fdi.dataset 包

子包

fdi.dataset.resources package

子模块

fdi.dataset.abstractcomposite 模块

class fdi.dataset.abstractcomposite.AbstractComposite(**kwds)[源代码]

基类：fdi.dataset.attributable.Attributable, fdi.dataset.listener.EventListener, fdi.dataset.composite.Composite, fdi.dataset.datawrapper.DataWrapperMapper

Composite 的一个可注释和可归属的子类。

Composite 通过 DataContainer 通过 EventListener 继承 annotatable。

__init__(**kwds)[源代码]

string(level=0, width=0, tablefmt='grid', tablefmt1='simple', tablefmt2='rst', extra=False, matprint=None, trans=True, beforedata='', heavy=True, center=- 1, **kwds)

matprint：外部矩阵打印功能

参数

**trans**（打印转置的二维矩阵。默认为True。）
——-

toString(level=0, width=0, tablefmt='grid', tablefmt1='simple', tablefmt2='rst', extra=False, matprint=None, trans=True, beforedata='', heavy=True, center=- 1, **kwds)[源代码]

matprint：外部矩阵打印功能

参数

**trans**（打印转置的二维矩阵。默认为True。）
——-

fdi.dataset.annotatable 模块

class fdi.dataset.annotatable.Annotatable(description='UNKNOWN', **kwds)[源代码]

基类：object

Annotatable 对象是一个可以给出人类可读描述的对象。

__init__(description='UNKNOWN', **kwds)[源代码]

getDescription()[源代码]

获取此 Annotatable 对象的描述。

返回: 当前描述。
返回类型: string

setDescription(newDescription)[源代码]

设置此 Annotatable 对象的描述。

参数: newDescription (string) – 新的描述。

fdi.dataset.arraydataset 模块

class fdi.dataset.arraydataset.ArrayDataset(data=None, unit=None, description=None, typ_=None, typecode=None, version=None, zInfo=None, alwaysMeta=True, **kwds)[源代码]

基类：fdi.dataset.dataset.GenericDataset, collections.abc.Iterable, fdi.dataset.shaped.Shaped

包含单个数组数据对象的特殊数据集。

mh：如果在实例化过程中省略参数名称，例如 ArrayDataset(a, b, c)，假设顺序是数据，单位，描述。 mh：包含提供方法 count()、index()、remove()、reverse() 的序列。可变序列还需要 append()、extend()、insert()、pop() 和 sort()。

数据: 此数据集的有效载荷数据。默认为无，返回 ——-

初始化一个 ArrayDataset。

默认 `None` 会将元数据参数初始化为它们的默认值。如果 data 不是 None 并且具有形状（len 适用），shape MDP 设置为实际的 data 形状。

__init__(data=None, unit=None, description=None, typ_=None, typecode=None, version=None, zInfo=None, alwaysMeta=True, **kwds)[源代码]

初始化一个 ArrayDataset。

默认 `None` 会将元数据参数初始化为它们的默认值。如果 data 不是 None 并且具有形状（len 适用），shape MDP 设置为实际的 data 形状。

append(*args, **kwargs)[源代码]: 附加到数据。

count(*args, **kwargs)[源代码]: 返回大小。

extend(*args, **kwargs)[源代码]: 扩展数据。

index(*args, **kwargs)[源代码]: 返回值的索引。

pop(*args, **kwargs)[源代码]: 删除和返回值

remove(*args, **kwargs)[源代码]: 在第一次出现时删除值。

setData(data)[源代码]

string(level=0, tablefmt='grid', tablefmt1='simple', tablefmt2='simple', width=0, param_widths=None, matprint=None, trans=True, center=- 1, heavy=True, **kwds): matprint：外部矩阵打印功能 trans：打印转置的二维矩阵。默认为真。

toString(level=0, tablefmt='grid', tablefmt1='simple', tablefmt2='simple', width=0, param_widths=None, matprint=None, trans=True, center=- 1, heavy=True, **kwds)[源代码]: matprint：外部矩阵打印功能 trans：打印转置的二维矩阵。默认为真。

class fdi.dataset.arraydataset.Column(*args, typ_='Column', **kwds)[源代码]

基类：fdi.dataset.arraydataset.ArrayDataset, fdi.dataset.listener.ColumnListener

列是表格的垂直切割，所有单元格都具有相同的签名。

Column 包含原始 ArrayData，以及可选的描述和单位。例子：：

table = TableDataset()
table.addColumn("Energy",Column(data=[1,2,3,4],description="desc",unit='eV'))

初始化一个 ArrayDataset。

默认 `None` 会将元数据参数初始化为它们的默认值。如果 data 不是 None 并且具有形状（len 适用），shape MDP 设置为实际的 data 形状。

fdi.dataset.arraydataset_datamodel 模块

fdi.dataset.attributable 模块

class fdi.dataset.attributable.Attributable(meta=None, zInfo=None, alwaysMeta=False, **kwds)[源代码]

基类：fdi.dataset.metadataholder.MetaDataHolder

Attributable 对象是具有元数据概念的对象。

MetaData Porperties (MDPs) are Attributes that store their properties in te metadata table.

Pick out arguments listed in zInfo then put updated parameters into MetaData meta.

meta: meta data container. zInfo: configuration alwaysMeta: always treat parameters as MetaDataProperties (MDPs).

