Why Does Comparing a Float and a Double With the Same Value Return False?

Unexpected Result when Comparing Double and Float

The comparison between a float variable f and a double variable d with the same value 1.1 surprisingly returns false. This unexpected result stems from the fundamental characteristics of floating-point numbers.

Precision and Rounding in Floating-Point Numbers

Floating-point numbers, including float and double types, have inherent limitations:

Precision: Floating-point numbers represent real numbers within a finite limit of significant digits. Values requiring more precision than the data type can handle will result in truncated representations.

Rounding: Binary numbers do not always have exact decimal representations. When converting binary to decimal, rounding occurs to fit the limited precision of floating-point types.

Impact on Comparisons

Due to these factors, float and double values are subject to rounding errors. These errors can cause discrepancies when comparing two numbers that should be equal. In the given example, the float and double representations of 1.1 have slight variations due to rounding, resulting in the counterintuitive outcome of f != d.

Best Practice

Avoid direct equality comparisons between floating-point numbers. Instead, opt for evaluating the absolute difference between the values and comparing it against an acceptable threshold (epsilon):

if (abs(x - y) < epsilon) { ... }

This approach accounts for the inherent inaccuracies in floating-point operations and provides a more reliable way to determine if two values are essentially equal.

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