v0.1.1-beta

Add RF slope equalizer class for frequency-dependent gain modeling
Modified : rf_utils/rf_essential_components.py

Full Changelog: v0.1.0-beta.2...v0.1.1-beta

v0.1.0-beta.1

Release notes — v0.1.0-beta.1

This is the first beta release of RF_chain_modeling, focused on end-to-end RF chain simulation with frequency-dependent component models and basic linearity characterization utilities.

Highlights

• RF chain simulation with cascaded components (antenna, filters, amplifiers, attenuator, cable) using a dedicated RFchain container.
• Signal generation and analysis utilities built around the Signals class (tones + thermal noise, spectrum/temporal views).
• Built-in characterization helpers to assess gain/phase/noise figure versus frequency and to run IP2/IP3-style assessments.

Included examples

• RF_chain_modeling/rf_chains/rf_chain_example.py: demonstrates building a multi-component RF chain, processing a multi-tone signal, plotting results, and running gain/IPx assessments across frequency.
• RF_chain_modeling/rf_components/zvq_183_s_plus.py: demonstrates creating a data-driven component from a TSV file (Mini-Circuits ZVQ-183+) using CSVDataTable, then plotting gain/phase/NF and running linearity-related checks.

Dependencies

• Requires numpy, scipy, matplotlib, and tqdm (see requirements.txt).

Known limitations (beta)

• Filter design uses digital IIR design (butter) and is constrained by the sampling rate used by generated signals, so some parameter combinations can trigger Nyquist-related errors during characterization runs.
• IPx/P1dB characterization may fail to converge or report “unable to characterize … finely” depending on sweep settings and signal configuration (resolution, span, power sweep).

Roadmap (next betas)

• More robust sampling-rate/bandwidth management for filter-based components during IPx/P1dB sweeps.
• Improved stability and reporting for nonlinearity characterization (better error handling, clearer diagnostics, optional plotting).

v0.1.0-beta.2

Release notes — v0.1.0-beta.2

Highlights

• RF chain simulation with cascaded components (antenna, filters, amplifiers, attenuator, cable) using a dedicated RFchain container.
• Signal generation and analysis utilities built around the Signals class (tones + thermal noise, spectrum/temporal views).
• Built-in characterization helpers to assess gain/phase/noise figure versus frequency and to run IP2/IP3-style assessments.

Included examples

• RF_chain_modeling/rf_chains/rf_chain_example.py: demonstrates building a multi-component RF chain, processing a multi-tone signal, plotting results, and running gain/IPx assessments across frequency.
• RF_chain_modeling/rf_components/zvq_183_s_plus.py: demonstrates creating a data-driven component from a TSV file (Mini-Circuits ZVQ-183+) using CSVDataTable, then plotting gain/phase/NF and running linearity-related checks.

Dependencies

• Requires numpy, scipy, matplotlib, and tqdm (see requirements.txt).

Known limitations (beta)

• Filter design uses digital IIR design (butter) and is constrained by the sampling rate used by generated signals, so some parameter combinations can trigger Nyquist-related errors during characterization runs.
• IPx/P1dB characterization may fail to converge or report “unable to characterize … finely” depending on sweep settings and signal configuration (resolution, span, power sweep).

Roadmap (next betas)

• More robust sampling-rate/bandwidth management for filter-based components during IPx/P1dB sweeps.
• Improved stability and reporting for nonlinearity characterization (better error handling, clearer diagnostics, optional plotting).

Notes:

• Enhance README: Expanded README with detailed framework features, installation instructions, usage examples, and project structure.
• Add GitHub Actions workflow for Python package publishing
• Add CITATION.cff for software citation guidance

Full Changelog: 0.1.0-beta.1...v0.1.0-beta.2