B d+9 @sdZddlZddlZddlmZmZddlmZ ddlm Z ddlm Z dZdd Zd d efd d efddejfddefddefddefddefddefddefddeff ZddZdd Zde fd!d"Zd,d#d$Zd-d&d'Zgggdd(d)fd*d+ZdS).z1 Reading HDF5 posterior sample chain HDF5 files. N)ColumnTable)+LALInferenceHDF5PosteriorSamplesDatasetName)LALINFERENCE_PARAM_FIXED)LALINFERENCE_PARAM_OUTPUT) read_samples write_samplesextract_metadatacCs|S)N)xr r a/work/yifan.wang/ringdown/master-ringdown-env/lib/python3.7/site-packages/lalinference/io/hdf5.py _identity sr ZrightascensionraZ declinationdecZ logdistancedistZdistanceZ polarisationpsiZ chirpmassZmcZa_spin1Za1Za_spin2Za2Z tilt_spin1Ztilt1Z tilt_spin2Ztilt2cCs6x0tD](\}}}||jkr||j|||<qWdS)N) _colname_mapcolnamescolumnspop)tableZold_namenew_namefuncr r r _remap_colnames0s rc snifdd}||tdkr6tdtdkr`tddt\}|S)agRecursively search an HDF5 group or file for a dataset by name. Parameters ---------- group : `h5py.File` or `h5py.Group` The file or group to search tablename : str The name of the table to search for Returns ------- table : `h5py.Dataset` The dataset whose name is `tablename` Raises ------ KeyError If the table is not found or if multiple matching tables are found Check that we can find a file by name: >>> import os.path >>> from tempfile import TemporaryDirectory >>> table = Table(np.eye(3), names=['a', 'b', 'c']) >>> with TemporaryDirectory() as dir: ... filename = os.path.join(dir, 'test.hdf5') ... table.write(filename, path='foo/bar', append=True) ... table.write(filename, path='foo/bat', append=True) ... table.write(filename, path='foo/xyzzy/bat', append=True) ... with h5py.File(filename, 'r') as f: ... _find_table(f, 'bar') Check that an exception is raised if the table is not found: >>> with TemporaryDirectory() as dir: ... filename = os.path.join(dir, 'test.hdf5') ... table.write(filename, path='foo/bar', append=True) ... table.write(filename, path='foo/bat', append=True) ... table.write(filename, path='foo/xyzzy/bat', append=True) ... with h5py.File(filename, 'r') as f: ... _find_table(f, 'plugh') Traceback (most recent call last): ... KeyError: 'Table not found: plugh' Check that an exception is raised if multiple tables are found: >>> with TemporaryDirectory() as dir: ... filename = os.path.join(dir, 'test.hdf5') ... table.write(filename, path='foo/bar', append=True) ... table.write(filename, path='foo/bat', append=True) ... table.write(filename, path='foo/xyzzy/bat', append=True) ... with h5py.File(filename, 'r') as f: ... _find_table(f, 'bat') Traceback (most recent call last): ... KeyError: 'Multiple tables called bat exist: foo/bat, foo/xyzzy/bat' cs$|d\}}}|kr ||<dS)N/) rpartition)keyvalue_name)results tablenamer r visitorqsz_find_table..visitorrzTable not found: {0}z%Multiple tables called {0} exist: {1}z, )Z visititemslenKeyErrorformatjoinsortedkeysvalues)groupr!r"rr )r r!r _find_table6s9    r,c Cst|d,}|dk r ||}n t||}t|}WdQRXx0t|jD]\}}|jd ||jd<qNWx|j D]\}}|dks||dks||dks|| drq|||j kr|j t|gt||dtid d d q|| t|gt||dtid q|W|jt||S) a<Read an HDF5 sample chain file. Parameters ---------- filename : str The path of the HDF5 file on the filesystem. path : str, optional The path of the dataset within the HDF5 file. tablename : str, optional The name of table to search for recursively within the HDF5 file. By default, search for 'posterior_samples'. Returns ------- table : `astropy.table.Table` The sample chain as an Astropy table. Test reading a file written using the Python API: >>> import os.path >>> from tempfile import TemporaryDirectory >>> table = Table([ ... Column(np.ones(10), name='foo', meta={'vary': FIXED}), ... Column(np.arange(10), name='bar', meta={'vary': LINEAR}), ... Column(np.arange(10) * np.pi, name='bat', meta={'vary': CIRCULAR}), ... Column(np.arange(10), name='baz', meta={'vary': OUTPUT}) ... ]) >>> with TemporaryDirectory() as dir: ... filename = os.path.join(dir, 'test.hdf5') ... write_samples(table, filename, path='foo/bar/posterior_samples') ... len(read_samples(filename)) 