gnps 0.3.3

Generalized Numerical P Systems simulator package

GNPS Project

GNPS (Generalized Numerical P Systems) is a Python package for parsing and simulating numerical P systems, and for exporting them to generated code.

Current Capabilities

• Python simulation of standalone and import-composed GNPS YAML systems
• Python source export through gnps-transform -t python, including import-composed systems as a single generated file
• Verilog/SystemVerilog export through gnps-transform -t verilog
• Optional import/composition metadata for Verilog generation

CLI

Simulator

python -m gnps <gnps_file.yaml> [input.csv] [output.csv] [options]

Options:

• -c, --compute_mode: run in continuous compute mode
• -s, --steps N: number of steps to run
• --csv: emit CSV in continuous mode

The simulator supports standalone GNPS YAML and import-composed GNPS systems. Files using externals still fail clearly in the Python runtime.

Transformer

gnps-transform <gnps_file.yaml> -t {python,verilog} [options]

Options:

• -o, --output-dir DIR: output directory
• --output-suffix SUFFIX: suffix inserted before the generated file extension
• --import-path DIR: extra import search path, may be repeated
• --import-paths LIST: path-separated import search list
• -v, --verbose: verbose logging

Import resolution order:

1. relative to the importing YAML file
2. --import-path / --import-paths directories in the order provided

YAML Schema

Standalone legacy files still work:

cells:
  - id: 1
    contents:
      - x = 0
      - y = 1
    input: [x]
    output: [y]

rules:
  - x + 1 -> y

Verilog/SystemVerilog-oriented extensions are optional:

module:
  name: controller_top
  zero_reset_mode: false
  real_encoding:
    kind: fixed_point
    signed: true
    width: 32
    frac_bits: 16
  clock:
    name: clk
  reset:
    name: rst
    active_high: true
  top_ports:
    - name: uart_rx
      dir: input
      kind: logic
      width: 1
      signed: false

constants:
  THRESHOLD: 5

aliases:
  sensed: sensor0.level

imports:
  - module: sensor.yaml
    as: sensor0
    connections:
      raw: sample

externals:
  - header: uart.header.yaml
    as: uart0
    connections:
      clk: top.clk
      rst: top.rst
      rx: top.uart_rx

cells:
  - id: 1
    contents:
      - sample = 0
      - alarm = 0
    output: [alarm]

rules:
  - sensed > THRESHOLD && uart0.rx_valid == 1 | uart0.rx_data + 1 -> alarm

Qualified references supported by the parser:

• local variable: x
• imported GNPS IO: sensor0.level
• external port: uart0.rx_valid
• top-level signal: top.uart_rx, top.clk, top.rst

Defaults

If module is absent, the effective defaults are:

• module name: source filename stem
• zero_reset_mode: false
• real_encoding.kind: fixed_point
• real_encoding.signed: true
• real_encoding.width: 32
• real_encoding.frac_bits: 16
• clock name: clk
• reset name: rst
• reset polarity: active high
• top ports: none

If constants, aliases, imports, or externals are absent, they default to empty.

These defaults are also documented in rules.md.

Generated RTL

The verilog backend emits SystemVerilog-style RTL:

• file extension: .sv
• wraps each generated module with `default_nettype none and restores `default_nettype wire afterward
• module parameters in the module header
• always_comb for next-state logic
• always_ff for sequential updates
• fixed-point values stay as integer literals in the emitted RTL, wrapped in generated module-local localparam aliases such as _VAL_1_0
• generated fixed-point state, helper signatures, and literals now follow module.real_encoding.signed instead of always being emitted as signed values
• boundary conversions use generated integer-only helper functions rather than real-based helpers
• if a GNPS input/output has the same name as a declared top_port, the generated RTL automatically converts between the module-local fixed-point encoding and the declared top-port integer/logic format at the module boundary
• plain variable names such as sample or alarm refer to the local GNPS variable, while top.sample refers to the raw top-level signal before or after that boundary conversion
• fixed-point to integer top-port conversion truncates toward zero
• generated literal aliases are documented with comments showing the original source values and fixed-point format

Supported expression subset:

• constants
• local variables
• qualified references
• addition and subtraction
• unary minus
• constant multiplication and constant division
• boolean comparisons
• boolean &&, ||, !

Rejected constructs:

• generic function calls
• variable-by-variable multiplication
• non-constant division
• arrays

Each GNPS module uses its own real_encoding. Boundary conversions are inserted automatically for imported GNPS IO and external ports. In the Verilog backend, consumed variables are reset to zero explicitly before productions are accumulated.

Examples

See src/examples/ for:

• standalone legacy-style YAML
• import-only Python/Verilog composition
• FPGA-oriented examples under src/examples/fpga/, including blink.yaml and blink_uart.yaml
• imported multicell Verilog composition
• external UART header and controller top module examples

Notes

• Top-level name and description are treated as metadata and ignored by Verilog generation.
• Python composition currently supports imports only.
• externals are not yet supported by the Python backend or runtime simulator.
• Declaring a variable in output only exposes it at the module boundary; it does not implicitly consume or reset that variable each step. If an output should behave like a per-step pulse/value rather than accumulated state, add an explicit consume/reset rule for it.
• module.zero_reset_mode: true changes only that module’s local variables: they are cleared to zero at the start of every step before productions are accumulated. Imported modules keep their own mode independently.
• Detailed behavior and schema rules live in rules.md.

Example:

cells:
  - id: 1
    contents:
      - alarm = 0
    output: [alarm]

rules:
  # Persistent output/state: alarm keeps its previous value unless consumed
  - sensor0.level > 2 | 1 -> alarm

cells:
  - id: 1
    contents:
      - alarm = 0
    output: [alarm]

rules:
  # Per-step output: first produce the value you want
  - sensor0.level > 2 | 1 -> alarm
  # Then consume/reset alarm each step so it does not accumulate
  - alarm * 0 -> alarm