openpathsampling.storage.Storage

class openpathsampling.storage.Storage(filename, mode=None, template=None, fallback=None)[source]

Create a netCDF+ storage for OPS Objects

A netCDF4 wrapper to store trajectories based on snapshots of an OpenMM simulation. This allows effective storage of shooting trajectories

Parameters:

filename (string) – filename of the netcdf file to be used or created
mode (string, default: None) – the mode of file creation, one of ‘w’ (write), ‘a’ (append) or None, which will append any existing files.
template (openpathsampling.Snapshot) – a Snapshot instance that contains a reference to a Topology, the number of atoms and used units

__init__(filename, mode=None, template=None, fallback=None)[source]

Create a storage for complex objects in a netCDF file

Parameters:

filename (string) – filename of the netcdf file to be used or created
mode (str) – the mode of file creation, one of ‘w’ (write), ‘a’ (append) or ‘r’ (read-only) None, which will append any existing files (equal to append), is the default.
fallback (openpathsampling.Storage) – the _fallback_ storage to be loaded from if an object is not present in this storage. By default you will not try to resave objects that could be found in the fallback. Note that the fall back does only work if use_uuid is enabled

Notes

A single file can be opened by multiple storages, but only one can be used for writing

Methods

`__init__`(filename[, mode, template, fallback])	Create a storage for complex objects in a netCDF file
`analysis_cache_sizes`()	Cache Sizes for analysis sessions
`cache_image`()	Return an dict containing information about all caches
`check_version`()
`close`()	`close(self)`
`createCompoundType`(datatype, datatype_name)	`createCompoundType(self, datatype, datatype_name)`
`createDimension`(dimname[, size])	`createDimension(self, dimname, size=None)`
`createEnumType`(datatype, datatype_name, ...)	`createEnumType(self, datatype, datatype_name, enum_dict)`
`createGroup`(groupname)	`createGroup(self, groupname)`
`createVLType`(datatype, datatype_name)	`createVLType(self, datatype, datatype_name)`
`createVariable`(varname, datatype[, ...])	`createVariable(self, varname, datatype, dimensions=(), compression=None, zlib=False, complevel=4, shuffle=True, fletcher32=False, contiguous=False, chunksizes=None, szip_coding='nn', szip_pixels_per_block=8, blosc_shuffle=1, endian='native', least_significant_digit=None, significant_digits=None, quantize_mode='BitGroom', fill_value=None, chunk_cache=None)`
`create_dimension`(dim_name[, size])	Initialize a new dimension in the storage.
`create_store`(name, store[, register_attr])	Create a special variable type obj.name that can hold storable objects
`create_type_delegate`(var_type)	Create a variable value delegator for var_type
`create_variable`(var_name, var_type, dimensions)	Create a new variable in the netCDF storage.
`create_variable_delegate`(var_name)	Create a delegate property that wraps the netcdf.Variable and takes care of type conversions
`default_cache_sizes`()	Cache sizes for standard sessions for medium production and analysis.
`delncattr`(name)	`delncattr(self,name,value)`
`filepath`([encoding])	`filepath(self,encoding=None)`
`finalize_stores`()	Run initializations for all added stores.
`find_store`(obj)	Return the default store used for an storable object
`fromcdl`(cdlfilename[, ncfilename, mode, format])	`fromcdl(cdlfilename, ncfilename=None, mode='a',format='NETCDF4')`
`get_value_parameters`(value)	Compute netcdfplus compatible parameters to store a value
`get_var_types`()	List all allowed variable type to be used in create_variable
`get_variables_by_attributes`(**kwargs)	`get_variables_by_attributes(self, kwargs)`**
`getncattr`(name[, encoding])	`getncattr(self,name)`
`has_blosc_filter`()	`has_blosc_filter(self)` returns True if blosc compression filter is available
`has_bzip2_filter`()	`has_bzip2_filter(self)` returns True if bzip2 compression filter is available
`has_szip_filter`()	`has_szip_filter(self)` returns True if szip compression filter is available
`has_zstd_filter`()	`has_zstd_filter(self)` returns True if zstd compression filter is available
`identify_var_type`(instance)	Identify common python and numpy types
`idx`(obj)	Return the index used to store the given object in this storage
`isopen`()	`isopen(self)`
`list_storable_objects`()	Return a list of storable object base classes
`list_stores`()	Return a list of registered stores
`load`(uuid)	Load an object from the storage
`lowmemory_cache_sizes`()	Cache sizes for very low memory
`memtest_cache_sizes`()	Cache Sizes for memtest debugging sessions
`ncattrs`()	`ncattrs(self)`
`no_cache_sizes`()	Set cache sizes to no caching at all.
`production_cache_sizes`()	Cache Sizes for production runs
`register_store`(name, store[, register_attr])	Add a object store to the file
`renameAttribute`(oldname, newname)	`renameAttribute(self, oldname, newname)`
`renameDimension`(oldname, newname)	`renameDimension(self, oldname, newname)`
`renameGroup`(oldname, newname)	`renameGroup(self, oldname, newname)`
`renameVariable`(oldname, newname)	`renameVariable(self, oldname, newname)`
`repr_json`(obj)	Return the JSON representation in the storage if available
`save`(obj[, idx])	Save a storable object into the correct Storage in the netCDF file
`set_always_mask`(value)	`set_always_mask(self, True_or_False)`
`set_auto_chartostring`(value)	`set_auto_chartostring(self, True_or_False)`
`set_auto_mask`(value)	`set_auto_mask(self, True_or_False)`
`set_auto_maskandscale`(value)	`set_auto_maskandscale(self, True_or_False)`
`set_auto_scale`(value)	`set_auto_scale(self, True_or_False)`
`set_caching_mode`([mode])	Set default values for all caches
`set_fill_off`()	`set_fill_off(self)`
`set_fill_on`()	`set_fill_on(self)`
`set_ncstring_attrs`(value)	`set_ncstring_attrs(self, True_or_False)`
`setncattr`(name, value)	`setncattr(self,name,value)`
`setncattr_string`(name, value)	`setncattr_string(self,name,value)`
`setncatts`(attdict)	`setncatts(self,attdict)`
`sync`()	`sync(self)`
`sync_all`()	Convenience function to use `self.cvs` and `self` at once.
`to_uuid_chunks`(x)
`tocdl`([coordvars, data, outfile])	`tocdl(self, coordvars=False, data=False, outfile=None)`
`unlimited_cache_sizes`()	Set cache sizes to no caching at all.
`update_delegates`()	Updates the set of delegates in self.vars
`update_storable_classes`()
`var_type_to_nc_type`(var_type)	Return the compatible netCDF variable type for var_type
`write_meta`()

Attributes

`USE_FEATURE_SNAPSHOTS`
`cmptypes`
`data_model`
`dimensions`
`disk_format`
`enumtypes`
`file_format`
`file_size`
`file_size_str`
`filename`
`groups`
`keepweakref`
`name`	string name of Group instance
`objects`	Return a dictionary of all objects stored.
`parent`
`path`
`support_simtk_unit`
`tags`
`variables`
`vltypes`