logo资料库

Python For ArcGIS 2016新书 无水印pdf 0分.pdf

发布时间：2022-06-15 发布人：admin 分类：说明书 资料大小：22.24M 资料格式：pdf 举报 版权申诉
第1页 / 共544页
第2页 / 共544页
第3页 / 共544页
第4页 / 共544页
第5页 / 共544页
第6页 / 共544页
第7页 / 共544页
第8页 / 共544页
资料共544页，剩余部分请下载后查看
    Cover
    Preface
    Acknowledgements
    Contents
    1: Introduction
    1.1 Python and GIS
    1.2 Sample Data and Scripts
    1.3 GIS Data Formats
    1.3.1 GRID Raster
    1.3.2 Shapefile
    1.3.3 dBASE Files
    1.3.4 Layer Files
    1.3.5 Geodatabase
    1.4 An Introductory Example
    1.5 Organization of This Book
    1.6 Key Terms
    2: Beginning Python
    2.1 Where to Write Code
    2.2 How to Run Code in PythonWin and PyScripter
    2.3 How to Pass Input to a Script
    2.4 Python Components
    2.4.1 Comments
    2.4.2 Keywords
    2.4.3 Indentation
    2.4.4 Built-in Functions
    2.4.5 Variables, Assignment Statements, and Dynamic Typing
    2.4.6 Variables Names and Tracebacks
    2.4.7 Built-in Constants and Exceptions
    2.4.8 Standard (Built-in) Modules
    2.5 Key Terms
    2.6 Exercises
    3: Basic Data Types: Numbers and Strings
    3.1 Numbers
    3.2 What Is a String?
    3.3 String Operations
    3.3.1 Find the Length of Strings
    3.3.2 Indexing into Strings
    3.3.3 Slice Strings
    3.3.4 Concatenate Strings
    3.3.5 Check for Substring Membership
    3.4 More Things with Strings (a.k.a. String Methods)
    3.5 File Paths and Raw Strings
    3.6 Unicode Strings
    3.7 Printing Strings and Numbers
    3.8 Key Terms
    3.9 Exercises
    4: Basic Data Types: Lists and Tuples
    4.1 Lists
    4.1.1 Sequence Operations on Lists
    4.1.2 List Methods
    4.1.3 The Built-in range Function
    4.1.4 Copying a List
    4.2 Tuples
    4.3 Syntax Check and Tracebacks
    4.4 Key Terms
    4.5 Exercises
    5: ArcGIS and Python
    5.1 ArcToolbox
    5.2 ArcGIS Python Resources
    5.3 Exporting Models
    5.4 Working with GIS Data
    5.5 ArcGIS + Python = arcpy
    5.6 arcpy Functions
    5.7 Environment Settings
    5.8 Key Terms
    5.9 Exercises
    6: Calling Tools with Arcpy
    6.1 Calling Tools
    6.2 Help Resources
    6.2.1 Tool Help
    6.2.2 Code Snippets
    6.3 Tool Parameters
    6.3.1 Linear Units
    6.3.2 Python Expressions as Inputs
    6.3.3 Multivalue Inputs
    6.3.4 Optional Parameters
    6.4 Return Values and Result Objects
    6.5 Spatial Analyst Toolbox
    6.5.1 Calling Spatial Analyst tools
    6.5.2 Importing spatial analyst
    6.5.3 Raster Calculator
    6.6 Temporary Feature Layers
    6.7 Using Variables for Multiple Tool Calls
    6.8 Calling Custom Tools
    6.9 A Word About Old Scripts
    6.10 Discussion
    6.11 Key Terms
    6.12 Exercises
    7: Getting User Input
    7.1 Hard-coding versus Soft-coding
    7.2 Using GetParameterAsText
    7.3 Using sys.argv
    7.4 Missing Arguments
    7.5 Argument Spacing
    7.6 Handling File Names and Paths with os Module Functions
    7.6.1 Getting the Script Path
    7.7 Key Terms
    7.8 Exercises
    8: Controlling Flow
    8.1 Outlining Workflow
    8.2 Key Terms
    8.3 Exercises
    9: Decision-Making and Describing Data
    9.1 Conditional Expressions
    9.1.1 Comparison Operators
    9.1.2 Equality vs. Assignment
    9.1.3 Logical Operators
    9.1.4 Membership Operators
    9.2 ArcGIS Tools That Make Selections
    9.2.1 Select by Attributes and Temporary Feature Layers
    9.3 Getting a Description of the Data
    9.3.1 Describe Object Properties
    9.3.2 Lists of Properties
    9.3.3 Using Specialized Properties
    9.3.4 Compound vs. Nested Conditions
    9.3.5 Testing Conditions
    9.4 Required and Optional Script Input
    9.5 Creating Output Directories
    9.6 Key Terms
    9.7 Exercises
    10: Repetition: Looping for Geoprocessing
    10.1 Looping Syntax
    10.1.1 WHILE-Loops
