ThermoMLDataSet

class openff.evaluator.datasets.thermoml.ThermoMLDataSet[source]

A dataset of physical property measurements created from a ThermoML dataset.

Examples

For example, we can use the DOI 10.1016/j.jct.2005.03.012 as a key for retrieving the dataset from the ThermoML Archive:

>>> dataset = ThermoMLDataSet.from_doi('10.1016/j.jct.2005.03.012')

You can also specify multiple ThermoML Archive keys to create a dataset from multiple ThermoML files:

>>> thermoml_keys = ['10.1021/acs.jced.5b00365', '10.1021/acs.jced.5b00474']
>>> dataset = ThermoMLDataSet.from_doi(*thermoml_keys)

__init__()[source]: Constructs a new ThermoMLDataSet object.

Methods

`__init__`()	Constructs a new ThermoMLDataSet object.
`add_properties`(*physical_properties[, validate])	Adds a physical property to the data set.
`from_doi`(*doi_list)	Load a ThermoML data set from a list of DOIs
`from_file`(*file_list)	Load a ThermoML data set from a list of files
`from_json`(file_path)	Create this object from a JSON file.
`from_pandas`(data_frame)	Constructs a data set object from a pandas `DataFrame` object.
`from_url`(*url_list)	Load a ThermoML data set from a list of URLs
`from_xml`(xml, default_source)	Load a ThermoML data set from an xml object.
`json`([file_path, format])	Creates a JSON representation of this class.
`merge`(data_set[, validate])	Merge another data set into the current one.
`parse_json`(string_contents)	Parses a typed json string into the corresponding class structure.
`properties_by_substance`(substance)	A generator which may be used to loop over all of the properties which were measured for a particular substance.
`properties_by_type`(property_type)	A generator which may be used to loop over all of properties of a particular type, e.g.
`to_pandas`()	Converts a PhysicalPropertyDataSet to a pandas.DataFrame object with columns of
`validate`()	Checks to ensure that all properties within the set are valid physical property object.

Attributes

`properties`	A list of all of the properties within this set.
`property_types`	The types of property within this data set.
`registered_properties`
`sources`	The sources from which the properties in this data set were gathered.
`substances`	The substances for which the properties in this data set were collected for.

classmethod from_doi(*doi_list)[source]

Load a ThermoML data set from a list of DOIs

Parameters: doi_list (str) – The list of DOIs to pull data from
Returns: The loaded data set.
Return type: ThermoMLDataSet

classmethod from_url(*url_list)[source]

Load a ThermoML data set from a list of URLs

Parameters: url_list (str) – The list of URLs to pull data from
Returns: The loaded data set.
Return type: ThermoMLDataSet

classmethod from_file(*file_list)[source]

Load a ThermoML data set from a list of files

Parameters: file_list (str) – The list of files to pull data from
Returns: The loaded data set.
Return type: ThermoMLDataSet

add_properties(*physical_properties, validate=True)

Adds a physical property to the data set.

Parameters

physical_properties (PhysicalProperty) – The physical property to add.
validate (bool) – Whether to validate the properties before adding them to the set.

classmethod from_json(file_path)

Create this object from a JSON file.

Parameters: file_path (str) – The path to load the JSON from.
Returns: The parsed class.
Return type: cls

classmethod from_pandas(data_frame: DataFrame) → PhysicalPropertyDataSet

Constructs a data set object from a pandas DataFrame object.

Notes

All physical properties are assumed to be source from experimental measurements.
Currently this method onlu supports data frames containing properties which are built-in to the framework (e.g. Density).
This method assumes the data frame has a structure identical to that produced by the PhysicalPropertyDataSet.to_pandas function.

Parameters: data_frame – The data frame to construct the data set from.
Return type: The constructed data set.

classmethod from_xml(xml, default_source)[source]

Load a ThermoML data set from an xml object.

Parameters

xml (str) – The xml string to parse.
default_source (Source) – The source to use if one cannot be parsed from the archive itself.

Returns

The loaded ThermoML data set.

Return type

ThermoMLDataSet

json(file_path=None, format=False)

Creates a JSON representation of this class.

Parameters

file_path (str, optional) – The (optional) file path to save the JSON file to.
format (bool) – Whether to format the JSON or not.

Returns

The JSON representation of this class.

Return type

str

merge(data_set, validate=True)

Merge another data set into the current one.

Parameters

data_set (PhysicalPropertyDataSet) – The secondary data set to merge into this one.
validate (bool) – Whether to validate the other data set before merging.

classmethod parse_json(string_contents)

Parses a typed json string into the corresponding class structure.

Parameters: string_contents (str or bytes) – The typed json string.
Returns: The parsed class.
Return type: Any

property properties

A list of all of the properties within this set.

Type: tuple of PhysicalProperty

properties_by_substance(substance)

A generator which may be used to loop over all of the properties which were measured for a particular substance.

Parameters: substance (Substance) – The substance of interest.
Return type: generator of PhysicalProperty

properties_by_type(property_type)

A generator which may be used to loop over all of properties of a particular type, e.g. all “Density” properties.

Parameters: property_type (str or type of PhysicalProperty) – The type of property of interest. This may either be the string class name of the property or the class type.
Return type: generator of PhysicalProperty

property property_types

The types of property within this data set.

Type: set of str

property sources

The sources from which the properties in this data set were gathered.

Type: set of Source

property substances

The substances for which the properties in this data set were collected for.

Type: set of Substance

to_pandas()

Converts a PhysicalPropertyDataSet to a pandas.DataFrame object with columns of

‘Id’

‘Temperature (K)’

‘Pressure (kPa)’

‘Phase’

‘N Components’

‘Component 1’

‘Role 1’

‘Mole Fraction 1’

‘Exact Amount 1’

…

‘Component N’

‘Role N’

‘Mole Fraction N’

‘Exact Amount N’

‘<Property 1> Value (<default unit>)’

‘<Property 1> Uncertainty / (<default unit>)’

…

‘<Property N> Value / (<default unit>)’

‘<Property N> Uncertainty / (<default unit>)’

‘Source’

where ‘Component X’ is a column containing the smiles representation of component X.

Returns: The create data frame.
Return type: DataFrame

validate(): Checks to ensure that all properties within the set are valid physical property object.