- •Matlab r2013a стр. 225
- •Continue Long Statements on Multiple Lines
- •Creating and Concatenating Matrices
- •Overview
- •Constructing a Simple Matrix
- •Entering Signed Numbers
- •Specialized Matrix Functions
- •Examples
- •Concatenating Matrices
- •Keeping Matrices Rectangular
- •Matrix Concatenation Functions
- •Examples
- •Generating a Numeric Sequence
- •The Colon Operator
- •Using the Colon Operator with a Step Value
- •Matrix Indexing
- •Accessing Single Elements
- •Linear Indexing
- •Functions That Control Indexing Style
- •Accessing Multiple Elements
- •Nonconsecutive Elements
- •The end Keyword
- •Specifying All Elements of a Row or Column
- •Using Logicals in Array Indexing
- •Logical Indexing – Example 1
- •Logical Indexing – Example 2
- •Logical Indexing with a Smaller Array
- •Single-Colon Indexing with Different Array Types
- •Indexing on Assignment
- •Arithmetic Operators
- •Arithmetic Operators and Arrays
- •Operator Precedence
- •Precedence of and and or Operators
- •Overriding Default Precedence
- •Relational Operators and Arrays
- •Relational Operators and Empty Arrays
- •Overview of the Logical Class
- •Logical Operators
- •Element-Wise Operators and Functions
- •Short-Circuit Operators
- •Precedence of and and or Operators
- •Symbol Reference
- •Asterisk — *
- •Filename Wildcard
- •Function Handle Constructor
- •Class Folder Designator
- •Line Continuation
- •Dynamic Structure Fields
- •Exclamation Point — !
- •Semicolon — ;
- •Array Row Separator
- •Output Suppression
- •Command or Statement Separator
- •Single Quotes — ' '
- •Square Brackets — [ ]
- •Fundamental matlab Classes
- •More About
- •Overview of Numeric Classes
- •Integers
- •Integer Classes
- •Creating Integer Data
- •Arithmetic Operations on Integer Classes
- •Largest and Smallest Values for Integer Classes
- •Integer Functions
- •Floating-Point Numbers
- •Double-Precision Floating Point
- •Single-Precision Floating Point
- •Creating Floating-Point Data
- •Creating Double-Precision Data
- •Creating Single-Precision Data
- •Arithmetic Operations on Floating-Point Numbers
- •Double-Precision Operations
- •Single-Precision Operations
- •Largest and Smallest Values for Floating-Point Classes
- •Largest and Smallest Double-Precision Values
- •Largest and Smallest Single-Precision Values
- •Accuracy of Floating-Point Data
- •Double-Precision Accuracy
- •Single-Precision Accuracy
- •Avoiding Common Problems with Floating-Point Arithmetic
- •Example 1 — Round-Off or What You Get Is Not What You Expect
- •Example 2 — Catastrophic Cancellation
- •Example 3 — Floating-Point Operations and Linear Algebra
- •Floating-Point Functions
- •Creating a Rectangular Character Array
- •Combining Strings Vertically
- •Combining Strings Horizontally
- •Identifying Characters in a String
- •Working with Space Characters
- •Expanding Character Arrays
- •String Comparisons
- •Comparing Strings for Equality
- •Comparing for Equality Using Operators
- •Categorizing Characters Within a String
- •Create a Structure Array
- •Access Data in a Structure Array
- •Concatenate Structures
- •Generate Field Names from Variables
- •Access Data in Nested Structures
- •Access Elements of a Nonscalar Struct Array
- •Create a Cell Array
- •Access Data in a Cell Array
- •Add Cells to a Cell Array
- •Delete Data from a Cell Array
- •Combine Cell Arrays
- •Pass Contents of Cell Arrays to Functions
- •Multilevel Indexing to Access Parts of Cells
- •Related Examples
- •What Is a Function Handle?