    10.1.2 FOR-Loops
    10.2 Nested Code Blocks
    10.3 Directory Inventory
    10.4 Indentation and the TabNanny
    10.5 Key Terms
    10.6 Exercises
    11: Batch Geoprocessing
    11.1 List GIS Data
    11.2 Specify Data Name and Type
    11.3 List Fields
    11.4 Administrative Lists
    11.5 Batch Geoprocess Lists of Data
    11.6 Debug: Step Through Code
    11.7 Key Terms
    11.8 Exercises
    12: Additional Looping Functions
    12.1 List Comprehension
    12.2 The Built-in enumerate Function
    12.3 The Built-in zip Function
    12.4 Walking Through Subdirectories
    12.5 Key Terms
    12.6 Exercises
    13: Debugging
    13.1 Syntax Errors
    13.2 Exceptions
    13.3 Logic Errors
    13.4 PythonWin Debugging Toolbar
    13.4.1 Using Breakpoints
    13.5 Running in Debug Mode
    13.6 PyScripter Debugging Toolbar
    13.7 Debugging Tips
    13.8 Key Terms
    13.9 Exercises
    14: Error Handling
    14.1 try/except Structures
    14.1.1 Using Named Exceptions
    14.1.2 Multiple except Blocks
    14.1.3 Error Handling Gotcha
    14.2 Geoprocessing and Error Handling
    14.2.1 Getting Geoprocessing Messages
    14.2.2 The arcpy Named Exception
    14.3 Catching Exceptions in Loops
    14.4 Discussion
    14.5 Key Terms
    14.6 Exercises
    15: User-Defined Functions
    15.1 A Word About Function Words
    15.1.1 How It Works
    15.1.2 The Docstring
    15.2 Custom Functions with Arguments
    15.2.1 Script Arguments vs. Functions Arguments
    15.2.2 Optional Arguments
    15.3 Returning Values
    15.3.1 A Common Mistake: Where Did the None Come from?
    15.3.2 Returning Multiple Values
    15.4 When to Write Functions
    15.4.1 Where to Define Functions
    15.5 Variables Inside and Outside of Functions
    15.5.1 Mutable Arguments Can Change
    15.5.2 Pass in Outside Variables
    15.6 Key Terms
    15.7 Exercises
    16: User-Defined Modules
    16.1 Importing User-Defined Modules
    16.2 Using Functions in Another Module
    16.3 Modifying User-Defined Modules (Reload!)
    16.4 Am I the Main Module? What's My Name?
    16.5 Time Handling Example
    16.6 Summary
    16.7 Key Terms
    16.8 Exercises
    17: Reading and Writing with Cursors
    17.1 Introduction to Cursors
    17.2 Reading Rows
    17.3 The Field Names Parameter
    17.4 The Shape Field and Geometry Tokens
    17.5 Looping with Cursors
    17.6 Locking
    17.6.1 The del Statement
    17.6.2 The with Statement
    17.7 Update Cursors
    17.8 Insert Cursors
    17.8.1 Inserting Geometric Objects
    17.9 Selecting Rows with SQL
    17.10 Key Terms
    17.11 Exercises
    18: Dictionaries
    18.1 Dictionary Terms and Syntax
    18.1.1 Access by Key, Not by Index
    18.1.2 Conditional Construct vs. Dictionary
    18.1.3 How to Modify: Update/Add/Delete Items
    18.2 Dictionary Operations and Methods
    18.2.1 Does It Have That Key?
    18.2.2 Listing Keys, Values, and Items
    18.2.3 Looping Through Dictionaries
    18.3 Populating a Dictionary
    18.3.1 Dictionaries and Cursors
    18.4 Discussion
    18.5 Key Terms
    18.6 Exercises
    19: Reading and Writing Text Files
    19.1 Working with file Objects
    19.1.1 The WITH Statement
    19.1.2 Writing Text Files
    19.1.3 Safe File Reading
    19.1.4 The os Working Directory vs. the arcpy Workspace
    19.1.5 Reading Text Files
    19.2 Parsing Line Contents
    19.2.1 Parsing Field Names
    19.3 Modifying Text Files
    19.3.1 Pseudocode for Modifying Text Files
    19.3.2 Working with Tabular Text
    19.4 Pickling
    19.5 Discussion
    19.6 Key Terms
    19.7 Exercises
    20: Working with HTML and KML
    20.1 Working with HTML
    20.1.1 Specifying Links
    20.1.2 Embedding Images
    20.1.3 HTML Lists
    20.1.4 HTML Tables
    20.1.5 Writing HTML with Python
