Julio Cárdenas-Rodríguez

Non-linear curve fitting in Python

Non-linear curve fitting (or non-linear parametric regression)is a fundamental part of the quantitative analysis performed in multiple scientific disciplines. The main idea is that we know (or assume) the model that describes an observed data. For example, it would seem reasonable to assume that the curve below is described by an exponential . . .

Read More

July 07, 2017

Interactive execution in Julia 0.5

I learned today about the @manipulate macro in Julia 0.5. It allows you to define variables, functions, plots (and etc) in an interactively fashion. I tried the following code in a Jupyter notebook in julia box:

# Add Packages if you don't have them
Pkg.add("Interact") # if needed
Pkg.build("Interact") # if . . .

Read More

July 07, 2017

Create a local module

I am migrating all my code from Matlab to Python. One of the first things I need to do is to have a code that plots a sum of multiple Lorentzian functions (the reason are described here). The first thing to do is to create is to ad the following code to our module (MRI.py`):

plot

# Collection of MRI function for the Cardenas . . .

Read More

July 07, 2017

Using MarkDown in my blog

Why efficient writing matters

One of my goals is to post my Python, Julia, and Matlab code as efficiently as possible. After some consideration, I realized that the best way to do it is using MarkDown. This blog is hosted at SilvBack which I believe is the bests place to post technical blogs. Some tests next:

Code blocks can use three back ticks (```). Syntax . . .

Read More

July 07, 2017

Hello World

Goal

I decided to start this blog to document my journey through 2017, a year during which I plan to:

  • Transition from academic imaging science to data science in the private sector.
  • Become a United States citizen
  • Loose 25 pounds
  • Guide my children as they start first grade and kindergarten (Mia and Diego I . . .

Read More

July 07, 2017

Archive