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575 results for “Modeling Codes”
(supplementary material) Fine-Tuning and Prompt Engineering for Large Language Models-based Code Review Automation
<div> <div> <div> <div>Supplementary material for paper <strong>"Fine-Tuning and Prompt Engineering for Large Language Models-based Code Review Automation"</strong></div> <div> </div> <div> <div> <div>The script for the paper can be found in this GitHub repository: https://github.com/awsm-research/LLM-for-code-review-automatiton</div> </div> </div> </div> </div> </div>
Code and Data Supplement for Using feature importance as exploratory data analysis tool on earth system models
<p>This contains:</p> <ul> <li>Code for all analyses in</li> <li>E3SM data</li> </ul> <p>For the paper Using <em>feature importance as exploratory data analysis tool on earth system models.</em></p>
A novel ChlF-free leaf spectra dataset and the PROSPECT-DP model code
<p><span>A novel ChlF-free leaf spectra dataset (n = 849, species = 95) collected at three sites in Beijing, China during June and August 2023. Directional-directional reflectance and transmittance spectra with or without ChlF contributions were simultaneously measured using an ASD FieldSpec 3 spectrometer coupled with an FluoWat leaf clip.</span></p> <p><span><span>PROSPECT-DP, a coupled leaf optical properties model, in which a principal component analysis approach was applied on the training dataset to derive the spectral vectors for leaf spectra reconstruction, while the coefficients of spectral vectors were determined by leveraging the simulated leaf spectra derived from the PROSPECT-D model.</span></span></p>
Modeling data and R code for Chrysodeixis chalcites ecological niche
<p>The golden twin-spot moth, <em>Chrysodeixis chalcites</em> Esper (Lepidoptera: Noctuidae), is a polyphagous, polyvoltine crop pest occurring natively from northern Europe to Mediterranean Africa and the Canary Islands. Larvae feed on a wide variety of naturally occurring plants as well as soybean and other legume crops, short staple cotton, tomato, potato, peppers, tobacco, and banana. <em>Chrysodeixis chalcites</em> has been recorded in agricultural lands in the Ontario peninsula in eastern Canada and in northern counties of Indiana, USA. Given the strong potential for <em>C. chalcites</em> to invade USA crop lands, it is important to identify environments most likely to sustain growing populations of this pest. Though <em>C.</em> chalcites is native to Europe and North Africa, it has invaded sub-Saharan Africa. Using occurrence data form the native and invaded ranges, and environmental predictors including bioclimatic conditions and human disturbance, we trained three ecological niche models to estimate an ensemble prediction of environmental suitability in the contiguous US. Because human impact is potentially a confounding predictor, models were trained both with and without it. High environmental suitability was projected for the Atlantic coast from New England to Florida, the Gulf coast, the lower Midwest, and the Pacific coast and Central Valley of California.</p>
Codes, Catalogues and Data for "Deep Learning Phase Pickers: How Well Can Existing Models Detect Hydraulic-Fracturing Induced Seismicity from a Downhole Array"
<p><strong>Codes, Catalogues and Data available for:</strong> <br>"Deep Learning Phase Pickers: How Well Can Existing Models Detect Hydraulic-Fracturing Induced Seismicity from a Downhole Array"</p> <p><strong>Catalog</strong> folder: Contains the CMM (beam-forming based) event catalogue as well as event and station information for the PNR-1z site.</p> <p><strong>Classification Test</strong> folder: Jupyter notebooks that run the classification tests and mseed input data of isolated phases (P, S, Noise).</p> <p><strong>DL_model_catalogues</strong> folder: Contains full catalogues for each DL phase picker (GPD, U-GPD, EQT and PhaseNet) and the LinMEF-filtered catalogues.</p> <p><strong>Model_run_docs</strong> folder: Util/core files for PhaseNet and EQTransformer to read data with different sampling frequencies (i.e., not 100 Hz)</p> <p><strong>Data</strong> folder: Contains one hour of continuous downhole data (11th December 2018, 9am-10am) from the PNR-1z dataset.</p>
