21 iterables, 41 iterrows(), 53 J JavaScript Object Notation (JSON) complex data structures, 187 MATLAB to Python, 187 Python to MATLAB, 187, 188 Just-in-time (JIT), 604, 657 K Keyword arguments, 171, 172 INDEX692 L Lambda function, 116 Linear algebra eigenvalue problems, 398–400 linear equations, 395, 396 MATLAB vs.Python, 394, 395 SVD, 397, 398 Linear indexing, 357–359 Linear programming (LP) problems integer-valued, 469 linprog(), 468 bridge module, 472 coefficients, 469 MATLAB, 471, 472 Python solution, 470 relationships, 469 sol object, 470 solution status, 470 objective function, 468 PuLP module, 473 server properties, 468 Linux, 316 list() function, 194 List of lists (LIL), 408 Lists, 163, 165 local scope, 52 Local variables, then enclosing, global, and built-in (LEGB), 52 Long expressions, 56 M macOS, 316 Mandelbrot set, 577 MATLAB .mat files data containers, 257–260 definition, 257 reading files, 260, 261 v7.3, 267, 268 writing files, 262, 264–267 MATLAB Anaconda’s Python distribution, 157 call functions existing session, 184, 185 new session, 183 cell arrays, 81 configuration Linux/macOS, 157 matlab command, 155 path, 156 pyenv command, 156 Windows, 156, 157 container.Map, 168 definition, 1 eigensolvers, 398, 399 environment variables, 158 errors, 158 functions, 3, 4 horzcat() function, 91 hybrid environment, 157 incompatible library function, 157 install engine, 182 install module, 183 libraries, 8 lower-level libraries, 158 maps, 111 matpy, 8, 9 py module, 1 Python, 2, 6 pyversion(), 183 software, 9 software engineering, 157 toolboxes, 5 MATLAB-native variable, 650 MATLAB performance, 612 MATLAB/Python interaction INDEX693 file I/O, 186 system calls, 186 TCP/IP exchange, 188 matplotlib module, 9, 493 Matrix slices, 656 maxsplit keyword, 194 MB() function, 606, 648, 651 Mixed-type mathematical expressions, 655 Modules/packages definition, 58 def main(), 60 dependency conflicts/virtual environments, 63 installation, 62 namespace, 58, 59 search path, 61 MongoDB, 290–292 bridge module, 296 delete, 300 read, 298, 299 updates, 300 mset function, 301 multiprocessing module, 589 N Natural Earth project, 523, 564 ncinfo command-line tool, 246 Network communication protocols HTTP, HTTPS, 276, 277 MATLAB client, 283, 284 Python as a web server, 278 TCP/IP, 280–283 TCP server, 284, 286 Numba, 604 keyword argument, 607 limitations, 607, 608 Mandelbrot program, 605 MATLAB, 613 parallel for loop, 606 performance, 607 Python, 604 Numeric arrays constants, 167 conversion, 166 MATLAB commands, 167 functions, 167 single-precision floats, 166 type, 166 NumPy definition, 335 eigensolvers, 398, 399 NumPy and SciPy, 7 NumPy arrays decimal to binary, 344 hexadecimal to decimal, 345 MATLAB, 66 scalars, 339 operations addition/subtraction, 368 elementwise, 369 Hermitian, 370 transpose, 370 terms of interest find() function, 388 smallest term, 385 sorted data, 387 text files, reading, 359 typecasting, 343 NumPy arrays binary files endian conversions, 366, 368 metadata, 362, 363 reading, 361, 363–365 INDEX694 binary to decimal, 344 broadcasting definition, 373 distance matrix, 375–377 memory, 374 normalize vectors, 374, 375 rules, 373 complex scalars, 355–357 creation diagonal matrices, 348 identity matrices, 348 inflating matrices, 353 linspace, 351 logspace, 351 meshgrid, 352 nan() function, 347 np.array() function, 345 ones, 346 random, 350 range() function, 347 stacking, 351, 352 test matrices, 354, 355 triangle matrices, 349 zeros() function, 346 data types, 341, 342 decimal to hexadecimal, 344 definition, 335 dimensions, 371, 373 dtype argument, 68 dtype argument, 68 formatting, 336, 337 import, 66 MATLAB, 66 vs. MATLAB matrices column major, 339, 340 dimensions, 338, 339 numeric literals, 338 .resize() method, 340, 341 scalars, 339 np.array() function, 67 NumPy module, 335 operations bitwise, 369 elementwise, 368 Hermitian, 370 multiplication, 370, 371 transpose, 370 submatrices extraction, 380–383 updation, 380–383 terms of interest closest term, 386 find() function, 387 longest term, 385, 386 sorted data, 387 values, 383 text files reading, 359 writing, 360 typecasting, 343 whos command, 