Latent Network Models to Account for Noisy, Multiply-Reported Social Network Data

Overview

VIMuRe

Github Badge codecov

Latent Network Models to Account for Noisy, Multiply-Reported Social Network Data.

If you use this code please cite this article (preprint).

De Bacco C, Contisciani M, Cardoso-Silva J, Safdari H, Baptista D, Sweet T, Young JG, Koster J, Ross CT, McElreath R, Redhead D. Latent Network Models to Account for Noisy, Multiply-Reported Social Network Data. arXiv preprint arXiv:2112.11396. 2021.

Notebooks

To understand how you could use the code or to replicate our research, check the notebooks folder:

Setup

Instructions on how to replicate our research either downloading our package via pip or by using the Docker setup used for developing the package.

Alternative 01: using pip

Install vimure==0.1 with the following command:

pip install git+https://github.com/latentnetworks/vimure.git#egg=vimure\&subdirectory=src/python/

Alternative 02: using Docker

If you are familiar with Docker, you could use the Docker containers provided in this repository. Use this setup if you want to modify anything in the package.

  1. Clone the repository to a directory in your machine
  2. Install Docker and docker-compose on your machine
  3. Open the terminal and build the project:
cd vimure
docker-compose build

The first time you run this build, it will take several minutes to complete. Trust me, it is better to run this and wait the building time than having to install each multiple python dependencies by hand and having to figure out why your colleague gets a weird and mysterious, previously unseen Exception when running the same code as you!

  1. Still on the terminal, run Jupyter server with the command:
docker-compose up

A URL will show up on your screen, either click on it or copy-paste to your browser and run the notebooks.

License

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NON INFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Comments
  • :sparkles: Implement ViMuRe model

    :sparkles: Implement ViMuRe model

    Closes #25 Closes #20 Related to #21

    Changes

    • Add VimureModel binding
    • Extend summary to summarise vimure model
    • Add build_custom_theta function
    • Add parse_graph_from_edgelist, parse_graph_from_csv, parse_graph_from_igraph
    • vimure should work with graph and matrix inputs
    • Add Rmarkdown

    How to validate

    • [x] Clone this repository
    • [x] Checkout to 25-vimure-v01-r-implement-vimuremodel and set the working directory to src/R
    • [x] Open Rstudio and run:
    library(devtools)
    install()
    

    If it is not your first time running vimure on R, R will ask if you want to remove vimure from virtual enviroment. Answer Yes. This is necessary to install the developing version of the Python package.

    • [x] Validate the scripts in notebooks/R
    • [x] Validate the docs help(vimure)
    • [x] Typo errors
    enhancement 
    opened by gabiborges1 2
  • 🪓 Change the way we calculate X_union and X_intersection

    🪓 Change the way we calculate X_union and X_intersection

    What's New

    • Adds comments with info about the Union and Intersection baselines
    • Changes the calculation of X_intersection to replace the previous erroneous calculation (count_ties == 2).
    • (No unit tests were added. I can add more test scenarios if we find it necessary)

    Closes #35

    How to validate

    • [x] Have a look at the changes in code as shown below on this PR
    • [x] Checkout the branch 35-vimure-v01-py-baseline-calc
    • [x] Build the environment with make venv-build to ensure your python environment has the same libraries as the version on Githrub
    • [x] Run the unit tests with make test
    • [x] See if you agree with the changes. If yes, approve the Pull Request. Otherwise, leave a comment/request for change.
    bug 
    opened by jonjoncardoso 2
  • Bump scipy from 1.7.1 to 1.8.0

    Bump scipy from 1.7.1 to 1.8.0

    Bumps scipy from 1.7.1 to 1.8.0.

    Release notes

    Sourced from scipy's releases.

    SciPy 1.8.0 Release Notes

    SciPy 1.8.0 is the culmination of 6 months of hard work. It contains many new features, numerous bug-fixes, improved test coverage and better documentation. There have been a number of deprecations and API changes in this release, which are documented below. All users are encouraged to upgrade to this release, as there are a large number of bug-fixes and optimizations. Before upgrading, we recommend that users check that their own code does not use deprecated SciPy functionality (to do so, run your code with python -Wd and check for DeprecationWarning s). Our development attention will now shift to bug-fix releases on the 1.8.x branch, and on adding new features on the master branch.