Data and Source Codes used in "Development of a Global Quasi-3-D Multiscale Modeling Framework: I. Vector Vorticity Model on Cubed Sphere as Cloud-Resolving Component"
<p>Data and Source Codes used in the paper "Development of a Global Quasi-3-D Multiscale Modeling Framework: I. Vector Vorticity Model on Cubed Sphere as Cloud-Resolving Component"</p> <p>Advection Test (ADV): East-West A_TST (100km, Cube), C_TST (25km, Cube), E_TST (5km, Cube),</p> <p> North-South K_TST (100km, Cube), M_TST (25km, Cube), O_TST (5km, Cube) </p> <p>Barotropic Test (BAR): A_TST5 (100km, Cube), Y_TST4 (100km, RLL), C_TST3 (5km, Cube), C_TST1 (5km, RLL)</p> <p>Baroclinic Test (BCL): J_TST30 (100km, Cube), J_TST20 (100km, RLL)</p>
Code and data for "Optimising habitat management for amphibians: from simple models to complex decisions"
<p>The zip archive contains code and data to reproduce the analysis contained in the following manuscript:</p> <p>Scroggie, M.P., Preece, K., Nicholson, E., McCarthy, M.A., Parris, K.M. and Heard, G.W. Optimising habitat management for amphibians: from simple models to complex decisions.</p> <p>Included in the archive is the source code of two R packages (METAPOP, and METAPOPPLAN), which must first be installed, along with their various dependencies which include Rcpp, RcppArmadillo, sp, spdep and rgeos. As package METAPOPPLAN contains C++ code, installation requires the presence of the appropriate C++ compilers and other software development tools. These should be available or easily installable on Linux or other Unix based systems, but Microsoft Windows users must first install the appropriate version of Rtools, which can be downloaded from https://cran.r-project.org/bin/windows/Rtools/.</p> <p>With all appropriate packages installed, the analysis can be replicated by running the included Makefile.</p> <p>Total execution time will be quite long, due to the large number of simulations that must be run. On my Windows system, with 12 cores and 4GB of RAM, execution took approximately 10 days. The code will run much faster if the various management scenarios included in the analysis are executed in parallel. This can be done by executing make with a -j argument specifying the number of cores to utilise. For example, if your system has 12 cores, invoke *make* as follows:</p> <p>make -j 12</p> <p>Overall execution time will scale roughly with the number of available cores, up to a maximum of 24 (the total number of management scenarios).<br> </p>
The Delta Maintainability Model: Measuring Maintainability of Fine-Grained Code Changes Technical Report
<p>Technical Report and dataset for "The Delta Maintainability Model: Measuring Maintainability of Fine-Grained Code Changes" submitted to the 2nd International Conference on Technical Debt (TechDebt 2019) - Montréal, Canada - May 26–27, 2019.</p>
Data, code, models for "Weakly Supervised Semantic Segmentation for Joint Key Local Structure Localization and Classification of Aurora Image"
<p>Data, code and models for https://ieeexplore.ieee.org/document/8410588/</p>
Numerical model code, input files and output data for publication "Rapid mixing and exchange of deep-ocean waters in an abyssal boundary current"
<p>Contains numerical model data (code, input files, selected output, matlab diagnostic routines) to supplement publication ``Rapid mixing and exchange of deep-ocean waters in an abyssal boundary current'', by Naveiro Garabato and co-authors. All numerical model data, including any errors, is the responsibility of Sonya Legg. This data set will allow reproduction of simulations, and reproduction of diagnostics shown in plots in the above-referenced paper.</p>
Code + simulated + publically accessable data for "Evaluating health facility access using Bayesian spatial models and location analysis methods"
