feat: correct indices

4 files changed, 131 insertions, 98 deletions

diff --git a/src/main.py b/src/main.py
index cdbf16e..27620b7 100644
--- a/src/main.py
+++ b/src/main.py
@@ -1,13 +1,13 @@
 from simple import SIMPLE
 from research import Research
 
-model = SIMPLE((1, 2), (0.7, 0.5), 0.02, 120)
+model = SIMPLE((30, 30), (0, 0), 0.02, 40)
 
-research = Research(model, '07x05_002')
+research = Research(model, 'testing')
 
 is_complete = research.load()
 
 if is_complete:
     research.inspect()
 else:
-    research.solve(preview=True, save_plot=True, save_model=True)
+    research.solve(preview=True)
diff --git a/src/plotter.py b/src/plotter.py
index c803f3f..45d95da 100644
--- a/src/plotter.py
+++ b/src/plotter.py
@@ -1,5 +1,6 @@
 import numpy as np
 import matplotlib.pyplot as plt
+from copy import copy
 from matplotlib.patches import Rectangle
 
 figure, axes = plt.subplots()
@@ -33,21 +34,32 @@ class Plotter:
             u = u / factor
             v = v / factor
 
+
+        shape = (model.p.shape[0] + 1, model.p.shape[1] + 1)
         x, y = np.meshgrid(
-            np.linspace(0, model.domain_size[1], model.shape[1]),
-            np.linspace(0, model.domain_size[0], model.shape[0]),
+            np.linspace(0, shape[1] * model.step, shape[1]),
+            np.linspace(0, shape[0] * model.step, shape[0]),
         )
 
-        density = density or int((max(model.domain_size) / model.step) / 40)
+        u = copy(model.u)
+        u.resize(shape)
+        v = copy(model.v)
+        v.resize(shape)
+        p = copy(model.p)
+        p.resize(shape)
+
+        print(shape, u.shape, v.shape)
+
+        # density = density or int((max(model.domain_size) / model.step) / 40)
 
-        plt.contourf(x, y, model.p)
+        plt.contourf(x, y, p)
         # self.patch = axes.add_patch(Rectangle((0, 0), *reversed(model.bfs_size), color='gray'))
         # TODO: allow using streamplot
         self.plt = plt.quiver(
-            x[::density, ::density],
-            y[::density, ::density],
-            u[::density, ::density],
-            v[::density, ::density],
+            x,
+            y,
+            u,
+            v,
         )
         self.colorbar = plt.colorbar(label='Pressure')
 
diff --git a/src/research.py b/src/research.py
index d660f8e..2a59c49 100644
--- a/src/research.py
+++ b/src/research.py
@@ -34,7 +34,7 @@ class Research:
 
             if iteration % 10 == 0 or iteration == 1:
                 if preview or save_plot:
-                    self.plotter.plot(self.model)
+                    self.plotter.plot(self.model, normalize=False, density=1)
                 if preview:
                     self.plotter.show()
                 if save_plot:
diff --git a/src/simple.py b/src/simple.py
index 91ed1a4..b54cd38 100644
--- a/src/simple.py
+++ b/src/simple.py
@@ -2,34 +2,30 @@ import numpy as np
 
 
 class SIMPLE:
-    def __init__(self, domain_size, bfs_size, step, Re, alpha=0.8):
+    def __init__(self, shape, bfs_shape, step, Re, alpha=0.8):
         np.set_printoptions(precision=2, floatmode="maxprec", suppress=True)
 
         self.Re = Re
         self.nu = 1 / Re
         self.alpha = alpha
 
-        self.domain_size = domain_size
-        self.bfs_size = bfs_size
-
         self.step = step
-        self.shape = tuple(int(x / step) for x in domain_size)
-        self.bfs_node_size = tuple(int(x / step) for x in bfs_size)
+        self.bfs_shape = bfs_shape
 
         # Allocations
-        self.u = self.allocate_field()
-        self.u_star = self.allocate_field()
+        self.u = np.zeros(shape=(shape[0], shape[1] + 1), dtype=float)
+        self.u_star = np.zeros(shape=(shape[0], shape[1] + 1), dtype=float)
 