    This release requires Python 3.8+ and NumPy 1.17.3 or greater.

    For running on PyPy, PyPy3 6.0+ is required.

    Highlights of this release

    • A sparse array API has been added for early testing and feedback; this work is ongoing, and users should expect minor API refinements over the next few releases.
    • The sparse SVD library PROPACK is now vendored with SciPy, and an interface is exposed via scipy.sparse.svds with solver='PROPACK'. It is currently default-off due to potential issues on Windows that we aim to resolve in the next release, but can be optionally enabled at runtime for friendly testing with an environment variable setting of USE_PROPACK=1.
    • A new scipy.stats.sampling submodule that leverages the UNU.RAN C library to sample from arbitrary univariate non-uniform continuous and discrete distributions
    • All namespaces that were private but happened to miss underscores in their names have been deprecated.

    New features

    scipy.fft improvements

    Added an orthogonalize=None parameter to the real transforms in scipy.fft which controls whether the modified definition of DCT/DST is used without changing the overall scaling.

    scipy.fft backend registration is now smoother, operating with a single

    ... (truncated)

    Commits
    • b5d8bab REL: 1.8.0 release commit.
    • d84f731 Merge pull request #15521 from tylerjereddy/treddy_prep_180_final
    • 315dd53 DOC: update 1.8.0 relnotes.
    • b54b7ae MAINT: fix broken link and remove CI badges
    • 920e27b REL: 1.8.0 unreleased.
    • ea004bd REL: 1.8.0rc4 released.
    • 4f3969d Merge pull request #15479 from tylerjereddy/treddy_180rc4
    • 8ed6aa9 DOC: update 1.8.0 relnotes.
    • efe4ca5 MAINT: PR 15479 revisions
    • 1803913 MAINT: remove non-default settings (except shallow) in .gitmodules
    • Additional commits viewable in compare view

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    dependencies 
    opened by dependabot[bot] 2
  • Bump numpy from 1.21.2 to 1.22.1

    Bump numpy from 1.21.2 to 1.22.1

    Bumps numpy from 1.21.2 to 1.22.1.

    Release notes

    Sourced from numpy's releases.

    v1.22.1

    NumPy 1.22.1 Release Notes

    The NumPy 1.22.1 is maintenance release that fixes bugs discovered after the 1.22.0 release. Notable fixes are:

    • Fix f2PY docstring problems (SciPy)
    • Fix reduction type problems (AstroPy)
    • Fix various typing bugs.

    The Python versions supported for this release are 3.8-3.10.

    Contributors

    A total of 14 people contributed to this release. People with a "+" by their names contributed a patch for the first time.

    • Arryan Singh
    • Bas van Beek
    • Charles Harris
    • Denis Laxalde
    • Isuru Fernando
    • Kevin Sheppard
    • Matthew Barber
    • Matti Picus
    • Melissa Weber Mendonça
    • Mukulika Pahari
    • Omid Rajaei +
    • Pearu Peterson
    • Ralf Gommers
    • Sebastian Berg

    Pull requests merged

    A total of 20 pull requests were merged for this release.

    • #20702: MAINT, DOC: Post 1.22.0 release fixes.
    • #20703: DOC, BUG: Use pngs instead of svgs.
    • #20704: DOC: Fixed the link on user-guide landing page
    • #20714: BUG: Restore vc141 support
    • #20724: BUG: Fix array dimensions solver for multidimensional arguments...
    • #20725: TYP: change type annotation for __array_namespace__ to ModuleType
    • #20726: TYP, MAINT: Allow ndindex to accept integer tuples
    • #20757: BUG: Relax dtype identity check in reductions
    • #20763: TYP: Allow time manipulation functions to accept date and timedelta...
    • #20768: TYP: Relax the type of ndarray.__array_finalize__
    • #20795: MAINT: Raise RuntimeError if setuptools version is too recent.
    • #20796: BUG, DOC: Fixes SciPy docs build warnings
    • #20797: DOC: fix OpenBLAS version in release note
    • #20798: PERF: Optimize array check for bounded 0,1 values

    ... (truncated)

