openquake.commonlib package¶

calc module¶

Here is an example of how to convert GMFs into mean hazard curves. Works in the case of sampling, when the weights are all equal. It keeps everything in memory and it is extremely fast. NB: parallelization would kill the performance:

def gmvs_to_mean_hcurves(dstore):
   # Convert GMFs into mean hazard curves. Works by keeping everything in
   # memory and it is extremely fast.
   # NB: parallelization would kill the performance.
   oq = dstore['oqparam']
   N = len(dstore['sitecol'])
   M = len(oq.imtls)
   L1 = oq.imtls.size // M
   gmf_df = dstore.read_df('gmf_data', 'sid')
   mean = numpy.zeros((N, 1, M, L1))
   for sid, df in gmf_df.groupby(gmf_df.index):
       gmvs = [df[col].to_numpy() for col in df.columns
               if col.startswith('gmv_')]
       mean[sid, 0] = calc.gmvs_to_poes(
           gmvs, oq.imtls, oq.ses_per_logic_tree_path)
   return mean

class openquake.commonlib.calc.RuptureImporter(dstore)[source]¶

Bases: object

Import an array of ruptures correctly, i.e. by populating the datasets ruptures, rupgeoms, events.

check_overflow(E)[source]¶: Raise a ValueError if the number of sites is larger than 65,536 or the number of IMTs is larger than 256 or the number of ruptures is larger than 4,294,967,296. The limits are due to the numpy dtype used to store the GMFs (gmv_dt). There also a limit of max_potential_gmfs on the number of sites times the number of events, to avoid producing too many GMFs. In that case split the calculation or be smarter.

get_eid_rlz(proxies, rlzs_by_gsim)[source]¶

Returns:	a composite array with the associations eid->rlz

import_rups(rup_array)[source]¶: Import an array of ruptures in the proper format

save_events(rup_array)[source]¶

Parameters:	rup_array – an array of ruptures with fields et_id
Returns:	a list of RuptureGetters

openquake.commonlib.calc.compute_hazard_maps(curves, imls, poes)[source]¶

Given a set of hazard curve poes, interpolate hazard maps at the specified poes.

Parameters:

curves – 2D array of floats. Each row represents a curve, where the values in the row are the PoEs (Probabilities of Exceedance) corresponding to imls. Each curve corresponds to a geographical location.
imls – Intensity Measure Levels associated with these hazard curves. Type should be an array-like of floats.
poes – Value(s) on which to interpolate a hazard map from the input curves. Can be an array-like or scalar value (for a single PoE).

Returns:

An array of shape N x P, where N is the number of curves and P the number of poes.

openquake.commonlib.calc.convert_to_array(pmap, nsites, imtls, inner_idx=0)[source]¶

Convert the probability map into a composite array with header of the form PGA-0.1, PGA-0.2 …

Parameters:	pmap – probability map nsites – total number of sites imtls – a DictArray with IMT and levels
Returns:	a composite array of lenght nsites

openquake.commonlib.calc.gmvs_to_poes(df, imtls, ses_per_logic_tree_path)[source]¶

Parameters:	df – a DataFrame with fields gmv_0, .. gmv_{M-1} imtls – a dictionary imt -> imls with M IMTs and L levels ses_per_logic_tree_path – a positive integer
Returns:	an array of PoEs of shape (M, L)

openquake.commonlib.calc.make_hmap(pmap, imtls, poes, sid=None)[source]¶

Compute the hazard maps associated to the passed probability map.

Parameters:	pmap – hazard curves in the form of a ProbabilityMap imtls – DictArray with M intensity measure types poes – P PoEs where to compute the maps sid – not None when pmap is actually a ProbabilityCurve
Returns:	a ProbabilityMap with size (N, M, P)

openquake.commonlib.calc.make_uhs(hmap, info)[source]¶

Make Uniform Hazard Spectra curves for each location.

Parameters:	hmap – array of shape (N, M, P) info – a dictionary with keys poes, imtls, uhs_dt
Returns:	a composite array containing uniform hazard spectra

hazard_writers module¶

Classes for serializing various NRML XML artifacts.

class openquake.commonlib.hazard_writers.BaseCurveWriter(dest, **metadata)[source]¶

Bases: object

Base class for curve writers.

Parameters:

dest – File path (including filename) or file-like object for results to be saved to.
metadata –
The following keyword args are required:
- investigation_time: Investigation time (in years) defined in the calculation which produced these results.
The following are more or less optional (combinational rules noted below where applicable):
- statistics: ‘mean’ or ‘quantile’
- quantile_value: Only required if statistics = ‘quantile’.
- smlt_path: String representing the logic tree path which produced these curves. Only required for non-statistical curves.
- gsimlt_path: String represeting the GSIM logic tree path which produced these curves. Only required for non-statisical curves.

serialize(_data)[source]¶: Implement in subclasses.

class openquake.commonlib.hazard_writers.DisaggXMLWriter(dest, **metadata)[source]¶

Bases: object

Parameters:

dest – File path (including filename) or file-like object for XML results to be saved to.
metadata –
The following keyword args are required:
- investigation_time: Investigation time (in years) defined in the calculation which produced these results.
- imt: Intensity measure type used to compute these matrices.
- lon, lat: Longitude and latitude associated with these results.
The following attributes define dimension context for the result matrices:
- mag_bin_edges: List of magnitude bin edges (floats)
- dist_bin_edges: List of distance bin edges (floats)
- lon_bin_edges: List of longitude bin edges (floats)
- lat_bin_edges: List of latitude bin edges (floats)
- eps_bin_edges: List of epsilon bin edges (floats)
- tectonic_region_types: List of tectonic region types (strings)
- smlt_path: String representing the logic tree path which produced these results. Only required for non-statistical results.
- gsimlt_path: String represeting the GSIM logic tree path which produced these results. Only required for non-statistical results.
The following are optional, depending on the imt:
- sa_period
- sa_damping

BIN_EDGE_ATTR_MAP = {'mag_bin_edges': 'magBinEdges', 'dist_bin_edges': 'distBinEdges', 'lon_bin_edges': 'lonBinEdges', 'lat_bin_edges': 'latBinEdges', 'eps_bin_edges': 'epsBinEdges', 'tectonic_region_types': 'tectonicRegionTypes'}¶: Maps metadata keywords to XML attribute names for bin edge information passed to the constructor.

DIM_LABEL_TO_BIN_EDGE_MAP = {'Mag': 'mag_bin_edges', 'Dist': 'dist_bin_edges', 'Lon': 'lon_bin_edges', 'Lat': 'lat_bin_edges', 'Eps': 'eps_bin_edges', 'TRT': 'tectonic_region_types'}¶

serialize(data)[source]¶

Parameters:

data –

A sequence of data where each datum has the following attributes:

matrix: N-dimensional numpy array containing the disaggregation histogram.
dim_labels: A list of strings which label the dimensions of a given histogram. For example, for a Magnitude-Distance-Epsilon histogram, we would expect dim_labels to be ['Mag', 'Dist', 'Eps'].
poe: The disaggregation Probability of Exceedance level for which these results were produced.
iml: Intensity measure level, interpolated from the source hazard curve at the given poe.

class openquake.commonlib.hazard_writers.HazardCurveXMLWriter(dest, **metadata)[source]¶

Bases: openquake.commonlib.hazard_writers.BaseCurveWriter

Hazard Curve XML writer. See BaseCurveWriter for a list of general constructor inputs.

The following additional metadata params are required:

imt: Intensity measure type used to compute these hazard curves.
imls: Intensity measure levels, which represent the x-axis values of each curve.

The following parameters are optional:

sa_period: Only used with imt = ‘SA’.
sa_damping: Only used with imt = ‘SA’.

add_hazard_curves(root, metadata, data)[source]¶: Add hazard curves stored into data as child of the root element with metadata. See the documentation of the method serialize and the constructor for a description of data and metadata, respectively.

serialize(data)[source]¶

Write a sequence of hazard curves to the specified file.

