Merge pull request #217 from control-toolbox/auto-juliaformatter-pr

[AUTO] JuliaFormatter.jl run

Author: ocots

ext/JuMPModels/balanced_field.jl

@@ -37,7 +37,7 @@ function OptimalControlProblems.balanced_field(
     span = params[:span]
     α_max = params[:α_max]
     T = params[:T]
-    
+
     r_t0 = params[:r_t0]
     v_t0 = params[:v_t0]
     h_t0 = params[:h_t0]
@@ -96,16 +96,16 @@ function OptimalControlProblems.balanced_field(
         model,
         begin
             Δt, (tf - t0) / N
-            
+
             q[i = 0:N], 0.5 * ρ * v[i]^2
             CL[i = 0:N], CL0 + (α[i] / α_max) * (CL_max - CL0)
             L[i = 0:N], q[i] * S * CL[i]
-            
+
             h_eff[i = 0:N], h[i] + h_w
             term_h[i = 0:N], 33.0 * abs(h_eff[i] / b)^1.5
             K[i = 0:N], K_nom * term_h[i] / (1.0 + term_h[i])
             D[i = 0:N], q[i] * S * (CD0 + K[i] * CL[i]^2)
-            
+
             dr[i = 0:N], v[i] * cos(γ[i])
             dv[i = 0:N], (T * cos(α[i]) - D[i]) / m - g * sin(γ[i])
             dh[i = 0:N], v[i] * sin(γ[i])

ext/JuMPModels/brachistochrone.jl

@@ -36,7 +36,7 @@ function OptimalControlProblems.brachistochrone(
 
     # parameters
     params = parameters_data(:brachistochrone, parameters)
-    g  = params[:g]
+    g = params[:g]
     t0 = params[:t0]
     x0 = params[:x0]
     y0 = params[:y0]
@@ -86,7 +86,7 @@ function OptimalControlProblems.brachistochrone(
             px[0] == x0
             py[0] == y0
             v[0] == v0
-            
+
             # End
             px[N] == xf
             py[N] == yf
@@ -104,10 +104,10 @@ function OptimalControlProblems.brachistochrone(
             # Dynamics expressions (Dymos formulation)
             # dpx/dt = v * sin(u)
             dpx[i = 0:N], v[i] * sin(u[i])
-            
+
             # dpy/dt = -v * cos(u)
             dpy[i = 0:N], -v[i] * cos(u[i])
-            
+
             # dv/dt = g * cos(u)
             dv[i = 0:N], g * cos(u[i])
         end
@@ -127,4 +127,4 @@ function OptimalControlProblems.brachistochrone(
     @objective(model, Min, tf)
 
     return model
-end
+end

ext/JuMPModels/bryson_denham.jl

@@ -44,25 +44,28 @@ function OptimalControlProblems.bryson_denham(
     model[:state_components] = ["x1", "x2"]
     model[:control_components] = ["u"]
     model[:costate_components] = ["p1", "p2"]
-    model[:variable_components] = []          
+    model[:variable_components] = []
 
     N = grid_size
-    Δt = (tf- t0) /N
+    Δt = (tf - t0) / N
 
     @variable(model, x1[0:N] <= x1_max, start = 0.0)
     @variable(model, x2[0:N], start = 0.0)
     @variable(model, u[0:N], start = 0.0)
 
-    @constraints(model, begin
-        x1[0] == x1_t0
-        x2[0] == x2_t0
-        x1[N] == x1_tf
-        x2[N] == x2_tf
-        p1[i = 1:N], x1[i] == x1[i-1] + 0.5* Δt * (x2[i] + x2[i-1])
-        p2[i = 1:N], x2[i] == x2[i-1] + 0.5 * Δt * (u[i] + u[i-1])
-    end)
+    @constraints(
+        model,
+        begin
+            x1[0] == x1_t0
+            x2[0] == x2_t0
+            x1[N] == x1_tf
+            x2[N] == x2_tf
+            p1[i = 1:N], x1[i] == x1[i - 1] + 0.5 * Δt * (x2[i] + x2[i - 1])
+            p2[i = 1:N], x2[i] == x2[i - 1] + 0.5 * Δt * (u[i] + u[i - 1])
+        end
+    )
 