    Commits
    • 7ce4118 Merge pull request #20820 from charris/prepare-for-1.22.1-release
    • 5e61926 REL: Prepare for the NumPy 1.22.1 release.
    • 914b11f Merge pull request #20819 from charris/backport-20791
    • d671964 Regression test for inverse indices in array_api set functions
    • 09a379c BUG: Return correctly shaped inverse indices in array_api
    • 0674d6b Merge pull request #20815 from charris/backport-20783
    • 55a2f24 Merge pull request #20814 from charris/backport-20629
    • 95e2165 change "The NumPy community" to "NumPy Developers"
    • fb9cd1d Update Copyright to 2022
    • a19410d DOC: Refer to NumPy, not pandas, in main page
    • Additional commits viewable in compare view

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    dependencies 
    opened by dependabot[bot] 2
  • Bump scikit-learn from 0.24.2 to 1.0.2

    Bump scikit-learn from 0.24.2 to 1.0.2

    Bumps scikit-learn from 0.24.2 to 1.0.2.

    Release notes

    Sourced from scikit-learn's releases.

    scikit-learn 1.0.2

    We're happy to announce the 1.0.2 release with several bugfixes:

    You can see the changelog here: https://scikit-learn.org/dev/whats_new/v1.0.html#version-1-0-2

    You can upgrade with pip as usual:

    pip install -U scikit-learn
    

    The conda-forge builds will be available shortly, which you can then install using:

    conda install -c conda-forge scikit-learn
    

    scikit-learn 1.0.1

    We're happy to announce the 1.0.1 release with several bugfixes:

    You can see the changelog here: https://scikit-learn.org/dev/whats_new/v1.0.html#version-1-0-1

    You can upgrade with pip as usual:

    pip install -U scikit-learn
    

    The conda-forge builds will be available shortly, which you can then install using:

    conda install -c conda-forge scikit-learn
    

    scikit-learn 1.0

    We're happy to announce the 1.0 release. You can read the release highlights under https://scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_1_0_0.html and the long version of the change log under https://scikit-learn.org/stable/whats_new/v1.0.html#changes-1-0

    This version supports Python versions 3.7 to 3.9.

    Commits

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    dependencies 
    opened by dependabot[bot] 2
  • Bump jupyterlab-execute-time from 2.0.5 to 2.1.0

    Bump jupyterlab-execute-time from 2.0.5 to 2.1.0

    Bumps jupyterlab-execute-time from 2.0.5 to 2.1.0.

    Changelog

    Sourced from jupyterlab-execute-time's changelog.

    2.1.0 (2021-10-1)

    Added

    • Ability to keep only cell execution time for cells that took longer than a threshold (still defaults to always show)

    Fixed

    • Click on a execute time output also selects the cell
    • Coloring when used with certain themes
    Commits

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    dependencies 
    opened by dependabot[bot] 2
  • Bump numpy from 1.21.2 to 1.22.0

    Bump numpy from 1.21.2 to 1.22.0

    Bumps numpy from 1.21.2 to 1.22.0.

    Release notes

    Sourced from numpy's releases.

    v1.22.0

    NumPy 1.22.0 Release Notes

    NumPy 1.22.0 is a big release featuring the work of 153 contributors spread over 609 pull requests. There have been many improvements, highlights are:

    • Annotations of the main namespace are essentially complete. Upstream is a moving target, so there will likely be further improvements, but the major work is done. This is probably the most user visible enhancement in this release.
    • A preliminary version of the proposed Array-API is provided. This is a step in creating a standard collection of functions that can be used across application such as CuPy and JAX.
    • NumPy now has a DLPack backend. DLPack provides a common interchange format for array (tensor) data.
    • New methods for quantile, percentile, and related functions. The new methods provide a complete set of the methods commonly found in the literature.
    • A new configurable allocator for use by downstream projects.

    These are in addition to the ongoing work to provide SIMD support for commonly used functions, improvements to F2PY, and better documentation.

    The Python versions supported in this release are 3.8-3.10, Python 3.7 has been dropped. Note that 32 bit wheels are only provided for Python 3.8 and 3.9 on Windows, all other wheels are 64 bits on account of Ubuntu, Fedora, and other Linux distributions dropping 32 bit support. All 64 bit wheels are also linked with 64 bit integer OpenBLAS, which should fix the occasional problems encountered by folks using truly huge arrays.

