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Fixing tutorials grammar (#242)

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* 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
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8
tutorials/tutorial3/tutorial.ipynb vendored
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@@ -54,7 +54,7 @@
"\\end{cases}\n",
"\\end{equation}\n",
"\n",
"where $D$ is a square domain $[0,1]^2$, and $\\Gamma_i$, with $i=1,...,4$, are the boundaries of the square, and the velocity in the standard wave equation is fixed to one."
"where $D$ is a squared domain $[0,1]^2$, and $\\Gamma_i$, with $i=1,...,4$, are the boundaries of the square, and the velocity in the standard wave equation is fixed to one."
]
},
{
@@ -305,7 +305,7 @@
"id": "35e51649",
"metadata": {},
"source": [
"The results are not so great, and we can clearly see that as time progress the solution get worse.... Can we do better?\n",
"The results are not so great, and we can clearly see that as time progress the solution gets worse.... Can we do better?\n",
"\n",
"A valid option is to impose the initial condition as hard constraint as well. Specifically, our solution is written as:\n",
"\n",
@@ -491,7 +491,7 @@
"id": "b7338109",
"metadata": {},
"source": [
"We can see now that the results are way better! This is due to the fact that previously the network was not learning correctly the initial conditon, leading to a poor solution when the time evolved. By imposing the initial condition the network is able to correctly solve the problem."
"We can see now that the results are way better! This is due to the fact that previously the network was not learning correctly the initial conditon, leading to a poor solution when time evolved. By imposing the initial condition the network is able to correctly solve the problem."
]
},
{
@@ -501,7 +501,7 @@
"source": [
"## What's next?\n",
"\n",
"Nice you have completed the two dimensional Wave tutorial of **PINA**! There are multiple directions you can go now:\n",
"Congratulations on completing the two dimensional Wave tutorial of **PINA**! There are multiple directions you can go now:\n",
"\n",
"1. Train the network for longer or with different layer sizes and assert the finaly accuracy\n",
"\n",

8
tutorials/tutorial3/tutorial.py vendored
View File

@@ -34,7 +34,7 @@ from pina import Condition, Plotter
# \end{cases}
# \end{equation}
#
# where $D$ is a square domain $[0,1]^2$, and $\Gamma_i$, with $i=1,...,4$, are the boundaries of the square, and the velocity in the standard wave equation is fixed to one.
# where $D$ is a squared domain $[0,1]^2$, and $\Gamma_i$, with $i=1,...,4$, are the boundaries of the square, and the velocity in the standard wave equation is fixed to one.
# Now, the wave problem is written in PINA code as a class, inheriting from `SpatialProblem` and `TimeDependentProblem` since we deal with spatial, and time dependent variables. The equations are written as `conditions` that should be satisfied in the corresponding domains. `truth_solution` is the exact solution which will be compared with the predicted one.
@@ -142,7 +142,7 @@ print('Plotting at t=1')
plotter.plot(pinn, fixed_variables={'t': 1.0})
# The results are not so great, and we can clearly see that as time progress the solution get worse.... Can we do better?
# The results are not so great, and we can clearly see that as time progress the solution gets worse.... Can we do better?
#
# A valid option is to impose the initial condition as hard constraint as well. Specifically, our solution is written as:
#
@@ -207,11 +207,11 @@ print('Plotting at t=1')
plotter.plot(pinn, fixed_variables={'t': 1.0})
# We can see now that the results are way better! This is due to the fact that previously the network was not learning correctly the initial conditon, leading to a poor solution when the time evolved. By imposing the initial condition the network is able to correctly solve the problem.
# We can see now that the results are way better! This is due to the fact that previously the network was not learning correctly the initial conditon, leading to a poor solution when time evolved. By imposing the initial condition the network is able to correctly solve the problem.
# ## What's next?
#
# Nice you have completed the two dimensional Wave tutorial of **PINA**! There are multiple directions you can go now:
# Congratulations on completing the two dimensional Wave tutorial of **PINA**! There are multiple directions you can go now:
#
# 1. Train the network for longer or with different layer sizes and assert the finaly accuracy
#