np.random.seed(123456789)
#
dimension = 20
+nbmeasures = 15
#
print("Defining a set of artificial physical fields")
from Models.TwoDimensionalInverseDistanceCS2010 \
Parameters = {
"Variant":"DEIM",
"SampleAsnUplet":Eq.get_sample_of_mu(15, 15),
- "MaximumNumberOfLocations":50,
+ "MaximumNumberOfLocations":nbmeasures,
"ErrorNorm":"Linf",
"ErrorNormTolerance":0.,
"StoreSupplementaryCalculations":[
case.setObservationOperator(OneFunction = Eq.OneRealisation)
case.execute()
#
+#-------------------------------------------------------------------------------
print()
print("Graphical display of the results")
#
sp = case.get("EnsembleOfSimulations")[-1]
+sv = case.get("SingularValues")[-1]
+op = case.get("OptimalPoints")[-1]
+#
x1, x2 = Eq.get_x()
x1, x2 = np.meshgrid(x1, x2)
-name = "Representation of a few snapshots of G out of a total of %i"%sp.shape[1]
-print(" -", name)
-fig, ax = plt.subplots(subplot_kw={"projection": "3d"}, figsize=(6, 6))
-fig.suptitle(name)
-ax.set_xlabel("Position x1", fontweight='bold', color='red')
-ax.set_ylabel("Position x2", fontweight='bold', color='red')
-ax.set_zlabel("Magnitude of G", fontweight='bold', color='red')
-for i in range(sp.shape[1]):
- if i % 44 != 0: continue
- ax.plot_surface(x1, x2, sp[:,i].reshape((dimension, dimension)), cmap='coolwarm')
-fig.savefig("simple_MeasurementsOptimalPositioningTask31.png")
-plt.close()
+posx1 = [x1.reshape((-1,))[ip] for ip in op]
+posx2 = [x2.reshape((-1,))[ip] for ip in op]
+Omega = Eq.get_bounds_on_space()
#
-sv = case.get("SingularValues")[-1]
-name = "Singular values of the set of G simulations"
+fig = plt.figure(figsize=(18, 6))
+name = "Measurement optimal points search by "
+name += '"ADAO/MeasurementsOptimalPositioningTask/DEIM"'
+fig.suptitle(name, fontsize=20, fontstyle='italic')
+#
+ax = fig.add_subplot(1, 3, 1)
+name = "Singular values of the set of %i G simulations"%sp.shape[1]
print(" -", name)
-fig, ax = plt.subplots(figsize=(6, 6))
-fig.suptitle(name)
+ax.set_title(name, fontstyle='italic', color='red')
ax.set_xlabel("Index of singular values, numbered from 1")
ax.set_ylabel("Magnitude of singular values")
ax.set_xlim(1, len(sv))
ax.set_yscale("log")
ax.grid(True)
ax.plot(range(1, 1 + len(sv)), sv)
-fig.savefig("simple_MeasurementsOptimalPositioningTask32.png")
-plt.tight_layout()
-plt.close()
#
-nbmax = 15
-op = case.get("OptimalPoints")[-1]
-posx1 = [x1.reshape((-1,))[ip] for ip in op[:nbmax]]
-posx2 = [x2.reshape((-1,))[ip] for ip in op[:nbmax]]
-name = "Set of %i first optimal points of measurement"%nbmax
-Omega = Eq.get_bounds_on_space()
+ax = fig.add_subplot(1, 3, 2, projection = "3d")
+name = "A few simulations of G out of a total of %i"%sp.shape[1]
print(" -", name)
-fig, ax = plt.subplots(figsize=(6, 6))
-fig.suptitle(name)
-ax.set_xlabel("Position x1", fontweight='bold', color='red')
-ax.set_ylabel("Position x2", fontweight='bold', color='red')
+ax.set_title(name, fontstyle='italic', color='red')
+ax.set_xlabel("Position x1")
+ax.set_ylabel("Position x2")
+ax.set_zlabel("Magnitude of G")
+for i in range(sp.shape[1]):
+ if i % 44 != 0: continue
+ Gfield = sp[:,i].reshape((dimension, dimension))
+ ax.plot_surface(x1, x2, Gfield, cmap='coolwarm')
+#
+ax = fig.add_subplot(1, 3, 3)
+name = "Set of %i first optimal points of measurement"%nbmeasures
+print(" -", name)
+ax.set_title(name, fontstyle='italic', color='red')
+ax.set_xlabel("Position x1")
+ax.set_ylabel("Position x2")
ax.set_xlim(Omega[0][0] - 0.05, Omega[0][1] + 0.05)
ax.set_ylim(Omega[1][0] - 0.05, Omega[1][1] + 0.05)
ax.grid(True, which='both', linestyle=(0, (1, 5)), linewidth=0.5)
ax.plot(posx1, posx2, markersize=6, marker="o", linestyle='')
for i in range(len(posx1)):
ax.text(posx1[i] + 0.005, posx2[i] + 0.01, str(i + 1), fontweight='bold')
-fig.savefig("simple_MeasurementsOptimalPositioningTask33.png")
+#
plt.tight_layout()
+fig.savefig("simple_MeasurementsOptimalPositioningTask3.png")
plt.close()