Parameters:

data –

Iterable of hazard curve data. Each datum must be an object with the following attributes:

poes: A list of probability of exceedence values (floats).
location: An object representing the location of the curve; must have x and y to represent lon and lat, respectively.

class openquake.commonlib.hazard_writers.HazardMapWriter(dest, **metadata)[source]¶

Bases: object

Parameters:

dest – File path (including filename) or a file-like object for results to be saved to.
metadata –
The following keyword args are required:
- investigation_time: Investigation time (in years) defined in the calculation which produced these results.
- imt: Intensity measure type used to compute these hazard curves.
- poe: The Probability of Exceedance level for which this hazard map was produced.
The following are more or less optional (combinational rules noted below where applicable):
- statistics: ‘mean’ or ‘quantile’
- quantile_value: Only required if statistics = ‘quantile’.
- smlt_path: String representing the logic tree path which produced these curves. Only required for non-statistical curves.
- gsimlt_path: String represeting the GSIM logic tree path which produced these curves. Only required for non-statisical curves.
- sa_period: Only used with imt = ‘SA’.
- sa_damping: Only used with imt = ‘SA’.

serialize(data)[source]¶

Write a sequence of hazard map data to the specified file.

Parameters:	data – Iterable of hazard map data. Each datum should be a triple of (lon, lat, iml) values.

class openquake.commonlib.hazard_writers.HazardMapXMLWriter(dest, **metadata)[source]¶

Bases: openquake.commonlib.hazard_writers.HazardMapWriter

NRML/XML implementation of a HazardMapWriter.

See HazardMapWriter for information about constructor parameters.

serialize(data)[source]¶

Serialize hazard map data to XML.

See HazardMapWriter.serialize() for details about the expected input.

class openquake.commonlib.hazard_writers.SESXMLWriter(dest)[source]¶

Bases: object

Parameters:	dest – File path (including filename) or a file-like object for XML results to be saved to. sm_lt_path (str) – Source model logic tree branch identifier of the logic tree realization which produced this collection of stochastic event sets. gsim_lt_path – GSIM logic tree branch identifier of the logic tree realization which produced this collection of stochastic event sets.

serialize(data, investigation_time)[source]¶

Serialize a collection of stochastic event sets to XML.

Parameters:

data –
A dictionary et_id -> list of openquake.commonlib.calc.Rupture objects. Each Rupture should have the following attributes:
- rupid
- events_by_ses
- magnitude
- strike
- dip
- rake
- tectonic_region_type
- is_from_fault_source (a bool)
- is_multi_surface (a bool)
- lons
- lats
- depths
If is_from_fault_source is True, the rupture originated from a simple or complex fault sources. In this case, lons, lats, and depths should all be 2D arrays (of uniform shape). These coordinate triples represent nodes of the rupture mesh.

If is_from_fault_source is False, the rupture originated from a point or area source. In this case, the rupture is represented by a quadrilateral planar surface. This planar surface is defined by 3D vertices. In this case, the rupture should have the following attributes:
- top_left_corner
- top_right_corner
- bottom_right_corner
- bottom_left_corner
Each of these should be a triple of lon, lat, depth.

If is_multi_surface is True, the rupture originated from a multi-surface source. In this case, lons, lats, and depths should have uniform length. The length should be a multiple of 4, where each segment of 4 represents the corner points of a planar surface in the following order:
- top left
- top right
- bottom left
- bottom right
Each of these should be a triple of lon, lat, depth.
investigation_time – Investigation time parameter specified in the job.ini

class openquake.commonlib.hazard_writers.UHSXMLWriter(dest, **metadata)[source]¶

Bases: openquake.commonlib.hazard_writers.BaseCurveWriter

UHS curve XML writer. See BaseCurveWriter for a list of general constructor inputs.

The following additional metadata params are required:

poe: Probability of exceedance for which a given set of UHS have been

computed
periods: A list of SA (Spectral Acceleration) period values, sorted

ascending order

serialize(data)[source]¶

Write a sequence of uniform hazard spectra to the specified file.

Parameters:

data –

Iterable of UHS data. Each datum must be an object with the following attributes:

imls: A sequence of Intensity Measure Levels
location: An object representing the location of the curve; must have x and y to represent lon and lat, respectively.

openquake.commonlib.hazard_writers.gen_gmfs(gmf_set)[source]¶: Generate GMF nodes from a gmf_set :param gmf_set: a sequence of GMF objects with attributes imt, sa_period, sa_damping, event_id and containing a list of GMF nodes with attributes gmv and location. The nodes are sorted by lon/lat.

openquake.commonlib.hazard_writers.rupture_to_element(rup, parent=None)[source]¶

Convert a rupture object into an Element object.

Parameters:	rup – must have attributes .rupid, .events_by_ses and .seed parent – parent of the returned element, or None

openquake.commonlib.hazard_writers.sub_elems(elem, rup, *names)[source]¶

logictree module¶

Logic tree parser, verifier and processor. See specs at https://blueprints.launchpad.net/openquake-old/+spec/openquake-logic-tree-module

A logic tree object must be iterable and yielding realizations, i.e. objects with attributes value, weight, lt_path and ordinal.

class openquake.commonlib.logictree.BranchTuple(trt, id, gsim, weight, effective)¶

Bases: tuple

effective¶: Alias for field number 4

gsim¶: Alias for field number 2

id¶: Alias for field number 1

trt¶: Alias for field number 0

weight¶: Alias for field number 3

class openquake.commonlib.logictree.FullLogicTree(source_model_lt, gsim_lt)[source]¶

Bases: object

The full logic tree as composition of

Parameters:	source_model_lt – `SourceModelLogicTree` object gsim_lt – `GsimLogicTree` object

et_ids(eri)[source]¶

Parameters:	eri – effective realization index
Returns:	array of T group IDs, being T the number of TRTs

classmethod fake(gsimlt=None)[source]¶

Returns:	a fake FullLogicTree instance with the given gsim logic tree object; if None, builds automatically a fake gsim logic tree

get_eri_by_ltp()[source]¶

Returns:	a dictionary sm_lt_path -> effective realization index

get_et_id(trt, eri)[source]¶

Returns:	et_id

get_gsims_by_trt()[source]¶

Returns:	a dictionary trt -> sorted gsims

get_num_potential_paths()[source]¶

Returns:	the number of potential realizations

get_num_rlzs(sm_rlz=None)[source]¶

Parameters:	sm_rlz – a Realization instance (or None)
Returns:	the number of realizations per source model (or all)

get_realizations()[source]¶

Returns:	the complete list of LtRealizations

get_rlzs_by_eri()[source]¶

Returns:	a dict eri -> rlzs

get_rlzs_by_grp()[source]¶

Returns:	a dictionary et_id -> [rlzis, …]

get_rlzs_by_gsim(et_id)[source]¶

Returns:	a dictionary gsim -> array of rlz indices

get_rlzs_by_gsim_grp()[source]¶

Returns:	a dictionary et_id -> gsim -> rlzs

get_rlzs_by_gsim_list(list_of_et_ids)[source]¶

Returns:	a list of dictionaries rlzs_by_gsim, one for each grp_id

get_sm_by_grp()[source]¶

Returns:	a dictionary et_id -> sm_id

get_trti_eri(et_id)[source]¶

Returns:	(trti, eri)

gsim_by_trt(rlz)[source]¶

Returns:	a dictionary trt->gsim for the given realization

init()[source]¶

num_samples¶

Returns:	the source_model_lt `num_samples` parameter

rlzs¶

Returns:	an array of realizations

sampling_method¶

Returns:	the source_model_lt `sampling_method` parameter

seed¶

Returns:	the source_model_lt seed

trt_by_et¶

Returns:	a list of TRTs, one for each et_id

class openquake.commonlib.logictree.GsimLogicTree(fname, tectonic_region_types=['*'], ltnode=None)[source]¶

Bases: object

A GsimLogicTree instance is an iterable yielding Realization tuples with attributes value, weight and lt_path, where value is a dictionary {trt: gsim}, weight is a number in the interval 0..1 and lt_path is a tuple with the branch ids of the given realization.