10 Test reading a file that was written using the LAL HDF5 C API: >>> table = read_samples('test.hdf5') >>> table.colnames ['uvw', 'opq', 'lmn', 'ijk', 'def', 'abc', 'rst', 'ghi'] rNzFIELD_{0}_VARYvaryZCLASSVERSIONZTITLEZFIELD_)rmetaT)Zrename_duplicate)h5pyFiler,rread enumeraterr*r0r&items startswithr add_columnrr$FIXEDclearr) filenamepathr!fricolumnrrr r r rs$&  "  rc Ks|}xL|jD]>}d|jkrt|d|ddkrHt|jd<qt|jd<qWx`t|j D]N\}}|jdtkrftj |dd|dd |j |d|j|<||=qfWx0t|jD]\}}|jd|jd |<qW|j|fddi||rt|d r}xj| D]^\}} xR| D]F\} } y| ||j| <Wn(tk rrtd || | YnXq0WqWWdQRXdS) aWrite an HDF5 sample chain file. Parameters ---------- table : `astropy.table.Table` The sample chain as an Astropy table. filename : str The path of the HDF5 file on the filesystem. metadata: dict (optional) Dictionary of (path, value) pairs of metadata attributes to add to the output file kwargs: dict Any keyword arguments for `astropy.table.Table.write`. Check that we catch columns that are supposed to be FIXED but are not: >>> table = Table([ ... Column(np.arange(10), name='foo', meta={'vary': FIXED}) ... ]) >>> write_samples(table, 'bar.hdf5', 'bat/baz') # doctest: +ELLIPSIS Traceback (most recent call last): ... AssertionError: Arrays are not equal Column foo is a fixed column, but its values are not identical ... And now try writing an arbitrary example to a temporary file. >>> import os.path >>> from tempfile import TemporaryDirectory >>> table = Table([ ... Column(np.ones(10), name='foo', meta={'vary': FIXED}), ... Column(np.arange(10), name='bar', meta={'vary': LINEAR}), ... Column(np.arange(10) * np.pi, name='bat', meta={'vary': CIRCULAR}), ... Column(np.arange(10), name='baz', meta={'vary': OUTPUT}) ... ]) >>> with TemporaryDirectory() as dir: ... write_samples( ... table, os.path.join(dir, 'test.hdf5'), path='bat/baz') r.rr#Nz>Column {0} is a fixed column, but its values are not identicalzFIELD_{0}_VARYr&Zhdf5az%Unable to set metadata {0}[{1}] = {2})copyrr*r0npallr8OUTPUTtupler5testingZassert_array_equalr&rr4writer1r2attrsr%) rr:metadatakwargsr>Zcolnamer=hdfZ internal_path attributesrrr r r rs4)    rraisecCs||kri||<x|D]}|||kr|dkrt|||||kr|dkrR|sRqqtd|||||||fq|dkrt|||tr|||||q|||||g|||<q|dkrqtd|q|||||<qWdS)zUpdates the sub-dictionary 'key' of 'metadata' with the values from 'attrs', while enforcing that existing values are equal to those with which the dict is updated. rLversionz3Metadata mismatch on level %r for key %r: %r != %rappendignorezInvalid value for collision: %rN) ValueError isinstancelistrN)rHlevelrGstrict_versions collisionrr r r update_metadatas(   rVFTc Cst|d}d} || } t|| | j|t|| dkrXtdt|| t|| d} d| } || } t|| | j|dd|r|| jd || jd || jd |d krt }d| d |} d| d t } || } t|| | j|dd| SQRXd S)a Extract metadata from HDF5 sample chain file Parameters ---------- filename : str The path of the HDF5 file on the filesystem. metadata : dict Dict into which to place metadata log_noise_evidences : array (optional) Array into which to place log noise evidences (if nest = True) log_max_likelihoods : array (optional) Array into which to place log max likelihoods (if nest = True) nlive : array (optional) Array into which to place number of live points (if nest = True) return_run_identifier : Boolean (optional : default False) Whether to return the run identifier nest : Boolean (optional : default False) Whether to output quantities that only exist for nest runs Returns ------- run_identifier : str The run identifier r-z /lalinferencer#z"Multiple run-identifiers found: %rrz/lalinference/rN)rUZlog_noise_evidenceZlog_max_likelihoodZnumber_live_pointsNrrO) r1r2rVrGr$r)r%rRrNPOSTERIOR_SAMPLES) r:rHZlog_noise_evidencesZlog_max_likelihoodsZnliveZ dset_namenestrTrJZ current_levelr+Zrun_identifierZcurrent_level_posteriorr r r r 3s,r )N)rL)__doc__numpyrAr1Z astropy.tablerrZ lalinferencerrWrr8rrC__all__r exprrr,rrrVr r r r r s0     MI I