Motivation Method Follow the link to install the add-on to blender https://github.com/eliemichel/MapsModelsImporter Install the RenderDoc program on windows, to inject process to Chrome to fetch 3d data from it. Create a shortcut to launch chrome with some additional debug flags Run chrome, record the process number, pause. Inject to that number in RenderDoc program Then start chrome and go to google map to your favorite buildings Capture through RenderDoc. Save to rdc files to disk. Load that rdc through Blender! and you have your 3d models! Post processing Join the patches to a single object. And merge vertices by distance。 Process texture and stuff to retain a single kind of material with the color. See the youtube video for a tutorial.
Motivation Common Formats Some formats are really common, so that python and matlab both have standard way to import, read and write. So these can be a common json, yaml Simple python dictionary could be easily dumped in yaml json formats, which record the hierachical structure and can store small amount of array data. The best part is it’s human readable. So it’s really suitable to store short configuration files.
Motivation Sometimes, animation is a great boost for a scientific idea in a paper. Though PDF is a old fashion communication media, we could add animation to it to give it some vigor. Method For small gif type short movie, using animate is a good choice. The syntax for using it is simple
Motivation Syntax highlighting for codes Procedurally adding lots of figures to slides using the same format (if you don’t want to copy paste in pptx) Adding lots of equations to it from latex format. Technical Choices Source of info
Motivation Handling parameter and recording them for numerical experiment is a pain in matlab. Solutions Option Parser Input the options as different fields of a structure and parse it through a function, fill in the fields that are missing by checking isfield
Motivation Matlab and matplotlib in python are plotting packages of daily usage. They share lots of structures but also have minor differences. For beginners using the plotting routines can suffice most daily needs, but for more refined control over layout, fontsize and so on, we need to better understand the object structure in matlab and matplotlib.
TOC {:toc} Deep Learning Environment Currently we find that multiple version of CUDA could be installed on windows. And different frameworks could use different CUDA version nicely together. PyTorch Tensorflow Co-environment Currently, we can have
Motivation pandas is a great tool for representing structured data in python, similar to Table in matlab and dataframe in R . Using it to interact with table data (like experimental records) on hard drive and process it in python is also great!
Motivation Sometimes we want to examine the Hessian or Jacobian of a function w.r.t some variables. For that purpose, autogradient algorithm can help us. Autograd mechanism In Essence, Autograd requires a computational graph. (Directed Acyclic Graph) For each computational node (e.g. $z=f(x,y)$), we define a forward computation $(x,y)\mapsto z,\ z=f(x,y)$ mapping bottom to top, and a backward computation mapping the partial derivative to top to the partial derivative to bottom. $\partial_z\mapsto (\partial_x,\partial_y); (gx,gy)=g(gz;x,y)$ .
Motivation Unlike matlab, plotting dynamics in python is not as easy or straight forward to use. And to interact with the figure is not always as simple as matlab native plotting routines.