e9571_math_lib Usage Examples

This document demonstrates the usage of the e9571_math_lib module in a Rust program, designed for casino-related mathematical operations such as calculating percentage changes, distances, and validating thresholds.

Source Code Example

Below is a Rust program showcasing various mathematical functions from the e9571_math_lib module. The code performs calculations relevant to casino scenarios, such as comparing betting amounts or validating changes.

use e9571_math_lib::e9571_math_lib::*;

fn main() {
    // Example 1: Count_Add
    println!("=== Count_Add ===");
    println!("Percentage change (Real=110, Close=100): {}", count_add("110", "100"));
    println!("Percentage change (Close=0): {}", count_add("110", "0"));

    // Example 2: Count_Amo_Add
    println!("\n=== Count_Amo_Add ===");
    println!("Percentage change (Real=110, Close=100): {}", count_amo_add("110", "100"));
    println!("Percentage change (Close=0): {}", count_amo_add("110", "0"));

    // Example 3: Count_Add_float
    println!("\n=== Count_Add_float ===");
    println!("Percentage change (Real=110, Close=100): {}", count_add_float(110.0, 100.0));
    println!("Percentage change (Close=0): {}", count_add_float(110.0, 0.0));

    // Example 4: IsWithinFivePercent
    println!("\n=== IsWithinFivePercent ===");
    println!("Within 5% (100, 104): {}", is_within_five_percent(100.0, 104.0));
    println!("Within 5% (100, 106): {}", is_within_five_percent(100.0, 106.0));

    // Example 5: CalculateDistance
    println!("\n=== CalculateDistance ===");
    println!("Distance (100, 110): {}", calculate_distance(100.0, 110.0));
    println!("Distance (-10, 10): {}", calculate_distance(-10.0, 10.0));
}

Explanation of Functions

The e9571_math_lib module provides mathematical utility functions for casino applications, such as calculating percentage changes, validating thresholds, and computing distances between values.

1. count_add:

   • Calculates the percentage change between two values provided as strings (real and close).
   • Use Case: Comparing actual and expected betting amounts in string format.

2. count_amo_add:

   • Similar to count_add, calculates percentage change for string inputs, possibly with different handling (e.g., for specific amount formats).
   • Use Case: Validating changes in aggregated bet amounts.

3. count_add_float:

   • Calculates the percentage change between two floating-point values (real and close).
   • Use Case: Precise calculations for financial data like payouts or balances.

4. is_within_five_percent:

   • Checks if two floating-point values are within 5% of each other.
   • Use Case: Validating if a bet or payout is within an acceptable margin.

5. calculate_distance:

   • Computes the absolute distance between two floating-point values.
   • Use Case: Measuring differences in betting amounts or game scores.

Casino Scenario Usage

These functions are ideal for casino applications, such as:

• Percentage Change: Calculating differences in betting amounts or payouts (count_add, count_amo_add, count_add_float).
• Threshold Validation: Ensuring payouts or bets are within acceptable limits (is_within_five_percent).
• Distance Calculation: Measuring differences in scores, balances, or odds (calculate_distance).

Example Output

The output depends on the implementation of e9571_math_lib. An example output might look like:

=== Count_Add ===
Percentage change (Real=110, Close=100): 10.0
Percentage change (Close=0): inf

=== Count_Amo_Add ===
Percentage change (Real=110, Close=100): 10.0
Percentage change (Close=0): inf

=== Count_Add_float ===
Percentage change (Real=110, Close=100): 10.0
Percentage change (Close=0): inf

=== IsWithinFivePercent ===
Within 5% (100, 104): true
Within 5% (100, 106): false

=== CalculateDistance ===
Distance (100, 110): 10.0
Distance (-10, 10): 20.0

Notes

• Module Dependency: The e9571_math_lib module is assumed to be available and correctly implemented.
• Error Handling: Ensure proper handling for edge cases (e.g., division by zero in percentage calculations).
• Casino Context: The functions are suitable for processing betting amounts, validating payouts, or comparing game metrics.
• GitHub Rendering: This Markdown uses Rust syntax highlighting, clear headings, and structured explanations for optimal display.
• Precision: Floating-point calculations (count_add_float, is_within_five_percent, calculate_distance) use f64 for accuracy.