-    @objective(model, Min, 0.5 * Δt * sum(0.5 * (u[i]^2 + u[i-1]^2) for i in 1:N))
+    @objective(model, Min, 0.5 * Δt * sum(0.5 * (u[i]^2 + u[i - 1]^2) for i in 1:N))
 
     return model
-end
+end

ext/JuMPModels/robot.jl

@@ -133,7 +133,7 @@ function OptimalControlProblems.robot(
         set_start_value(dρ[k], 0.0)
         set_start_value(dθ[k], 0.0)
         set_start_value(dϕ[k], 0.0)
-        
+
         set_start_value(uρ[k], 0.0)
         set_start_value(uθ[k], 0.0)
         set_start_value(uϕ[k], 0.0)

ext/MetaData/balanced_field.jl

@@ -1,29 +1,29 @@
 balanced_field_meta = OrderedDict(
     :grid_size => 200,
     :parameters => (
-        t0 = 0.0,
-        m = 79015.8,      # mass (kg)
-        g = 9.80665,      # gravity (m/s^2)
-        ρ = 1.225,        # air density (kg/m^3)
-        S = 124.7,        # surface (m^2)
-        CD0 = 0.03,       # zero-lift drag coefficient
-        AR = 9.45,        # aspect ratio
-        e = 0.801,        # Oswald efficiency
-        CL0 = 0.5,        # zero-alpha lift coefficient
-        CL_max = 2.0,     # max lift coefficient
-        h_w = 1.0,        # height of wing above CoG (m)
-        span = 35.7,      # wingspan (m)
-        α_max = 0.1745,   # alpha at CL_max (10 degrees in rad)
-        T = 120102.0,     # thrust (N) - one engine out
-        r_t0 = 600.0,     # initial range (m) at V1
-        v_t0 = 70.0,      # initial velocity (m/s) at V1
-        h_t0 = 0.0,       # initial altitude (m)
-        γ_t0 = 0.0,       # initial flight path angle (rad)
-        h_tf = 10.668,    # final altitude (35 ft in m)
-        γ_tf = 0.0873,    # final flight path angle (5 degrees in rad)
-        v_min = 0.0,
-        v_max = 100.0,
-        α_min = -0.1745,  # -10 degrees
-        α_max_ctrl = 0.2618, # 15 degrees
+        t0=0.0,
+        m=79015.8,      # mass (kg)
+        g=9.80665,      # gravity (m/s^2)
+        ρ=1.225,        # air density (kg/m^3)
+        S=124.7,        # surface (m^2)
+        CD0=0.03,       # zero-lift drag coefficient
+        AR=9.45,        # aspect ratio
+        e=0.801,        # Oswald efficiency
+        CL0=0.5,        # zero-alpha lift coefficient
+        CL_max=2.0,     # max lift coefficient
+        h_w=1.0,        # height of wing above CoG (m)
+        span=35.7,      # wingspan (m)
+        α_max=0.1745,   # alpha at CL_max (10 degrees in rad)
+        T=120102.0,     # thrust (N) - one engine out
+        r_t0=600.0,     # initial range (m) at V1
+        v_t0=70.0,      # initial velocity (m/s) at V1
+        h_t0=0.0,       # initial altitude (m)
+        γ_t0=0.0,       # initial flight path angle (rad)
+        h_tf=10.668,    # final altitude (35 ft in m)
+        γ_tf=0.0873,    # final flight path angle (5 degrees in rad)
+        v_min=0.0,
+        v_max=100.0,
+        α_min=-0.1745,  # -10 degrees
+        α_max_ctrl=0.2618, # 15 degrees
     ),
 )

ext/MetaData/brachistochrone.jl

@@ -1,14 +1,14 @@
 brachistochrone_meta = OrderedDict(
-    :grid_size => 500,                 
+    :grid_size => 500,
     :parameters => (
-        g  = 9.80665,                 
-        t0 = 0.0,                      
-        x0 = 0.0,                      
-        y0 = 10.0,                     
-        v0 = 0.0,                    
-        xf = 10.0,                    
-        yf = 5.0,
-        u_min = -pi,
-        u_max = pi,
+        g=9.80665,
+        t0=0.0,
+        x0=0.0,
+        y0=10.0,
+        v0=0.0,
+        xf=10.0,
+        yf=5.0,
+        u_min=(-pi),
+        u_max=pi,
     ),
-)
+)

ext/MetaData/bryson_denham.jl

@@ -1,12 +1,12 @@
 bryson_denham_meta = OrderedDict(
     :grid_size => 500,
     :parameters => (
-        t0     = 0.0,       # Initial time
-        tf     = 1.0,       # Final time
-        x1_t0  = 0.0,       # Initial position
-        x2_t0  = 1.0,       # Initial velocity
-        x1_tf  = 0.0,       # Final position
-        x2_tf  = -1.0,      # Final velocity
-        x1_max = 1/9        # State constraint: x1(t) <= x1_max
+        t0=0.0,       # Initial time
+        tf=1.0,       # Final time
+        x1_t0=0.0,       # Initial position
+        x2_t0=1.0,       # Initial velocity
+        x1_tf=0.0,       # Final position
+        x2_tf=-1.0,      # Final velocity
+        x1_max=1/9,        # State constraint: x1(t) <= x1_max
     ),
-)
+)