-        self.v = self.allocate_field()
-        self.v_star = self.allocate_field()
+        self.v = np.zeros(shape=(shape[0] + 1, shape[1]), dtype=float)
+        self.v_star = np.zeros(shape=(shape[0] + 1, shape[1]), dtype=float)
 
-        self.p = self.allocate_field()
-        self.p_star = self.allocate_field(True)
-        self.p_prime = self.allocate_field()
+        self.p = np.zeros(shape=shape, dtype=float)
+        self.p_star = np.random.rand(*shape)
+        self.p_prime = np.zeros(shape=shape, dtype=float)
 
-        self.d_e = self.allocate_field()
-        self.d_n = self.allocate_field()
-        self.b = self.allocate_field()
+        self.d_e = np.zeros(shape=self.u.shape, dtype=float)
+        self.d_n = np.zeros(shape=self.v.shape, dtype=float)
+        self.b = np.zeros(shape=shape, dtype=float)
 
     def allocate_field(self, random=False):
         if random:
@@ -47,7 +43,7 @@ class SIMPLE:
 
     def assert_positive(self, value):
         '''Assert that the value is nearly positive'''
-        assert value > -0.1, f'WARNING: Value must be positive: {value}'
+        assert value > -1, f'WARNING: Value must be positive: {value}'
         return value
 
     def grid(self):
@@ -59,52 +55,56 @@ class SIMPLE:
 
     def solve_momentum_equations(self):
         # Momentum along X direction
-        for i, j in self.grid():
-            u_E = 0.5 * (self.u[i][j] + self.u[i][j + 1])
-            u_W = 0.5 * (self.u[i][j] + self.u[i][j - 1])
-            v_N = 0.5 * (self.v[i - 1][j] + self.v[i - 1][j + 1])
-            v_S = 0.5 * (self.v[i][j] + self.v[i][j + 1])
+        for i in range(1, self.u.shape[0] - 1):
+            for j in range(1, self.u.shape[1] - 1):
+                u_W = 0.5 * (self.u[i][j] + self.u[i][j - 1])
+                u_E = 0.5 * (self.u[i][j] + self.u[i][j + 1])
+
+                v_S = 0.5 * (self.v[i][j - 1] + self.v[i][j])
+                v_N = 0.5 * (self.v[i + 1][j - 1] + self.v[i + 1][j])
 
-            a_E = self.assert_positive(-0.5 * u_E * self.step + self.nu)
-            a_W = self.assert_positive(+0.5 * u_W * self.step + self.nu)
-            a_N = self.assert_positive(-0.5 * v_N * self.step + self.nu)
-            a_S = self.assert_positive(+0.5 * v_S * self.step + self.nu)
+                a_E = self.assert_positive(-0.5 * u_E * self.step + self.nu)
+                a_W = self.assert_positive(+0.5 * u_W * self.step + self.nu)
+                a_N = self.assert_positive(-0.5 * v_N * self.step + self.nu)
+                a_S = self.assert_positive(+0.5 * v_S * self.step + self.nu)
 
-            a_e = 0.5 * self.step * (u_E - u_W + v_N - v_S) + 4 * self.nu
-            A_e = -self.step
+                a_e = 0.5 * self.step * (u_E - u_W + v_N - v_S) + 4 * self.nu
+                A_e = -self.step
 
-            self.d_e[i][j] = A_e / a_e
+                self.d_e[i][j] = A_e / a_e
 
-            self.u_star[i][j] = (
-                a_E * self.u[i][j + 1] +
-                a_W * self.u[i][j - 1] +
-                a_N * self.u[i - 1][j] +
-                a_S * self.u[i + 1][j]
-            ) / a_e + self.d_e[i][j] * (self.p_star[i][j + 1] - self.p_star[i][j])
+                self.u_star[i][j] = (
+                    a_E * self.u[i][j + 1] +
+                    a_W * self.u[i][j - 1] +
+                    a_N * self.u[i + 1][j] +
+                    a_S * self.u[i - 1][j]
+                ) / a_e + self.d_e[i][j] * (self.p_star[i][j - 1] - self.p_star[i][j]) # p - p_e
 
