Source code for node_correlate

# This file is part of Sympathy for Data.
# Copyright (c) 2017, Combine Control Systems AB
#
# SYMPATHY FOR DATA COMMERCIAL LICENSE
# You should have received a link to the License with Sympathy for Data.
import numpy as np

from sympathy.api import node
from sympathy.api.exceptions import SyConfigurationError
from sympathy.api.nodeconfig import Port, Ports, Tag, Tags




class Correlate(node.Node):
    """
    """
    name = 'Correlate / Convolution'
    author = 'Mathias Broxvall'
    icon = 'convolution.svg'
    description = (
        'Performs linear correlation or convolution of two 1D signals'
    )
    nodeid = 'com.sympathyfordata.timeseriesanalysis.correlate'
    tags = Tags(Tag.Analysis.SignalProcessing)

    parameters = node.parameters()
    parameters.set_string(
        'operation',
        label='Operation',
        value='correlation',
        description='Operation to perform',
        editor=node.editors.combo_editor(
            options=['correlation', 'convolution']))
    parameters.set_string(
        'mode',
        label='Mode',
        value='valid',
        description='Mode for handling border data. \n'
                    '\n "Full" applies operation '
                    'on each point of overlap, giving a larger output than '
                    'inputs and boundary effects may be seen. \n \n "Same" '
                    'limits output length to max of input lengths and '
                    'boundary effects are still visible. \n \n "Valid" '
                    'performs operation only on fully overlapping data',
        editor=node.editors.combo_editor(
            options=['full', 'same', 'valid']))
    parameters.set_string(
        'combinations',
        label='Combinations',
        value='by column number',
        description=(
            'Determines which combinations of signals are operated on.'),
        editor=node.editors.combo_editor(
            options=[
                'by column number', 'by column name', 'all combinations']))

    inputs = Ports([
        Port.Table('A', name='A'),
        Port.Table('V', name='V')
    ])
    outputs = Ports([
        Port.Table('result', name='result')
    ])

    def execute(self, node_context):
        op = node_context.parameters['operation'].value
        mode = node_context.parameters['mode'].value
        combinations = node_context.parameters['combinations'].value
        A_tbl = node_context.input['A']
        V_tbl = node_context.input['V']
        out = node_context.output['result']

        def process_columns(A_col, V_col, name):
            A = A_col.data
            V = V_col.data
            if op == 'correlation':
                res = np.correlate(A, V, mode=mode)
            elif op == 'convolution':
                res = np.convolve(A, V, mode=mode)
            else:
                raise SyConfigurationError(
                    'Invalid operation parameter in correlation node')
            out.set_column_from_array(name, res)

        if combinations == 'by column number':
            for i in range(
                    min(A_tbl.number_of_columns(), V_tbl.number_of_columns())):
                process_columns(
                    A_tbl.cols()[i], V_tbl.cols()[i], '{}'.format(i))

        elif combinations == 'by column name':
            for A_col in A_tbl.cols():
                if A_col.name in V_tbl.column_names():
                    V_col = V_tbl.col(A_col.name)
                    process_columns(A_col, V_col, A_col.name)

        elif combinations == 'all combinations':
            for A_col in A_tbl.cols():
                for V_col in V_tbl.cols():
                    process_columns(A_col, V_col, A_col.name+'_'+V_col.name)

        else:
            raise SyConfigurationError('Invalid setting for combinations')