Parameters:	fname (str) – full path of the gsim_logic_tree file tectonic_region_types – a sequence of distinct tectonic region types ltnode – usually None, but it can also be a `openquake.hazardlib.nrml.Node` object describing the GSIM logic tree XML file, to avoid reparsing it

check_imts(imts)[source]¶: Make sure the IMTs are recognized by all GSIMs in the logic tree

collapse(branchset_ids)[source]¶

Collapse the GsimLogicTree by using AgvGMPE instances if needed

Parameters:	branchset_ids – branchset ids to collapse
Returns:	a collapse GsimLogicTree instance

classmethod from_(gsim)[source]¶: Generate a trivial GsimLogicTree from a single GSIM instance.

get_gsims(trt)[source]¶

Parameters:	trt – tectonic region type
Returns:	sorted list of available GSIMs for that trt

get_num_branches()[source]¶: Return the number of effective branches for tectonic region type, as a dictionary.

get_num_paths()[source]¶: Return the effective number of paths in the tree.

reduce(trts)[source]¶

Reduce the GsimLogicTree.

Parameters:	trts – a subset of tectonic region types
Returns:	a reduced GsimLogicTree instance

req_site_params¶

sample(n, seed, sampling_method)[source]¶

Parameters:	n – number of samples seed – random seed sampling_method – by default ‘early_weights’
Returns:	n Realization objects

class openquake.commonlib.logictree.ImtWeight(branch, fname)[source]¶

Bases: object

A composite weight by IMTs extracted from the gsim_logic_tree_file

is_one()[source]¶: Check that all the inner weights are 1 up to the precision

class openquake.commonlib.logictree.Info(smpaths, applytosources)¶

Bases: tuple

applytosources¶: Alias for field number 1

smpaths¶: Alias for field number 0

exception openquake.commonlib.logictree.InvalidLogicTree[source]¶: Bases: Exception

class openquake.commonlib.logictree.LtRealization(ordinal, sm_lt_path, gsim_rlz, weight)[source]¶

Bases: object

Composite realization build on top of a source model realization and a GSIM realization.

gsim_lt_path¶

class openquake.commonlib.logictree.Realization(value, weight, ordinal, lt_path, samples=1)[source]¶

Bases: object

Generic Realization object with attributes value, weight, ordinal, lt_path, samples.

name¶: Compact representation for the names

pid¶

class openquake.commonlib.logictree.SourceModelLogicTree(filename, seed=0, num_samples=0, sampling_method='early_weights')[source]¶

Bases: object

Source model logic tree parser.

Parameters:	filename – Full pathname of logic tree file
Raises:	LogicTreeError – If logic tree file has a logic error, which can not be prevented by xml schema rules (like referencing sources with missing id).

FILTERS = ('applyToTectonicRegionType', 'applyToSources', 'applyToSourceType')¶

apply_branchset(apply_to_branches, lineno, branchset)[source]¶

See superclass’ method for description and signature specification.

Parses branchset node’s attribute @applyToBranches to apply following branchests to preceding branches selectively. Branching level can have more than one branchset exactly for this: different branchsets can apply to different open ends.

Checks that branchset tries to be applied only to branches on previous branching level which do not have a child branchset yet.

bset_values(sm_rlz)[source]¶

Parameters:	sm_rlz – an effective realization
Returns:	a list of B - 1 pairs (branchset, value)

collapse(branchset_ids)[source]¶: Set the attribute .collapsed on the given branchsets

collect_source_model_data(branch_id, source_model)[source]¶: Parse source model file and collect information about source ids, source types and tectonic region types available in it. That information is used then for validate_filters() and validate_uncertainty_value().

classmethod fake()[source]¶

Returns:	a fake SourceModelLogicTree with a single branch

on_each_source¶: True if there is an applyToSources for each source.

parse_branches(branchset_node, branchset)[source]¶

Create and attach branches at branchset_node to branchset.

Parameters:	branchset_node – Same as for `parse_branchset()`. branchset – An instance of `BranchSet`.

Checks that each branch has valid value, unique id and that all branches have total weight of 1.0.

Returns:	`None`, all branches are attached to provided branchset.

parse_branchset(branchset_node, depth)[source]¶

Parameters:	node (branchset) – `etree.Element` object with tag “logicTreeBranchSet”. depth – The sequential number of this branching level, based on 0.

Enumerates children branchsets and call parse_branchset(), validate_branchset(), parse_branches() and finally apply_branchset() for each.

Keeps track of “open ends” – the set of branches that don’t have any child branchset on this step of execution. After processing of every branchset only those branches that are listed in it can have child branchsets (if there is one on the next level).

parse_filters(branchset_node, uncertainty_type, filters)[source]¶

See superclass’ method for description and signature specification.

Converts “applyToSources” filter value by just splitting it to a list.

parse_tree(tree_node)[source]¶: Parse the whole tree and point root_branchset attribute to the tree’s root.

validate_branchset(branchset_node, depth, branchset)[source]¶

See superclass’ method for description and signature specification.

Checks that the following conditions are met:

First branching level must contain exactly one branchset, which must be of type “sourceModel”.
All other branchsets must not be of type “sourceModel” or “gmpeModel”.

validate_filters(branchset_node, uncertainty_type, filters)[source]¶

See superclass’ method for description and signature specification.

Checks that the following conditions are met:

“sourceModel” uncertainties can not have filters.
Absolute uncertainties must have only one filter – “applyToSources”, with only one source id.
All other uncertainty types can have either no or one filter.
Filter “applyToSources” must mention only source ids that exist in source models.
Filter “applyToTectonicRegionType” must mention only tectonic region types that exist in source models.
Filter “applyToSourceType” must mention only source types that exist in source models.

openquake.commonlib.logictree.capitalize(words)[source]¶: Capitalize words separated by spaces.

openquake.commonlib.logictree.collect_info(smlt)[source]¶

Given a path to a source model logic tree, collect all of the path names to the source models it contains and build:

a dictionary source model branch ID -> paths
a dictionary source model branch ID -> source IDs in applyToSources

Parameters:	smlt – source model logic tree file
Returns:	an Info namedtupled containing the two dictionaries

openquake.commonlib.logictree.get_effective_rlzs[source]¶: Group together realizations with the same path and yield the first representative of each group.

openquake.commonlib.logictree.get_field(data, field, default)[source]¶

Parameters:	data – a record with a field field, possibily missing

openquake.commonlib.logictree.keyno(branch_id, no, fname='', chars='0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ')[source]¶

Parameters:	branch_id – a branch ID string no – number of the branch in the branchset (starting from 0)
Returns:	a 1-char string for the branch_id based on the branch number

openquake.commonlib.logictree.read_source_groups(fname)[source]¶

Parameters:	fname – a path to a source model XML file
Returns:	a list of SourceGroup objects containing source nodes

openquake.commonlib.logictree.shorten(path, shortener)[source]¶

Path:	sequence of strings
Shortener:	dictionary longstring -> shortstring
Returns:	shortened version of the path

openquake.commonlib.logictree.unique(objects, key=None)[source]¶: Raise a ValueError if there is a duplicated object, otherwise returns the objects as they are.

logs module¶

Set up some system-wide loggers

class openquake.commonlib.logs.LogDatabaseHandler(job_id)[source]¶

Bases: logging.Handler

Log stream handler

emit(record)[source]¶

class openquake.commonlib.logs.LogFileHandler(job_id, log_file)[source]¶

Bases: logging.FileHandler

Log file handler

emit(record)[source]¶

class openquake.commonlib.logs.LogStreamHandler(job_id)[source]¶

Bases: logging.StreamHandler

Log stream handler

emit(record)[source]¶

openquake.commonlib.logs.dbcmd(action, *args)[source]¶

A dispatcher to the database server.

Parameters:	action (string) – database action to perform args (tuple) – arguments

openquake.commonlib.logs.handle(job_id, log_level='info', log_file=None)[source]¶

Context manager adding and removing log handlers.

