back in black

test/verification/analytic/azurv1/plot.py

@@ -30,8 +30,8 @@
 # Flux - average
 fig = plt.figure()
 ax = plt.axes(
-    xlim=(-2,2),#(-21.889999999999997, 21.89), 
-    ylim=(-0.042992644459595206, 2)#0.9028455336514992)
+    xlim=(-2, 2),  # (-21.889999999999997, 21.89),
+    ylim=(-0.042992644459595206, 2),  # 0.9028455336514992)
 )
 ax.grid()
 ax.set_xlabel(r"$x$")

test/verification/analytic/azurv1_gaussianIC/input.py

@@ -29,12 +29,17 @@
 # Set source
 # =============================================================================
 # Isotropic pulse at x=t=0
-x = np.linspace(-15,15,int(1e4))
-gaussian = np.exp(-4*x**2)
-dx = x[2]-x[1]
-edges_x = np.append(x-dx/2,x[-1]+dx/2)
-for ii, (x1,x2) in enumerate(zip(edges_x[:-1],edges_x[1:])):
-    mcdc.source(x=[x1,x2],prob=gaussian[ii]*0.8862269254527580136490837416705725913987747280611935641069038949,time=[1e-10, 1e-10])
+x = np.linspace(-15, 15, int(1e4))
+gaussian = np.exp(-4 * x**2)
+dx = x[2] - x[1]
+edges_x = np.append(x - dx / 2, x[-1] + dx / 2)
+for ii, (x1, x2) in enumerate(zip(edges_x[:-1], edges_x[1:])):
+    mcdc.source(
+        x=[x1, x2],
+        prob=gaussian[ii]
+        * 0.8862269254527580136490837416705725913987747280611935641069038949,
+        time=[1e-10, 1e-10],
+    )
 
 
 # =============================================================================

test/verification/analytic/azurv1_gaussianIC/makereference.py

@@ -1,16 +1,19 @@
 import numpy as np
 import h5py
 import scipy
-x = np.linspace(-20.5,20.5,202)
-t = np.linspace(.5,19.5,20)
-phi = np.empty((10001,201))
-tavg = np.linspace(0,20,10001)
-with h5py.File("../benchmarks.hdf5",'r') as f:
+
+x = np.linspace(-20.5, 20.5, 202)
+t = np.linspace(0.5, 19.5, 20)
+phi = np.empty((10001, 201))
+tavg = np.linspace(0, 20, 10001)
+with h5py.File("../benchmarks.hdf5", "r") as f:
     for i in range(10001):
-        key = 'gaussian_IC/t = '+str(tavg[i])+'x0=0.5'
-        phi[i,:] = f[key][1,:]
-phiavg = np.empty((20,201))
+        key = "gaussian_IC/t = " + str(tavg[i]) + "x0=0.5"
+        phi[i, :] = f[key][1, :]
+phiavg = np.empty((20, 201))
 for i in range(20):
     for j in range(201):
-        phiavg[i,j] = scipy.integrate.simpson(y = phi[(500*i):(500*i+500),j],x = tavg[(500*i):(500+500*i)])
+        phiavg[i, j] = scipy.integrate.simpson(
+            y=phi[(500 * i) : (500 * i + 500), j], x=tavg[(500 * i) : (500 + 500 * i)]
+        )
 np.savez("reference.npz", x=x, t=t, phi=phiavg)

test/verification/analytic/azurv1_gaussianIC/plot.py

@@ -19,7 +19,10 @@
     dt = t[1:] - t[:-1]
     K = len(t) - 1
 
-    phi = f["tally/flux/mean"][:]*0.8862269254527580136490837416705725913987747280611935641069038949
+    phi = (
+        f["tally/flux/mean"][:]
+        * 0.8862269254527580136490837416705725913987747280611935641069038949
+    )
     phi_sd = f["tally/flux/sdev"][:]
 
     # Normalize

test/verification/analytic/azurv1_gaussianIC/process.py

@@ -31,7 +31,10 @@
         dt = t[1:] - t[:-1]
         K = len(t) - 1
 
-        phi = f["tally/flux/mean"][:]*0.8862269254527580136490837416705725913987747280611935641069038949
+        phi = (
+            f["tally/flux/mean"][:]
+            * 0.8862269254527580136490837416705725913987747280611935641069038949
+        )
 
