era5cli: the command line interface to ERA5 data

2021 ◽  
Author(s):  
Stef Smeets ◽  
Jaro Camphuijsen ◽  
Niels Drost ◽  
Fakhereh Alidoost ◽  
Bouwe Andela ◽  
...  
Keyword(s):  
High Resolution ◽  
Source Code ◽  
Reanalysis Data ◽  
Command Line ◽  
Climate Data ◽  
Web Interface ◽  
Command Line Interface ◽  
Data Store ◽  
Recent Developments ◽  
Advanced Knowledge

<p>With the release of the ERA5 dataset, worldwide high-resolution reanalysis data became available with open access for public use. The Copernicus CDS (Climate Data Store) offers two options for accessing the data: a web interface and a Python API. Consequently, automated downloading of the data requires advanced knowledge of Python and a lot of work. To make this process easier, we developed <em>era5cli</em>. </p><p>The command line interface tool <em>era5cli </em>enables automated downloading of ERA5 using a single command. All variables and options available in the CDS web form are now available for download in an efficient way. Both the monthly and hourly dataset are supported. Besides automation, <em>era5cli </em>adds several useful functionalities to the download pipeline.</p><p>One of the key options in <em>era5cli </em>is to spread one download command over multiple CDS requests, resulting in higher download speeds. Files can be saved in both GRIB and NETCDF format with automatic, yet customizable file names. The <em>info </em>command lists correct names of the available variables and pressure levels for 3D variables. For debugging purposes and testing the <em>dryrun </em>option can be selected to return only the CDS request. An overview of all available options, including instructions on how to configure your CDS account, is available in our documentation. Recent developments include support for ERA5 back extension and ERA5-Land. The source code for era5cli is available on https://github.com/eWaterCycle/era5cli.</p>

era5cli: The command line tool to download ERA5 data

2020 ◽  
Author(s):  
Jaro Camphuijsen ◽  
Ronald van Haren ◽  
Yifat Dzigan ◽  
Niels Drost ◽  
Fakhareh Alidoost ◽  
...  
Keyword(s):  
Source Code ◽  
Reanalysis Data ◽  
Command Line ◽  
Climate Data ◽  
Web Interface ◽  
Command Line Interface ◽  
Short Introduction ◽  
Data Store ◽  
Command Line Tool ◽  
Advanced Knowledge

<p>With the release of the ERA5 dataset, worldwide high resolution reanalysis data became available with open access for public use. The Copernicus CDS (Climate Data Store) offers two options for accessing the data: a web interface and a Python API. Consequently, automated downloading of the data requires advanced knowledge of Python and a lot of work. To make this process easier, we developed era5cli. </p><p>The command line interface tool era5cli enables automated downloading of ERA5 using a single command. All variables and options available in the CDS web form are now available for download in an efficient way. Both the monthly and hourly dataset are supported. Besides automation, era5cli adds several useful functionalities to the download pipeline.</p><p>One of the key options in era5cli is to spread one download command over multiple CDS requests, resulting in higher download speeds. Files can be saved in both GRIB and NETCDF format with automatic, yet customizable file names. The `info` command lists correct names of the available variables and pressure levels for 3D variables. For debugging purposes and testing the `--dryrun` option can be selected to return only the CDS request. An overview of all available options, including instructions on how to configure your CDS account, is available in our documentation. Source code is available on https://github.com/eWaterCycle/era5cli.</p><p>In this PICO presentation we will provide an overview of era5cli, as well as a short introduction on how to use era5cli.</p>

scholarly journals Recent developments in theCCP-EMsoftware suite

2017 ◽  
Vol 73 (6) ◽  
pp. 469-477 ◽  
Author(s):  
Tom Burnley ◽  
Colin M. Palmer ◽  
Martyn Winn
Keyword(s):  
Easy Access ◽  
Software Framework ◽  
Command Line ◽  
Command Line Interface ◽  
Software Suite ◽  
Computational Support ◽  
Recent Developments ◽  
User Friendly ◽  
Different Levels ◽  
Friendly Graphical User Interface

