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python3-oq-engine (3.11.0-1~bionic01~dev1611248606+736b3d9) bionic; urgency=low

  [Automatic Script]
  * Development version from 736b3d9 commit

  [Michele Simionato]
  * Extended `oq plot` to draw more than 2 plots
  * Raised an early error for zero probabilities in the hypocenter distribution
    or the nodal plane distribution
  * Extended the autostart zmq distribution logic to celery and dask
  * Stored the _poes during the classical phase and not after, to save time
  * Implemented a memory-saving logic in the classical calculator based on
    the `memory.limit` parameter in openquake.cfg;

  [Richard Styron]
  * Added TaperedGRMFD to hazardlib

  [Michele Simionato]
  * Fixed a wrong check failing in the case of multi-exposures with multiple
    cost types
  * Removed a check causing a false error "Missing vulnerability function
    for taxonomy"
  * Consequence functions associated to a taxonomy missing in the exposure
    are now simply discarded, instead of raising an error
  * Added a warning when there are zero losses for nonzero GMFs
  * Added a command `oq plot avg_gmf?imt=IMT`
  * Internal: stored `avg_gmf` as a DataFrame
  * Honored the `individual_curves` parameter in avg_losses, agg_losses and
    and agg_curves (i.e. by default only expose the statistical results)
  * Refactored the `oq commands` and removed the redundant `oq help` since
    there is `oq --help` instead
  * Support for input URLs associated to an input archive
  * Introduced `deformation_component` parameter in the secondary perils
  * Optimized the storage of the risk model with a speedup of 60x
    for a calculation with ~50,000 fragility functions (2 minutes->2seconds)
    and a 3x reduction on disk space
  * Accepted aggregate_by=id in scenario/event based calculations
  * Accepted aggregate_by=site_id in scenario/event based calculations
  * Removed the generation of asset loss maps from event_based_risk
  * Made the "Aggregate Losses" output in scenario_risk consistent with
    event_based_risk and scenario_risk and supported `aggregate_by`
  * Perform the disaggregation checks before starting the classical part
  * Changed the "Aggregate Loss Curves" CSV exporter to generate a file for
    each realization, for consistency with the other exporters
  * The ebrisk outputs "Total Losses" and "Total Loss Curves" are now included
    in the outputs "Aggregate Losses" and "Aggregate Curves"
  * Introduced an `agg_loss_table` dataset and optimized the generation of
    aggregate loss curves (up to 100x speedup)
  * Removed misleading zero losses in agg_losses.csv
  * Fixed `oq recompute_losses` and renamed it to `oq reaggregate`
  * Added a limit of 65,536 to the maximum number of aggregation tags
  * Bug fix: ignore_covs=true now sets the coefficient of variations to zero

  [Anirudh Rao]
  * Improved error handling of bad or zero coefficients of variation
    for the Beta distribution for vulnerability

  [Michele Simionato]
  * Fixed 32 bit rounding issues in scenario_risk: now the total losses and
    and the sum of the average losses are much closer
  * Internal: made the loss type `occupants` a bit less special
  * Documented `oq to_nrml`

  [Claudia Mascandola]
  * Added the Lanzano et al. (2019) GMPE

  [Michele Simionato]
  * Honored `minimum_asset_loss` also in the fully aggregated loss table,
    not only in the partially aggregated loss tables and average losses
  * Bug fixed: the log was disappearing in presence of an unrecognized
    variable in the job.ini
  * Implemented `minimum_asset_loss` in scenario_risk for consistency
    with the `ebrisk` calculator
  * Added a command `oq plot gridded_sources?`
  * Fixed `oq recompute_losses` to expose the outputs to the database
  * Fixed `oq engine --run --params` that was not working for
    the `pointsource_distance`
  * Changed the meaning of the `pointsource_distance` approximation

  [Marco Pagani, Michele Simionato, Thomas Chartier]
  * Added experimental version of KiteSource and KiteSurface

  [Michele Simionato]
  * Changed the serialization of ruptures to support MultiSurfaces
  * Fixed a small bug of logic in the WebUI: if the authentication is
    turned off, everyone must be able to see all calculations
  * Fixed a bug in the calculation of averages losses in scenario_risk
    calculations in presence of sites with zero hazard
  * Optimized the prefiltering by using a KDTree
  * Experimental: implemented gridding of point sources
  * Reduced slow tasks due to big complex fault sources
  * Moved the parameter `num_cores` into openquake.cfg
  * Internal: introduced the environment variable OQ_REDUCE
  * Using pandas to export the GMF in CSV format
  * Internal: required h5py == 2.10.0
  * Internal: made the classical ruptures pandas-friendly
  * Internal: made the damage distributions pandas-friendly

  [Marco Pagani]
  * Added a new type of undertainty for the seismic source characterisation
    logic tree called `TruncatedGRFromSlipAbsolute`
  * Added a get_fault_surface_area method to sources

  [Michele Simionato]
  * Changed the source seed algorithm in event based calculations
  * Added an estimate of the portfolio damage error due to the seed dependency
  * Stored the damage distributions in a pandas-friendly way and extended
    `DataStore.read_df` to accept multi-indices

  [Viktor Polak]
  * Added the Phung et al. (2020) GMPE

  [Michele Simionato]
  * Implemented `truncGutenbergRichterMFD` from slip rate and rigidity
  * Fixed bug when computing the damage distributions per asset and event
  * Simplified/optimized the UCERF filtering

  [Viktor Polak]
  * Added the Chao et al. (2020) GMPE

  [Michele Simionato]
  * Introduced an early memory check in classical calculations
  * Reduced the memory occupation in classical calculations
  * Implemented AvgPoeGMPE
  * Forbidded the usage of `aggregate_by` except in ebrisk calculations
  * Added a check on valid branch ID names: only letters, digits and
    the characters "#:-_." are accepted
  * Huge performance improvement for very complex logic trees
  * Shortened the logic tree paths when exporting the realizations

  [Graeme Weatherill]
  * Refactor of the Kotha et al. (2020) GMM and its adjustments for ESHM20

  [Michele Simionato]
  * Huge speedup in models with src_multiplicity > 1
  * Fixed bug in source model logic tree sampling with more than 2 branchsets
  * Fixed hazard maps all zeros for individual_curves=true and more than 1 site
  * Fixed a bug in `oq prepare_site_model` when sites.csv is
    the same as the vs30.csv file and there is a grid spacing
  * Speeding up the preclassical calculator
  * Added an entry point /extract/eids_by_gsim for the QGIS plugin
  * Internal: automatically convert the source IDs into unique IDs
  * Changed scenario calculations to depend on the `ses_seed`, not the
    `random_seed`
  * Added check on the versions of numpy, scipy and pandas between master and
    workers
  * Added a check for large seed dependency in the GMFs and an estimate of the
    portfolio error due to the seed dependency

  [Viktor Polak]
  * Added fpeak site parameter
  * Added the Hassani and Atkinson (2020) GMPE

  [Marco Pagani]
  * Added a check on DEFINED_FOR_REFERENCE_VELOCITY when using amplification
  * Added a method to create a TruncatedGRMFD from a value of scalar seismic
    moment
  * Added a method to the modifiable GMPE to add (or subtract) a delta std
  * Added a method to the modifiable GMPE to set the total std as the sum of
    tau plus a delta

 -- Automatic Packager (GEM Foundation) <email address hidden>  Thu, 21 Jan 2021 18:03:26 +0100

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