67 O Object-oriented programming (OOP) class method, 391–394 collisions, 389, 390 computational performance, 388 performance implications, 333 simulation, 388 vectorized solution, 394 open() function, 189 Operating system computer’s hardware, 322 CPU cycles, 323 NumPy arrays (cont.) INDEX695 environment variables, 315, 316 independent method, 322 MATLAB, 315, 316 memory, 322, 323 numerical analyses, 322 program iterates, 323 Python, 315, 324 random vector, 325 setenv() function, 316 simulations, 322 TypeError error, 316 P pack() function, 281 Pandas, 539, 540 Parallel program, 643 pathlib.Path() object, 191 Pickle files, 255–257 pinned, 19 Pivot tables multilevel aggregation, 558 single-level aggregation, 556, 557 Plotly, 493 Plots batch mode, 535, 536 editing, 536, 537 line, 493 point, 493 stack, 504, 505 Plotting areas, 519 Cartopy, 514 exploration, 514 lines, 517, 519 points, 514–516 Point/line plots date and time, 499, 500 histograms, 502–504 MATLAB, 493, 494 matplotlib commands, 495 metric vs. US customary, 500 Python, 493–495 saving command, 497 formats, 496 MATLAB, 496 matplotlib’s function, 496 Python, 496 subplots() function, 497, 499 Young’s modulus, 500, 501 PostgreSQL, 286–289, 293–295 prange() function, 598 Prime factors, 618, 620 print() function, 190 purchase_orders, 296 py2mat() function, 299 Python deployment, 4 distributions, 4 list, 81 .append() method, 90, 91 comprehension, 98 .count() method, 99 creation, 83 empty, 82, 92 .extend () method, 91 extract range, 85–87 find() function, 95, 96 IndexError, 87–89 indexing, 84, 85 .insert() method, 93 length, 83 list comprehension, 97, 98 INDEX696 membership test, 94, 95 merging, 101–103 methods, 81, 82 nested containers, 93, 94 .pop() method, 99, 100 .remove() method, 100, 101 .reverse() method, 106 sorting, 105 subset of items, 98, 99 unmerging, 103, 104 ValueError exception, 96 zipped, 174 modules, importing, 159 multiple computers, 646 substantial cost, 4 sys.path, 174 alias, 175 append(), 176, 177 insert(), 175, 176 tuples creation, 107 hashable, 107 parentheses, 108 vs. Python lists, 106 wrapping, 108 variables, 81 Python Package Index (PyPI), 62 Python-specific aspects, 576 Pythran, 599 comments, 600 MATLAB, 613 parallel for loop, 601, 603 performance, 603 Q Qt library, 529 R range() function, 51 .ravel() method, 640 Read-evaluate-print-loop (REPL), 13 readmatrix() function, 200 read_text() method, 191 Redis, 300, 301, 303–305 Regression confidence intervals, 453, 454, 456, 457, 460–462 least squares ordinary, 449, 451, 452 weighted, 452, 453, 457–459 prediction intervals, 453, 454, 456, 457, 460–462 Regular expressions, 195 Remote computer, 638 re.split(), 195 Roots multivariate, 465, 466 nonlinear equations, 466, 467 univariate, 463, 464 rstrip() method, 190 S Satellite, 635 save() command, 258 Scalars, 161–163 Scalene, 584, 586 SciPy coordinate format (COO), 402 definition, 335 eigensolvers, 398, 399 functions, 415 optimization module, 463 scipy.interpolate module, 427 scipy.optimize module, 467 Python (cont.) INDEX697 sparse module, 401 sparse matrix, 401 scipy.io.loadmat(), 268 Seaborn, 493 Sea surface temperature (SST) CARTOPY_USER_ BACKGROUNDS, 520 data, 520, 521 earth_veg_index.jpeg, 520 orthographic projection, 522 Second-order differential equation, 635 .send() and .recv() functions, 281 Set operations MATLAB, unique() function, 109–110 Python, .issuperset() method, 110 iteration/casting, 109, 110 set() function, 109 Simulated annealing Annealer-derived class, 474 automatic estimator, 475, 477 compute_distances() function, 475 concept, 474 .distance_matrix attribute, 474 energy() method, 474 parameters, 475 requirements, 474 .state attribute, 474 TSP, 440, 446, 477, 478 Singular value decomposition (SVD), 397, 398 sleeper() and add_numbers(), 46 Solver code, 641 Solver function, 638 South American wheat production, 527 add_geometries() function, 524 borders, 524 Cartopy, 523 cases, 525, 526 country names, 523, 524 database, 523 low resolution file, 523 polygonal regions, 524 Sparse matrices BSR, 411–413 creation COO, 402, 403 csr_matrix(), 401 dense matrix, 401, 402 dense representation, 403 COO