    Expired deprecations

    Deprecated numeric style dtype strings have been removed

    Using the strings "Bytes0", "Datetime64", "Str0", "Uint32", and "Uint64" as a dtype will now raise a TypeError.

    (gh-19539)

    Expired deprecations for loads, ndfromtxt, and mafromtxt in npyio

    numpy.loads was deprecated in v1.15, with the recommendation that users use pickle.loads instead. ndfromtxt and mafromtxt were both deprecated in v1.17 - users should use numpy.genfromtxt instead with the appropriate value for the usemask parameter.

    (gh-19615)

    ... (truncated)

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    dependencies 
    opened by dependabot[bot] 2
  • Bump scipy from 1.7.1 to 1.7.3

    Bump scipy from 1.7.1 to 1.7.3

    Bumps scipy from 1.7.1 to 1.7.3.

    Release notes

    Sourced from scipy's releases.

    SciPy 1.7.3 Release Notes

    SciPy 1.7.3 is a bug-fix release that provides binary wheels for MacOS arm64 with Python 3.8, 3.9, and 3.10. The MacOS arm64 wheels are only available for MacOS version 12.0 and greater, as explained in Issue 14688.

    Authors

    • Anirudh Dagar
    • Ralf Gommers
    • Tyler Reddy
    • Pamphile Roy
    • Olivier Grisel
    • Isuru Fernando

    A total of 6 people contributed to this release. People with a "+" by their names contributed a patch for the first time. This list of names is automatically generated, and may not be fully complete.

    SciPy 1.7.2 Release Notes

    SciPy 1.7.2 is a bug-fix release with no new features compared to 1.7.1. Notably, the release includes wheels for Python 3.10, and wheels are now built with a newer version of OpenBLAS, 0.3.17. Python 3.10 wheels are provided for MacOS x86_64 (thin, not universal2 or arm64 at this time), and Windows/Linux 64-bit. Many wheels are now built with newer versions of manylinux, which may require newer versions of pip.

    Authors

    • Peter Bell
    • da-woods +
    • Isuru Fernando
    • Ralf Gommers
    • Matt Haberland
    • Nicholas McKibben
    • Ilhan Polat
    • Judah Rand +
    • Tyler Reddy
    • Pamphile Roy
    • Charles Harris
    • Matti Picus
    • Hugo van Kemenade
    • Jacob Vanderplas

    ... (truncated)

    Commits
    • 59e6539 REL: 1.7.3 release commit.
    • 9fcfc45 Merge pull request #15088 from tylerjereddy/treddy_backports_173
    • 7275c59 DOC: update 1.7.3 relnotes.
    • 20c42c2 MAINT: PR 15088 revisions
    • 759f76e DOC: draft 1.7.3 release notes
    • 4f14791 BUG: out of bounds indexing in stats.qmc.update_discrepancy.
    • 1b9e907 Merge pull request #15090 from rgommers/arm64-17x
    • d75f647 TST: skip failing integrate tests on macOS arm64 - zvode issue
    • b785d56 TST: skip a failing arpack test on macOS arm64
    • 526e6c4 TST: mark an mpmath test that appears to hang as xslow
    • Additional commits viewable in compare view

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    dependencies 
    opened by dependabot[bot] 2
  • Bump networkx from 2.6.2 to 2.6.3

    Bump networkx from 2.6.2 to 2.6.3

    Bumps networkx from 2.6.2 to 2.6.3.

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    dependencies 
    opened by dependabot[bot] 2
  • Add `install_vimure` to customize the version of the Python package

    Add `install_vimure` to customize the version of the Python package

    Closes #42

    How to validate?

    • [x] Clone this repository
    • [x] Checkout to 42-r-change-the-way-of-installing-python-dependencies
    • [x] Remove all current installation of vimure (Bash pip uninstall vimure; R remove.packages("vimure"))
    • [x] Install vimure
    setwd("src/R")
    devtools::install()
    
    • [x] Try to execute a vimure function
    gm_Multitensor(N=20, M=20)
    

    You should see an error similar to:

    Error: Valid installation of `vimure` not found.
    