ext/MetaData/mountain_car.jl

@@ -1,21 +1,21 @@
 mountain_car_meta = OrderedDict(
     :grid_size => 200,
     :parameters => (
-        t0 = 0.0,
-        tf_start = 110.0,
-        tf_min = 0.1,
-        pos_t0 = -0.5,
-        vel_t0 = 0.0,
-        pos_tf = 0.5,
-        vel_tf_min = 0.0,
-        pos_min = -1.2,
-        pos_max = 0.5,
-        vel_min = -0.07,
-        vel_max = 0.07,
-        u_min = -1.0,
-        u_max = 1.0,
-        a = 0.001,
-        b = 0.0025,
-        c = 3.0,
+        t0=0.0,
+        tf_start=110.0,
+        tf_min=0.1,
+        pos_t0=-0.5,
+        vel_t0=0.0,
+        pos_tf=0.5,
+        vel_tf_min=0.0,
+        pos_min=-1.2,
+        pos_max=0.5,
+        vel_min=-0.07,
+        vel_max=0.07,
+        u_min=-1.0,
+        u_max=1.0,
+        a=0.001,
+        b=0.0025,
+        c=3.0,
     ),
 )

ext/OptimalControlModels/balanced_field.jl

@@ -46,7 +46,7 @@ function OptimalControlProblems.balanced_field(
     span = params[:span]
     α_max = params[:α_max]
     T = params[:T]
-    
+
     r_t0 = params[:r_t0]
     v_t0 = params[:v_t0]
     h_t0 = params[:h_t0]
@@ -75,7 +75,7 @@ function OptimalControlProblems.balanced_field(
 
         h(tf) == h_tf
         γ(tf) == γ_tf
-        
+
         0 ≤ α(t) ≤ α_max_ctrl # alpha
         tf ≥ 0.1
         h(t) ≥ 0
@@ -88,21 +88,21 @@ function OptimalControlProblems.balanced_field(
 
     function dynamics(x, α, m, g, ρ, S, CD0, CL0, CL_max, α_max, T, b, K_nom, h_w)
         r, v, h, γ = x
-        
+
         q = 0.5 * ρ * v^2
         CL = CL0 + (α / α_max) * (CL_max - CL0)
         L = q * S * CL
-        
+
         h_eff = h + h_w
         term_h = 33.0 * abs(h_eff / b)^1.5
         K = K_nom * term_h / (1.0 + term_h)
         D = q * S * (CD0 + K * CL^2)
-        
+
         rdot = v * cos(γ)
         vdot = (T * cos(α) - D) / m - g * sin(γ)
         hdot = v * sin(γ)
         γdot = (T * sin(α) + L) / (m * v) - (g * cos(γ)) / v
-        
+
         return [rdot, vdot, hdot, γdot]
     end
 

ext/OptimalControlModels/brachistochrone.jl

@@ -33,9 +33,8 @@ function OptimalControlProblems.brachistochrone(
     parameters::Union{Nothing,NamedTuple}=nothing,
     kwargs...,
 )
-    
     params = parameters_data(:brachistochrone, parameters)
-    g  = params[:g]
+    g = params[:g]
     t0 = params[:t0]
     x0 = params[:x0]
     y0 = params[:y0]
@@ -48,23 +47,23 @@ function OptimalControlProblems.brachistochrone(
     ocp = @def begin
         tf ∈ R, variable
         t ∈ [t0, tf], time
-        
+
         z = (px, py, v) ∈ R³, state
         u ∈ R, control
 
         -1.57 ≤ u(t) ≤ 1.57
-        0.1 ≤ tf ≤ 20.0 
+        0.1 ≤ tf ≤ 20.0
 
         px(t0) == x0
         py(t0) == y0
-        v(t0)  == v0
-        
+        v(t0) == v0
+
         px(tf) == xf
         py(tf) == yf
 
         ∂(px)(t) == v(t) * sin(u(t))
         ∂(py)(t) == -v(t) * cos(u(t))
-        ∂(v)(t)  == g * cos(u(t))
+        ∂(v)(t) == g * cos(u(t))
 
         # Objectif
         tf → min
@@ -73,24 +72,24 @@ function OptimalControlProblems.brachistochrone(
     # initial guess: linear interpolation to match JuMP
     tf_guess = 2.0
     init = (
-        state = t -> [
+        state=t -> [
             x0 + (t - t0) / (tf_guess - t0) * (xf - x0),
             y0 + (t - t0) / (tf_guess - t0) * (yf - y0),
-            v0 + (t - t0) / (tf_guess - t0) * 10.0
+            v0 + (t - t0) / (tf_guess - t0) * 10.0,
         ],
-        control = 1.57,
-        variable = tf_guess
+        control=1.57,
+        variable=tf_guess,
     )
 
     docp = direct_transcription(
         ocp,
         description...;
         lagrange_to_mayer=false,
-        init = init,
-        grid_size = grid_size,
+        init=init,
+        grid_size=grid_size,
         disc_method=:trapeze,
-        kwargs...
+        kwargs...,
     )
 
     return docp
-end
+end