     # Normalize
     for k in range(K):

test/verification/analytic/azurv1_gaussiansource/input.py

@@ -29,12 +29,17 @@
 # Set source
 # =============================================================================
 # Isotropic pulse at x=t=0
-x = np.linspace(-15,15,int(1e4))
-gaussian = np.exp(-4*x**2)
-dx = x[2]-x[1]
-edges_x = np.append(x-dx/2,x[-1]+dx/2)
-for ii, (x1,x2) in enumerate(zip(edges_x[:-1],edges_x[1:])):
-    mcdc.source(x=[x1,x2],prob=gaussian[ii]*0.8862269254527580136490837416705725913987747280611935641069038949,time=[1e-10, 5])
+x = np.linspace(-15, 15, int(1e4))
+gaussian = np.exp(-4 * x**2)
+dx = x[2] - x[1]
+edges_x = np.append(x - dx / 2, x[-1] + dx / 2)
+for ii, (x1, x2) in enumerate(zip(edges_x[:-1], edges_x[1:])):
+    mcdc.source(
+        x=[x1, x2],
+        prob=gaussian[ii]
+        * 0.8862269254527580136490837416705725913987747280611935641069038949,
+        time=[1e-10, 5],
+    )
 
 
 # =============================================================================

test/verification/analytic/azurv1_gaussiansource/makereference.py

@@ -1,16 +1,19 @@
 import numpy as np
 import h5py
 import scipy
-x = np.linspace(-20.5,20.5,202)
-t = np.linspace(.5,19.5,20)
-phi = np.empty((10001,201))
-tavg = np.linspace(0,20,10001)
-with h5py.File("../benchmarks.hdf5",'r') as f:
+
+x = np.linspace(-20.5, 20.5, 202)
+t = np.linspace(0.5, 19.5, 20)
+phi = np.empty((10001, 201))
+tavg = np.linspace(0, 20, 10001)
+with h5py.File("../benchmarks.hdf5", "r") as f:
     for i in range(10001):
-        key = 'gaussian_source/t = '+str(tavg[i])+'x0=0.5'
-        phi[i,:] = f[key][1,:]
-phiavg = np.empty((20,201))
+        key = "gaussian_source/t = " + str(tavg[i]) + "x0=0.5"
+        phi[i, :] = f[key][1, :]
+phiavg = np.empty((20, 201))
 for i in range(20):
     for j in range(201):
-        phiavg[i,j] = scipy.integrate.simpson(y = phi[(500*i):(500*i+500),j],x = tavg[(500*i):(500+500*i)])
+        phiavg[i, j] = scipy.integrate.simpson(
+            y=phi[(500 * i) : (500 * i + 500), j], x=tavg[(500 * i) : (500 + 500 * i)]
+        )
 np.savez("reference.npz", x=x, t=t, phi=phiavg)

test/verification/analytic/azurv1_gaussiansource/plot.py

@@ -19,7 +19,11 @@
     dt = t[1:] - t[:-1]
     K = len(t) - 1
 
-    phi = f["tally/flux/mean"][:]*5*0.8862269254527580136490837416705725913987747280611935641069038949
+    phi = (
+        f["tally/flux/mean"][:]
+        * 5
+        * 0.8862269254527580136490837416705725913987747280611935641069038949
+    )
     phi_sd = f["tally/flux/sdev"][:]
 
     # Normalize

test/verification/analytic/azurv1_gaussiansource/process.py

@@ -31,7 +31,11 @@
         dt = t[1:] - t[:-1]
         K = len(t) - 1
 
-        phi = f["tally/flux/mean"][:]*5*0.8862269254527580136490837416705725913987747280611935641069038949
+        phi = (
+            f["tally/flux/mean"][:]
+            * 5
+            * 0.8862269254527580136490837416705725913987747280611935641069038949
+        )
 