__init__(meta=None, zInfo=None, alwaysMeta=False, **kwds)[源代码]

Pick out arguments listed in zInfo then put updated parameters into MetaData meta.

meta: meta data container. zInfo: configuration alwaysMeta: always treat parameters as MetaDataProperties (MDPs).

makeMdpMethods(outputfile=None)[源代码]: Generates a mix-in class file according to MetaData Property list.

property meta

setMdp(name, value, met=None)[源代码]

setMeta(newMetadata)[源代码]

Replaces the current MetaData with specified argument.

Product will override this to add listener when meta is replaced. _defaults which usually is self.zInfo is added to new meta so str(meta) can ommit the parameters with default value.

setParameters(params)[源代码]

Set a group of name-value pairs to the object as properties.

params: a dictionary of name:value where value is a subclass of AbstractParameter. value can be the value of a registered MDP. type will be used if typ_ is given as the name.

fdi.dataset.attributable.MdpInfo = {}: Names not for mormal properties.

class fdi.dataset.attributable.MetaDataProperties[源代码]

基类：object

Mix-in place-holder for Class denifitions that has not their own property.py generated by :meth: makeMdpMethods.

fdi.dataset.attributable.Reserved_Property_Names = ['history', 'meta', 'refs', 'dataset', 'zInfo', '_MDP', 'extraMdp', 'alwaysMeta', 'toString', 'string', 'yaml', 'tree']: These MetaData Parameters (MDPs) and vital attrbutes are Set By Parent classes: | Special MDPs and attrbutes | set by parent Classes | attribute holder | | ‘meta’ | Attributable | _meta | | ‘description’ | Annotatable | description | | ‘data’ and ‘shape’ | DataWrapper | _data | | ‘listeners’ | EventSender | _listener |

fdi.dataset.attributable.addMetaDataProperty(cls)[源代码]

mh: Add MDP to a class so that although they are metadata, they can be accessed by for example, productfoo.creator.

dynamic properties see https://stackoverflow.com/a/2584050 https://stackoverflow.com/a/1355444

fdi.dataset.attributable.make_class_properties(attrs, reserved=None)[源代码]: Generates class properties source code string according to given attribute names.

fdi.dataset.attributable.value2parameter(name, value, descriptor)[源代码]

returns a parameter with correct type and attributes according to its value and name.

value: type must be compatible with data_type. For example [0, 0] is wrong; Vector2d([0, 0)] is right if data_type``==``vector2d. descriptor: is zInfo(‘metadata’] or zInfo[‘dataset’][xxx]

fdi.dataset.baseproduct module

class fdi.dataset.baseproduct.BaseProduct(description='UNKNOWN', typ_='BaseProduct', level='ALL', creator='UNKNOWN', creationDate=FineTime(Unknown), rootCause='UNKNOWN', version='0.8', FORMATV='1.6.0.10', zInfo=None, **kwds)[源代码]

基类：fdi.dataset.abstractcomposite.AbstractComposite, fdi.dataset.copyable.Copyable, fdi.dataset.listener.EventSender

A BaseProduct is the starting point of te whole product tree, and a generic result that can be passed on between processes.

In general a Product contains zero or more datasets, history, optional reference pointers and metadata some required metadata fields. A Product is expected to fully describe itself; this includes the way how this product was achieved (its history). As it is the result of a process, it should be able to save to and restore from an Archive device.

Many times a Product may contain a single dataset and for this purpose the first dataset entry can be accessed by the getDefault() method. Note that the datasets may be a composite of datasets by themselves.

A built-in attributes in Model[‘metadata’] (“MetaData Parameter” or MDP) can be accessed with e.g. p.creator, or p.meta[‘creator’].value:
p.creator='foo'
assert p.creatur=='foo'
assert p.meta['creator']=='foo'
p.meta['creator']=Parameter('bar')
assert p.meta['creator']==Parameter('bar')
BaseProduct class schema 1.6 inheriting [None].

Automatically generated from fdi/dataset/resources/BaseProduct.yml on 2021-12-13 09:38:07.494042.

Description: FDI base class data model

property FORMATV

accept(visitor)[源代码]: Hook for adding functionality to meta data object through visitor pattern.

property creationDate

property creator

property description

property history: xx 必须是 self.xx = yy 的属性，才能在 xx 也被子类设置为属性后在超类中工作。

property level

property rootCause

string(level=0, tablefmt='grid', tablefmt1='rst', tablefmt2='rst', matprint=None, trans=True, beforedata='', **kwds): like AbstractComposite but with history

targetChanged(event)[源代码]: Informs that an event has happened in a target of any type. Paremeters ———-

toString(level=0, tablefmt='grid', tablefmt1='rst', tablefmt2='rst', matprint=None, trans=True, beforedata='', **kwds)[源代码]: like AbstractComposite but with history

property type

property version

fdi.dataset.booleanparameter module

fdi.dataset.browseproduct module

class fdi.dataset.browseproduct.BrowseProduct(description='UNKNOWN', typ_='BrowseProduct', level='ALL', creator='UNKNOWN', creationDate=FineTime(Unknown), rootCause='UNKNOWN', version='0.8', FORMATV='1.6.0.1', zInfo=None, **kwds)[源代码]

基类：fdi.dataset.baseproduct.BaseProduct

BrowseProduct class schema 1.6 inheriting [‘BaseProduct’].

Automatically generated from fdi/dataset/resources/BrowseProduct.yml on 2021-12-13 09:38:07.543630.

Description: Container of media data for browsing.

Generally a Product (inheriting BaseProduct) has project-wide attributes and can be extended to define a plethora of specialized products.