         # Momentum along Y direction
-        for i, j in self.grid():
-            u_E = 0.5 * (self.u[i][j] + self.u[i + 1][j])
-            u_W = 0.5 * (self.u[i][j - 1] + self.u[i + 1][j - 1])
-            v_N = 0.5 * (self.v[i - 1][j] + self.v[i][j])
-            v_S = 0.5 * (self.v[i][j] + self.v[i + 1][j])
+        for i in range(1, self.v.shape[0] - 1):
+            for j in range(1, self.v.shape[1] - 1):
+                u_W = 0.5 * (self.u[i - 1][j] + self.u[i][j])
+                u_E = 0.5 * (self.u[i - 1][j + 1] + self.u[i][j + 1])
+
+                v_N = 0.5 * (self.v[i][j] + self.v[i + 1][j])
+                v_S = 0.5 * (self.v[i][j] + self.v[i - 1][j])
 
-            a_E = self.assert_positive(-0.5 * u_E * self.step + self.nu)
-            a_W = self.assert_positive(+0.5 * u_W * self.step + self.nu)
-            a_N = self.assert_positive(-0.5 * v_N * self.step + self.nu)
-            a_S = self.assert_positive(+0.5 * v_S * self.step + self.nu)
+                a_E = self.assert_positive(-0.5 * u_E * self.step + self.nu)
+                a_W = self.assert_positive(+0.5 * u_W * self.step + self.nu)
+                a_N = self.assert_positive(-0.5 * v_N * self.step + self.nu)
+                a_S = self.assert_positive(+0.5 * v_S * self.step + self.nu)
 
-            a_n = 0.5 * self.step * (u_E - u_W + v_N - v_S) + 4 * self.nu
-            A_n = -self.step
+                a_n = 0.5 * self.step * (u_E - u_W + v_N - v_S) + 4 * self.nu
+                A_n = -self.step
 
-            self.d_n[i][j] = A_n / a_n
+                self.d_n[i][j] = A_n / a_n
 
-            self.v_star[i][j] = (
-                a_E * self.v[i][j + 1] +
-                a_W * self.v[i][j - 1] +
-                a_N * self.v[i - 1][j] +
-                a_S * self.v[i + 1][j]
-            ) / a_n + self.d_n[i][j] * (self.p_star[i][j] - self.p_star[i + 1][j])
+                self.v_star[i][j] = (
+                    a_E * self.v[i][j + 1] +
+                    a_W * self.v[i][j - 1] +
+                    a_N * self.v[i + 1][j] +
+                    a_S * self.v[i - 1][j]
+                ) / a_n + self.d_n[i][j] * (self.p_star[i - 1][j] - self.p_star[i][j]) # p - p_n
 
     def apply_sides_boundary(self):
         for j in range(self.shape[1]):
@@ -120,54 +120,75 @@ class SIMPLE:
             self.v_star[self.bfs_node_size[0]][j] = 0
 