Parameters:	job_id – ID of the current job log_level – one of debug, info, warn, error, critical log_file – log file path (if None, logs on stdout only)

openquake.commonlib.logs.init(calc_id='nojob', level=20)[source]¶

initialize the root logger (if not already initialized)
set the format of the root handlers (if any)
return a new calculation ID candidate if calc_id is ‘job’ or ‘nojob’ (with ‘nojob’ the calculation ID is not stored in the database)

openquake.commonlib.logs.touch_log_file(log_file)[source]¶: If a log file destination is specified, attempt to open the file in ‘append’ mode (‘a’). If the specified file is not writable, an IOError will be raised.

oqvalidation module¶

Full list of configuration parameters¶

Engine Version: 3.11.4

Some parameters have a default that it is used when the parameter is not specified in the job.ini file. Some other parameters have no default, which means that not specifying them will raise an error when running a calculation for which they are required.

aggregate_by:: Used to compute aggregate losses and aggregate loss curves in risk calculations. Takes in input one or more exposure tags. Example: aggregate_by = region, taxonomy. Default: empty list
amplification_method:: Used in classical PSHA calculations to amplify the hazard curves with the convolution or kernel method. Example: amplification_method = convolution. Default: None
area_source_discretization:: Discretization parameters (in km) for area sources. Example: area_source_discretization = 10. Default: 10
ash_wet_amplification_factor:: Used in volcanic risk calculations. Example: ash_wet_amplification_factor=1.0. Default: 1.0
asset_correlation:: Used in risk calculations to take into account asset correlation. Accepts only the values 1 (full correlation) and 0 (no correlation). Example: asset_correlation=1. Default: 0
asset_hazard_distance:: In km, used in risk calculations to print a warning when there are assets too distant from the hazard sites. Example: asset_hazard_distance = 5. Default: 15
asset_life_expectancy:: Used in the classical_bcr calculator. Example: asset_life_expectancy = 50. Default: no default
assets_per_site_limit:: INTERNAL
avg_losses:: Used in risk calculations to compute average losses. Example: avg_losses=false. Default: True
base_path:: INTERNAL
cachedir:: INTERNAL
calculation_mode:: One of classical, disaggregation, event_based, scenario, scenario_risk, scenario_damage, event_based_risk, classical_risk, classical_bcr. Example: calculation_mode=classical Default: no default
collapse_gsim_logic_tree:: INTERNAL
collapse_level:: INTERNAL
compare_with_classical:: Used in event based calculation to perform also a classical calculation, so that the hazard curves can be compared. Example: compare_with_classical = true. Default: False
complex_fault_mesh_spacing:: In km, used to discretize complex faults. Example: complex_fault_mesh_spacing = 15. Default: 5
concurrent_tasks:: A hint to the engine for the number of tasks to generate. Do not set it unless you know what you are doing. Example: concurrent_tasks = 100. Default: twice the number of cores
conditional_loss_poes:: Used in classical_risk calculations to compute loss curves. Example: conditional_loss_poes = 0.01 0.02. Default: empty list
float_dmg_dist:: Flag used in scenario_damage calculations to specify that the damage distributions should be stored as floating point numbers (float32) and not as integers (uint32). Example: float_dmg_dist = true. Default: False
continuous_fragility_discretization:: Used when discretizing continuuos fragility functions. Example: continuous_fragility_discretization = 10. Default: 20
coordinate_bin_width:: Used in disaggregation calculations. Example: coordinate_bin_width = 1.0. Default: no default
cross_correlation:: Used in ShakeMap calculations. Valid choices are “yes”, “no” “full”, same as for spatial_correlation. Example: cross_correlation = no. Default: “yes”
description:: A string describing the calculation. Example: description = Test calculation. Default: no default
disagg_by_src:: Flag used to enable disaggregation by source when possible. Example: disagg_by_src = true. Default: False
disagg_outputs:: Used in disaggregation calculations to restrict the number of exported outputs. Example: disagg_outputs = Mag_Dist Default: list of all possible outputs
discard_assets:: Flag used in risk calculations to discard assets from the exposure. Example: discard_assets = true. Default: False
discard_trts:: Used to discard tectonic region types that do not contribute to the hazard. Example: discard_trts = Volcanic. Default: empty list
distance_bin_width:: In km, used in disaggregation calculations to specify the distance bins. Example: distance_bin_width = 20. Default: no default
ebrisk_maxsize:: INTERNAL
export_dir:: Set the export directory. Example: export_dir = /tmp. Default: the current directory, “.”
exports:: Specify what kind of outputs to export by default. Example: exports = csv, rst. Default: empty list
ground_motion_correlation_model:: Enable ground motion correlation. Example: ground_motion_correlation_model = JB2009. Default: None
ground_motion_correlation_params:: To be used together with ground_motion_correlation_model. Example: ground_motion_correlation_params = {“vs30_clustering”: False}. Default: empty dictionary
ground_motion_fields:: Flag to turn on/off the calculation of ground motion fields. Example: ground_motion_fields = false. Default: True
gsim:: Used to specify a GSIM in scenario or event based calculations. Example: gsim = BooreAtkinson2008. Default: “[FromFile]”
hazard_calculation_id:: Used to specify a previous calculation from which the hazard is read. Example: hazard_calculation_id = 42. Default: None
hazard_curves_from_gmfs:: Used in scenario/event based calculations. If set, generates hazard curves from the ground motion fields. Example: hazard_curves_from_gmfs = true. Default: False
hazard_maps:: Set it to true to export the hazard maps. Example: hazard_maps = true. Default: False
ignore_covs:: Used in risk calculations to set all the coefficients of variation of the vulnerability functions to zero. Example ignore_covs = true Default: False
ignore_missing_costs:: Accepts exposures with missing costs (by discarding such assets). Example: ignore_missing_costs = nonstructural, business_interruption. Default: False
iml_disagg:: Used in disaggregation calculations to specify an intensity measure type and level. Example: iml_disagg = {‘PGA’: 0.02}. Default: no default
individual_curves:: When set, store the individual hazard curves and/or individual risk curves for each realization. Example: individual_curves = true. Default: False
inputs:: INTERNAL. Dictionary with the input files paths.
intensity_measure_types:: List of intensity measure types in an event based calculation. Example: intensity_measure_types = PGA SA(0.1). Default: empty list
intensity_measure_types_and_levels:: List of intensity measure types and levels in a classical calculation. Example: intensity_measure_types_and_levels={“PGA”: logscale(0.1, 1, 20)}. Default: empty dictionary
interest_rate:: Used in classical_bcr calculations. Example: interest_rate = 0.05. Default: no default
investigation_time:: Hazard investigation time in years, used in classical and event based calculations. Example: investigation_time = 50. Default: no default
lrem_steps_per_interval:: Used in the vulnerability functions. Example: lrem_steps_per_interval = 1. Default: 0
mag_bin_width:: Width of the magnitude bin used in disaggregation calculations. Example: mag_bin_width = 0.5. Default: no default
master_seed:: Seed used to control the generation of the epsilons, relevant for risk calculations with vulnerability functions with nonzero coefficients of variation. Example: master_seed = 1234. Default: 0
max:: Compute the maximum across realizations. Akin to mean and quantiles. Example: max = true. Default: False
max_data_transfer:: INTERNAL. Restrict the maximum data transfer in disaggregation calculations.
max_potential_gmfs:: Restrict the product num_sites * num_events. Example: max_potential_gmfs = 1E9. Default: 2E11
max_potential_paths:: Restrict the maximum number of realizations. Example: max_potential_paths = 200. Default: 100
max_sites_disagg:: Maximum number of sites for which to store rupture information. In disaggregation calculations with many sites you may be forced to raise max_sites_disagg, that must be greater or equal to the number of sites. Example: max_sites_disagg = 100 Default: 10
max_sites_per_gmf:: Restrict the maximum number of sites in event based calculation with GMFs. Example: max_sites_per_gmf = 100_000. Default: 65536
max_sites_per_tile:: INTERNAL
max_weight:: INTERNAL
maximum_distance:: Integration distance. Can be give as a scalar, as a dictionary TRT -> scalar or as dictionary TRT -> [(mag, dist), …] Example: maximum_distance = 200. Default: no default
mean:: Flag to enable/disable the calculation of mean curves. Example: mean = false. Default: True
min_weight:: INTERNAL
minimum_asset_loss:: Used in risk calculations. If set, losses smaller than the minimum_asset_loss are consider zeros. Example: minimum_asset_loss = {“structural”: 1000}. Default: empty dictionary
minimum_intensity:: If set, ground motion values below the minimum_intensity are considered zeros. Example: minimum_intensity = {‘PGA’: .01}. Default: empty dictionary
minimum_magnitude:: If set, ruptures below the minimum_magnitude are discarded. Example: minimum_magnitude = 5.0. Default: 0
modal_damage_state:: Used in scenario_damage calculations to export only the damage state with the highest probability. Example: modal_damage_state = true. Default: false
num_epsilon_bins:: Number of epsilon bins in disaggregation calculations. Example: num_epsilon_bins = 3. Default: no default
num_rlzs_disagg:: Used in disaggregation calculation to specify how many outputs will be generated. Example: num_rlzs_disagg=1. Default: None
number_of_ground_motion_fields:: Used in scenario calculations to specify how many random ground motion fields to generate. Example: number_of_ground_motion_fields = 100. Default: no default
number_of_logic_tree_samples:: Used to specify the number of realizations to generate when using logic tree sampling. If zero, full enumeration is performed. Example: number_of_logic_tree_samples = 0. Default: no default
poes:: Probabilities of Exceedance used to specify the hazard maps or hazard spectra to compute. Example: poes = 0.01 0.02. Default: empty list
poes_disagg:: Alias for poes.
pointsource_distance:: Used in classical calculations to collapse the point sources. Can also be used in conjunction with ps_grid_spacing. Example: pointsource_distance = 50. Default: empty dictionary
ps_grid_spacing:: Used in classical calculations to grid the point sources. Requires the pointsource_distance to be set too. Example: ps_grid_spacing = 50. Default: no default
quantiles:: List of probabilities used to compute the quantiles across realizations. Example: quantiles = 9.15 0.50 0.85 Default: empty list
random_seed:: Seed used in the sampling of the logic tree. Example: random_seed = 1234. Default: 42
reference_backarc:: Used when there is no site model to specify a global backarc parameter, used in some GMPEs. Can be True or False Example: reference_backarc = true. Default: False
reference_depth_to_1pt0km_per_sec:: Used when there is no site model to specify a global z1pt0 parameter, used in some GMPEs. Example: reference_depth_to_1pt0km_per_sec = 100. Default: no default
reference_depth_to_2pt5km_per_sec:: Used when there is no site model to specify a global z2pt5 parameter, used in some GMPEs. Example: reference_depth_to_2pt5km_per_sec = 5. Default: no default
reference_siteclass:: Used when there is no site model to specify a global site class. The siteclass is a one-character letter used in some GMPEs, like the McVerry (2006), and has values “A”, “B”, “C” or “D”. Example: reference_siteclass = “A”. Default: “D”
reference_vs30_type:: Used when there is no site model to specify a global vs30 type. The choices are “inferred” or “measured” Example: *reference_vs30_type = inferred”. Default: “measured”
reference_vs30_value:: Used when there is no site model to specify a global vs30 value. Example: reference_vs30_value = 760. Default: no default
region:: A list of lon/lat pairs used to specify a region of interest Example: region = 10.0 43.0, 12.0 43.0, 12.0 46.0, 10.0 46.0 Default: None
region_grid_spacing:: Used together with the region option to generate the hazard sites. Example: region_grid_spacing = 10. Default: None
return_periods:: Used in the computation of the loss curves. Example: return_periods = 200 500 1000. Default: empty list.
risk_imtls:: INTERNAL. Automatically set by the engine.
risk_investigation_time:: Used in risk calculations. If not specified, the (hazard) investigation_time is used instead. Example: risk_investigation_time = 50. Default: None
rlz_index:: Used in disaggregation calculations to specify the realization from which to start the disaggregation. Example: rlz_index = 0. Default: None
rupture_mesh_spacing:: Set the discretization parameter (in km) for rupture geometries. Example: rupture_mesh_spacing = 2.0. Default: 5.0
ruptures_per_block:: INTERNAL
sampling_method:: One of early_weights, late_weights, early_latin, late_latin) Example: sampling_method = early_latin. Default: ‘early_weights’
save_disk_space:: INTERNAL
sec_peril_params:: INTERNAL
secondary_perils:: INTERNAL
secondary_simulations:: INTERNAL
sensitivity_analysis:: Dictionary describing a sensitivity analysis. Example: sensitivity_analysis = {‘maximum_distance’: [200, 300]}. Default: empty dictionary
ses_per_logic_tree_path:: Set the number of stochastic event sets per logic tree realization in event based calculations. Example: ses_per_logic_tree_path = 100. Default: 1
ses_seed:: Seed governing the generation of the ground motion field. Example: ses_seed = 123. Default: 42
shakemap_id:: Used in ShakeMap calculations to download a ShakeMap from the USGS site Example: shakemap_id = usp000fjta. Default: no default
shift_hypo:: Used in classical calculations to shift the rupture hypocenter. Example: shift_hypo = true. Default: false
site_effects:: Flag used in ShakeMap calculations to turn out GMF amplification Example: site_effects = true. Default: False
sites:: Used to specify a list of sites. Example: sites = 10.1 45, 10.2 45.
sites_slice:: INTERNAL
soil_intensities:: Used in classical calculations with amplification_method = convolution
source_id:: Used for debugging purposes. When given, restricts the source model to the given source IDs. Example: source_id = src001 src002. Default: empty list
spatial_correlation:: Used in the ShakeMap calculator. The choics are “yes”, “no” and “full”. Example: spatial_correlation = full. Default: “yes”
specific_assets:: INTERNAL
split_sources:: INTERNAL
std:: Compute the standard deviation across realizations. Akin to mean and max. Example: std = true. Default: False
steps_per_interval:: Used in the fragility functions when building the intensity levels Example: steps_per_interval = 4. Default: 1
time_event:: Used in scenario_risk calculations when the occupancy depend on the time. Valid choices are “day”, “night”, “transit”. Example: time_event = day. Default: None
truncation_level:: Truncation level used in the GMPEs. Example: truncation_level = 0 to compute median GMFs. Default: no default
uniform_hazard_spectra:: Flag used to generated uniform hazard specta for the given poes Example: uniform_hazard_spectra = true. Default: False
vs30_tolerance:: Used when amplification_method = convolution. Example: vs30_tolerance = 20. Default: 0
width_of_mfd_bin:: Used to specify the width of the Magnitude Frequency Distribution. Example: width_of_mfd_bin = 0.2. Default: None

