Python vs MATLAB Parity

This page tracks the functional parity between the Python adctoolbox package and the original MATLAB implementation. The goal is to keep both versions feature-equivalent.

Last updated: 2026-03-10

Function Mapping

The table below maps every MATLAB core function to its Python equivalent. Legacy/deprecated MATLAB wrappers (e.g., sineFit → sinfit) are omitted; only the current MATLAB name is listed.

MATLAB	Python	Status
plotspec	analyze_spectrum	Matched
plotphase	analyze_spectrum_polar	Matched
sinfit	fit_sine_4param	Matched
findbin	find_coherent_frequency	Matched
findfreq	estimate_frequency	Matched
alias	fold_frequency_to_nyquist, fold_bin_to_nyquist	Matched
tomdec	analyze_decomposition_time, analyze_decomposition_polar	Matched
errsin	analyze_error_by_phase, analyze_error_by_value	Matched
inlsin	analyze_inl_from_sine	Matched
wcalsin	calibrate_weight_sine	Matched
bitchk	analyze_overflow	Matched
plotwgt	analyze_weight_radix	Matched
ntfperf	ntf_analyzer	Matched
adcpanel	toolset/generate_aout_dashboard, toolset/generate_dout_dashboard	Matched
cdacwgt	not implemented	MATLAB only
ifilter	not implemented	MATLAB only
perfosr	not implemented	MATLAB only
plotres	not implemented	MATLAB only

MATLAB-Only Functions

The following four MATLAB functions have no Python equivalent yet:

cdacwgt(cd, cb, cp)

Calculate bit weights for a multi-segment capacitive DAC (CDAC) with bridge capacitors and parasitic capacitances. Returns normalized weights and total capacitance.

ifilter(sigin, passband)

Ideal FFT-based brickwall filter. Retains only the specified frequency bands from an input signal. Operates column-wise on matrices.

perfosr(sig, ...)

Sweep ADC performance (SNDR, SFDR, ENOB) versus oversampling ratio (OSR). Separates ideal signal from error via sine fitting, then re-evaluates metrics at narrowing bandwidths.

plotres(sig, bits, ...)

Plot partial-sum residuals of an ADC bit matrix. Scatter-plots residuals between bit stages to reveal correlations, nonlinearity patterns, and redundancy.

Python-Only Functions

The following functions exist only in the Python package and have no MATLAB counterpart.

Analog Error Analysis

• analyze_error_pdf — Error probability density function via KDE.

• analyze_error_spectrum — Error spectrum computed from fitting residual.

• analyze_error_autocorr — Autocorrelation function (ACF) of error signal.

• analyze_error_envelope_spectrum — Envelope spectrum via Hilbert transform to reveal AM modulation patterns.

• fit_static_nonlin — Extract static nonlinearity coefficients (k2, k3) from a distorted sinewave.

Digital Output Analysis

• analyze_bit_activity — Percentage of 1’s per bit (DC offset / clipping detection).

• analyze_enob_sweep — ENOB vs. number of calibration bits.

Unit Conversions & Metrics

These are small utilities that MATLAB users typically write inline:

• db_to_mag, mag_to_db, db_to_power, power_to_db

• snr_to_enob, enob_to_snr, snr_to_nsd, nsd_to_snr

• lsb_to_volts, volts_to_lsb

• dbm_to_vrms, vrms_to_dbm, dbm_to_mw, mw_to_dbm

• sine_amplitude_to_power, amplitudes_to_snr

• bin_to_freq, freq_to_bin

• calculate_walden_fom, calculate_schreier_fom

• calculate_thermal_noise_limit, calculate_jitter_limit

Signal Generation

The Python siggen module provides a Nonidealities class for building realistic ADC test signals with chainable impairments. This has no MATLAB equivalent:

• Thermal noise, clock jitter, quantization noise

• Static nonlinearity (polynomial or harmonic-dB specification)

• Memory effect, incomplete sampling / settling

• Residue amplifier gain error (static and dynamic)

• Reference error (settling + droop)

• AM noise, AM tone, clipping, drift, glitch injection

• First-order noise shaping

Summary

Category	MATLAB	Python
Core analysis functions	18	43
Matched across both	14	14
MATLAB-only	4	—
Python-only	—	29
Signal generation module	No	Yes (siggen)
Unit conversion utilities	No (inline)	Yes (20 functions)
Two-tone analysis	No	Yes