     # Normalize
     for k in range(K):

test/verification/analytic/azurv1_planeIC/makereference.py

@@ -1,22 +1,32 @@
 import numpy as np
 import h5py
 import scipy
-x = np.linspace(-20.5,20.5,202)
-t = np.linspace(.5,19.5,20)
-phi = np.empty((100001,201))
-tavg = np.linspace(0,20,100001)
-with h5py.File("../benchmarks.hdf5",'r') as f:
+
+x = np.linspace(-20.5, 20.5, 202)
+t = np.linspace(0.5, 19.5, 20)
+phi = np.empty((100001, 201))
+tavg = np.linspace(0, 20, 100001)
+with h5py.File("../benchmarks.hdf5", "r") as f:
     for i in range(100001):
-        key = 'plane_IC/t = '+str(tavg[i])
-        phi[i,:] = f[key][1,:]
-phiavg = np.empty((20,201))
+        key = "plane_IC/t = " + str(tavg[i])
+        phi[i, :] = f[key][1, :]
+phiavg = np.empty((20, 201))
 for i in range(20):
     for j in range(201):
         if i == 0:
-            if np.fabs(x[j])-.25<0:
-                phiavg[i,j] = scipy.integrate.simpson(y = phi[(5000*i+200):(5000*i+5000),j],x = tavg[(5000*i+200):(5000+5000*i)])
+            if np.fabs(x[j]) - 0.25 < 0:
+                phiavg[i, j] = scipy.integrate.simpson(
+                    y=phi[(5000 * i + 200) : (5000 * i + 5000), j],
+                    x=tavg[(5000 * i + 200) : (5000 + 5000 * i)],
+                )
             else:
-                phiavg[i,j] = scipy.integrate.simpson(y = phi[(5000*i):(5000*i+5000),j],x = tavg[(5000*i):(5000+5000*i)])
+                phiavg[i, j] = scipy.integrate.simpson(
+                    y=phi[(5000 * i) : (5000 * i + 5000), j],
+                    x=tavg[(5000 * i) : (5000 + 5000 * i)],
+                )
         else:
-            phiavg[i,j] = scipy.integrate.simpson(y = phi[(5000*i):(5000*i+5000),j],x = tavg[(5000*i):(5000+5000*i)])
+            phiavg[i, j] = scipy.integrate.simpson(
+                y=phi[(5000 * i) : (5000 * i + 5000), j],
+                x=tavg[(5000 * i) : (5000 + 5000 * i)],
+            )
 np.savez("reference.npz", x=x, t=t, phi=phiavg)

test/verification/analytic/azurv1_planeIC/plot.py

@@ -30,8 +30,7 @@
 # Flux - average
 fig = plt.figure()
 ax = plt.axes(
-    xlim=(-21.889999999999997, 21.89), 
-    ylim=(-0.042992644459595206,  0.9028455336514992)
+    xlim=(-21.889999999999997, 21.89), ylim=(-0.042992644459595206, 0.9028455336514992)
 )
 ax.grid()
 ax.set_xlabel(r"$x$")
@@ -45,7 +44,7 @@
 
 
 def animate(k):
-    
+
     global fb
     fb.remove()
     line1.set_data(x_mid, phi[k, :])

test/verification/analytic/azurv1_squareIC/input.py

@@ -30,7 +30,7 @@
 # =============================================================================
 # Isotropic pulse at x=t=0
 
-mcdc.source(x=[-.5,.5], isotropic=True, time=[1e-10, 1e-10])
+mcdc.source(x=[-0.5, 0.5], isotropic=True, time=[1e-10, 1e-10])
 
 # =============================================================================
 # Set tally, setting, and run mcdc

test/verification/analytic/azurv1_squareIC/makereference.py

@@ -1,22 +1,32 @@
 import numpy as np
 import h5py
 import scipy
-x = np.linspace(-20.5,20.5,202)
-t = np.linspace(.5,19.5,20)
-phi = np.empty((100001,201))
-tavg = np.linspace(0,20,100001)
-with h5py.File("../benchmarks.hdf5",'r') as f:
+
+x = np.linspace(-20.5, 20.5, 202)
+t = np.linspace(0.5, 19.5, 20)
+phi = np.empty((100001, 201))
+tavg = np.linspace(0, 20, 100001)
+with h5py.File("../benchmarks.hdf5", "r") as f:
     for i in range(100001):
-        key = 'square_IC/t = '+str(tavg[i])+'x0=0.5'
-        phi[i,:] = f[key][1,:]
-phiavg = np.empty((20,201))
+        key = "square_IC/t = " + str(tavg[i]) + "x0=0.5"
+        phi[i, :] = f[key][1, :]
+phiavg = np.empty((20, 201))
 for i in range(20):
     for j in range(201):
         if i == 0:
-            if np.fabs(x[j])-.25<0:
-                phiavg[i,j] = scipy.integrate.simpson(y = phi[(5000*i):(5000*i+5000),j],x = tavg[(5000*i):(5000+5000*i)])
+            if np.fabs(x[j]) - 0.25 < 0:
+                phiavg[i, j] = scipy.integrate.simpson(
+                    y=phi[(5000 * i) : (5000 * i + 5000), j],
+                    x=tavg[(5000 * i) : (5000 + 5000 * i)],
+                )
             else:
-                phiavg[i,j] = scipy.integrate.simpson(y = phi[(5000*i):(5000*i+5000),j],x = tavg[(5000*i):(5000+5000*i)])
+                phiavg[i, j] = scipy.integrate.simpson(
+                    y=phi[(5000 * i) : (5000 * i + 5000), j],
+                    x=tavg[(5000 * i) : (5000 + 5000 * i)],
+                )
         else:
-            phiavg[i,j] = scipy.integrate.simpson(y = phi[(5000*i):(5000*i+5000),j],x = tavg[(5000*i):(5000+5000*i)])
+            phiavg[i, j] = scipy.integrate.simpson(
+                y=phi[(5000 * i) : (5000 * i + 5000), j],
+                x=tavg[(5000 * i) : (5000 + 5000 * i)],
+            )
 np.savez("reference.npz", x=x, t=t, phi=phiavg)

test/verification/analytic/azurv1_squaresource/input.py

@@ -30,7 +30,7 @@
 # =============================================================================
 # Isotropic pulse at x=t=0
 