Initializes instances with more metadata as attributes, set to default values.

Put description keyword argument here to allow e.g. BaseProduct(“foo”) and description=’foo’

__init__(description='UNKNOWN', typ_='BrowseProduct', level='ALL', creator='UNKNOWN', creationDate=FineTime(Unknown), rootCause='UNKNOWN', version='0.8', FORMATV='1.6.0.1', zInfo=None, **kwds)[源代码]

Initializes instances with more metadata as attributes, set to default values.

Put description keyword argument here to allow e.g. BaseProduct(“foo”) and description=’foo’

fdi.dataset.classes module

class fdi.dataset.classes.Classes[源代码]

基类：object

A dictionary of class names and their class objects that are allowed to be deserialized.

An fdi package built-in dictionary (in the format of locals() output) is kept internally. Users who need add more deserializable class can for example:

Define new classes ``class Myclass():

….``

update Classes Classes.classes.update({'myClasses': MyClass})

and use new_instance = Classes.mapping['MyClass']

For a new package with many classes:

Import user classes in a python file for example projectclasses.py:

`` Class PC(Classes):

module_class = {
‘mypackage.mymodule’: [‘MyClass1’, ‘MyClass2’],

} # from another module defining a dict of modulename-Classobj pairs try:

from mypackage.mymodule import pairs

except (ImportError, ModuleNotFoundError) as e:
logger.info(e)

else:
module_class.update(pairs)

_package = {} _classes = {}

``

To use: `` from fdi.dataset.classes import Classes from my.package.projectclasses import PC prjcls = Classes.mapping Classes.updateMapping(PC.updateMapping())

new_instance = prjcls[‘MyClass1’]

class fdi.dataset.classes.Classes_meta(*args, **kwds)[源代码]

基类：type

metaclass for ‘classproperty’. # https://stackoverflow.com/a/1800999

Class is initialized with built-in classes by default.

__init__(*args, **kwds)[源代码]: Class is initialized with built-in classes by default.

importModuleClasses(rerun=False, exclude=None, ignore_error=False, verbose=False)[源代码]

The set of deserializable classes in module_class is maintained by hand.

Do nothing if the classes mapping is already made so repeated calls will not cost more time.

rerun: set to True to force re-import. If the module-class list has never been imported, it will be imported regardless rerun. exclude: modules whose names (without ‘.’) are in exclude are not imported.

property mapping

Returns the dictionary of classes allowed for deserialization, including the fdi built-ins and user added classes.

Will update the classes if the list is empty

module_class = {'fdi.dataset.arraydataset': ['ArrayDataset', 'Column'], 'fdi.dataset.baseproduct': ['BaseProduct'], 'fdi.dataset.browseproduct': ['BrowseProduct'], 'fdi.dataset.dataset': ['GenericDataset', 'CompositeDataset'], 'fdi.dataset.datatypes': ['Vector', 'Vector2D', 'Quaternion'], 'fdi.dataset.dateparameter': ['DateParameter'], 'fdi.dataset.deserialize': ['deserialize'], 'fdi.dataset.eq': ['DeepEqual'], 'fdi.dataset.finetime': ['FineTime', 'FineTime1', 'utcobj'], 'fdi.dataset.history': ['History'], 'fdi.dataset.listener': ['ListnerSet'], 'fdi.dataset.mediawrapper': ['MediaWrapper'], 'fdi.dataset.metadata': ['AbstractParameter', 'Parameter', 'MetaData'], 'fdi.dataset.numericparameter': ['NumericParameter', 'BooleanParameter'], 'fdi.dataset.odict': ['ODict'], 'fdi.dataset.product': ['Product'], 'fdi.dataset.readonlydict': ['ReadOnlyDict'], 'fdi.dataset.serializable': ['Serializable'], 'fdi.dataset.stringparameter': ['StringParameter'], 'fdi.dataset.tabledataset': ['TableDataset', 'IndexedTableDataset'], 'fdi.dataset.testproducts': ['TP', 'TC', 'TM'], 'fdi.dataset.unstructureddataset': ['UnstrcturedDataset'], 'fdi.pal.context': ['AbstractContext', 'Context', 'MapContext', 'RefContainer', 'ContextRuleException'], 'fdi.pal.productref': ['ProductRef'], 'fdi.pal.query': ['AbstractQuery', 'MetaQuery', 'StorageQuery'], 'fdi.pal.urn': ['Urn']}

reloadClasses()[源代码]: re-import classes in list.

updateMapping(c=None, rerun=False, exclude=None, verbose=False, ignore_error=False)[源代码]: Updates classes mapping. Make the package mapping if it has not been made.

fdi.dataset.classes.logger = <Logger fdi.dataset.classes (WARNING)>

this has to be in a different file where other interface classes are defined to avoid circular dependency (such as , Serializable.

Type: Note

fdi.dataset.collectionsMockUp module

class fdi.dataset.collectionsMockUp.ContainerMockUp[源代码]: 基类：object

class fdi.dataset.collectionsMockUp.MappingMockUp[源代码]: 基类：object

class fdi.dataset.collectionsMockUp.SequenceMockUp[源代码]: 基类：object

fdi.dataset.composite module

class fdi.dataset.composite.Composite(data=None, **kwds)[源代码]

基类：fdi.dataset.datawrapper.DataContainer, fdi.dataset.serializable.Serializable, collections.abc.MutableMapping

A container of named Datasets.