    Python environments searched for 'vimure' package:
     /home/gabriela-borges/anaconda3/envs/vimure/bin/python3.6
     /usr/bin/python3.8
     /home/gabriela-borges/anaconda3/bin/python3.8
     /home/gabriela-borges/anaconda3/envs/fastapi/bin/python3.9
     /home/gabriela-borges/anaconda3/envs/streamlit/bin/python3.9
     /home/gabriela-borges/anaconda3/envs/streamlit3/bin/python3.9
    
    Python exception encountered:
     Traceback (most recent call last):
      File "/home/gabriela-borges/R/x86_64-pc-linux-gnu-library/4.1/reticulate/python/rpytools/loader.py", line 39, in _import_hook
        module = _import(
    ModuleNotFoundError: No module named 'vimure'
    
    
    You can install `vimure` using the install_vimure() function.
    
    • [x] Install vimure with install_vimure() and execute the same function
    install_vimure()
    library(vimure)
    gm_Multitensor(N=20, M=20)
    
    • Typo errors
    • README.md files
    enhancement 
    opened by gabiborges1 1
  • Bump tqdm from 4.62.0 to 4.64.0

    Bump tqdm from 4.62.0 to 4.64.0

    Bumps tqdm from 4.62.0 to 4.64.0.

    Release notes

    Sourced from tqdm's releases.

    tqdm v4.64.0 stable

    • add contrib.slack (#1313)

    tqdm v4.63.2 stable

    • rich: expose options kwargs (#1282)
    • autonotebook: re-enable VSCode (#1309)
    • misc docs typos (#1301, #1299)
    • update dev dependencies (#1311)

    tqdm v4.63.1 stable

    • fix stderr/stdout missing flush() (#1248 <- #1177)
    • misc speed improvements/optimisations

    tqdm v4.63.0 stable

    • add __reversed__()
    • add efficient __contains__()
    • improve CLI startup time (replace pkg_resources => importlib)
    • tqdm.autonotebook warning & std fallback on missing ipywidgets (#1218 <- #1082, #1217)
    • warn on positional CLI arguments
    • misc build/test framework updates
      • enable py3.10 tests
      • add conda dependencies
      • update pre-commit hooks
      • fix pytest config (nbval, asyncio)
      • fix dependencies & tests
      • fix site deployment

    tqdm v4.62.3 stable

    • fix minor typo (#1246)
    • minor example fix (#1246)
    • misc tidying & refactoring
    • misc build/dev framework updates
      • update dependencies
      • update linters
      • update docs deployment branches
    • misc test/ci updates
      • test forks
      • tidy OS & Python version tests
      • bump primary python version 3.7 => 3.8
      • beta py3.10 testing
      • fix py2.7 tests
      • better timeout handling

    tqdm v4.62.2 stable

    • fix notebook memory leak (#1216)
    • fix contrib.concurrent with generators (#1233 <- #1231)

    tqdm v4.62.1 stable

    • contrib.logging: inherit existing handler output stream (#1191)
    • fix PermissionError by using weakref in DisableOnWriteError (#1207)

    ... (truncated)

    Commits

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    dependencies 
    opened by dependabot[bot] 1
  • [IMPROVEMENT] Allow `vimure()` to accept a `BaseNetwork` object directly

    [IMPROVEMENT] Allow `vimure()` to accept a `BaseNetwork` object directly

    Refactor vimure function to accept a BaseNetwork object directly so that we do not need to pass the x attribute here:

    model <- vimure(vm_graph$X, num_realisations=1, max_iter=100, seed=5, mutuality = TRUE)
    
    enhancement R-version 
    opened by jonjoncardoso 0
  • Refactor documentation

    Refactor documentation

    Feedback given by @eapower while testing the R package:

    • [x] In the Install the released version section of the website, add a line about library(vimure) at the top
    • [ ] Double-check vimure_config()
    • [ ] Python interface --> rename to "python in R" or similar
    • [ ] Work on #55 --> dimensionality of X is confusing.
    • [ ] Require ggcorrplot
    • [ ] The vimure function inheritS
    • [ ] Quick start -> Make it more conversational
    • [x] VimuDeModel to VimureModel
    ♻️ refactoring R-version 
    opened by jonjoncardoso 0
  • Align python version of the parse_graph_* functions with the new version of the R package

    Align python version of the parse_graph_* functions with the new version of the R package

    Considering the new version of parse_graph_* functions introduced in the R package (first introduced here and then modified here), ensure that parse_graph_* functions in the Python code work the same way.

    feature request python-package 
    opened by jonjoncardoso 0
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