-mcdc.source(x=[-.5,.5], isotropic=True, time=[1e-10, 5])
+mcdc.source(x=[-0.5, 0.5], isotropic=True, time=[1e-10, 5])
 
 # =============================================================================
 # Set tally, setting, and run mcdc

test/verification/analytic/azurv1_squaresource/makereference.py

@@ -1,16 +1,19 @@
 import numpy as np
 import h5py
 import scipy
-x = np.linspace(-20.5,20.5,202)
-t = np.linspace(.5,19.5,20)
-phi = np.empty((10001,201))
-tavg = np.linspace(0,20,10001)
-with h5py.File("../benchmarks.hdf5",'r') as f:
+
+x = np.linspace(-20.5, 20.5, 202)
+t = np.linspace(0.5, 19.5, 20)
+phi = np.empty((10001, 201))
+tavg = np.linspace(0, 20, 10001)
+with h5py.File("../benchmarks.hdf5", "r") as f:
     for i in range(10001):
-        key = 'square_source/t = '+str(tavg[i])+'x0=0.5'
-        phi[i,:] = f[key][1,:]
-phiavg = np.empty((20,201))
+        key = "square_source/t = " + str(tavg[i]) + "x0=0.5"
+        phi[i, :] = f[key][1, :]
+phiavg = np.empty((20, 201))
 for i in range(20):
     for j in range(201):
-        phiavg[i,j] = scipy.integrate.simpson(y = phi[(500*i):(500*i+500),j],x = tavg[(500*i):(500+500*i)])
+        phiavg[i, j] = scipy.integrate.simpson(
+            y=phi[(500 * i) : (500 * i + 500), j], x=tavg[(500 * i) : (500 + 500 * i)]
+        )
 np.savez("reference.npz", x=x, t=t, phi=phiavg)

test/verification/analytic/azurv1_squaresource/plot.py

@@ -19,7 +19,7 @@
     dt = t[1:] - t[:-1]
     K = len(t) - 1
 
-    phi = f["tally/flux/mean"][:]*5
+    phi = f["tally/flux/mean"][:] * 5
     phi_sd = f["tally/flux/sdev"][:]
 
     # Normalize

test/verification/analytic/azurv1_squaresource/process.py

@@ -31,7 +31,7 @@
         dt = t[1:] - t[:-1]
         K = len(t) - 1
 
-        phi = f["tally/flux/mean"][:]*5
+        phi = f["tally/flux/mean"][:] * 5
 
     # Normalize
     for k in range(K):

test/verification/analytic/task.py

@@ -28,25 +28,25 @@
 # Azurv1 variants
 # Plane IC
 task["azurv1_planeIC"] = {}
-task["azurv1_planeIC"]["N_lim"] = [3,6]
+task["azurv1_planeIC"]["N_lim"] = [3, 6]
 task["azurv1_planeIC"]["N"] = 9
 
 # Square IC
 task["azurv1_squareIC"] = {}
-task["azurv1_squareIC"]["N_lim"] = [3,6]
+task["azurv1_squareIC"]["N_lim"] = [3, 6]
 task["azurv1_squareIC"]["N"] = 9
 
 # Square Source
 task["azurv1_squaresource"] = {}
-task["azurv1_squaresource"]["N_lim"] = [3,6]
+task["azurv1_squaresource"]["N_lim"] = [3, 6]
 task["azurv1_squaresource"]["N"] = 9
 
 # Gaussian IC
 task["azurv1_gaussianIC"] = {}
-task["azurv1_gaussianIC"]["N_lim"] = [3,6]
+task["azurv1_gaussianIC"]["N_lim"] = [3, 6]
 task["azurv1_gaussianIC"]["N"] = 9
 
 # Gaussian Source
 task["azurv1_gaussiansource"] = {}
-task["azurv1_gaussiansource"]["N_lim"] = [3,7]
-task["azurv1_gaussiansource"]["N"] = 7
+task["azurv1_gaussiansource"]["N_lim"] = [3, 7]
+task["azurv1_gaussiansource"]["N"] = 7