This container can hold zero or more datasets, each of them stored against a unique name. The order of adding datasets to this Composite is important, that is: the keySet() method will return a set of labels of the datasets in the sequence as they were added. Note that replacing a dataset with the same name, will keep the order.

DeepEqual must stay to the left of MutableMapping so its __eq__ will get to run. Serializable becomes a parent for having __setstate__.

数据: default None will init with a dict.

__init__(data=None, **kwds)[源代码]

containsKey(name)[源代码]: Returns true if this map contains a mapping for the specified name.

get(name, default=Invalid)[源代码]

Returns the dataset to which this composite maps the specified name.

If the attrbute does not exist and default unspecified, raise a KeyError.

参数: default: assigne to None or anything for missing name.

getDatasetNames(): Returns a list view of the keys contained in this composite.

getDefault()[源代码]: Convenience method that returns the first dataset belonging to this composite.

getSets()[源代码]: Provide access to the Map < String, Dataset > . mh: api from CompositeDataset

isEmpty()[源代码]: Returns true if this map contains no key - value mappings.

keySet()[源代码]: Returns a list view of the keys contained in this composite.

remove(name)[源代码]: Removes the mapping for this name from this composite. mh: returns None if name is None or item does not exist.

set(name, dataset)[源代码]: Associates the specified dataset with the specified key in this map(optional operation). If the map previously contained a mapping for this key, the old dataset is replaced by the specified dataset. this composite does not permit null or empty keys.

size()[源代码]: Returns the number of key - value mappings in this map.

string(level=0, matprint=None, trans=True, **kwds)

toString(level=0, matprint=None, trans=True, **kwds)[源代码]

class fdi.dataset.composite.UserDictAdapter(data=None, *args, **kwds)[源代码]

基类：collections.UserDict

Adapter class to make UserDict cooperative to multiple inheritance and take data keyword arg.

REf. https://rhettinger.wordpress.com/2011/05/26/super-considered-super/

参数: data: initialize UserDict.

__init__(data=None, *args, **kwds)[源代码]

参数: data: initialize UserDict.

fdi.dataset.copyable module

class fdi.dataset.copyable.Copyable(**kwds)[源代码]

基类：object

Interface for objects that can make a copy of themselves.

__init__(**kwds)[源代码]

copy()[源代码]: Makes a deep copy of itself.

fdi.dataset.dataset module

class fdi.dataset.dataset.CompositeDataset(**kwds)[源代码]

基类：fdi.dataset.listener.MetaDataListener, fdi.dataset.abstractcomposite.AbstractComposite

An CompositeDataset is a Dataset that contains zero or more named Datasets. It allows to build arbitrary complex dataset structures.

It also defines the iteration ordering of its children, which is the order in which the children were inserted into this dataset.

__init__(**kwds)[源代码]

class fdi.dataset.dataset.Dataset(**kwds)[源代码]

基类：fdi.dataset.attributable.Attributable, fdi.dataset.datawrapper.DataContainer, fdi.dataset.serializable.Serializable, fdi.dataset.listener.MetaDataListener

Attributable and annotatable information data container that can be be part of a Product.

developer notes: The intent is that developers do not derive from this interface

directly. Instead, they should inherit from one of the generic datasets that this package provides:

mh: GenericDataset, UnstrcturedDataset ArrayDataset. TableDataset or CompositeDataset.

__init__(**kwds)[源代码]

accept(visitor)[源代码]: Hook for adding functionality to object through visitor pattern. Parameter ———

string(level=0, tablefmt='grid', tablefmt1='simple', tablefmt2='rst', param_widths=None, width=0, matprint=None, trans=True, heavy=True, center=- 1, **kwds): matprint: an external matrix print function trans: print 2D matrix transposed. default is True. Parameter ———

toString(level=0, tablefmt='grid', tablefmt1='simple', tablefmt2='rst', param_widths=None, width=0, matprint=None, trans=True, heavy=True, center=- 1, **kwds)[源代码]: matprint: an external matrix print function trans: print 2D matrix transposed. default is True. Parameter ———

class fdi.dataset.dataset.GenericDataset(**kwds)[源代码]

基类：fdi.dataset.dataset.Dataset, fdi.dataset.typed.Typed, fdi.dataset.datawrapper.DataWrapper

mh: Contains one typed data item with a unit and a typecode.

__init__(**kwds)[源代码]

fdi.dataset.dataset.make_title_meta_l0(self, level=0, heavy=True, center=0, html=False, **kwds)[源代码]

make toString title and metadata.

Heavy: use bold symbols for separaters.
Center: 0 for no centering; -1 for centering with metadata table; other for str.center(<center>.

fdi.dataset.datatypes module

fdi.dataset.datatypes.DataTypes = {'': 'None', 'baseProduct': 'BaseProduct', 'binary': 'int', 'boolean': 'bool', 'byte': 'int', 'finetime': 'FineTime', 'finetime1': 'FineTime1', 'float': 'float', 'hex': 'int', 'integer': 'int', 'list': 'list', 'mapContext': 'MapContext', 'product': 'Product', 'quaternion': 'Quaternion', 'short': 'int', 'string': 'str', 'tuple': 'tuple', 'vector': 'Vector', 'vector2d': 'Vector2D'}: maps class type names to human-friendly types

class fdi.dataset.datatypes.Quaternion(components=None, **kwds)[源代码]

基类：fdi.dataset.datatypes.Vector

Quaternion with 4-component data.

invoked with no argument results in a vector of [0, 0, 0, 0] components

__init__(components=None, **kwds)[源代码]: invoked with no argument results in a vector of [0, 0, 0, 0] components

class fdi.dataset.datatypes.Vector(components=None, **kwds)[源代码]

基类：fdi.dataset.quantifiable.Quantifiable, fdi.dataset.serializable.Serializable, fdi.dataset.eq.DeepcmpEqual

N dimensional vector.