    20.1.6 Parsing HTML with BeautifulSoup
    20.2 Fetching and Uncompressing Data
    20.2.1 Fetching HTML
    20.2.2 Fetching Compressed Data
    20.2.3 Expanding Compressed Data
    20.3 Working with KML
    20.3.1 The Structure of KML
    20.3.2 Parsing KML
    20.3.3 Converting KML to Shapefile
    20.4 Discussion
    20.5 Key Terms
    20.6 Exercises
    21: Classes
    21.1 Why Use OOP?
    21.2 Defining a Class
    21.3 Object Initialization and Self
    21.4 Using Class Objects
    21.5 Where to Define a Class
    21.6 Classes Within a Separate User-Defined Module
    21.7 Discussion
    21.8 Key Terms
    21.9 Exercises
    22: User Interfaces for File and Folder Selection
    22.1 A Simple Interface with raw_input
    22.2 File Handling with tkFileDialog
    22.2.1 Getting File and Directory Names
    22.2.2 Options
    22.2.2.1 File-Handling Options
    File Types
    Initial Directory
    Initial File
    Multiple Files
    Existing Directories
    22.2.2.2 Close the Tk Window
    22.2.3 Opening Files for Reading and Writing
    22.3 Discussion
    22.4 Key Terms
    22.5 Exercises
    23: ArcGIS Python GUIs
    23.1 Creating a Script Tool
    23.1.1 Printing from a Script Tool
    23.1.2 Making a Script Tool Button
    23.1.3 Pointing to a Script
    23.2 Creating a GUI
    23.2.1 Using Parameter Data Types
    23.2.2 Using Parameter Properties
    23.2.2.1 Type
    23.2.2.2 Direction
    23.2.2.3 Multivalue
    23.2.2.4 Default or Schema
    23.2.2.5 Environment
    23.2.2.6 Filter
    23.2.2.7 Obtained from
    23.2.2.8 Symbology
    23.3 Showing Progress
    23.4 Validating Input
    23.4.1 The ToolValidator Class
    23.4.1.1 Initializing Parameter Objects
    23.4.1.2 An updateMessages Example
    23.4.1.3 An initializeParameters Example
    23.4.1.4 An updateParameters Example
    23.5 Python Toolboxes
    23.5.1 Setting Up Parameters (getParameterInfo)
    23.5.2 Checking for Licenses (isLicensed)
    23.5.3 Validation (updateParameters and updateMessages)
    23.5.4 Running the Code (execute)
    23.5.5 Comparing Tools
    23.6 Discussion
    23.7 Key Terms
    23.8 Exercises
    24: Mapping Module
    24.1 Map Documents
    24.1.1 Map Name or'CURRENT' Map
    24.1.2 MapDocument Properties
    24.1.3 Saving Map Documents
    24.2 Working with Data Frames
    24.3 Working with Layers
    24.3.1 Moving, Removing, and Adding Layers
    24.3.2 Working with Symbology
    24.4 Managing Layout Elements
    24.5 Discussion
    24.6 Key Terms
    24.7 Exercises
    Index
    LauraTateosian Python For ArcGIS
    Python For ArcGIS
    Laura Tateosian Python For ArcGIS
    Laura Tateosian North Carolina State University Raleigh , NC , USA ISBN 978-3-319-18397-8 DOI 10.1007/978-3-319-18398-5 ISBN 978-3-319-18398-5 (eBook) Library of Congress Control Number: 2015943490 Springer Cham Heidelberg New York Dordrecht London © Springer International Publishing Switzerland 2015 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifi cally the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfi lms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specifi c statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Esri images are used by permission. Copyright © 2015 Esri. All rights reserved. Python is copyright the Python Software Foundation. Used by permission. PyScripter is an OpenSource software authored by Kiriakos Vlahos. Printed on acid-free paper Springer International Publishing AG Switzerland is part of Springer Science+Business Media (www.springer.com)