class openquake.commonlib.oqvalidation.OqParam(**names_vals)[source]¶

Bases: openquake.hazardlib.valid.ParamSet

KNOWN_INPUTS = {'nonstructural_fragility', 'insurance', 'nonstructural_vulnerability', 'nonstructural_consequence', 'consequence', 'contents_consequence', 'amplification', 'reqv', 'shakemap', 'business_interruption_fragility', 'sites', 'multi_peril', 'gmfs', 'gsim_logic_tree', 'business_interruption_consequence', 'structural_consequence', 'hazard_curves', 'contents_fragility', 'business_interruption_vulnerability', 'occupants_vulnerability', 'fragility', 'structural_vulnerability_retrofitted', 'source_model_logic_tree', 'taxonomy_mapping', 'contents_vulnerability', 'structural_vulnerability', 'structural_fragility', 'input_zip', 'rupture_model', 'site_model', 'source_model', 'job_ini', 'exposure'}¶

aggregate_by¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

all_cost_types¶: Return the cost types of the computation (including occupants if it is there) in order.

all_imts()[source]¶

Returns:	gmv_0, … gmv_M, sec_imt…

amplification_method¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

area_source_discretization¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

ash_wet_amplification_factor¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

asset_correlation¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

asset_hazard_distance¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

asset_life_expectancy¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

assets_per_site_limit¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

avg_losses¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

base_path¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

cachedir¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

calculation_mode¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

check_gsims(gsims)[source]¶

Parameters:	gsims – a sequence of GSIM instances

check_missing(param, action)[source]¶: Make sure the given parameter is missing in the job.ini file

check_source_model()[source]¶

check_uniform_hazard_spectra()[source]¶

collapse_gsim_logic_tree¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

collapse_level¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

compare_with_classical¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

complex_fault_mesh_spacing¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

concurrent_tasks¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

conditional_loss_poes¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

continuous_fragility_discretization¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

coordinate_bin_width¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

correl_model¶: Return a correlation object. See openquake.hazardlib.correlation for more info.

