[DRAFT] Coherent random numbers #133
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…f variable between simulations. Experimenting in ART. Added logic to do transmission by acquiring node rather than edge. Slow, but rng safe. Discovered np.random.poisson in Gonorrhea set_prognosis - likely needs to be passed index of infecting agent, which I do not currently calculate. TODO!
* Redo transmission and identification of source * Added a poisson stream * Initializing intervention streams * Now set prognosis based on infector UID
…f of concept. Added a PrEP intervention that's like ART but modifies rel_sus.
* Breaking relationships on death
* Now calling finalize * ART reduces transmission * In ART and PrEP, changed capacity to coverage * Bug fix in networks * Updated "simple.py" example, need more testing
…mit that simple.py now runs two simulations and visualizes them side by side for each time step.
* Making ART reduce transmission * Added a simple "ladder" network in which 1<-->2, 3<-->4, ... for testing purposes * Improved graph visualization in simple.py, but will likely revert this to a simple test later. * Adding simple_ladder.py to run and plot the ladder network
* One member of each dyad is initally HIV+ * 50% of HIV+ are on ART
* Added checking to ensure a stream is not called twice in a row without a reset() or a step()
* Bug fix in test_stream.py
* Improving test for Stream object. * Improving streams.py: - Exception handling - reset() - Avoiding dependence of Stream on Sim object, now taking a Streams object and a block_size_object.
* module streams by layer, about to fix. * Checking for repeat stream names.
* Adding run_multistream.py to compare a simple HIV simulation with and without random stream coherence. * Stream block size now determined automatically * Stream seed offsets are now determined by hashing the stream name instead of sequentially. Thanks to @RomeshA for the suggestion. * New transmission calcs. Now determining acquisition probability across all layers and edge directions before using one random draw to determine acquisition. * This change makes it more challenging to determine whom the infection came from, that is currently a N^2 operation that needs optimization. * Adding ability to disable multiple streams through parameter named "multistream" * The ability switch from MultiStream (the default) to CentralizedStream adds some complexity. Consider removing this feature later. * As a result, everything now has parameters. * Fixed prevalence calculation to include only people who are alive in the denominator. * Additional error checking for streams, for example when the index array is boolean or empty. * The _pre_draw decorator is now applied to more MultiStream calls for error checking. * New CentralizedStream class that behaves like MultiStream but calls into a centralized random number generator. * Fixed a small bug in states.py regarding the size of grow(). * Improved stream and streams tests.
* renaming stable_monogamy.py to run_stable_monogamy.py * Adjusting test_base.py, it need some work to restore test_networks()
* Now using scipy to compute the distance matrix, it's faster * Added a normal draw to streams.
* run_multistream now compares multstrem on and off for either ART or PrEP * New run_sweep.py sweeps beta with multstream on or off
Interface still a bit messy. Need to fix Centralized RNG now.
* Catching edge cases * Update and cleanup of test scripts * Removing prep * Making art_efficacy a parameter * Removed step from negative binomial
* In states.py, added check for DynamicView
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Much-improved v2 on the way. |
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Optionally use multiple random number streams and other tricks to maintain coherence between simulations.
Enabled by the
multistreamoption and only fully compatible with thesimple_embeddingnetwork.See #73 and #118.