If unit, description, type etc meta data is needed, use a Parameter.

A Vector can compare with a value whose type is in DataTypes, the quantity being used is the magnitude.

invoked with no argument results in a vector of [0, 0, 0] components.

__init__(components=None, **kwds)[源代码]: invoked with no argument results in a vector of [0, 0, 0] components.

property components: for property getter

getComponents()[源代码]: Returns the actual components that is allowed for the components of this vector.

setComponents(components)[源代码]: Replaces the current components of this vector.

string(level=0, **kwds)

toString(level=0, **kwds)[源代码]

class fdi.dataset.datatypes.Vector2D(components=None, **kwds)[源代码]

基类：fdi.dataset.datatypes.Vector

Vector with 2-component data

invoked with no argument results in a vector of [0, 0] components

__init__(components=None, **kwds)[源代码]: invoked with no argument results in a vector of [0, 0] components

fdi.dataset.datatypes.cast(val, typ_, namespace=None)[源代码]

casts the input value to type specified, which is in DataTypeNames.

For example ‘binary’ type ‘0x9’ is casted to int 9.

namespace: default is Classes.mapping.

fdi.dataset.datatypes.logger = <Logger fdi.dataset.datatypes (WARNING)>: Allowed data (Parameter and Dataset) types and the corresponding classe names. The keys are mnemonics for humans; the values are type(x).__name__.

fdi.dataset.datatypes.lookup_bd(t)[源代码]

fdi.dataset.datawrapper module

class fdi.dataset.datawrapper.DataContainer(data=None, **kwds)[源代码]

基类：fdi.dataset.annotatable.Annotatable, fdi.dataset.copyable.Copyable, fdi.dataset.eq.DeepcmpEqual, collections.abc.Container

A DataContainer is a composite of data and description.

mh: note that There is no metadata. Implemented partly from AbstractDataWrapper.

data: a Container. Default is None.

__init__(data=None, **kwds)[源代码]: data: a Container. Default is None.

property data

getData()[源代码]

Returns the data in this dw

返回
返回类型: self._data or None if ‘._data’ is missing. e.g. subclass overriding setData calling getData from its setData that is called by ‘this.__init__’.

hasData()[源代码]

Returns whether this data wrapper has data.

返回
返回类型: False if data does not exist or is None or empty, True if otherwise.

setData(data)[源代码]: Replaces the current DataData with specified argument. mh: subclasses can override this to add listener whenevery data is replaced.

class fdi.dataset.datawrapper.DataWrapper(*args, **kwds)[源代码]

基类：fdi.dataset.datawrapper.DataContainer, fdi.dataset.quantifiable.Quantifiable

A DataWrapper is a composite of data, unit and description.

mh: note that all data are in the same unit. There is no metadata. Implemented from AbstractDataWrapper.

__init__(*args, **kwds)[源代码]

class fdi.dataset.datawrapper.DataWrapperMapper(*args, **kwds)[源代码]

基类：object

Object holding a map of data wrappers.

__init__(*args, **kwds)[源代码]

getDataWrappers()[源代码]: Gives the data wrappers, mapped by name.

fdi.dataset.dateparameter module

class fdi.dataset.dateparameter.DateParameter(value=None, description='UNKNOWN', default=None, valid=None, **kwds)[源代码]

基类：fdi.dataset.metadata.Parameter, fdi.dataset.typecoded.Typecoded

has a FineTime as the value.

Set up a parameter whose value is a point in TAI time.

__init__(value=None, description='UNKNOWN', default=None, valid=None, **kwds)[源代码]: Set up a parameter whose value is a point in TAI time.

setDefault(default)[源代码]: accept any type that a FineTime does.

setValue(value)[源代码]: accept any type that a FineTime does.

class fdi.dataset.dateparameter.DateParameter1(value=None, description='UNKNOWN', default=None, valid=None, **kwds)[源代码]

基类：fdi.dataset.dateparameter.DateParameter

Like DateParameter but usese FineTime1.

Set up a parameter whose value is a point in TAI time.

setDefault(default)[源代码]: accept any type that a FineTime1 does.

setValue(value)[源代码]: accept any type that a FineTime1 does.

fdi.dataset.deserialize module

class fdi.dataset.deserialize.IntDecoder(*, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, strict=True, object_pairs_hook=None)[源代码]

基类：json.decoder.JSONDecoder

adapted from https://stackoverflow.com/questions/45068797/how-to-convert-string-int-json-into-real-int-with-json-loads modified to also convert keys in dictionaries.

object_hook, if specified, will be called with the result of every JSON object decoded and its return value will be used in place of the given dict. This can be used to provide custom deserializations (e.g. to support JSON-RPC class hinting).

object_pairs_hook, if specified will be called with the result of every JSON object decoded with an ordered list of pairs. The return value of object_pairs_hook will be used instead of the dict. This feature can be used to implement custom decoders that rely on the order that the key and value pairs are decoded (for example, collections.OrderedDict will remember the order of insertion). If object_hook is also defined, the object_pairs_hook takes priority.

parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).

parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).

parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.

