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Math.Tests.Tan.md

Math.Tests.Tan ​

Computes the tangent of constant and time-varying inputs.

Connects a constant source with value 0 to a Tan block and verifies that tan(0) = 0. A second Tan block is driven by a sine wave (amplitude 1.4 rad) that stays within (-π/2, π/2), away from the tangent asymptotes, while sweeping negative and positive angles.

Usage ​

BlockComponents.Math.Tests.Tan()

Behavior ​

julia
using BlockComponents #hide
using ModelingToolkit #hide
@named sys = BlockComponents.Math.Tests.Tan() #hide
let eqs = full_equations(sys); Base.length(eqs) > 25 ? nothing : eqs end #hide
<< @example-block not executed in draft mode >>

Source ​

dyad
"""
Computes the tangent of constant and time-varying inputs.

Connects a constant source with value 0 to a Tan block and verifies that
tan(0) = 0. A second Tan block is driven by a sine wave (amplitude 1.4 rad)
that stays within (-π/2, π/2), away from the tangent asymptotes, while
sweeping negative and positive angles.
"""
test component Tan
  "Constant source providing the input value"
  c1 = BlockComponents.Sources.Constant(k = 0) {
    "Dyad": {
      "placement": {
        "diagram": {"iconName": "default", "x1": 20, "y1": 20, "x2": 120, "y2": 120, "rot": 0}
      },
      "tags": []
    }
  }
  "Sine source kept inside (-π/2, π/2) to avoid the tangent asymptotes"
  sine = BlockComponents.Sources.Sine(amplitude = 1.4, frequency = 1) {
    "Dyad": {
      "placement": {
        "diagram": {"iconName": "default", "x1": 20, "y1": 140, "x2": 120, "y2": 240, "rot": 0}
      },
      "tags": []
    }
  }
  "Tan block under test"
  tan_block = BlockComponents.Math.Tan() {
    "Dyad": {
      "placement": {
        "diagram": {"iconName": "default", "x1": 160, "y1": 20, "x2": 260, "y2": 120, "rot": 0}
      },
      "tags": []
    }
  }
  "Second Tan block driven by the sine source"
  tan_block_2 = BlockComponents.Math.Tan() {
    "Dyad": {
      "placement": {
        "diagram": {"iconName": "default", "x1": 160, "y1": 140, "x2": 260, "y2": 240, "rot": 0}
      },
      "tags": []
    }
  }
relations
  connect(c1.y, tan_block.u) {"Dyad": {"edges": [{"S": 1, "M": [], "E": 2}], "renderStyle": "standard"}}
  connect(sine.y, tan_block_2.u) {"Dyad": {"edges": [{"S": 1, "M": [], "E": 2}], "renderStyle": "standard"}}
metadata {
  "Dyad": {
    "icons": {"default": "dyad://BlockComponents/Example.svg"},
    "tests": {
      "case1": {"stop": 1, "expect": {"signals": ["tan_block.y", "tan_block_2.y", "sine.y"]}}
    }
  }
}
end
Flattened Source
dyad
"""
Computes the tangent of constant and time-varying inputs.

Connects a constant source with value 0 to a Tan block and verifies that
tan(0) = 0. A second Tan block is driven by a sine wave (amplitude 1.4 rad)
that stays within (-π/2, π/2), away from the tangent asymptotes, while
sweeping negative and positive angles.
"""
test component Tan
  "Constant source providing the input value"
  c1 = BlockComponents.Sources.Constant(k = 0) {
    "Dyad": {
      "placement": {
        "diagram": {"iconName": "default", "x1": 20, "y1": 20, "x2": 120, "y2": 120, "rot": 0}
      },
      "tags": []
    }
  }
  "Sine source kept inside (-π/2, π/2) to avoid the tangent asymptotes"
  sine = BlockComponents.Sources.Sine(amplitude = 1.4, frequency = 1) {
    "Dyad": {
      "placement": {
        "diagram": {"iconName": "default", "x1": 20, "y1": 140, "x2": 120, "y2": 240, "rot": 0}
      },
      "tags": []
    }
  }
  "Tan block under test"
  tan_block = BlockComponents.Math.Tan() {
    "Dyad": {
      "placement": {
        "diagram": {"iconName": "default", "x1": 160, "y1": 20, "x2": 260, "y2": 120, "rot": 0}
      },
      "tags": []
    }
  }
  "Second Tan block driven by the sine source"
  tan_block_2 = BlockComponents.Math.Tan() {
    "Dyad": {
      "placement": {
        "diagram": {"iconName": "default", "x1": 160, "y1": 140, "x2": 260, "y2": 240, "rot": 0}
      },
      "tags": []
    }
  }
relations
  connect(c1.y, tan_block.u) {"Dyad": {"edges": [{"S": 1, "M": [], "E": 2}], "renderStyle": "standard"}}
  connect(sine.y, tan_block_2.u) {"Dyad": {"edges": [{"S": 1, "M": [], "E": 2}], "renderStyle": "standard"}}
metadata {
  "Dyad": {
    "icons": {"default": "dyad://BlockComponents/Example.svg"},
    "tests": {
      "case1": {"stop": 1, "expect": {"signals": ["tan_block.y", "tan_block_2.y", "sine.y"]}}
    }
  }
}
end


Test Cases ​

julia
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 ​

julia
@named model_case1 = BlockComponents.Math.Tests.Tan()
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 >>
julia
df_case1 = DataFrame(:t => sol_case1[:t], :actual => sol_case1[model_case1.tan_block.y])
dfr_case1 = try CSV.read(joinpath(snapshotsdir, "BlockComponents.Math.Tests.Tan_case1_sig0.ref"), DataFrame); catch e; nothing; end
plt = plot(sol_case1, idxs=[model_case1.tan_block.y], width=2, label="Actual value of tan_block.y")
if !isnothing(dfr_case1)
  scatter!(plt, dfr_case1.t, dfr_case1.expected, mc=:red, ms=3, label="Expected value of tan_block.y")
end
<< @setup-block not executed in draft mode >>
julia
plt
<< @example-block not executed in draft mode >>
julia
df_case1 = DataFrame(:t => sol_case1[:t], :actual => sol_case1[model_case1.tan_block_2.y])
dfr_case1 = try CSV.read(joinpath(snapshotsdir, "BlockComponents.Math.Tests.Tan_case1_sig1.ref"), DataFrame); catch e; nothing; end
plt = plot(sol_case1, idxs=[model_case1.tan_block_2.y], width=2, label="Actual value of tan_block_2.y")
if !isnothing(dfr_case1)
  scatter!(plt, dfr_case1.t, dfr_case1.expected, mc=:red, ms=3, label="Expected value of tan_block_2.y")
end
<< @setup-block not executed in draft mode >>
julia
plt
<< @example-block not executed in draft mode >>
julia
df_case1 = DataFrame(:t => sol_case1[:t], :actual => sol_case1[model_case1.sine.y])
dfr_case1 = try CSV.read(joinpath(snapshotsdir, "BlockComponents.Math.Tests.Tan_case1_sig2.ref"), DataFrame); catch e; nothing; end
plt = plot(sol_case1, idxs=[model_case1.sine.y], width=2, label="Actual value of sine.y")
if !isnothing(dfr_case1)
  scatter!(plt, dfr_case1.t, dfr_case1.expected, mc=:red, ms=3, label="Expected value of sine.y")
end
<< @setup-block not executed in draft mode >>
julia
plt
<< @example-block not executed in draft mode >>