<p># README</p> <p>These files contain r data objects and R files that represent the key details of the paper, "Evaluating health facility access using Bayesian spatial models and location analysis methods".</p> <p>The following datasources are available for simulation of some of the ideas in the paper.</p> <p>- dat_grid_sim: simulated data of the grid and grid cells<br> - dat_ohca_cv_sim: simulated data containing the cross validated test/training sets of OHCA data<br> - dat_ohca_sim: simulated OHCA event data<br> - dat_aed_sim: simulated AED location data<br> - dat_bldg_sim: simulated building location data<br> - dat_municipality_sim: simulated municipality information<br> - table_1: Table 1 information containing key demographic data</p> <p>These data were produced using the code in 01-create-sim-data.R, and one of the statistical models is demonstrated in 02-demo-inla-model.R</p> <p>In terms of the paper itself, the functions and code used in the manuscript are located in:</p> <p>* 01_tidy.Rmd - analysis code used to tidy up the data</p> <p>* 02_fit_fixed_all_cv.Rmd - analysis code used to place AEDs</p> <p>* 02_model.Rmd - analysis code used to fit the model in INLA</p> <p>* 03_manuscript.Rmd - Full code and text used to create the paper</p> <p>* 04_supp_materials.Rmd - full code and text used to create the supplementary materials</p> <p>The following files are a part of an R package "swatial" that was developed along with the paper. These files are:</p> <p>* DESCRIPTION</p> <p>* NAMESPACE</p> <p>* LICENSE</p> <p>* LICENSE.md</p> <p>* decay.R</p> <p>* spherical-distance.R</p> <p>* test-figure-data-matches.R</p> <p>* test-table-data-matches.R</p> <p>* testthat.R</p> <p>* tidy-inla.R</p> <p>* tidy-posterior-coefs.R</p> <p>* tidy-predictions.R</p> <p>* utils-pipe.R</p> <p>* All files that end in .Rd are documentation files for the functions.</p> <p>## Regarding data sources</p> <p>Census information for Ticino was transcribed from the Annual Statistical Report of Canton Ticino from years 2010 to 2015. This data was taken from their publicly accessible annual reports - for example: (https://www3.ti.ch/DFE/DR/USTAT/allegati/volume/ast_2015.pdf). The raw data was extracted from these annual reports, and placed into the file: "swiss_census_popn_2010_2015.xlsx". These data are put into analysis ready format in the file “01_tidy.Rmd”</p> <p>Housing and other relevant geospatial data can be accessed via http://map.housing-stat.ch/ and https://data.geo.admin.ch/. The maps of buildings from the REA (Register of Buildings and Dwellings) can be found here: https://map.geo.admin.ch/?zoom=11&bgLayer=ch.swisstopo.pixelkarte-grau&lang=en&topic=ech&layers=ch.bfs.gebaeude_wohnungs_register,ch.swisstopo.swissboundaries3d-gemeinde-flaeche.fill,ch.bfs.volkszaehlung-gebaeudestatistik_gebaeude,ch.bfs.volkszaehlung-gebaeudestatistik_wohnungen,ch.swisstopo.swissbuildings3d_1.metadata,ch.swisstopo.swissbuildings3d_2.metadata&E=2717616.28&N=1096597.25&catalogNodes=687,696&layers_timestamp=,,2016,2016,,&layers_visibility=true,false,false,false,false,false&layers_opacity=1,1,1,1,1,0.75</p> <p>For further enquiries on this data, contact the Swiss federal Office of Statistics at the details listed here: https://www.bfs.admin.ch/bfs/en/home/services/contact.html</p> <p>The shapefiles of the Comuni can be accessed here: https://www4.ti.ch/dfe/de/ucr/documentazione/download-file/?noMobile=1</p> <p>Data from the people living in the Municipalities in Ticino can be downloaded here: https://www3.ti.ch/DFE/DR/USTAT/index.php?fuseaction=dati.home&tema=33&id2=61&id3=65&c1=01&c2=02&c3=02</p> <p>## Future work</p> <p>In the future, these functions from the paper may be generalised and put into their own package. If that happens, this repository will be updated with a link to updated functions.</p>
Codes and datasets associated with the paper "Dynamic LES modeling of a diurnal cycle"
