spellcheck + hrunic

Author: pogudingleb

benchmarking/benchmarks.jl

@@ -1285,7 +1285,7 @@ benchmarks = Dict(
         :ode => @ODEmodel(
             C'(t) = u(t) - k1 * C(t) / (k2 + C(t)),
             T'(t) = ka * T(t) - kb * C(t) * T(t) / (kc + T(t)) - kd * T(t) * I(t),
-            I'(t) = X(t) - ke * T(t) * I(t) - kf * C(t)  * I(t) - kg * I(t) * Y(t) - kh * I(t),
+            I'(t) = X(t) - ke * T(t) * I(t) - kf * C(t) * I(t) - kg * I(t) * Y(t) - kh * I(t),
             X'(t) = C(t) / (1 + C(t) * ki_inv) - kj * X(t) - kk * X(t) * Y(t),
             Y'(t) = I(t) / (1 + C(t) * kl_inv) - km * Y(t) * C(t),
             y(t) = T(t)

src/output_saturation.jl

@@ -2,7 +2,7 @@
     saturate_outputs(ode, orders, max_deg = 5)
 
 Adds extra outputs extracted from the Lie derivatives of the existing outputs up to the prescribed order.
-Adds only the outputs which are algebraically independent over the existing outputs, paramaters, and inputs
+Adds only the outputs which are algebraically independent over the existing outputs, parameters, and inputs
 (and, thus, may be useful in the differential elimination process).
 
 Inputs:
@@ -13,10 +13,10 @@ Inputs:
 Output: a new ode model with inputs inserted
 """
 function saturate_outputs(
-    ode::ODE{P},
-    orders::Dict{P, Int},
-    max_deg = 5,
-) where {P <: MPolyRingElem}
+        ode::ODE{P},
+        orders::Dict{P, Int},
+        max_deg = 5,
+    ) where {P <: MPolyRingElem}
     lie_ders = lie_derivatives_up_to(ode, Dict(ode.y_equations[y] => ord for (y, ord) in orders))
     @info "Degrees: $([(total_degree(numerator(f)), total_degree(denominator(f))) for f in lie_ders])"
 
@@ -28,7 +28,7 @@ function saturate_outputs(
             current_y = RationalFunctionField([generators(current_y)..., f])
         end
     end
-    new_outputs = generators(current_y)[length(ode.y_vars) + length(ode.u_vars) + length(ode.parameters) + 1 : end]
+    new_outputs = generators(current_y)[(length(ode.y_vars) + length(ode.u_vars) + length(ode.parameters) + 1):end]
 
     idx = 1
     old_y_names = map(var_to_str, ode.y_vars)

src/primality_check.jl

@@ -18,7 +18,7 @@ function check_primality_zerodim(J::Array{QQMPolyRingElem, 1})
         push!(matrices, M)
     end
     generic_multiplication = sum(Nemo.QQ(rand(1:100)) * M for M in matrices)
-    @debug "Generic mulitplication matrix computed"
+    @debug "Generic multiplication matrix computed"
     @debug "Trying reductions over primed first"
     NUM_PRIMES = 10
     p = 2^31 - 1

test/y_saturation.jl

@@ -30,7 +30,7 @@ if GROUP == "All" || GROUP == "Core"
             y5(t) = x2(t),
             y6(t) = x12(t)
         )
-        
+
         nfkb_orders = propose_orders(nfkb)
         new_nfkb = saturate_outputs(nfkb, nfkb_orders)
         @test length(new_nfkb.y_vars) == 14
@@ -41,25 +41,25 @@ if GROUP == "All" || GROUP == "Core"
 
         # TumorPilis model from the benchmarks
         tum_pil = @ODEmodel(
-                    T'(t) =
-                        a * T(t) * (1 - b * T(t)) - c1 * N(t) * T(t) - D(t) * T(t) -
-                        KT * M(t) * T(t), #tumor cells
-                    L'(t) =
-                        -m * L(t) - q * L(t) * T(t) - ucte * L(t)^2 +
-                        r2 * C(t) * T(t) +
-                        pI * L(t) * I(t) / (gI + I(t)) +
-                        u1(t) - KL * M(t) * L(t), # tumor-specific effector cells, T-celss
-                    N'(t) =
-                        alpha1 - f * N(t) + g * T(t) * N(t) / (h + T(t)) - p * N(t) * T(t) - KN * M(t) * N(t), # non-specific effector cells, NK cells
-                    C'(t) = alpha2 - beta * C(t) - KC * M(t) * C(t), #circulating lymphocytes
-                    I'(t) =
-                        pt * T(t) * L(t) / (gt + T(t)) + w * L(t) * I(t) - muI * I(t) + u2(t), # IL-2, VI = u2 aplicación directa, terapia de IL2
-                    M'(t) = -gamma * M(t) + u1(t), #chemotherapy drug, terapia/aplicación de quimio, u1 = VM
-                    y1(t) = L(t),
-                    y2(t) = N(t),
-                    y3(t) = M(t)
-                )
-        
+            T'(t) =
+                a * T(t) * (1 - b * T(t)) - c1 * N(t) * T(t) - D(t) * T(t) -
+                KT * M(t) * T(t), #tumor cells
+            L'(t) =
+                -m * L(t) - q * L(t) * T(t) - ucte * L(t)^2 +
+                r2 * C(t) * T(t) +
+                pI * L(t) * I(t) / (gI + I(t)) +
+                u1(t) - KL * M(t) * L(t), # tumor-specific effector cells, T-celss
+            N'(t) =
+                alpha1 - f * N(t) + g * T(t) * N(t) / (h + T(t)) - p * N(t) * T(t) - KN * M(t) * N(t), # non-specific effector cells, NK cells
+            C'(t) = alpha2 - beta * C(t) - KC * M(t) * C(t), #circulating lymphocytes
+            I'(t) =
+                pt * T(t) * L(t) / (gt + T(t)) + w * L(t) * I(t) - muI * I(t) + u2(t), # IL-2, VI = u2 aplicación directa, terapia de IL2
+            M'(t) = -gamma * M(t) + u1(t), #chemotherapy drug, terapia/aplicación de quimio, u1 = VM
+            y1(t) = L(t),
+            y2(t) = N(t),
+            y3(t) = M(t)
+        )
+
         tum_pil_orders = propose_orders(tum_pil)
         new_tum_pil = saturate_outputs(tum_pil, tum_pil_orders)
         @test length(new_tum_pil.y_vars) == 6