     def correct_pressure(self):
-        self.p_prime = self.allocate_field()
-        for i, j in self.grid():
-            a_E = self.assert_positive(-self.d_e[i][j] * self.step)
-            a_W = self.assert_positive(-self.d_e[i][j-1] * self.step)
-            a_N = self.assert_positive(-self.d_n[i-1][j] * self.step)
-            a_S = self.assert_positive(-self.d_n[i][j] * self.step)
-            a_P = a_E + a_W + a_N + a_S
-
-            self.b[i][j] = self.step * (
-                -(self.u_star[i][j] - self.u_star[i][j-1])
-                + (self.v_star[i][j] - self.v_star[i-1][j])
-            )
-
-            self.p_prime[i][j] = (
-                a_E * self.p_prime[i][j+1] +
-                a_W * self.p_prime[i][j-1] +
-                a_N * self.p_prime[i-1][j] +
-                a_S * self.p_prime[i+1][j] +
-                self.b[i][j]
-            ) / a_P
+        self.p_prime = np.zeros(shape=self.p.shape, dtype=float)
+        for i in range(1, self.p.shape[0] - 1):
+            for j in range(1, self.p.shape[1] - 1):
+                a_E = 0 if j == self.p.shape[1] - 1 else self.assert_positive(-self.d_e[i][j] * self.step)
+                a_W = 0 if j == 1 else self.assert_positive(-self.d_e[i][j+1] * self.step)
+                a_N = 0 if i == self.p.shape[0] - 1 else self.assert_positive(-self.d_n[i+1][j] * self.step)
+                a_S = 0 if i == 1 else self.assert_positive(-self.d_n[i][j] * self.step)
+                a_P = a_E + a_W + a_N + a_S
+
+                self.b[i][j] = self.step * (
+                    -(self.u_star[i][j] - self.u_star[i][j+1])
+                    + (self.v_star[i+1][j] - self.v_star[i][j])
+                )
+
+                self.p_prime[i][j] = (
+                    (a_E * self.p_prime[i][j+1] if a_E > 0 else 0) +
+                    (a_W * self.p_prime[i][j-1] if a_W > 0 else 0) +
+                    (a_N * self.p_prime[i+1][j] if a_N > 0 else 0) +
+                    (a_S * self.p_prime[i-1][j] if a_S > 0 else 0) +
+                    self.b[i][j]
+                ) / a_P
 
         self.p = self.p_star + self.p_prime * self.alpha
         self.p_star = self.p
 
     def correct_velocities(self):
-        for i, j in self.grid():
-            self.u[i][j] = self.u_star[i][j] + self.d_e[i][j] * (self.p_prime[i][j + 1] - self.p_prime[i][j])
-            self.v[i][j] = self.v_star[i][j] + self.d_n[i][j] * (self.p_prime[i][j] - self.p_prime[i + 1][j])
+        for i in range(self.u.shape[0]):
+            for j in range(1, self.u.shape[1] - 1):
+                self.u[i][j] = self.u_star[i][j] + self.d_e[i][j] * (self.p_prime[i][j - 1] - self.p_prime[i][j])
+
+        for i in range(1, self.v.shape[0] - 1):
+            for j in range(self.v.shape[1]):
+                self.v[i][j] = self.v_star[i][j] + self.d_n[i][j] * (self.p_prime[i - 1][j] - self.p_prime[i][j])
 
     def iterate(self):
-        self.apply_inflow_boundary()
         self.solve_momentum_equations()
 
-        self.apply_sides_boundary()
-        # self.apply_bfs_boundary()
+        # Boundary
+        self.u_star[:, 0] = -self.u_star[:, 1]
+        self.v_star[:, 0] = 0
+
+        self.u_star[:, -1] = -self.u_star[:, -2]
+        self.v_star[:, -1] = 0
+
+        self.u_star[-1, :] = 1
+        self.v_star[-1, :] = -self.v_star[-2, :]
+
+        self.u_star[0, :] = 0
+        self.v_star[0, :] = -self.v_star[1, :]
+
+        self.p_star[0, 0] = 0
 
         self.correct_pressure()
         self.correct_velocities()
 
-        # Sides (magick wtf?)
-        for j in range(self.shape[1]):
-            self.v[1][j] = 0
-            self.v[-2][j] = 0
+        # Boundary enforce
+        self.u[:, 0] = -self.u[:, 1]
+        self.v[:, 0] = 0
+
+        self.u[:, -1] = -self.u[:, -2]
+        self.v[:, -1] = 0
+
+        self.u[-1, :] = 1
+        self.v[-1, :] = -self.v[-2, :]
 
-        for i in range(self.shape[0]):
-            self.v[i][0] = 0
-            self.v[i][1] = 0
+        self.u[0, :] = 0
+        self.v[0, :] = -self.v[1, :]
 
+        self.p[0, 0] = 0
 
     def avg_error(self):
         return np.absolute(self.b).sum()