This repository contains tutorials for the py4DSTEM Python package

Overview
Comments
  • Binder dev

    Binder dev

    • Binder link created, currently lands in Index.ipynb
    • data loaded as part of the notebooks, running all cells on notebooks inside binder will work.
    • Added file_getter.py which takes command-line arguments, which makes extending the download to more notebooks fairly straightforward.
    • Both notebooks work, make_probe_templates.ipynb required adding some clean-up steps to avoid going over 2GB ram limit, the alternative is to split them into more separate notebooks.
    • There's a slight issue that if people don't shutdown notebooks properly or if they have multiple notebooks over, they may cause kernel panics, both notebooks peak memory usage push the 2GB limit .
    • I haven't given much attention to style or formatting currently just wanted to get something functional and working to see if works as required.
    opened by alex-rakowski 1
  • SSB tutorial notebooks with new dataset

    SSB tutorial notebooks with new dataset

    These are two new tutorial notebooks I updated. One is for single-run reconstruction, the other is for interactive mode with ipywidgets and matplotlib visualization.

    opened by PhilippPelz 0
  • Binder dev

    Binder dev

    • Binder link created, currently lands in Index.ipynb
    • data loaded as part of the notebooks, running all cells on notebooks inside binder will work.
    • Added file_getter.py which takes command-line arguments, which makes extending the download to more notebooks fairly straightforward.
    • Both notebooks work, make_probe_templates.ipynb required adding some clean-up steps to avoid going over 2GB ram limit, the alternative is to split them into more separate notebooks.
    • There's a slight issue that if people don't shutdown notebooks properly or if they have multiple notebooks over, they may cause kernel panics, both notebooks peak memory usage push the 2GB limit .
    • I haven't given much attention to style or formatting currently just wanted to get something functional and working to see if works as required.
    opened by alex-rakowski 0
  • Add simulations for dynamical scattering

    Add simulations for dynamical scattering

    I found that there is almost no proper documentation for the dynamical scattering simulation in py4DSTEM unless you read the source code (actually I couldn't find the documentation for the whole diffraction module). So I created a tutorial using NaCl as an example. Hope I have done it right.

    opened by Taimin 0
  • py4DSTEM.process.virtualimage.get_virtualimage_circ (strain mapping tutorial)

    py4DSTEM.process.virtualimage.get_virtualimage_circ (strain mapping tutorial)

    in the strain mapping tutorial, this step doesn't work !

    [12]

    Next, create a BF virtual detector using the the center beam position (qxy0, qy0)

    We will expand the BF radius slightly (+ 2 px).

    The DF virtual detector can be set to all remaining pixels.

    expand_BF = 2.0 image_BF = py4DSTEM.process.virtualimage.get_virtualimage_circ( dataset, qx0, qy0, probe_semiangle + expand_BF) image_DF = py4DSTEM.process.virtualimage.get_virtualimage_ann( dataset, qx0, qy0, probe_semiangle + expand_BF, 1e3)

    [return]

    AttributeError Traceback (most recent call last) Input In [168], in <cell line: 5>() 1 # Next, create a BF virtual detector using the the center beam position (qxy0, qy0) 2 # We will expand the BF radius slightly (+ 2 px). 3 # The DF virtual detector can be set to all remaining pixels. 4 expand_BF = 2.0 ----> 5 image_BF = py4DSTEM.process.get_virtualimage_circ( 6 dataset, 7 qx0, qy0, 8 probe_semiangle + expand_BF) 9 image_DF = py4DSTEM.process.virtualimage.get_virtualimage_ann( 10 dataset, 11 qx0, qy0, 12 probe_semiangle + expand_BF, 13 1e3)

    AttributeError: module 'py4DSTEM.process' has no attribute 'get_virtualimage_circ'

    Any tips to fix that ?

    py4DSTEM.process.virtualimage.virtualimage.get_virtualimage_circ or py4DSTEM.process.virtualimage.get_virtualimage_circ ?

    opened by lylofu 0
  • ACOM_03_Au_NP_sim.ipynb bugs

    ACOM_03_Au_NP_sim.ipynb bugs

    Running the ACOM_03 notebook as downloaded, cell 25 gives the following error:

    ---------------------------------------------------------------------------
    NameError                                 Traceback (most recent call last)
    /var/folders/ts/tq6v7mks7hvg37ys5zvs1c2w0000gn/T/ipykernel_3012/3733081456.py in <module>
         14 
         15 # Fit an ellipse to the elliptically corrected bvm
    ---> 16 qx0_corr,qy0_corr,a_corr,e_corr,theta_corr = py4DSTEM.process.calibration.fit_ellipse_1D(bvm_ellipsecorr,(qx0,qy0),(qmin,qmax))
         17 
         18 py4DSTEM.visualize.show_elliptical_fit(
    
    NameError: name 'qmin' is not defined
    

    I think someone changed qmin, qmax to be a list called qrange and never actually tested the notebook in a fresh state.

    opened by sezelt 0
  • AttributeError: module 'py4DSTEM.process' has no attribute 'diffraction'

    AttributeError: module 'py4DSTEM.process' has no attribute 'diffraction'

    When I run the "ACOM Tutorial Notebook 01", it gives a following error message.