    Pref ace Imagine... You’ve just begun a new job as a GIS specialist for the National Park Service. Your supervisor has asked you to analyze some wildlife data. She gives you a specifi c example to start with: One data table (Bird Species) contains a list of over 600 bird species known to be native to North Carolina. Another data table (Bird Inventory) contains over 5,000 records, each corresponding to a sighting of a par- ticular bird. Your task is to clean the data, reformat the fi le for GIS compatibility, and summarize the data by determining what percent of the native Bird Species appear in the inventory and map the results. Once you complete this, she would like v
    vi Preface you to repeat this process for historical datasets for the last 10 years of monthly records. After that, the next assignment will be to answer the same question based on monthly species inventory datasets for fi sh and invertebrates. Performing this process manually for one dataset could be time consuming and error prone. Performing this manually for numerous datasets is completely imprac- tical. Common GIS tasks such as this provide a strong motivation for learning how to automate workfl ows. Python programming to the rescue! This analysis can be performed in single Python script. You could even use Python to automatically add the sighting loca- tions to ArcMap® and create a report with the results. You could also add a graphi- cal user interface (GUI) so that colleagues can run the analysis themselves on other datasets. This book will equip you to do all of these things and more. This book is aimed primarily at teaching GIS Python scripting to GIS users who have little or no Python programming experience. Topics are organized to build upon each other, so for this audience, reading the chapters sequentially is recom- mended. Computer programmers who are not familiar with ArcGIS can also use this book to learn to automate GIS analyses with the ArcGIS Python API, accessible through the arcpy package. These readers can quickly peruse the general Python concepts and focus mainly on the sections describing arcpy package functionality. The book comes with hundreds of example Python scripts. Download these along with the sample datasets so that you can run the examples and modify them to experiment as you follow the text. Where and how to download the supplementary material is explained in the fi rst chapter. Rolling your sleeves up and trying things yourself will really boost your understanding as you use this book. Remember, the goal is to become empowered to save time by using Python and be more effi cient in your work. Enjoy! Raleigh, NC Laura Tateosian
    Acknowledgements Thank you to the numerous people who have helped with this project. Over the years, many students have studied from drafts of this material and made suggestions for improvements. They have also expressed enthusiasm about how useful this knowledge has been for their work, which encouraged me to enable a wider distri- bution by writing this book. Special thanks to those who have reviewed the book, Pankaj Chopra of Emory University, Brian McLean of the North Carolina Department of Agriculture and Consumer Services, Holly Brackett of Wake Technical Community College, Rahul Bhosle of GIS Data Resources, Inc., and Makiko Shukunobe of North Carolina State University. Thank you to Sarah Tateosian for the artwork. Thank you to Tom Danninger, Michael Kanters, Joe Roise Justin Shedd, and Bill Slocumb of North Carolina State University and Cheryl Sams at the National Park Service for assis- tance with datasets. I also would like to thank Mark Hammond and Kiriakos Vlahos, the authors of PythonWin and PyScripter, respectively. Finally, I would like to express my gratitude for mentorship from Hugh Devine, Christopher Healey, Helena Mitasova, Sarah Stein, and Alan Tharp. vii
    分享到：
    赞 收藏

    相关推荐

    资料库

    后端

    共收录2142份资料，累计10个分类，关注成员有19位，主要包括：Perl,Docker,Delphi,VB,PHP,Java,C,C#,Python,C++

    热门标签

    Perl Docker Delphi VB PHP Java C C# Python C++

    最新资料