As part of its remit to provide computational support to the cryo-EM community, the Collaborative Computational Project for Electron cryo-Microscopy (CCP-EM) has produced a software framework which enables easy access to a range of programs and utilities. The resulting software suite incorporates contributions from different collaborators by encapsulating them in Python task wrappers, which are then made accessibleviaa user-friendly graphical user interface as well as a command-line interface suitable for scripting. The framework includes tools for project and data management. An overview of the design of the framework is given, together with a survey of the functionality at different levels. The currentCCP-EMsuite has particular strength in the building and refinement of atomic models into cryo-EM reconstructions, which is described in detail.

scholarly journals DamageProfiler: Fast damage pattern calculation for ancient DNA

2021 ◽  
Author(s):  
Judith Neukamm ◽  
Alexander Peltzer ◽  
Kay Nieselt
Keyword(s):  
Ancient Dna ◽  
Source Code ◽  
Supplementary Information ◽  
Command Line ◽  
Central Importance ◽  
Command Line Interface ◽  
Analysis Pipeline ◽  
File Formats ◽  
Programming Knowledge ◽  
User Friendly

Abstract Motivation In ancient DNA research, the authentication of ancient samples based on specific features remains a crucial step in data analysis. Because of this central importance, researchers lacking deeper programming knowledge should be able to run a basic damage authentication analysis. Such software should be user-friendly and easy to integrate into an analysis pipeline. Results DamageProfiler is a Java based, stand-alone software to determine damage patterns in ancient DNA. The results are provided in various file formats and plots for further processing. DamageProfiler has an intuitive graphical as well as command line interface that allows the tool to be easily embedded into an analysis pipeline. Availability All of the source code is freely available on GitHub (https://github.com/Integrative-Transcriptomics/DamageProfiler). Supplementary information Supplementary data are available at Bioinformatics online.

BCdatabaser: on-the-fly reference database creation for (meta-)barcoding

2019 ◽  
Author(s):  
Alexander Keller ◽  
Sonja Hohlfeld ◽  
Andreas Kolter ◽  
Jörg Schultz ◽  
Birgit Gemeinholzer ◽  
...  
Keyword(s):  
Dna Barcoding ◽  
Source Code ◽  
Taxonomic Group ◽  
Reference Database ◽  
Command Line ◽  
Command Line Interface ◽  
Meta Data ◽  
Constant Growth

DNA barcoding and meta-barcoding have become irreplaceable in research and applications, where identification of taxa alone or within a mixture, respectively, becomes relevant. Pioneering studies were in the microbiological context, yet nowadays also plants and animals become targeted. Given the variety of markers used, formatting requirements for classifiers and constant growth of primary databases, there is need for dedicated reference database creation. We developed a web and command line interface to generate such on-the-fly for any applicable marker and taxonomic group with optional filtering, formatting and restriction specific for (meta-)barcoding purposes. Also, databases optionally receive a DOI, making them well documented with meta-data, publicly sharable and citable.Availability: source code: https://www.github.com/molbiodiv/bcdatabaser, webservice: https://bcdatabaser.molecular.eco

scholarly journals WFDE5: bias-adjusted ERA5 reanalysis data for impact studies

2020 ◽  
Vol 12 (3) ◽  
pp. 2097-2120 ◽  
Author(s):  
Marco Cucchi ◽  
Graham P. Weedon ◽  
Alessandro Amici ◽  
Nicolas Bellouin ◽  
Stefan Lange ◽  
...  
Keyword(s):  
Hydrological Model ◽  
Absolute Error ◽  
Reanalysis Data ◽  
Monthly Precipitation ◽  
Climate Data ◽  
Water Balance Components ◽  
Data Store ◽  
Complete Dataset ◽  
Meteorological Observations ◽  
Globally Distributed