    AttributeError: module 'py4DSTEM.process' has no attribute 'diffraction'

    version python 3.8.0 py4DSTEM 0.12.6 pywin32 302

    error

    opened by nomurayuki0503 0
Releases(v0.13.8-alpha)
Per-Pixel Classification is Not All You Need for Semantic Segmentation

MaskFormer: Per-Pixel Classification is Not All You Need for Semantic Segmentation Bowen Cheng, Alexander G. Schwing, Alexander Kirillov [arXiv] [Proj

Facebook Research 1k Jan 08, 2023
[MedIA2021]MIDeepSeg: Minimally Interactive Segmentation of Unseen Objects from Medical Images Using Deep Learning

MIDeepSeg: Minimally Interactive Segmentation of Unseen Objects from Medical Images Using Deep Learning [MedIA or Arxiv] and [Demo] This repository pr

Healthcare Intelligence Laboratory 92 Dec 08, 2022
The implementation of the paper "HIST: A Graph-based Framework for Stock Trend Forecasting via Mining Concept-Oriented Shared Information".

The HIST framework for stock trend forecasting The implementation of the paper "HIST: A Graph-based Framework for Stock Trend Forecasting via Mining C

Wentao Xu 110 Dec 27, 2022
Iowa Project - My second project done at General Assembly, focused on feature engineering and understanding Linear Regression as a concept

Project 2 - Ames Housing Data and Kaggle Challenge PROBLEM STATEMENT Inferring or Predicting? What's more valuable for a housing model? When creating

Adam Muhammad Klesc 1 Jan 03, 2022
Classification Modeling: Probability of Default

Credit Risk Modeling in Python Introduction: If you've ever applied for a credit card or loan, you know that financial firms process your information

Aktham Momani 2 Nov 07, 2022
天勤量化开发包, 期货量化, 实时行情/历史数据/实盘交易

TqSdk 天勤量化交易策略程序开发包 TqSdk 是一个由信易科技发起并贡献主要代码的开源 python 库. 依托快期多年积累成熟的交易及行情服务器体系, TqSdk 支持用户使用极少的代码量构建各种类型的量化交易策略程序, 并提供包含期货、期权、股票的 历史数据-实时数据-开发调试-策略回测-

信易科技 2.8k Dec 30, 2022
Reading list for research topics in Masked Image Modeling

awesome-MIM Reading list for research topics in Masked Image Modeling(MIM). We list the most popular methods for MIM, if I missed something, please su

ligang 231 Dec 07, 2022
AI Based Smart Exam Proctoring Package

AI Based Smart Exam Proctoring Package It takes image (base64) as input: Provide Output as: Detection of Mobile phone. Detection of More than 1 person

NARENDER KESWANI 3 Sep 09, 2022
A library of extension and helper modules for Python's data analysis and machine learning libraries.

Mlxtend (machine learning extensions) is a Python library of useful tools for the day-to-day data science tasks. Sebastian Raschka 2014-2020 Links Doc

Sebastian Raschka 4.2k Jan 02, 2023
DeceFL: A Principled Decentralized Federated Learning Framework

DeceFL: A Principled Decentralized Federated Learning Framework This repository comprises codes that reproduce experiments in Ye, et al (2021), which

Huazhong Artificial Intelligence Lab (HAIL) 10 May 31, 2022
A collection of resources and papers on Diffusion Models, a darkhorse in the field of Generative Models

This repository contains a collection of resources and papers on Diffusion Models and Score-based Models. If there are any missing valuable resources

5.1k Jan 08, 2023
QuadTree Attention for Vision Transformers (ICLR2022)

This repository contains codes for quadtree attention. This repo contains codes for feature matching, image classficiation, object detection and seman

tangshitao 222 Dec 28, 2022
[ICCV 2021] Self-supervised Monocular Depth Estimation for All Day Images using Domain Separation

ADDS-DepthNet This is the official implementation of the paper Self-supervised Monocular Depth Estimation for All Day Images using Domain Separation I

LIU_LINA 52 Nov 24, 2022
A unofficial pytorch implementation of PAN(PSENet2): Efficient and Accurate Arbitrary-Shaped Text Detection with Pixel Aggregation Network

Efficient and Accurate Arbitrary-Shaped Text Detection with Pixel Aggregation Network Requirements pytorch 1.1+ torchvision 0.3+ pyclipper opencv3 gcc

zhoujun 400 Dec 26, 2022
House_prices_kaggle - Predict sales prices and practice feature engineering, RFs, and gradient boosting

House Prices - Advanced Regression Techniques Predicting House Prices with Machine Learning This project is build to enhance my knowledge about machin

Gurpreet Singh 1 Jan 01, 2022
Canonical Appearance Transformations

CAT-Net: Learning Canonical Appearance Transformations Code to accompany our paper "How to Train a CAT: Learning Canonical Appearance Transformations

STARS Laboratory 54 Dec 24, 2022
Tensorflow Implementation of Pixel Transposed Convolutional Networks (PixelTCN and PixelTCL)

Pixel Transposed Convolutional Networks Created by Hongyang Gao, Hao Yuan, Zhengyang Wang and Shuiwang Ji at Texas A&M University. Introduction Pixel

Hongyang Gao 95 Jul 24, 2022
PyTorch implementation of 1712.06087 "Zero-Shot" Super-Resolution using Deep Internal Learning

Unofficial PyTorch implementation of "Zero-Shot" Super-Resolution using Deep Internal Learning Unofficial Implementation of 1712.06087 "Zero-Shot" Sup

Jacob Gildenblat 196 Nov 27, 2022
Out-of-boundary View Synthesis towards Full-frame Video Stabilization

Out-of-boundary View Synthesis towards Full-frame Video Stabilization Introduction | Update | Results Demo | Introduction This repository contains the

25 Oct 10, 2022
Implementation of ReSeg using PyTorch

Implementation of ReSeg using PyTorch ReSeg: A Recurrent Neural Network-based Model for Semantic Segmentation Pascal-Part Annotations Pascal VOC 2010

Onur Kaplan 46 Nov 23, 2022