Graph tools

 

𝐓𝐨𝐨𝐥𝐬 𝐭𝐨 𝐦𝐚𝐢𝐧𝐥𝐲 𝐯𝐢𝐬𝐮𝐚𝐥𝐢𝐳𝐞 𝐧𝐞𝐭𝐰𝐨𝐫𝐤𝐬:
- Geph - https://gephi.org
- Gephisto- https://lnkd.in/diSp3BWN
- VOSviewer - https://www.vosviewer.com
- Cytoscape - https://cytoscape.org
- Kumu - https://kumu.io
- GraphInsight - https://lnkd.in/d5XnkWJr
- NodeXL - https://nodexl.com
- Orange - https://lnkd.in/dZU8Zx3D
- Graphia - https://graphia.app
- Graphistry - https://www.graphistry.com
- SocNetV - https://socnetv.org
- Tulip - https://lnkd.in/dtc_BD33


𝐍𝐞𝐭𝐰𝐨𝐫𝐤 𝐥𝐢𝐛𝐫𝐚𝐫𝐢𝐞𝐬 𝐢𝐧 𝐏𝐲𝐭𝐡𝐨𝐧:
- networkx - https://lnkd.in/dKCCXjif
- graphviz - https://lnkd.in/dtrTeqRv
- pydot - https://lnkd.in/dA46YZvy
- python-igraph - https://lnkd.in/dCGsRXh2
- pyvis - https://lnkd.in/dVrQ64nN
- ipycytoscape - https://lnkd.in/d-hJjDdG
- pygsp - https://lnkd.in/dS7s-A_v
- graph-tool - https://lnkd.in/dvytUzdu
- nxviz - https://lnkd.in/duHbKGPN
- py2cytoscape - https://lnkd.in/dWUU8TZH
- ipydagred3 - https://lnkd.in/diXgFWMD
- ipysigma - https://lnkd.in/dP55J5et
- Py3Plex - https://lnkd.in/dhwe7f_g
- net wulf - https://lnkd.in/dxrHAm2P
 

Render tools - POV Ray

Compiling

https://github.com/POV-Ray/povray/releases/tag/v3.8.0-beta.2 

configure error: Could not link against boost_

sudo apt-get install libboost-all-dev

Update Gimp

From 2.8 to 2.10 using apt-get

$ sudo add-apt-repository ppa:otto-kesselgulasch/gimp

$ sudo apt-get update

$ sudo apt-get install gimp

 

References:

https://linuxhint.com/install_gimp_210_ubuntu_1804/

ASNetwork : Breaking ambiguity

 

 

[1] Salient Object Detection Driven by Fixation Prediction https://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Salient_Object_Detection_CVPR_2018_paper.pdf

[2] Action Schema Networks https://ipc2023-learning.github.io/abstracts/asnets.pdf

Volume Fractions

Thesis

[1] Smooth Interface Reconstruction from Volume Fraction Data Using Variational
Techniques and Level Set Methods

https://escholarship.org/content/qt2466j56f/qt2466j56f_noSplash_4c9dcb1c6cacafb1bcdc4a7bab220630.pdf?t=odypru

 

Volume Fractions in Rectangular Grids

Analytical Relations Connecting Linear Interfaces and Volume Fractions in Rectangular Grids
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.536.848&rep=rep1&type=pdf
[1] Markers - A front-tracking algorithm for accurate representation of surface tension (Zaleski)
https://hal.archives-ouvertes.fr/hal-01445441/document



[2] Level Set Methods (LSM)
[2.1] Tutorial Level Set vs Marching Methods https://math.berkeley.edu/~sethian/2006/Explanations/level_set_explain.html

[2.2-1] Part I (Def) https://wiseodd.github.io/techblog/2016/11/05/levelset-method/
[2.2-2] Part II(Application for segmentation) https://wiseodd.github.io/techblog/2016/11/20/levelset-segmentation/

Deep Gan Applications

Super Resolution

[0] https://replicate.com/collections/super-resolution 

[1] https://replicate.com/nightmareai/real-esrgan  /require github account

[2] https://replicate.com/mv-lab/swin2sr (alternative) 