cross_correlation¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

description¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

disagg_by_src¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

disagg_outputs¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

discard_assets¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

discard_trts¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

distance_bin_width¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

classmethod docs()[source]¶

Returns:	a dictionary parameter name -> parameter documentation

ebrisk_maxsize¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

export_dir¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

exports¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

float_dmg_dist¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

get_kinds(kind, R)[source]¶: Yield ‘rlz-000’, ‘rlz-001’, …’, ‘mean’, ‘quantile-0.1’, …

get_primary_imtls()[source]¶

Returns:	IMTs and levels which are not secondary

get_reqv()[source]¶

Returns:	an instance of class:RjbEquivalent if reqv_hdf5 is set

get_sec_imts()[source]¶

Returns:	a list of secondary outputs

get_sec_perils()[source]¶

Returns:	a list of secondary perils

gmf_data_dt()[source]¶

Returns:	a composite data type for the GMFs

ground_motion_correlation_model¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

ground_motion_correlation_params¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

ground_motion_fields¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

gsim¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

hazard_calculation_id¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

hazard_curves_from_gmfs¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

hazard_imtls = {}¶

hazard_maps¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

hazard_precomputed()[source]¶

Returns:	True if the hazard is precomputed

hazard_stats()[source]¶: Return a dictionary stat_name -> stat_func

hmap_dt()[source]¶

Returns:	a composite dtype (imt, poe)

ignore_covs¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

ignore_missing_costs¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

iml_disagg¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

imt_dt(dtype=<class 'numpy.float64'>)[source]¶

Returns:	a numpy dtype {imt: float}

imt_periods()[source]¶

Returns:	the IMTs with a period, as objects

imtls¶: Returns a DictArray with the risk intensity measure types and levels, if given, or the hazard ones.

individual_curves¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

input_dir¶

Returns:	absolute path to where the job.ini is

inputs¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

intensity_measure_types¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

intensity_measure_types_and_levels¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

interest_rate¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

investigation_time¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

is_event_based()[source]¶: The calculation mode is event_based, event_based_risk or ebrisk

is_ucerf()[source]¶

Returns:	True for UCERF calculations, False otherwise

is_valid_aggregate_by()[source]¶: At the moment only aggregate_by=id or aggregate_by=site_id are accepted

is_valid_complex_fault_mesh_spacing()[source]¶: The complex_fault_mesh_spacing parameter can be None only if rupture_mesh_spacing is set. In that case it is identified with it.

is_valid_export_dir()[source]¶: export_dir={export_dir} must refer to a directory, and the user must have the permission to write on it.

is_valid_geometry()[source]¶: It is possible to infer the geometry only if exactly one of sites, sites_csv, hazard_curves_csv, region is set. You did set more than one, or nothing.

is_valid_intensity_measure_levels()[source]¶: In order to compute hazard curves, intensity_measure_types_and_levels must be set or extracted from the risk models.

is_valid_intensity_measure_types()[source]¶: If the IMTs and levels are extracted from the risk models, they must not be set directly. Moreover, if intensity_measure_types_and_levels is set directly, intensity_measure_types must not be set.

is_valid_maximum_distance()[source]¶: Invalid maximum_distance={maximum_distance}: {error}

is_valid_poes()[source]¶: When computing hazard maps and/or uniform hazard spectra, the poes list must be non-empty.

is_valid_shakemap()[source]¶: hazard_calculation_id must be set if shakemap_id is set

is_valid_soil_intensities()[source]¶: soil_intensities can be set only if amplification_method=convolution

is_valid_specific_assets()[source]¶: Read the special assets from the parameters specific_assets or specific_assets_csv, if present. You cannot have both. The concept is meaninful only for risk calculators.

is_valid_truncation_level()[source]¶: In presence of a correlation model the truncation level must be nonzero

is_valid_truncation_level_disaggregation()[source]¶: Truncation level must be set for disaggregation calculations

job_type¶: ‘hazard’ or ‘risk’

levels_per_imt()[source]¶

Returns:	the number of levels per IMT (a.ka. L1)

loss_dt(dtype=<class 'numpy.float32'>)[source]¶

Returns:	a composite dtype based on the loss types including occupants

loss_dt_list(dtype=<class 'numpy.float32'>)[source]¶

Returns:	a data type list [(loss_name, dtype), …]

loss_maps_dt(dtype=<class 'numpy.float32'>)[source]¶: Return a composite data type for loss maps

loss_names¶: Loss types plus insured types, if any

lrem_steps_per_interval¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

lti¶: Dictionary extended_loss_type -> extended_loss_type index

mag_bin_width¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

master_seed¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

max¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

max_data_transfer¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

max_potential_gmfs¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

max_potential_paths¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

max_sites_disagg¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

max_sites_per_gmf¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

max_sites_per_tile¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

max_weight¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

maximum_distance¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

mean¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

mean_hazard_curves¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

min_iml¶

Returns:	a dictionary of intensities, one per IMT

min_weight¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

minimum_asset_loss¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

minimum_intensity¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

minimum_magnitude¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

modal_damage_state¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

no_imls()[source]¶: Return True if there are no intensity measure levels

num_epsilon_bins¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

num_rlzs_disagg¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

number_of_ground_motion_fields¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

number_of_logic_tree_samples¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

poes¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

poes_disagg¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

pointsource_distance¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

ps_grid_spacing¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

quantile_hazard_curves¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

quantiles¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

random_seed¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

reference_backarc¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

reference_depth_to_1pt0km_per_sec¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

reference_depth_to_2pt5km_per_sec¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

reference_siteclass¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

reference_vs30_type¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

reference_vs30_value¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

region¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

region_grid_spacing¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

return_periods¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

risk_files¶

risk_imtls¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

risk_investigation_time¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

rlz_index¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

rupture_mesh_spacing¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

ruptures_per_block¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

sampling_method¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

save_disk_space¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

sec_peril_params¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

secondary_perils¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

secondary_simulations¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

sensitivity_analysis¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

ses_per_logic_tree_path¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

ses_ratio¶

The ratio

risk_investigation_time / investigation_time / ses_per_logic_tree_path

ses_seed¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

set_risk_imts(risklist)[source]¶

Parameters:	risklist – a list of risk functions with attributes .id, .loss_type, .kind

Set the attribute risk_imtls.

shakemap_id¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

shift_hypo¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

site_effects¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

siteparam = {'vs30measured': 'reference_vs30_type', 'vs30': 'reference_vs30_value', 'z1pt0': 'reference_depth_to_1pt0km_per_sec', 'z2pt5': 'reference_depth_to_2pt5km_per_sec', 'siteclass': 'reference_siteclass', 'backarc': 'reference_backarc'}¶

sites¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

sites_slice¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

soil_intensities¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

source_id¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

spatial_correlation¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

specific_assets¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

split_sources¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

std¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

steps_per_interval¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

time_event¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

truncation_level¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

tses¶: Return the total time as investigation_time * ses_per_logic_tree_path * (number_of_logic_tree_samples or 1)

uhs_dt()[source]¶

Returns:	a composity dtype (poe, imt)

uniform_hazard_spectra¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

vs30_tolerance¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

width_of_mfd_bin¶

A descriptor for validated parameters with a default, to be used as attributes in ParamSet objects.

Parameters:	validator – the validator default – the default value

openquake.commonlib.oqvalidation.check_same_levels(imtls)[source]¶

Parameters:	imtls – a dictionary (or dict-like) imt -> imls
Returns:	the periods and the levels
Raises:	a ValueError if the levels are not the same across all IMTs

readinput module¶

exception openquake.commonlib.readinput.DuplicatedPoint[source]¶

Bases: Exception

Raised when reading a CSV file with duplicated (lon, lat) pairs

class openquake.commonlib.readinput.Site(sid, lon, lat)¶

Bases: tuple

lat¶: Alias for field number 2

lon¶: Alias for field number 1

sid¶: Alias for field number 0

openquake.commonlib.readinput.collect_files(dirpath, cond=<function <lambda>>)[source]¶

Recursively collect the files contained inside dirpath.