dimension, 404 index values, 405 indices/values, 405, 406 row/columns, 404 sparse() function, 404 .sum_duplicates() method, 405 CSC, 406, 407 CSR, 406, 407 definition, 401 diagonal (DIA), 411–413 DOK, 410 formats/capabilities, 424, 425 input and output (I/O) component parts, 416, 417 mat files, 416 pickle files, 418 LIL, 408–410 linear algebra eigenvalue problem, 422, 423 finite element–based symmetric, 418 linear equations, 421, 422 matrix summary, 419, 420 matrix-vector product, 420 scipy.sparse.linalg module, 418 Sturm sequence number, 423 INDEX698 MATLAB, 401 SciPy, 401 .split() method, 195 SQLite, 249–252 Stack plots, 504, 505 start_new_order() function, 296 startup directory, 21 startup.m file, 159–161 strftime() function, 141 Strings byte arrays, 68, 69 character arrays, 68, 69 formatting, 74, 75 operations append, 71, 72 commands, 70 conversion, 72 length, 71 key, 70 method chaining, 73, 74 repeat, 72 replace characters, 73 regular expressions purposes, 77 replacing, 79, 80 separation, 78 substrings, 78, 79 splitting, 75, 76 templates, 80, 81 testing equality, 76 starting characters, 77 substring, 77 trailing characters, 76 struct() function, 299 struct’s pack() function, 225 Structured data classes, 122, 123 hasattr() function, 122 isfield() function, 122 namedtuple method, 121 SimpleNamespace method, 121 Structured Query Language (SQL), 249, 250 Symbolic mathematics char attribute, 487 collisions, 486 derivatives, 482 integrals, 483 laplace_transform() function, 487 linear algebra, 484, 486 s.doit(), 487 series, 486 solving equations, 484 SymPy code generators, 481 variables, 482 sys.exc_info() function, 57 T Tables columns adding, 558, 559 deletion, 560, 561 names, 543, 544 types, 543, 544 creation, 550 .describe() method, 545 groupsummary() method, 546 head() function, 546 indexing, 552 .info() method, 545 joins flavors, 561 food costs, 563 Sparse matrices (cont.) INDEX699 food type, 561, 562 how= keyword, 562 wxp column, 563, 564 loading MATLAB’s table, 541 pets.csv file, 540 read_csv(), 543 string/floating-point types, 542 rows iteration, 555, 556 sorting, 551 size, 543, 544 subsets all columns, selected rows, 553 all rows, selected columns, 552 filter rows, conditional operations, 555 selected rows, selected columns, 553, 555 summary() function, 545 tail() function, 546 .value_counts() method, 546 Test matrices arrow matrix, 415 random sparse arrays, 413 spy() function, 414 Text files assignments, 190 binary files, 222–225 CSV definition, 200 NumPy’s genfromtxt() function, 203 pandas, 201, 202 python module, 200 ini files, 214–216 I/O exceptions, 192 JSON, 213 MATLAB/Python, 189 parsing text operations, 193 regex’s, 195 re.split(), 195 splitting string, substring, 194 string search, 196–198 stripping whitespace, 193 pathlib, reading corrupted files, 191 reading/writing numeric arrays, 192 read ini file, 218, 219 STDOUT, 189 write ini file, 220, 221 write YAML files, 217 XML lxml modules, 203 with namespaces, 207–209 pretty-printing, 211 without namespaces, 203, 204, 206 writing XML, 210 YAML, 212 Time current, 137 definition, 137 module, 137 string formats, 138, 139 tic/toc/%timeit, 140 time.strftime() function, 137 time.time() function, 137 Timezones, 144, 147 .tobytes() method, 281 to_datetime() function, 550 .to_excel() method, 231 .tofile() method, 223 Traveling Salesman Problem (TSP), 474 Traversing generators, 172, 173 Tuples, np.ones() function, 165, 166 Two-dimensional array, 640 INDEX700 U Unit systems defining units, 489, 490 MATLAB, 491 metric values, 488 NumPy array, 489 pint/Symbolic Toolbox, 488, 489 Python, 491 Unix epoch seconds, 148 urlread() function, 278 V Variable assignment =, 23, 24 in-place update operators, 25 languages, 23 print expressions, 27, 28 walrus operator, 26 Vectorization, 592 Virtual environments Anaconda, 18, 19 commands, 17 definition, 15 matpy, 16 open source languages, 15 W which command, 62 While loops, 37 whosmat() function, 259 write() method, 190 X $max aggregation, 298 Y yield keyword, 50 Young’s modulus, 500 Z zoneinfo, 151, 152 zoneinfo module, 144 #ماتلاب,#متلاب,#Matlab,
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