Abstract. The WFDE5 dataset has been generated using the WATCH Forcing Data (WFD) methodology applied to surface meteorological variables from the ERA5 reanalysis. The WFDEI dataset had previously been generated by applying the WFD methodology to ERA-Interim. The WFDE5 is provided at 0.5∘ spatial resolution but has higher temporal resolution (hourly) compared to WFDEI (3-hourly). It also has higher spatial variability since it was generated by aggregation of the higher-resolution ERA5 rather than by interpolation of the lower-resolution ERA-Interim data. Evaluation against meteorological observations at 13 globally distributed FLUXNET2015 sites shows that, on average, WFDE5 has lower mean absolute error and higher correlation than WFDEI for all variables. Bias-adjusted monthly precipitation totals of WFDE5 result in more plausible global hydrological water balance components when analysed in an uncalibrated hydrological model (WaterGAP) than with the use of raw ERA5 data for model forcing. The dataset, which can be downloaded from https://doi.org/10.24381/cds.20d54e34 (C3S, 2020b), is distributed by the Copernicus Climate Change Service (C3S) through its Climate Data Store (CDS, C3S, 2020a) and currently spans from the start of January 1979 to the end of 2018. The dataset has been produced using a number of CDS Toolbox applications, whose source code is available with the data – allowing users to regenerate part of the dataset or apply the same approach to other data. Future updates are expected spanning from 1950 to the most recent year. A sample of the complete dataset, which covers the whole of the year 2016, is accessible without registration to the CDS at https://doi.org/10.21957/935p-cj60 (Cucchi et al., 2020).

scholarly journals Coffea-casa: an analysis facility prototype

2021 ◽  
Vol 251 ◽  
pp. 02061
Author(s):  
Matous Adamec ◽  
Garhan Attebury ◽  
Kenneth Bloom ◽  
Brian Bockelman ◽  
Carl Lundstedt ◽  
...  
Keyword(s):  
Data Analysis ◽  
Data Access ◽  
End Users ◽  
Command Line ◽  
Web Interface ◽  
Command Line Interface ◽  
Interactive Interface ◽  
Batch Systems ◽  
Interactive Computing ◽  
Programming Paradigms

Data analysis in HEP has often relied on batch systems and event loops; users are given a non-interactive interface to computing resources and consider data event-by-event. The “Coffea-casa” prototype analysis facility is an effort to provide users with alternate mechanisms to access computing resources and enable new programming paradigms. Instead of the command-line interface and asynchronous batch access, a notebook-based web interface and interactive computing is provided. Instead of writing event loops, the columnbased Coffea library is used. In this paper, we describe the architectural components of the facility, the services offered to end users, and how it integrates into a larger ecosystem for data access and authentication.

scholarly journals IsoCor: isotope correction for high-resolution MS labeling experiments

2019 ◽  
Vol 35 (21) ◽  
pp. 4484-4487 ◽  
Author(s):  
Pierre Millard ◽  
Baudoin Delépine ◽  
Matthieu Guionnet ◽  
Maud Heuillet ◽  
Floriant Bellvert ◽  
...  
Keyword(s):  
High Resolution ◽  
Chemical Species ◽  
Chemical Processes ◽  
Correction Algorithm ◽  
Command Line Interface ◽  
Naturally Occurring ◽  
Isotopic Species ◽  
Isotopic Studies ◽  
Recent Developments ◽  
Streamline Integration

Abstract Summary Mass spectrometry (MS) is widely used for isotopic studies of metabolism and other (bio)chemical processes. Quantitative applications in systems and synthetic biology require to correct the raw MS data for the contribution of naturally occurring isotopes. Several tools are available to correct low-resolution MS data, and recent developments made substantial improvements by introducing resolution-dependent correction methods, hence opening the way to the correction of high-resolution MS (HRMS) data. Nevertheless, current HRMS correction methods partly fail to determine which isotopic species are resolved from the tracer isotopologues and should thus be corrected. We present an updated version of our isotope correction software (IsoCor) with a novel correction algorithm which ensures to accurately exploit any chemical species with any isotopic tracer, at any MS resolution. IsoCor v2 also includes a novel graphical user interface for intuitive use by end-users and a command-line interface to streamline integration into existing pipelines. Availability and implementation IsoCor v2 is implemented in Python 3 and was tested on Windows, Unix and MacOS platforms. The source code and the documentation are freely distributed under GPL3 license at https://github.com/MetaSys-LISBP/IsoCor/ and https://isocor.readthedocs.io/.