Parameters:	dirpath – path to a readable directory cond – condition on the path to collect the file

openquake.commonlib.readinput.extract_from_zip(path, ext='.ini')[source]¶

Given a zip archive and a function to detect the presence of a given filename, unzip the archive into a temporary directory and return the full path of the file. Raise an IOError if the file cannot be found within the archive.

Parameters:	path – pathname of the archive ext – file extension to search for

openquake.commonlib.readinput.get_amplification(oqparam)[source]¶

Returns:	a DataFrame (ampcode, level, PGA, SA() …)

openquake.commonlib.readinput.get_checksum32(oqparam, h5=None)[source]¶

Build an unsigned 32 bit integer from the hazard input files

Parameters:	oqparam – an OqParam instance

openquake.commonlib.readinput.get_composite_source_model(oqparam, h5=None)[source]¶

Parse the XML and build a complete composite source model in memory.

Parameters:	oqparam – an `openquake.commonlib.oqvalidation.OqParam` instance h5 – an open hdf5.File where to store the source info

openquake.commonlib.readinput.get_crmodel(oqparam)[source]¶

Return a openquake.risklib.riskinput.CompositeRiskModel instance

Parameters:	oqparam – an `openquake.commonlib.oqvalidation.OqParam` instance

openquake.commonlib.readinput.get_csv_header(fname, sep=', ')[source]¶

Parameters:	fname – a CSV file sep – the separator (default comma)
Returns:	the first line of fname

openquake.commonlib.readinput.get_exposure(oqparam)[source]¶

Read the full exposure in memory and build a list of openquake.risklib.asset.Asset instances.

Parameters:	oqparam – an `openquake.commonlib.oqvalidation.OqParam` instance
Returns:	an `Exposure` instance or a compatible AssetCollection

openquake.commonlib.readinput.get_full_lt(oqparam)[source]¶

Parameters:	oqparam – an `openquake.commonlib.oqvalidation.OqParam` instance
Returns:	a `openquake.commonlib.logictree.FullLogicTree` instance

openquake.commonlib.readinput.get_gsim_lt(oqparam, trts=('*', ))[source]¶

Parameters:	oqparam – an `openquake.commonlib.oqvalidation.OqParam` instance trts – a sequence of tectonic region types as strings; trts=[‘*’] means that there is no filtering
Returns:	a GsimLogicTree instance obtained by filtering on the provided tectonic region types.

openquake.commonlib.readinput.get_imts(oqparam)[source]¶: Return a sorted list of IMTs as hazardlib objects

openquake.commonlib.readinput.get_input_files(oqparam, hazard=False)[source]¶

Parameters:	oqparam – an OqParam instance hazard – if True, consider only the hazard files
Returns:	input path names in a specific order

openquake.commonlib.readinput.get_mesh(oqparam, h5=None)[source]¶

Extract the mesh of points to compute from the sites, the sites_csv, the region, the site model, the exposure in this order.

Parameters:	oqparam – an `openquake.commonlib.oqvalidation.OqParam` instance

openquake.commonlib.readinput.get_oqparam(job_ini, pkg=None, calculators=None, kw={}, validate=1)[source]¶

Parse a dictionary of parameters from an INI-style config file.

Parameters:

job_ini – Path to configuration file/archive or dictionary of parameters
pkg – Python package where to find the configuration file (optional)
calculators – Sequence of calculator names (optional) used to restrict the valid choices for calculation_mode
kw – Dictionary of strings to override the job parameters
validate – Flag. By default it is true and the parameters are validated

Returns:

An openquake.commonlib.oqvalidation.OqParam instance containing the validate and casted parameters/values parsed from the job.ini file as well as a subdictionary ‘inputs’ containing absolute paths to all of the files referenced in the job.ini, keyed by the parameter name.

openquake.commonlib.readinput.get_params(job_ini, kw={})[source]¶

Parse a .ini file or a .zip archive

Parameters:	job_ini – Configuration file \| zip archive \| URL kw – Optionally override some parameters
Returns:	A dictionary of parameters

openquake.commonlib.readinput.get_pmap_from_csv(oqparam, fnames)[source]¶

Parameters:	oqparam – an `openquake.commonlib.oqvalidation.OqParam` instance fnames – a space-separated list of .csv relative filenames
Returns:	the site mesh and the hazard curves read by the .csv files

openquake.commonlib.readinput.get_rupture(oqparam)[source]¶

Read the rupture_model file and by filter the site collection

Parameters:	oqparam – an `openquake.commonlib.oqvalidation.OqParam` instance
Returns:	an hazardlib rupture

openquake.commonlib.readinput.get_ruptures(fname_csv)[source]¶: Read ruptures in CSV format and return an ArrayWrapper

openquake.commonlib.readinput.get_site_collection(oqparam, h5=None)[source]¶

Returns a SiteCollection instance by looking at the points and the site model defined by the configuration parameters.

Parameters:	oqparam – an `openquake.commonlib.oqvalidation.OqParam` instance

openquake.commonlib.readinput.get_site_model(oqparam)[source]¶

Convert the NRML file into an array of site parameters.

Parameters:	oqparam – an `openquake.commonlib.oqvalidation.OqParam` instance
Returns:	an array with fields lon, lat, vs30, …

openquake.commonlib.readinput.get_sitecol_assetcol(oqparam, haz_sitecol=None, cost_types=())[source]¶

Parameters:	oqparam – calculation parameters haz_sitecol – the hazard site collection cost_types – the expected cost types
Returns:	(site collection, asset collection, discarded)

openquake.commonlib.readinput.get_source_model_lt(oqparam)[source]¶

Parameters:	oqparam – an `openquake.commonlib.oqvalidation.OqParam` instance
Returns:	a `openquake.commonlib.logictree.SourceModelLogicTree` instance

openquake.commonlib.readinput.levels_from(header)[source]¶

openquake.commonlib.readinput.normalize(key, fnames, base_path)[source]¶

openquake.commonlib.readinput.reduce_sm(paths, source_ids)[source]¶

Parameters:	paths – list of source_model.xml files source_ids – dictionary src_id -> array[src_id, code]
Returns:	dictionary with keys good, total, model, path, xmlns

NB: duplicate sources are not removed from the XML

openquake.commonlib.readinput.reduce_source_model(smlt_file, source_ids, remove=True)[source]¶

Extract sources from the composite source model.

Parameters:	smlt_file – path to a source model logic tree file source_ids – dictionary source_id -> records (src_id, code) remove – if True, remove sm.xml files containing no sources
Returns:	the number of sources satisfying the filter vs the total

openquake.commonlib.readinput.save_source_info(csm, h5)[source]¶

openquake.commonlib.readinput.taxonomy_mapping(oqparam, taxonomies)[source]¶

Parameters:	oqparam – OqParam instance taxonomies – array of strings tagcol.taxonomy
Returns:	a dictionary loss_type -> [[(taxonomy, weight), …], …]

openquake.commonlib.readinput.unzip_rename(zpath, name)[source]¶

Parameters:	zpath – full path to a .zip archive name – exposure.xml or ssmLT.xml
Returns:	path to an .xml file with the same name of the archive

source_reader module¶

class openquake.commonlib.source_reader.CompositeSourceModel(full_lt, src_groups)[source]¶

Bases: object

Parameters:	full_lt – a `FullLogicTree` instance src_groups – a list of SourceGroups event_based – a flag True for event based calculations, flag otherwise

count_ruptures()[source]¶: Call src.count_ruptures() on each source. Slow.

get_et_ids()[source]¶

Returns:	an array of et_ids (to be stored as an hdf5.vuint32 array)

get_floating_spinning_factors()[source]¶

Returns:	(floating rupture factor, spinning rupture factor)

get_groups(eri)[source]¶

Parameters:	eri – effective source model realization ID
Returns:	SourceGroups associated to the given eri

get_mags_by_trt()[source]¶

Returns:	a dictionary trt -> magnitudes in the sources as strings

get_sources(atomic=None)[source]¶

Returns:	list of sources in the composite source model

update_source_info(calc_times, nsites=False)[source]¶: Update (eff_ruptures, num_sites, calc_time) inside the source_info

openquake.commonlib.source_reader.et_ids(src)[source]¶

openquake.commonlib.source_reader.get_csm(oq, full_lt, h5=None)[source]¶: Build source models from the logic tree and to store them inside the source_full_lt dataset.