- •Creating a Function Handle
- •Maximum Length of a Function Name
- •The Role of Scope, Precedence, and Overloading When Creating a Function Handle
- •Obtaining Permissions from Class Methods
- •Example
- •Using Function Handles for Anonymous Functions
- •Arrays of Function Handles
- •Calling a Function Using Its Handle
- •Calling Syntax
- •Calling a Function with Multiple Outputs
- •Returning a Handle for Use Outside of a Function File
- •Example — Using Function Handles in Optimization
- •Preserving Data from the Workspace
- •Preserving Data with Anonymous Functions
- •Preserving Data with Nested Functions
- •Loading a Saved Handle to a Nested Function
- •Applications of Function Handles
- •Example of Passing a Function Handle
- •Pass a Function to Another Function
- •Example 1 — Run integral on Varying Functions
- •Example 2 — Run integral on Anonymous Functions
- •Example 3 — Compare integral Results on Different Functions
- •Capture Data Values For Later Use By a Function
- •Example 1 — Constructing a Function Handle that Preserves Its Variables
- •Example 2 — Varying Data Values Stored in a Function Handle
- •Example 3 — You Cannot Vary Data in a Handle to an Anonymous Function
- •Call Functions Outside of Their Normal Scope
- •Save the Handle in a mat-File for Use in a Later matlab Session
- •Parameterizing Functions
- •Overview
- •Parameterizing Using Nested Functions
- •Parameterizing Using Anonymous Functions
- •See Also
- •More About
- •Saving and Loading Function Handles
- •Invalid or Obsolete Function Handles
- •Advanced Operations on Function Handles
- •Examining a Function Handle
- •Converting to and from a String
- •Converting a String to a Function Handle
- •Converting a Function Handle to a String
- •Comparing Function Handles
- •Comparing Handles Constructed from a Named Function
- •Comparing Handles to Anonymous Functions
- •Comparing Handles to Nested Functions
- •Comparing Handles Saved to a mat-File
- •Overview of the Map Data Structure
- •Description of the Map Class
- •Properties of the Map Class
- •Methods of the Map Class
- •Creating a Map Object
- •Constructing an Empty Map Object
- •Constructing An Initialized Map Object
- •Combining Map Objects
- •Examining the Contents of the Map
- •Reading and Writing Using a Key Index
- •Reading From the Map
- •Adding Key/Value Pairs
- •Building a Map with Concatenation
- •Modifying Keys and Values in Map
- •Removing Keys and Values from the Map
- •Modifying Values
- •Modifying Keys
- •Modifying a Copy of the Map
- •Mapping to Different Value Types
- •Mapping to a Structure Array
- •Mapping to a Cell Array
Arithmetic Operations on Integer Classes
MATLAB can perform integer arithmetic on the following types of data:
Integers or integer arrays of the same integer data type. This yields a result that has the same data type as the operands:
x = uint32([132 347 528]) .* uint32(75);
class(x)
ans =
uint32
Integers or integer arrays and scalar double-precision floating-point numbers. This yields a result that has the same data type as the integer operands:
x = uint32([132 347 528]) .* 75.49;
class(x)
ans =
uint32
For all binary operations in which one operand is an array of integer data type (except 64-bit integers) and the other is a scalar double, MATLAB computes the operation using elementwise double-precision arithmetic, and then converts the result back to the original integer data type. For binary operations involving a 64-bit integer array and a scalar double, MATLAB computes the operation as if 80-bit extended-precision arithmetic were used, to prevent loss of precision.
For a list of the operations that support integer classes, see Nondouble Data Type Support (R2013a>MATLAB>Language Fundamentals>
Operators and Elementary Operations>Arithmetic>Arithmetic Operators + - * / \ ^ ') in the arithmetic operators reference page.
Largest and Smallest Values for Integer Classes
For each integer data type, there is a largest and smallest number that you can represent with that type. The table shown under Integers (R2013a>MATLAB>Language Fundamentals>Data Types>Numeric Types) lists the largest and smallest values for each integer data type in the "Range of Values" column.
You can also obtain these values with the intmax and intmin functions:
intmax('int8') % Или intmax int8. intmin('int8') % Или intmin int8.
ans = ans =
127 -128
If you convert a number that is larger than the maximum value of an integer data type to that type, MATLAB sets it to the maximum value. Similarly, if you convert a number that is smaller than the minimum value of the integer data type, MATLAB sets it to the minimum value. For example,
x = int8(300) x = int8(-300)
x = x =
127 -128
Also, when the result of an arithmetic operation involving integers exceeds the maximum (or minimum) value of the data type, MATLAB sets it to the maximum (or minimum) value:
x = int8(100) * 3 x = int8(-100) * 3
x = x =
127 -128
Integer Functions
See Integer Functions (R2013a>MATLAB>Language Fundamentals>Data Types>Numeric Types>Function Summary) for a list of functions most commonly used with integers in MATLAB.
R2013a>MATLAB>Language Fundamentals>Data Types>Numeric Types
Floating-Point Numbers
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Double-Precision Floating Point Single-Precision Floating Point Creating Floating-Point Data Arithmetic Operations on Floating-Point Numbers Largest and Smallest Values for Floating-Point Classes Accuracy of Floating-Point Data Avoiding Common Problems with Floating-Point Arithmetic Floating-Point Functions References |
MATLAB® represents floating-point numbers in either double-precision or single-precision format. The default is double precision, but you can make any number single precision with a simple conversion function.