folivo/PINA
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Fixing tutorials grammar (#242)

Browse Source 
* grammar check and sparse rephrasing
* rst created
* meta copyright adjusted
This commit is contained in:
Giuseppe Alessio D'Inverno
2024-03-05 10:43:34 +01:00
committed by GitHub
parent 15136e13f8
commit b10e02103b
23 changed files with 272 additions and 237 deletions
Download Patch File Download Diff File Expand all files Collapse all files

6
tutorials/tutorial5/tutorial.py vendored
View File

@@ -4,7 +4,7 @@
# # Tutorial: Two dimensional Darcy flow using the Fourier Neural Operator
# In this tutorial we are going to solve the Darcy flow problem in two dimensions, presented in [*Fourier Neural Operator for
# Parametric Partial Differential Equation*](https://openreview.net/pdf?id=c8P9NQVtmnO). First of all we import the modules needed for the tutorial. Importing `scipy` is needed for input output operations.
# Parametric Partial Differential Equation*](https://openreview.net/pdf?id=c8P9NQVtmnO). First of all we import the modules needed for the tutorial. Importing `scipy` is needed for input-output operations.
# In[1]:
@@ -22,7 +22,7 @@ import matplotlib.pyplot as plt
# ## Data Generation
#
# We will focus on solving the a specfic PDE, the **Darcy Flow** equation. The Darcy PDE is a second order, elliptic PDE with the following form:
# We will focus on solving a specific PDE, the **Darcy Flow** equation. The Darcy PDE is a second-order elliptic PDE with the following form:
#
# $$
# -\nabla\cdot(k(x, y)\nabla u(x, y)) = f(x) \quad (x, y) \in D.
@@ -112,7 +112,7 @@ err = float(metric_err(u_test.squeeze(-1), solver.neural_net(k_test).squeeze(-1)
print(f'Final error testing {err:.2f}%')
# ## Solving the problem with a Fuorier Neural Operator (FNO)
# ## Solving the problem with a Fourier Neural Operator (FNO)
#
# We will now move to solve the problem using a FNO. Since we are learning operator this approach is better suited, as we shall see.