scholarly journals tspex: a tissue-specificity calculator for gene expression data

2020 ◽  
Author(s):  
Antonio P. Camargo ◽  
Adrielle A. Vasconcelos ◽  
Mateus B. Fiamenghi ◽  
Gonçalo A. G. Pereira ◽  
Marcelo F. Carazzolle
Keyword(s):  
Gene Expression ◽  
Gene Expression Data ◽  
Web Application ◽  
Tissue Specificity ◽  
Source Code ◽  
Command Line ◽  
Expression Data ◽  
Web Interface ◽  
User Friendly ◽  
Different Tissues

Abstract When comparing gene expression data of different tissues it is often interesting to identify tissue-specific genes or transcripts. Even though there are several metrics to measure tissue-specificity, a user-friendly tool that facilitates this analysis is not available yet. We present tspex, a software that allows easy computation of a comprehensive set of different tissue-specificity metrics from gene expression data. tspex can be used through a web interface, command-line or the Python API. Its package version also provides visualization functions that facilitate inspection of results. The documentation and the source code of tspex are available at https://apcamargo.github.io/tspex/ and the web application can be accessed at https://tspex.lge.ibi.unicamp.br/

scholarly journals Reconciling high resolution climate datasets using KrigR

2021 ◽  
Author(s):  
Richard Davy ◽  
Erik Kusch
Keyword(s):  
High Resolution ◽  
Temporal Resolution ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
R Package ◽  
Reanalysis Data ◽  
Climate Data ◽  
Community Of Researchers ◽  
The Difference

Abstract There is an increasing need for high spatial and temporal resolution climate data for the wide community of researchers interested in climate change and its consequences. Currently, there is a large mismatch between the spatial resolutions of global climate model and reanalysis datasets (at best around 0.25o and 0.1o respectively) and the resolutions needed by many end-users of these datasets, which are typically on the scale of 30 arcseconds (~900m). This need for improved spatial resolution in climate datasets has motivated several groups to statistically downscale various combinations of observational or reanalysis datasets. However, the variety of downscaling methods and inputs used makes it difficult to reconcile the resultant differences between these high-resolution datasets. Here we make use of the KrigR R-package to statistically downscale the world-leading ERA5(-Land) reanalysis data using kriging. We show that kriging can accurately recover spatial heterogeneity of climate data given strong relationships with co-variates; that by preserving the uncertainty associated with the statistical downscaling, one can investigate and account for confidence in high-resolution climate data; and that the statistical uncertainty provided by KrigR can explain much of the difference between widely used high resolution climate datasets (CHELSA, TerraClimate, and WorldClim2) depending on variable, timescale, and region. This demonstrates the advantages of using KrigR to generate customized high spatial and/or temporal resolution climate data.

TPS (Task Preparation System): A Tool for Developing Tasks in Programming Contests

2019 ◽  
Vol 13 ◽  
pp. 209-215
Author(s):  
Kian MIRJALALI ◽  
Amir Keivan MOHTASHAMI ◽  
Mohammad ROGHANI ◽  
Hamid ZARRABI-ZADEH
Keyword(s):  
Command Line ◽  
Web Interface ◽  
Command Line Interface ◽  
System A ◽  
Task Preparation

The task preparation system (TPS) is a tool developed mainly for preparing IOI tasks. It was originally developed for, and successfully used in IOI 2017, and since then, it has been used in several other nationwide and international programming contests, including IOI 2019. The tool consists of a command-line interface for local (offline) work, and a web interface which integrates with git and provides more features. This article presents the main features of the task preparation system, and briefly describes how it works.

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