[3] Nightmare https://www.nightmare-ai.com/playground

Styles

[1] https://replicate.com/collections/ml-makeovers 

Restoration

[1] 5byday https://www.restorephotos.io/restore (based on replicate)

[2] https://replicate.com/collections/image-restoration

[3] https://replicate.com/microsoft/bringing-old-photos-back-to-life

 

Alternatives

[1] https://ai.nero.com/photo-restore

[2] https://www.aiease.ai/app/restore-photo

[3] https://photobooth.online/en-us/photo-restoration/upload

[4] https://www.photorestore.io/restore 

[5] https://jpghd.com/

Frequence space ( Source codes )

References:

[1] Elliptic Harmonics http://www.cs.utah.edu/~jfishbau/advimproc/project3/



Resources:
 0) Discrete Fourier Transform 1D, source code c/c++/java/python and more https://www.nayuki.io/page/how-to-implement-the-discrete-fourier-transform
1) Discret Sine Tranform  https://people.sc.fsu.edu/~jburkardt/cpp_src/sine_transform/sine_transform.html
  1.1) Python version http://www-personal.umich.edu/~mejn/computational-physics/dcst.py

2) Haar Wavelet compression https://people.math.osu.edu/husen.1/teaching/wi2010/572/572.html

3) Fast Fourier Tranform 1d/2d http://www.kurims.kyoto-u.ac.jp/~ooura/fft.html
4) Elliptic Fourier Transform source code python https://github.com/hbldh/pyefd
5) Spatial Elliptical Fourier Descriptors python https://spatial-efd.readthedocs.io/en/latest/raster_link.html 

6) Morphometric in R https://github.com/MomX/Momocs/

Visual Computing

 

 

[1] Definition https://link.springer.com/content/pdf/10.1007/978-3-642-85023-3_1.pdf

Web Screen-Space methods for fluid rendering

 

[1] https://www.babylonjs.com/

Writing

[1]  Writing and Publishing Scientific Papers Image de couverture Series https://books.openbookpublishers.com/10.11647/obp.0235.pdf

AI Surfaces

 

[1] https://dsilvavinicius.github.io/nise/

Geo DataScience

Datasets

[1] Flood Mapping https://ieee-dataport.org/competitions/2024-ieee-grss-data-fusion-contest-flood-rapid-mapping

 

[1] datos https://www.datosabiertos.gob.pe/

[2] lat/long Perú https://github.com/jmcastagnetto/ubigeo-peru-aumentado

[3] variables vivienda y conocimiento https://www.redalyc.org/journal/6357/635767693004/html/

CONCLUSIONES

El conocimiento sobre dengue, las viviendas que presentan depósitos de basura y agua acumulada están relacionadas a los casos de Dengue en los distritos de Luyando y Rupa Rupa, en la provincia de Leoncio Prado. Persisten conductas de riesgo a pesar del adecuado conocimiento sobre la enfermedad. No se encontró asociación con el tipo de vivienda, género, material predominante en las viviendas, tipo de abastecimiento de agua y servicios higiénicos.

 

[4] datos amazonia https://www.dge.gob.pe/sala-situacional-dengue/#grafico27

[5] Mapas Perú .shp https://www.geogpsperu.com/2014/03/base-de-datos-peru-shapefile-shp-minam.html

[6] Información Geoespacial Perú https://www.idep.gob.pe/geovisor/descarga/visor.html

[6] Hidrografía https://data.humdata.org/dataset/hidrografia-de-peru?

   https://data.humdata.org/dataset

[7] Áreas  naturales protegidas https://geo.sernanp.gob.pe/visorsernanp/

[8] Biomasa Brasil https://mapbiomas.org/download

Processing 

[1] plotting maps https://ggplot2-book.org/maps.html

[1.1] https://community.rstudio.com/t/geom-label-with-custom-background-and-color-text/45161

[2] poly2nb https://www.rdocumentation.org/packages/spdep/versions/1.2-8/topics/poly2nb