openquake.commonlib.source_reader.read_source_model(fname, converter, monitor)[source]¶

Parameters:	fname – path to a source model XML file converter – SourceConverter monitor – a Monitor instance
Returns:	a SourceModel instance

openquake.commonlib.source_reader.reduce_sources(sources_with_same_id)[source]¶

Parameters:	sources_with_same_id – a list of sources with the same source_id
Returns:	a list of truly unique sources, ordered by et_id

util module¶

openquake.commonlib.util.closest_to_ref(arrays, ref, cutoff=1e-12)[source]¶

Parameters:	arrays – a sequence of arrays ref – the reference array
Returns:	a list of indices ordered by closeness

This function is used to extract the realization closest to the mean in disaggregation. For instance, if there are 2 realizations with indices 0 and 1, the first hazard curve having values

>>> c0 = numpy.array([.99, .97, .5, .1])

and the second hazard curve having values

>>> c1 = numpy.array([.98, .96, .45, .09])

with weights 0.6 and 0.4 and mean

>>> mean = numpy.average([c0, c1], axis=0, weights=[0.6, 0.4])

then calling closest_to_ref will returns the indices 0 and 1 respectively:

>>> closest_to_ref([c0, c1], mean)
[0, 1]

This means that the realization 0 is the closest to the mean, as expected, since it has a larger weight. You can check that it is indeed true by computing the sum of the quadratic deviations:

>>> ((c0 - mean)**2).sum()
0.0004480000000000008
>>> ((c1 - mean)**2).sum()
0.0010079999999999985

If the 2 realizations have equal weights the distance from the mean will be the same. In that case both the realizations will be okay; the one that will be chosen by closest_to_ref depends on the magic of floating point approximation (theoretically identical distances will likely be different as numpy.float64 numbers) or on the magic of Python list.sort.

openquake.commonlib.util.compose_arrays(a1, a2, firstfield='etag')[source]¶: Compose composite arrays by generating an extended datatype containing all the fields. The two arrays must have the same length.

openquake.commonlib.util.get_assets(dstore)[source]¶

Parameters:	dstore – a datastore with keys ‘assetcol’
Returns:	an array of records (id, tag1, …, tagN, lon, lat)

openquake.commonlib.util.log(array, cutoff)[source]¶: Compute the logarithm of an array with a cutoff on the small values

openquake.commonlib.util.max_rel_diff(curve_ref, curve, min_value=0.01)[source]¶

Compute the maximum relative difference between two curves. Only values greather or equal than the min_value are considered.

>>> curve_ref = [0.01, 0.02, 0.03, 0.05, 1.0]
>>> curve = [0.011, 0.021, 0.031, 0.051, 1.0]
>>> round(max_rel_diff(curve_ref, curve), 2)
0.1

openquake.commonlib.util.max_rel_diff_index(curve_ref, curve, min_value=0.01)[source]¶

Compute the maximum relative difference between two sets of curves. Only values greather or equal than the min_value are considered. Return both the maximum difference and its location (array index).

>>> curve_refs = [[0.01, 0.02, 0.03, 0.05], [0.01, 0.02, 0.04, 0.06]]
>>> curves = [[0.011, 0.021, 0.031, 0.051], [0.012, 0.022, 0.032, 0.051]]
>>> max_rel_diff_index(curve_refs, curves)
(0.2, 1)

openquake.commonlib.util.read(calc_id, username=None)[source]¶

Parameters:	calc_id – a calculation ID username – if given, restrict the search to the user’s calculations
Returns:	the associated DataStore instance

openquake.commonlib.util.rmsep(array_ref, array, min_value=0)[source]¶

Root Mean Square Error Percentage for two arrays.

Parameters:	array_ref – reference array array – another array min_value – compare only the elements larger than min_value
Returns:	the relative distance between the arrays

>>> curve_ref = numpy.array([[0.01, 0.02, 0.03, 0.05],
... [0.01, 0.02, 0.04, 0.06]])
>>> curve = numpy.array([[0.011, 0.021, 0.031, 0.051],
... [0.012, 0.022, 0.032, 0.051]])
>>> str(round(rmsep(curve_ref, curve, .01), 5))
'0.11292'

openquake.commonlib.util.shared_dir_on()[source]¶

Returns:	True if a shared_dir has been set in openquake.cfg, else False

writers module¶

class openquake.commonlib.writers.CsvWriter(sep=', ', fmt='%12.8E')[source]¶

Bases: object

Class used in the exporters to save a bunch of CSV files

getsaved()[source]¶: Returns the list of files saved by this CsvWriter

save(data, fname, header=(), comment=None, renamedict=None)[source]¶

Save data on fname.

Parameters:	data – numpy array, list of lists or pandas DataFrame fname – path name header – header to use comment – optional dictionary to be converted in a comment renamedict – a dictionary for renaming the columns

save_block(data, dest)[source]¶: Save data on dest, which is a file open in ‘a’ mode

openquake.commonlib.writers.build_header(dtype)[source]¶

Convert a numpy nested dtype into a list of strings suitable as header of csv file.

>>> imt_dt = numpy.dtype([('PGA', numpy.float32, 3),
...                       ('PGV', numpy.float32, 4)])
>>> build_header(imt_dt)
['PGA:3', 'PGV:4']
>>> gmf_dt = numpy.dtype([('A', imt_dt), ('B', imt_dt),
...                       ('idx', numpy.uint32)])
>>> build_header(gmf_dt)
['A~PGA:3', 'A~PGV:4', 'B~PGA:3', 'B~PGV:4', 'idx']

openquake.commonlib.writers.castable_to_int(s)[source]¶: Return True if the string s can be interpreted as an integer

openquake.commonlib.writers.extract_from(data, fields)[source]¶

Extract data from numpy arrays with nested records.

>>> imt_dt = numpy.dtype([('PGA', float, 3), ('PGV', float, 4)])
>>> a = numpy.array([([1, 2, 3], [4, 5, 6, 7])], imt_dt)
>>> extract_from(a, ['PGA'])
array([[1., 2., 3.]])

>>> gmf_dt = numpy.dtype([('A', imt_dt), ('B', imt_dt),
...                       ('idx', numpy.uint32)])
>>> b = numpy.array([(([1, 2, 3], [4, 5, 6, 7]),
...                  ([1, 2, 4], [3, 5, 6, 7]), 8)], gmf_dt)
>>> extract_from(b, ['idx'])
array([8], dtype=uint32)
>>> extract_from(b, ['B', 'PGV'])
array([[3., 5., 6., 7.]])

openquake.commonlib.writers.parse_header(header)[source]¶

Convert a list of the form [‘fieldname:fieldtype:fieldsize’,…] into a numpy composite dtype. The parser understands headers generated by openquake.commonlib.writers.build_header(). Here is an example:

>>> parse_header(['PGA:float32', 'PGV', 'avg:float32:2'])
(['PGA', 'PGV', 'avg'], dtype([('PGA', '<f4'), ('PGV', '<f4'), ('avg', '<f4', (2,))]))

Params header:	a list of type descriptions
Returns:	column names and the corresponding composite dtype

openquake.commonlib.writers.write_csv(dest, data, sep=', ', fmt='%.6E', header=(), comment=None, renamedict=None)[source]¶

Parameters:	dest – None, file, filename or io.StringIO instance data – array to save sep – separator to use (default comma) fmt – formatting string (default ‘%12.8E’) header – optional list with the names of the columns to display comment – optional comment dictionary

openquake.commonlib package¶

calc module¶

hazard_writers module¶

logictree module¶

logs module¶

oqvalidation module¶

Full list of configuration parameters¶

readinput module¶

source_reader module¶

util module¶

writers module¶

Table Of Contents

Previous topic

Next topic

This Page