<p>Here, you will find some of the codes, images, and datasets utilized in the article: </p> <p>Basu et al. (2008). "Dynamic LES modeling of a diurnal cycle", Journal of Applied Meteorology and Climatology, 47, 1156-1174. (<a href="https://journals.ametsoc.org/doi/pdf/10.1175/2007JAMC1677.1">https://journals.ametsoc.org/doi/pdf/10.1175/2007JAMC1677.1</a>)</p> <p>Matlab codes: MatlabCodes.tar.gz (Contains all the analyses and visualization codes used in the paper)</p> <p>Observational data: Wangara_Observations.tar.gz (These data were manually typed directly from the original Wangara document)</p> <p>LES data (binary): LES_160x160x160.tar.gz and LES_80x80x80.tar.gz</p>
Code and data to reproduce the results of the paper: "Land Use Patterns and Climate Change---A Modeled Scenario of the Late Bronze Age in Southern Greece"
<p>Code and data to reproduce the results of Knitter et al. (2019): Land Use Patterns and Climate Change---A Modeled Scenario of the Late Bronze Age in Southern Greece. ERL.</p>
Matlab code of the ANN model for total alkalinity estimation
<p>Matlab code of the ANN model including generate and execute codes and 5 cruises data building the model.</p>
Matlab code of the ANN model for pH estimation
<p>Matlab code of the ANN model including generate and execute codes and 11 cruises data building the model.</p>
Model source code, modified model code, and all scripts of the paper "A comprehensive estimate of the anthropogenic aerosol radiative effects using the GAMIL model with reduced complexity".
<p>Model source code, modified model code, and all scripts of the paper "A comprehensive estimate of the anthropogenic aerosol radiative effects using the GAMIL model with reduced complexity".</p>
Model source code, simulation results, and all scripts for the paper "A comprehensive estimate of the anthropogenic aerosol radiative effects using the GAMIL model with reduced complexity".
<p>FigureTable_Scripts.rar is NCL scripts used for figures and tables. <br> Model_Scripts.rar is the modified model code and scripts used for running model.<br> models.rar is the GAMIL model source code.<br> ModelResults.rar is the model results. Note that only the variables used for making plots.</p>
source code of the ANN model for pH estimation
<p>The source code of paper: Retrieving monthly and interannual pHT on the East China Sea Shelf using an artificial neural network: ANN-pHT-v1<br> </p>
Data and Code for "Mesoscale modeling of deformations and defects in thin crystalline sheets"
<p>Research data and code supporting the paper ""Mesoscale modeling of deformations and defects in thin crystalline sheets"".</p> <p> </p> <p><strong>Code (apfc-python-surf.zip)</strong></p> <p>The implementation of the APFC model is performed in python by exploiting the pseudo-spectral Fourier method. Library pyfftw is adopted. However, standard fft libraries can be used as well by changing the corresponding module/functions. The code supports equations of the APFC model both coupling with the evolution of the surface considered in this work and on a simple flat domain. Updates can be found in the GitLab repository linked below.</p> <p> </p> <p><strong>GitLab repository for the code</strong></p> <p><a href="https://gitlab.com/3ms-group/apfc_python/">https://gitlab.com/3ms-group/apfc_python/</a></p> <p> </p> <p><strong>Data</strong></p> <p>The data.zip files contain the simulation results and auxiliary scripts used to produce the results illustrated in the paper's figures. The folder numbering refers to the one used for the figures in the final version.</p> <p> </p> <p>For further information please contact the authors.</p>
Langmark: annotations for scenes with semantic inconsistencies connecting distributional semantic models to vision science – data and code
<p>Data (including object annotations) and code from the following manuscript:</p> <p><em>Langmark: annotations for scenes with semantic inconsistencies connecting distributional semantic models to vision science</em>.</p>
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.