[3] Indicadores demograficos Perú (teoria) https://www.inei.gob.pe/media/MenuRecursivo/publicaciones_digitales/Est/Lib1743/Libro.pdf

R Installation and more

 

* R installation




$sudo apt install r-base

 

* Package installation

install.packages('readr')

 

* install.packages('sf')

//Configuration failed because libudunits2.so was not found


sudo add-apt-repository ppa:ubuntugis/ubuntugis-unstable
sudo apt-get update
sudo apt-get install libudunits2-dev libgdal-dev libgeos-dev libproj-dev 

* install.packages('dplyr') //dataframe, works with R version >= 3.5

* install.packages('tidyverse') //Contains other packages (dplyr, ggplot2, etc.)  

* install.packages('spdep') //Spatial Dependence: Weighting Schemes, Statistics. A collection of functions to create spatial weights matrix objects from polygon

* install.packages('GGally') //extends 'ggplot2'

 

* install.packages('leaflet') //makes it easy to integrate and control Leaflet maps in R.

* install.packages('coda')

 

* install.packages('CARBayes')

* install.packages('CARBayesdata') 

 

* install.packages('xlsx')  

 

    dependences:

      1) java

      2) sudo apt-get install openjdk-11-jdk

      3) sudo R CMD javareconf    

      4) https://github.com/PCRE2Project/pcre2/releases  

      4.1) compilation https://www.appsloveworld.com/r/100/371/how-to-solve-lpcre2-8-error-while-installing-rjava-package-in-r


* install.packages('readxl')

 

* install.packages('tmap')


 

 

 

References:

[1] rstudio https://linuxconfig.org/rstudio-on-ubuntu-18-04-bionic-beaver-linux

[2] R 3.5 installation on Linux 18 https://rtask.thinkr.fr/installation-of-r-3-5-on-ubuntu-18-04-lts-and-tips-for-spatial-packages

[2] rstudio previous https://docs.posit.co/previous-versions/rstudio/

Latex writing

Highlighting code

[1] Custom C https://tex.stackexchange.com/questions/312789/lstdefinelanguage-cannot-handle-keywords-if-endif

Multi references

\bibliography{paper,references2019}

Soundscape works

 

[1] A pipeline for identification of bird and frog species in tropical soundscape recordings using a convolutional neural network

https://www.sciencedirect.com/science/article/pii/S1574954120300637?via%3Dihub

[2] https://www.frontiersin.org/articles/10.3389/fevo.2021.738537/full

Backtesting

 

[1] popular code https://github.com/kernc/backtesting.py/tree/master/backtesting

[2] https://blog.devgenius.io/algorithmic-trading-backtesting-a-strategy-in-python-3a136be16ece

[3]  https://towardsdatascience.com/backtest-your-trading-strategy-with-only-3-lines-of-python-3859b4a4ab44

Python Genetic Algorithms

 

[1] pyGAD https://github.com/ahmedfgad/GeneticAlgorithmPython

Transformers in Computer Vision

 

[1] Review https://sh-tsang.medium.com/review-vision-transformer-vit-406568603de0

[2] Colab ViT Tutorial https://colab.research.google.com/github/hirotomusiker/schwert_colab_data_storage/blob/master/notebook/Vision_Transformer_Tutorial.ipynb

[3] ViT pytorch https://github.com/lucidrains/vit-pytorch

[4] Vit Keras https://wandb.ai/ayush-thakur/keras_cv_vit/reports/Image-Classification-Using-Vision-Transformer-and-KerasCV--VmlldzozNTE4MzMz

[5] Fine tunning https://huggingface.co/blog/fine-tune-vit

[6] Full material https://github.com/cmhungsteve/Awesome-Transformer-Attention

Watercolor tips

 

Material

[1] https://www.nicoletalle.com/como-elegir-el-mejor-set-de-acuarelas/

Paper

[1] ...

Latex - Format listing environment

minted package 

References:

[1] https://www.overleaf.com/learn/latex/Code_Highlighting_with_minted