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24.10.2024

Optimize your curves

@@ -64,15 +64,15 @@

Oslo Python MeetUp

Sunniva Indrehus

-
+

📈 + 💪 + 🐍 = ❓

-
sunniva@ngi$ echo $(whoami)
+
sunniva@ngi$ echo $(whoami)
 

 

 

-

+

 
Problem

 
@@ -88,7 +88,7 @@ 
Problem

 
 

 

 

-

+

 

 
Optimization: an act, process, or methodology of making something (such as a design, system, or decision) as fully perfect, functional, or effective as possible

 specifically : the mathematical procedures (such as finding the maximum of a function) involved in this

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Problem

 

 

 

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A solution

 
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A solution

 
 

 

 

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Another solution

 
@@ -131,7 +131,7 @@ 
Another solution

 
 

 

 

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A third solution

 
@@ -147,7 +147,7 @@ 
A third solution

 
 

 

 

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+

 
❗ Choose your model ❗

 
@@ -163,7 +163,7 @@ 

 
-

+

 

 
 Figure credit: PAGE, Ana M., et al. A macro-element pile foundation model for integrated analyses of monopile-based offshore wind turbines. Ocean Engineering, 2018, 167: 23-35.

 
 
Real (NGI work) life example

@@ -190,7 +190,7 @@ 
Real (NGI work) life example

 
 

 

-

+

 

 
 Figure credit: PAGE, Ana M., et al. A macro-element pile foundation model for integrated analyses of monopile-based offshore wind turbines. Ocean Engineering, 2018, 167: 23-35.

 
 
Real (NGI work) life example

@@ -219,10 +219,10 @@ 
Real (NGI work) life example

 
 

 

-

+

 
What is Curve Fitting?

 
    
-
  • Find the best-fit curve for a dataset using a known model
+
  • Find the best-fit curve for a dataset using a known model
 
      
 
    • Minimize the difference between observed and predicted values
      • 
 
    
@@ -236,7 +236,7 @@ 
    What is Curve Fitting?
    
 

 

 

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Difference between observed and predicted values

 

 

@@ -247,7 +247,7 @@ 

 

 

 

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+

 
Curve fitting requirements

 
    
 
  • Estimate parameter uncertainties
    • 
@@ -257,7 +257,7 @@ 
    Curve fitting requirements
    
 

 

 

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Recommended tool (by me)

 

 

@@ -291,7 +291,7 @@ 
Recommended tool (by me)

 
 

 

 

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+

 
A new non-linear problem

 
@@ -310,11 +310,11 @@ 
A new non-linear problem

 
 

 

 

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+

 
✨ Let's see some code ✨ 

 

 

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+

 
Problem setup

 
from lmfit import Minimizer, create_params
 
@@ -338,7 +338,7 @@ 
Problem setup

 

 

 

-

+

 
Handling bounds

 
from lmfit import Parameters
 
@@ -358,7 +358,7 @@ 
Handling bounds

 

 

 

-

+

 
Interpret simulation results

 
[[Fit Statistics]]
     # fitting method   = least_squares
@@ -381,15 +381,15 @@ 
Interpret simulation results

 

 

 

-

+

 

 

 

-

+

 
📈 + 💪 + 🐍 = ❓

 

 

-

+

 
📈 + 💪 + 🐍 = ❤️

 
 

diff --git a/talk/slides.md b/talk/slides.md
index 0610311..a1920a6 100755
--- a/talk/slides.md
+++ b/talk/slides.md
@@ -146,7 +146,7 @@ Horizontal displacement curves under load
 
 # What *is* Curve Fitting?
 
-* Find the **best-fit curve** for a dataset using a known model
+* Find the **best-fit curve** for a dataset using a *known model*
     * **Minimize** the difference between *observed* and *predicted* values
         $$
         \chi^2 = \sum_{i=1}^{N} \frac{(y_i^\text{obs} - y_i^\text{pred})^2}{\sigma_i^2}