If strict is false (true is the default), then control characters will be allowed inside strings. Control characters in this context are those with character codes in the 0-31 range, including '\t' (tab), '\n', '\r' and '\0'.

decode(s)[源代码]

class fdi.dataset.deserialize.IntDecoderOD(*, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, strict=True, object_pairs_hook=None)[源代码]

基类：fdi.dataset.deserialize.IntDecoder

object_hook, if specified, will be called with the result of every JSON object decoded and its return value will be used in place of the given dict. This can be used to provide custom deserializations (e.g. to support JSON-RPC class hinting).

object_pairs_hook, if specified will be called with the result of every JSON object decoded with an ordered list of pairs. The return value of object_pairs_hook will be used instead of the dict. This feature can be used to implement custom decoders that rely on the order that the key and value pairs are decoded (for example, collections.OrderedDict will remember the order of insertion). If object_hook is also defined, the object_pairs_hook takes priority.

parse_float, if specified, will be called with the string of every JSON float to be decoded. By default this is equivalent to float(num_str). This can be used to use another datatype or parser for JSON floats (e.g. decimal.Decimal).

parse_int, if specified, will be called with the string of every JSON int to be decoded. By default this is equivalent to int(num_str). This can be used to use another datatype or parser for JSON integers (e.g. float).

parse_constant, if specified, will be called with one of the following strings: -Infinity, Infinity, NaN. This can be used to raise an exception if invalid JSON numbers are encountered.

If strict is false (true is the default), then control characters will be allowed inside strings. Control characters in this context are those with character codes in the 0-31 range, including '\t' (tab), '\n', '\r' and '\0'.

fdi.dataset.deserialize.constructSerializable(obj, lookup=None, debug=False)[源代码]: mh: reconstruct object from the output of jason.loads(). Recursively goes into nested class instances that are not encoded by default by JSONEncoder, instantiate and fill in variables. Objects to be deserialized must have their classes loaded. _STID cannot have module names in it (e.g. dataset.Product) or locals()[classname] or globals()[classname] will not work.

fdi.dataset.deserialize.decode_str(a0)[源代码]

fdi.dataset.deserialize.deserialize(js, lookup=None, debug=False, usedict=True)[源代码]

Loads classes with _STID from the results of serialize.

if usedict is True dict insted of ODict will be used.

fdi.dataset.deserialize.deserialize_args(all_args, not_quoted=False, first_string=True, serialize_out=False)[源代码]

parse the command path to get positional and keywords arguments.

if not_quoted is True, split everythine to the left of first { with Serialize_Args_Sep append the part startin from the {. mark=’{’
else after splitting all_args with Serialize_Args_Sep: mark=’%7B%22’ (quote(‘{‘))

Scan from left. if all_args[i] not start with mark

else decode_str() if `not_quoted==False` else only substitute SAS_Avatar with Serialize_Args_Sep. Then deserialize() this segment to become `{'apiargs':list, 'foo':bar ...}`, append value of `apiargs` to the converted-list above, remove the `apiargs`-`val` pair.
return 200 as the reurn code followed by the converted-list and the deserialized `dict`.

All_args: a list of path segments for the args list.
First_string: Do not try to change the type of the first arg (assumed to be the function/method name).

fdi.dataset.deserialize.encode_str(a0)[源代码]: quote to remove general url offenders then use a mostly harmless str to substitute Serialize_Args_Sep.

fdi.dataset.deserialize.logger = <Logger fdi.dataset.deserialize (WARNING)>

this has to be in a different file where other interface classes are defined to avoid circular dependency (such as , Serializable.

Type: Note

fdi.dataset.deserialize.serialize_args(*args, not_quoted=False, **kwds)[源代码]

Serialize all positional and keywords arguements as they would appear in a function call. Arguements are assumed to have been placed in the same order of a valid function/method call. They are scanned from left to right from args[i] i = 0, 1,… to kwds[j] j = 0, 1, …

Scan args from i=0. if is of args[i] is of bool, int, float types, convert with str, if str(), convert with encode_str(), if bytes or bytearray’ types, with ```0x```+`hex(), save to the convered-list, and move on to the next element.
else if finding a segment not of any of the above types,

** put this and the rest of `args` as the `value` in `{'apiargs':value}`, ** and append kwds key-val pairs after this pair, ** serialize the disctionary with serialize() and encode_str() ** append the result to the converted-list. ** break from the args scan loop. * if args scan loop reaches its end, if kwds is not empty, serialize it with serialize() and encode_str(), or scanning reaches the end of args. * append the result to the converted-list. * join the converted-list with Serialize_Args_Sep. * return the result string

fdi.dataset.eq module

exception fdi.dataset.eq.CircularCallError[源代码]: 基类：RuntimeError

fdi.dataset.eq.DeepEqual: alias of fdi.dataset.eq.DeepcmpEqual

class fdi.dataset.eq.DeepcmpEqual(*args, **kwds)[源代码]

基类：object

Equality tested by deepcmp.

Must pass args so DataWrapper in Composite can get data.

__init__(*args, **kwds)[源代码]: Must pass args so DataWrapper in Composite can get data.

equals(obj, **kwds)[源代码]: compares using `deepcmp.

class fdi.dataset.eq.EqualDict(**kwds)[源代码]

基类：object

mh: Can compare key-val pairs of another object with self. False if compare with None or exceptions raised, e.g. obj does not have items()

equals(obj, verbose=False)[源代码]

class fdi.dataset.eq.EqualODict(**kwds)[源代码]

基类：object

mh: Can compare order and key-val pairs of another object with self. False if compare with None or exceptions raised, e.g. obj does not have items()

equals(obj, verbose=False)[源代码]

class fdi.dataset.eq.StateEqual(*args, **kwds)[源代码]

基类：object

Equality tested by hashed state.

