Value and Precision Features

This feature governs how the control handles the numeric value to be humanized and defines the precision threshold for floating-point comparisons.

Overview

The Value and Precision Features of the SiticoneHumanizerFloat control allow developers to assign a numeric value for humanization while ensuring its validity through finite number checks and boundary constraints. Additionally, the Epsilon property is used to define the acceptable threshold for floating-point equality comparisons, ensuring precision-sensitive operations behave as expected.

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Key Points

Item	Description
Value	Represents the numeric value to be humanized; it must be finite and conform to any set minimum or maximum constraints.
Epsilon	Defines the tolerance level for floating-point equality comparisons; must be a positive number to ensure proper precision handling.

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Best Practices

Aspect	Recommendation
Validate Input Values	Ensure that the value assigned to the Value property is a finite number and falls within the defined range (if MinimumValue/MaximumValue are set).
Set an Appropriate Epsilon	Choose an Epsilon value that reflects the required precision of your application, especially when dealing with very small or high-precision numbers.
Integrate with Validation	Use the Value and Epsilon features in tandem with the control's validation properties to maintain data integrity and avoid unexpected behavior.

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Common Pitfalls

Issue	Description	Resolution
Assigning Non-finite Values	Setting Value to NaN, Infinity, or -Infinity will trigger an exception as only finite numbers are allowed.	Validate the input before assignment to ensure it is a finite number.
Negative or Zero Epsilon	Using a non-positive value for Epsilon will result in an exception because Epsilon must be greater than zero.	Always assign a positive value to Epsilon to maintain proper floating-point precision comparisons.
Ignoring Precision Impacts	Overlooking the role of Epsilon may lead to incorrect equality comparisons in precision-sensitive operations.	Adjust Epsilon according to the required level of precision to ensure accurate floating-point comparisons in your application.

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Usage Scenarios

Scenario	Description
High-Precision Calculations	When performing scientific or engineering computations, use Epsilon to manage precision in floating-point comparisons.
Data Validation	Before processing user input or sensor data, use the Value property to validate that inputs are within expected ranges.
Error Prevention in Conversions	Use the Value property to ensure that values are within set boundaries, preventing issues during numeric formatting conversions.

Code Example: Setting Value and Epsilon

// Create an instance of the humanizer control
var humanizer = new SiticoneHumanizerFloat();

// Set an appropriate epsilon value for precision-sensitive comparisons
humanizer.Epsilon = 1e-10;

// Assign a finite numeric value to be humanized
humanizer.Value = 12345.6789;

// Output the humanized value
Console.WriteLine("Humanized Value: " + humanizer.Humanized);

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Real Life Usage Scenarios

Scenario	Description
Scientific Instrumentation	Ensuring sensor measurements are within acceptable ranges and using Epsilon to accurately compare small variations in data.
Financial Data Processing	Validating monetary amounts to ensure they are finite and within established limits before formatting them for reports.
Real-Time Monitoring Systems	Using the Value property to continuously update the display while ensuring that minor fluctuations do not trigger false comparisons.

Code Example: Data Validation and Precision Management

try
{
    // Example: processing a value from an external sensor input
    double sensorInput = 0.000000123; // Simulated sensor input value

    // Set an Epsilon that is appropriate for the sensor's precision
    humanizer.Epsilon = 1e-12;
    
    // Assign the sensor input to the humanizer
    humanizer.Value = sensorInput;
    
    Console.WriteLine("Sensor Value: " + humanizer.Humanized);
}
catch (ArgumentException ex)
{
    Console.WriteLine("Error: " + ex.Message);
}
catch (ArgumentOutOfRangeException ex)
{
    Console.WriteLine("Out of range: " + ex.Message);
}

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Troubleshooting Tips

Issue	Possible Cause	Suggested Action
Exception on Setting Value	The value being assigned is either NaN, Infinity, or outside the specified minimum and maximum range.	Validate the input number before assignment and adjust MinimumValue/MaximumValue as needed.
Exception on Setting Epsilon	The assigned Epsilon is zero or negative, violating the condition that it must be greater than zero.	Ensure that the Epsilon value is positive; adjust the value to meet the required precision.
Inaccurate Floating-Point Comparisons	The default Epsilon might not be sensitive enough for high-precision applications.	Experiment with smaller Epsilon values to achieve the desired level of precision for floating-point comparisons.

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Review

Aspect	Review Notes
Reliability	The Value and Epsilon features provide robust mechanisms to ensure that numeric data is valid and comparisons are accurate.
Flexibility	Developers can adjust both the numeric value and the precision threshold to suit diverse application requirements.
Integration	Seamless integration with validation features ensures that only acceptable values are processed.
Potential Issues	Improper configuration of Value or Epsilon can lead to runtime exceptions, so careful setup is essential.

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Summary

Summary Point	Description
Valid and Finite Values	The Value property ensures that only valid, finite numbers are processed by the control.
Precision Control	The Epsilon property allows developers to define the precision level for floating-point comparisons effectively.
Enhanced Data Integrity	Together, these features prevent erroneous numeric data from affecting the humanization process, improving reliability.
Flexible Configuration	Suitable for a range of applications from high-precision scientific computing to robust financial data processing.

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Additional Considerations

Consideration	Description
Consistency in Precision	Ensure that all parts of your application use a consistent Epsilon value when performing floating-point comparisons.
Regular Testing	Regularly test edge cases, especially when working with extremely small or large numbers, to verify precision.
Detailed Documentation	Document the chosen Epsilon and value validation logic to assist in future maintenance and troubleshooting.

Code Example: Comprehensive Exception Handling for Value and Precision

try
{
    // Attempt to assign an invalid (non-finite) value
    humanizer.Value = double.NaN;
}
catch (ArgumentException ex)
{
    Console.WriteLine("Invalid numeric value: " + ex.Message);
}

try
{
    // Attempt to set an invalid Epsilon value (zero or negative)
    humanizer.Epsilon = 0; // This will throw an exception
}
catch (ArgumentException ex)
{
    Console.WriteLine("Invalid epsilon value: " + ex.Message);
}

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By leveraging the Value and Precision Features of the SiticoneHumanizerFloat control, developers can ensure that numeric values are both valid and precisely compared. This enhances data integrity and the overall robustness of applications that rely on accurate number formatting and humanization.