LIBRARY

Tables.Tests.InterpolationTable

Tests interpolation by applying linear interpolation to a dataset of squares.

This component creates an interpolation object configured with linear interpolation and a dataset containing time values from 0 to 1 and their corresponding squared values. The current simulation time is used as the input to the interpolation, and the interpolated output is assigned to the variable y. The metadata includes a test case that runs until time=1 and verifies the y signal.

Usage

BlockComponents.Tables.Tests.InterpolationTable()

Parameters:

Name	Description	Units	Default value
dataset	Dataset containing time values from 0 to 1 and their squares, with 'ts' as independent variable and 'data' as dependent variable	–	DyadTimeseries(hcat(0:0.1:1, square(0:0.1:1)), dependent_vars=["data"], independent_var="ts")

Variables

Name	Description	Units
y	Output variable that receives the interpolated value	–

Behavior

Behavior of this component cannot be rendered because it includes path variables.

Source

"""
Tests interpolation by applying linear interpolation to a dataset of squares.

This component creates an interpolation object configured with linear interpolation and a dataset
containing time values from 0 to 1 and their corresponding squared values. The current simulation
time is used as the input to the interpolation, and the interpolated output is assigned to the
variable `y`. The metadata includes a test case that runs until time=1 and verifies the `y` signal.
"""
test component InterpolationTable
  "Interpolation object that performs linear interpolation on the dataset"
  interp = BlockComponents.Tables.Interpolation(interpolation_type = InterpolationType.LinearInterpolation(), dataset = dataset) {
    "Dyad": {
      "placement": {
        "diagram": {"iconName": "default", "x1": 170, "y1": 70, "x2": 270, "y2": 170, "rot": 0}
      }
    }
  }
  "Dataset containing time values from 0 to 1 and their squares, with 'ts' as independent variable and 'data' as dependent variable"
  structural parameter dataset::DyadData.DyadTimeseries = DyadTimeseries(hcat(0:0.1:1, square(0:0.1:1)), dependent_vars = ["data"], independent_var = "ts")
  "Output variable that receives the interpolated value"
  variable y::Real
relations
  interp.u = time
  interp.y = y
metadata {
  "Dyad": {
    "icons": {"default": "dyad://BlockComponents/Example.svg"},
    "tests": {"case1": {"stop": 1, "expect": {"signals": ["y"]}}},
    "doc": {"behavior": false}
  }
}
end

Flattened Source

"""
Tests interpolation by applying linear interpolation to a dataset of squares.

This component creates an interpolation object configured with linear interpolation and a dataset
containing time values from 0 to 1 and their corresponding squared values. The current simulation
time is used as the input to the interpolation, and the interpolated output is assigned to the
variable `y`. The metadata includes a test case that runs until time=1 and verifies the `y` signal.
"""
test component InterpolationTable
  "Interpolation object that performs linear interpolation on the dataset"
  interp = BlockComponents.Tables.Interpolation(interpolation_type = InterpolationType.LinearInterpolation(), dataset = dataset) {
    "Dyad": {
      "placement": {
        "diagram": {"iconName": "default", "x1": 170, "y1": 70, "x2": 270, "y2": 170, "rot": 0}
      }
    }
  }
  "Dataset containing time values from 0 to 1 and their squares, with 'ts' as independent variable and 'data' as dependent variable"
  structural parameter dataset::DyadData.DyadTimeseries = DyadTimeseries(hcat(0:0.1:1, square(0:0.1:1)), dependent_vars = ["data"], independent_var = "ts")
  "Output variable that receives the interpolated value"
  variable y::Real
relations
  interp.u = time
  interp.y = y
metadata {
  "Dyad": {
    "icons": {"default": "dyad://BlockComponents/Example.svg"},
    "tests": {"case1": {"stop": 1, "expect": {"signals": ["y"]}}},
    "doc": {"behavior": false}
  }
}
end

Test Cases

using BlockComponents
using DyadInterface: TransientAnalysis, rebuild_sol, ODEAlg
using ModelingToolkit: toggle_namespacing, get_initial_conditions, @named
using CSV, DataFrames, Plots

snapshotsdir = joinpath(dirname(dirname(pathof(BlockComponents))), "test", "snapshots")

<< @setup-block not executed in draft mode >>

Test Case case1

@named model_case1 = BlockComponents.Tables.Tests.InterpolationTable()
model_case1 = toggle_namespacing(model_case1, false)

model_case1 = toggle_namespacing(model_case1, true)
result_case1 = TransientAnalysis(; model = model_case1, alg = ODEAlg.Auto(), start = 0e+0, stop = 1e+0, abstol=1e-6, reltol=1e-6)
sol_case1 = rebuild_sol(result_case1)

<< @setup-block not executed in draft mode >>

df_case1 = DataFrame(:t => sol_case1[:t], :actual => sol_case1[model_case1.y])
dfr_case1 = try CSV.read(joinpath(snapshotsdir, "BlockComponents.Tables.Tests.InterpolationTable_case1_sig0.ref"), DataFrame); catch e; nothing; end
plt = plot(sol_case1, idxs=[model_case1.y], width=2, label="Actual value of y")
if !isnothing(dfr_case1)
  scatter!(plt, dfr_case1.t, dfr_case1.expected, mc=:red, ms=3, label="Expected value of y")
end

<< @setup-block not executed in draft mode >>

plt

<< @example-block not executed in draft mode >>

Related

• Examples

• Experiments

• Analyses

• Tests

  • Interpolation