Must pass args so DataWrapper in Composite can get data.

__init__(*args, **kwds)[源代码]: Must pass args so DataWrapper in Composite can get data.

equals(obj, **kwds): compares hash.

hash(**kwds)[源代码]

fdi.dataset.eq.deepcmp(obj1, obj2, seenlist=None, verbose=False, eqcmp=False)[源代码]

Recursively descends into obj1’s every component and compares with its counterpart in obj2.

Factors includes; * if they are the same object * type * quick string * `__eq__` or `__cmp__` if requested * state from `__getstate__` * quick length * members if is `Mapping`, `Sequence` ( set, list, dict, ordereddict, UserDict … ) * properties/attributes in `__dict__`

Detects cyclic references.

返回

None if finds no difference, a string of explanation
otherwise.
eqcmp: if True, use __eq__ or __cmp__ if the objs have them. If False only use as the last resort. default True.

fdi.dataset.eq.xhash(hash_list=None, seenlist=None, verbose=None)[源代码]

get the hash of a tuple of hashes of all members of given sequence.

Hash_list: use instead of self.getstate__()
Verbose: set to trace.

fdi.dataset.finetime module

class fdi.dataset.finetime.FineTime(date=None, format=None, **kwds)[源代码]

基类：fdi.dataset.copyable.Copyable, fdi.dataset.eq.DeepcmpEqual, fdi.dataset.serializable.Serializable

Atomic time (SI seconds) elapsed since the TAI epoch of 1 January 1958 UT2. The resolution is one microsecond and the allowable range is: epoch + /-290, 000 years approximately.

This has the following advantages, compared with the standard class:

It has better resolution(microseconds) Time differences are correct across leap seconds It is immutable.

Initiate with a UTC date or an integer TAI.

date; time to be set to. Acceptable types: int for TAI, datetime.datetime, string for ISO format date-time, or bytes-like classed that can get string by calling its decode(encoding=’utf-8’)

DEFAULT_FORMAT = '%Y-%m-%dT%H:%M:%S.%f'

EPOCH = datetime.datetime(1958, 1, 1, 0, 0, tzinfo=datetime.timezone.utc): number of TAI units in a second

RESOLUTION = 1000000

RETURNFMT = '%s.%06d'

TIMESPEC = 'microseconds'

UTC_LOW_LIMIT = datetime.datetime(1958, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)

__init__(date=None, format=None, **kwds)[源代码]

Initiate with a UTC date or an integer TAI.

date; time to be set to. Acceptable types: int for TAI, datetime.datetime, string for ISO format date-time, or bytes-like classed that can get string by calling its decode(encoding=’utf-8’)

classmethod datetimeToFineTime(dtm)[源代码]: Return given Python Datetime in FineTime to the precision of the input. Rounded to the last digit. Unit is decided by RESOLUTION.

getFormat()[源代码]: format cannot be a property name as it is a built so`@format.setter` is not allowed.

getTime()[源代码]: Returns the time related to this object.

isoutc(format='%Y-%m-%dT%H:%M:%S.%f')[源代码]

Returns a String representation of this objet in ISO format without timezone. sub-second set to TIMESPEC.

If tai is None return ‘’. ;format: time format. default ‘%Y-%m-%dT%H:%M:%S’ prints like 2019-02-17T12:43:04.577000

microsecondsSinceEPOCH()[源代码]: Return the rounded integer number of microseconds since the epoch: 1 Jan 1958.

setTime(time)[源代码]

Sets the time of this object.

If an integer is given, it will be taken as the TAI. If a datetime object or a string code is given, the timezone will be set to UTC. Only when current TAI is 0, so a non-zero instance is immutable. Violation gets a TypeError.

string(level=0, width=0, **kwds): Returns a String representation of this object according to self.format. level: 0 prints like 2019-02-17T12:43:04.577000 TAI(…) width: if non-zero, insert newline to break simplified output into shorter lines. For level=0 it is ` #TODO `

subtract(time)[源代码]: Subract the specified time and return the difference in microseconds.

property time

toDate(tai=None)

Return given FineTime as a Python Datetime.

tai: if not given or given as None, return this object’s time as a Python Datetime.

toDatetime(tai=None)[源代码]

Return given FineTime as a Python Datetime.

tai: if not given or given as None, return this object’s time as a Python Datetime.

toString(level=0, width=0, **kwds)[源代码]: Returns a String representation of this object according to self.format. level: 0 prints like 2019-02-17T12:43:04.577000 TAI(…) width: if non-zero, insert newline to break simplified output into shorter lines. For level=0 it is ` #TODO `

class fdi.dataset.finetime.FineTime1(*args, **kwds)[源代码]

基类：fdi.dataset.finetime.FineTime

Same as FineTime but Epoch is 2017-1-1 0 UTC and unit is millisecond

Initiate with a UTC date or an integer TAI.

date; time to be set to. Acceptable types: int for TAI, datetime.datetime, string for ISO format date-time, or bytes-like classed that can get string by calling its decode(encoding=’utf-8’)

EPOCH = datetime.datetime(2017, 1, 1, 0, 0, tzinfo=datetime.timezone.utc): number of TAI units in a second

RESOLUTION = 1000

RETURNFMT = '%s.%03d'

