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Introduction to computing with finite difference methods
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Index
A
|
B
|
C
|
D
|
E
|
F
|
G
|
H
|
I
|
L
|
M
|
N
|
O
|
P
|
R
|
S
|
T
|
V
|
W
A
A-stable methods
Adams-Bashforth scheme, 2nd-order
Adams-Bashforth scheme, 3rd order
adaptive time stepping
algebraic equation
amplification factor
array arithmetics
,
[1]
array computing
,
[1]
averaging
arithmetic
geometric
B
backward difference
Backward Euler scheme
backward scheme, 1-step
backward scheme, 2-step
BDF2 scheme
C
centered difference
chemical reactions
irreversible
reversible
consistency
continuous function norms
convergence
convergence rate
Crank-Nicolson scheme
cropping images
D
decay ODE
difference equation
directory
discrete equation
discrete function norms
doc strings
Dormand-Prince Runge-Kutta 4-5 method
E
EPS plot
error
amplification factor
global
norms
explicit schemes
exponential decay
F
finite difference operator notation
finite difference scheme
finite differences
backward
centered
forward
folder
format string syntax (Python)
forward difference
Forward Euler scheme
G
geometric mean
grid
H
Heun's method
I
implicit schemes
interactive Python
isympy
L
L-stable methods
lambda functions
Leapfrog scheme
Leapfrog scheme, filtered
logistic model
M
mesh
mesh function
mesh function norms
method of manufactured solutions
MMS (method of manufactured solutions)
montage program
N
norm
continuous
discrete (mesh function)
O
ode45
operator notation, finite differences
P
PDF plot
pdfcrop program
pdfnup program
pdftk program
plotting curves
PNG plot
population dynamics
printf format
R
radioactive decay
representative (mesh function)
RK4
Runge-Kutta, 2nd-order method
Runge-Kutta, 4th-order method
S
scalar computing
scaling
stability
,
[1]
sympy
T
Taylor-series methods (for ODEs)
terminal velocity
theta-rule
,
[1]
,
[2]
,
[3]
time step
V
vectorization
,
[1]
verification
viewing graphics files
visualizing curves
W
weighted average
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Introduction to computing with finite difference methods
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