Source code for pySimBlocks.gui.blocks.operators.discrete_derivator

# ******************************************************************************
#                                  pySimBlocks
#                     Copyright (c) 2026 Université de Lille & INRIA
# ******************************************************************************
#  This program is free software: you can redistribute it and/or modify it
#  under the terms of the GNU Lesser General Public License as published by
#  the Free Software Foundation, either version 3 of the License, or (at your
#  option) any later version.
#
#  This program is distributed in the hope that it will be useful, but WITHOUT
#  ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
#  FITNESS FOR A PARTICULAR PURPOSE.  See the GNU Lesser General Public License
#  for more details.
#
#  You should have received a copy of the GNU Lesser General Public License
#  along with this program.  If not, see <https://www.gnu.org/licenses/>.
# ******************************************************************************
#  Authors: see Authors.txt
# ******************************************************************************

from pySimBlocks.gui.blocks.block_meta import BlockMeta
from pySimBlocks.gui.blocks.parameter_meta import ParameterMeta
from pySimBlocks.gui.blocks.port_meta import PortMeta




class DiscreteDerivatorMeta(BlockMeta):
    """Describe the GUI metadata of the discrete-derivator block."""

    def __init__(self):
        """Initialize discrete-derivator block metadata.

        Args:
            None.

        Raises:
            None.
        """
        self.name = "DiscreteDerivator"
        self.category = "operators"
        self.type = "discrete_derivator"
        self.summary = "Discrete-time differentiator block."
        self.description = (
            "Computes a backward finite-difference approximation of the derivative:\n"
            "$$\n"
            "y[k] = \\frac{u[k] - u[k-1]}{dt}\n"
            "$$\n"
        )

        self.parameters = [
            ParameterMeta(
                name="initial_output",
                type="scalar | vector | matrix"
            ),
            ParameterMeta(
                name="sample_time",
                type="float"
            )
        ]

        self.inputs = [
            PortMeta(
                name="in",
                display_as="in",
                shape=["n", "m"],
                description="Input signal."
            )
        ]

        self.outputs = [
            PortMeta(
                name="out",
                display_as="out",
                shape=["n", "m"],
                description="Discrete-time derivative of the input."
            )
        ]