{"categories":[{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/6"},{"label":"Mathematics","url":"https://skillfed.io/packages/category/scientific-engineering-mathematics/3"},{"label":"Physics","url":"https://skillfed.io/packages/category/scientific-engineering-physics"}],"enrichment":{"capability":"Fxpmath provides fixed-point arithmetic with arbitrary word and fractional sizes, supporting signed and unsigned numbers, numpy arrays, and bitwise operations for DSP and FPGA applications.","skillfed_tags":["fpga-simulation","dsp-prototyping","fixed-point"],"use_cases":["Prototype DSP algorithms in Python before deploying to fixed-point hardware or FPGA","Simulate fixed-point quantization effects on signal processing pipelines to predict hardware behavior","Test arithmetic overflow and underflow handling strategies with configurable saturation and rounding modes","Verify bit-width requirements for embedded systems by experimenting with different word and fractional sizes","Teach fixed-point representation and binary arithmetic concepts with interactive examples"],"what_it_does":"Fxpmath is a Python library for simulating fixed-point arithmetic in software, mimicking hardware behavior on FPGAs and DSP systems. It represents numbers with configurable word length and fractional bit positions, supporting signed and unsigned formats, and works seamlessly with numpy arrays and operations.\n\nThe library handles the full lifecycle of fixed-point values: creation from multiple input types (int, float, complex, strings in binary/hex/decimal, numpy arrays), arithmetic and bitwise operations, configurable rounding and overflow behaviors, and output in multiple bases. It tracks status flags and precision loss, making it useful for algorithm prototyping before hardware implementation or for educational exploration of fixed-point behavior.","worth_installing":"Yes. Fxpmath is actively maintained, has no known vulnerabilities, installs with minimal friction (numpy only), and fills a specific niche for fixed-point algorithm development and FPGA prototyping. The MIT license and stable API make it suitable for both research and production use. Install if you need to simulate or verify fixed-point behavior before hardware implementation."},"id":"fxpmath","links":{"html":"https://skillfed.io/packages/fxpmath","md":"https://skillfed.io/packages/fxpmath.md","pypi":"https://pypi.org/project/fxpmath/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-03-24","license_spdx":"MIT","license_treatment":"permissive","name":"fxpmath","python_support":"supports_current","summary":"A python library for fractional fixed-point (base 2) arithmetic and binary manipulation with Numpy compatibility."},"popularity":{"monthly_downloads":194177,"position":9843,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.4.10"}