Minimal working example of data acquisition with nidaqmx python API

Overview

Data Aquisition using NI-DAQmx python API

Based on this project

It is a minimal working example for data acquisition using the NI-DAQmx python API.

It works only in Windows systems.

Using DEBUG_MODE = True in the configuration file allows the use of the GUI without having nidaqmx installed. Data is simulated.

Content:

  • daq_interface_main.py: main script with the GUI definition

  • reader.py: definitions related to data acquisition

  • plotter.py: definitions related to visualizing the data

  • parameters.py: definition of the parameters

  • config.py: configuration file of the interface

  • misc_functions.py: keeping apart auxiliary functions

  • data_io.py: record acquiered data to file

By defoult the data is writen in Output_Data.dat (see data_io.py). One column per channel.

Owner
Pablo
Pablo
Show you how to integrate Zeppelin with Airflow

Introduction This repository is to show you how to integrate Zeppelin with Airflow. The philosophy behind the ingtegration is to make the transition f

Jeff Zhang 11 Dec 30, 2022
🌍 Create 3d-printable STLs from satellite elevation data 🌏

mapa 🌍 Create 3d-printable STLs from satellite elevation data Installation pip install mapa Usage mapa uses numpy and numba under the hood to crunch

Fabian Gebhart 13 Dec 15, 2022
The OHSDI OMOP Common Data Model allows for the systematic analysis of healthcare observational databases.

The OHSDI OMOP Common Data Model allows for the systematic analysis of healthcare observational databases.

Bell Eapen 14 Jan 02, 2023
Collections of pydantic models

pydantic-collections The pydantic-collections package provides BaseCollectionModel class that allows you to manipulate collections of pydantic models

Roman Snegirev 20 Dec 26, 2022
Demonstrate a Dataflow pipeline that saves data from an API into BigQuery table

Overview dataflow-mvp provides a basic example pipeline that pulls data from an API and writes it to a BigQuery table using GCP's Dataflow (i.e., Apac

Chris Carbonell 1 Dec 03, 2021
Python package to transfer data in a fast, reliable, and packetized form.

pySerialTransfer Python package to transfer data in a fast, reliable, and packetized form.

PB2 101 Dec 07, 2022
Finding project directories in Python (data science) projects, just like there R rprojroot and here packages

Find relative paths from a project root directory Finding project directories in Python (data science) projects, just like there R here and rprojroot

Daniel Chen 102 Nov 16, 2022
A highly efficient and modular implementation of Gaussian Processes in PyTorch

GPyTorch GPyTorch is a Gaussian process library implemented using PyTorch. GPyTorch is designed for creating scalable, flexible, and modular Gaussian

3k Jan 02, 2023
scikit-survival is a Python module for survival analysis built on top of scikit-learn.

scikit-survival scikit-survival is a Python module for survival analysis built on top of scikit-learn. It allows doing survival analysis while utilizi

Sebastian Pölsterl 876 Jan 04, 2023
Containerized Demo of Apache Spark MLlib on a Data Lakehouse (2022)

Spark-DeltaLake-Demo Reliable, Scalable Machine Learning (2022) This project was completed in an attempt to become better acquainted with the latest b

8 Mar 21, 2022
Using Python to scrape some basic player information from www.premierleague.com and then use Pandas to analyse said data.

PremiershipPlayerAnalysis Using Python to scrape some basic player information from www.premierleague.com and then use Pandas to analyse said data. No

5 Sep 06, 2021
A Python Tools to imaging the shallow seismic structure

ShallowSeismicImaging Tools to imaging the shallow seismic structure, above 10 km, based on the ZH ratio measured from the ambient seismic noise, and

Xiao Xiao 9 Aug 09, 2022
Average time per match by division

HW_02 Unzip matches.rar to access .json files for matches. Get an API key to access their data at: https://developer.riotgames.com/ Average time per m

11 Jan 07, 2022
Pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).

AWS Data Wrangler Pandas on AWS Easy integration with Athena, Glue, Redshift, Timestream, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretMana

Amazon Web Services - Labs 3.3k Jan 04, 2023
Implementation in Python of the reliability measures such as Omega.

reliabiliPy Summary Simple implementation in Python of the [reliability](https://en.wikipedia.org/wiki/Reliability_(statistics) measures for surveys:

Rafael Valero Fernández 2 Apr 27, 2022
Reading streams of Twitter data, save them to Kafka, then process with Kafka Stream API and Spark Streaming

Using Streaming Twitter Data with Kafka and Spark Reading streams of Twitter data, publishing them to Kafka topic, process message using Kafka Stream

Rustam Zokirov 1 Dec 06, 2021
Automatic earthquake catalog building workflow: EQTransformer + Siamese EQTransformer + PickNet + REAL + HypoInverse

Automatic regional-scale earthquake catalog building workflow: EQTransformer + Siamese EQTransforme

Xiao Zhuowei 9 Nov 27, 2022
Python utility to extract differences between two pandas dataframes.

Python utility to extract differences between two pandas dataframes.

Jaime Valero 8 Jan 07, 2023
A simplified prototype for an as-built tracking database with API

Asbuilt_Trax A simplified prototype for an as-built tracking database with API The purpose of this project is to: Model a database that tracks constru

Ryan Pemberton 1 Jan 31, 2022