TAI_AT_EPOCH = 1861920037000000

TIMESPEC = 'milliseconds'

classmethod datetimeToFineTime(dtm)[源代码]: Return given Python Datetime in FineTime to the precision of the input. Rounded to the last digit. Unit is decided by RESOLUTION.

toDatetime(tai=None)[源代码]

Return given FineTime as a Python Datetime.

tai: if not given or given as None, return this object’s time as a Python Datetime.

fdi.dataset.history module

class fdi.dataset.history.History(other=None, **kwds)[源代码]

基类：fdi.dataset.dataset.CompositeDataset

Public interface to the history dataset. Contains the main methods for retrieving a script and copying the history.

mh: The copy constructor is better not be implemented. Use copy() instead. Remember: not only copies the datasets, but also changes the history ID in the metadata and relevant table entries to indicate that this a new independent product of which the history may change.

__init__(other=None, **kwds)[源代码]: mh: The copy constructor is better not be implemented. Use copy() instead. Remember: not only copies the datasets, but also changes the history ID in the metadata and relevant table entries to indicate that this a new independent product of which the history may change.

accept(visitor)[源代码]: Hook for adding functionality to meta data object through visitor pattern.

getOutputVar()[源代码]: Returns the final output variable of the history script.

getScript()[源代码]: Creates a Jython script from the history.

getTaskHistory()[源代码]: Returns a human readable formatted history tree.

saveScript(file)[源代码]: Saves the history script to a file.

fdi.dataset.indexed module

class fdi.dataset.indexed.Indexed(indexPattern=None, **kwds)[源代码]

基类：object

Abstract class with an index table for efficient records look-up.

indexPattern: specifies which columns to use to do look up.

__init__(indexPattern=None, **kwds)[源代码]: indexPattern: specifies which columns to use to do look up.

clearToc()[源代码]: Clears the index table of content.

getColumnsToLookup()[源代码]

returns an iterator that gives a number of sequences to looking up over.

Default is a tuple of the data attributes of every columns specified by indexPattern. To be overrided for different data model.

property indexPattern

property toc: returns the index table of content.

updateToc(which=None, for_records=None)[源代码]: Build index in format specified in indexPattern for retrieving record. which: an iterator that gives a number of sequences to looking up over. Default is getColumnsToLookup(). for_records: a list or a Slice of record (row) numbers. Those are changed records that caused updating. default is all records.

vLookUp(key, return_index=True, multiple=False)[源代码]: Similar to Excel VLOOKUP, return all records (rows) that match the key. key: taken as a dictionary key unless multiple is True. return_index: if True (default) return index in the array of columns. multiple: if True (default is False) loop through key as a sequence of keys and return a sequece.

fdi.dataset.invalid module

class fdi.dataset.invalid.InvalidType[源代码]: 基类：object

fdi.dataset.listener module

class fdi.dataset.listener.ColumnListener(**kwds)[源代码]

基类：fdi.dataset.listener.EventListener

Listener for events occuring in a Column.

Available types:

* DESCRIPTION_CHANGED
* UNIT_CHANGED
* DATA_CHANGED

Cause is always null.

__init__(**kwds)[源代码]

class fdi.dataset.listener.DatasetEvent(source, target, typ_, change, cause, rootCause, **kwds)[源代码]

基类：fdi.dataset.serializable.Serializable

__init__(source, target, typ_, change, cause, rootCause, **kwds)[源代码]

string(level=0, **kwds)

toString(level=0, **kwds)[源代码]

class fdi.dataset.listener.DatasetEventSender(**kwds)[源代码]

基类：fdi.dataset.listener.EventSender

__init__(**kwds)[源代码]

class fdi.dataset.listener.DatasetListener(**kwds)[源代码]

基类：fdi.dataset.listener.EventListener

Listener for events occuring in MetaData. Available types:

* DESCRIPTION_CHANGED, METADATA_CHANGED (all datasets)
* DATA_CHANGED, UNIT_CHANGED (ArrayDataset)
* COLUMN_ADDED, COLUMN_REMOVED, COLUMN_CHANGED, ROW_ADDED, VALUE_CHANGED (TableDataset)
* DATASET_ADDED, DATASET_REMOVED, DATASET_CHANGED (CompositeDataset)

Possible causes:

* not null (METADATA_CHANGED, COLUMN_CHANGED, DATASET_CHANGED)
* null (rest)

Warning: The listener handler must be a class attribute in order to create an object hard reference. See DatasetBaseListener.

__init__(**kwds)[源代码]

class fdi.dataset.listener.EventListener(*args, **kwds)[源代码]

基类：fdi.dataset.annotatable.Annotatable

Generic interface for listeners that will listen to anything

targetChanged(*args, **kwargs)[源代码]: Informs that an event has happened in a target of any type. Paremeters ———-

class fdi.dataset.listener.EventSender(**kwds)[源代码]

基类：object

adapted from Peter Thatcher’s https://stackoverflow.com/questions/1092531/event-system-in-python/1096614#1096614

参数: Returns

__init__(**kwds)[源代码]

参数: Returns

addListener(listener, cls=<class 'fdi.dataset.listener.EventListener'>)[源代码]: Adds a listener to this. Paremeters ———-

fire(*args, **kwargs)[源代码]

getListenerCount()[源代码]

getListeners()[源代码]: Returns the current Listeners. Paremeters ———-

property listeners

参数: Returns

removeListener(listener)[源代码]: Removes a listener from this. Paremeters ———-

setListeners(listeners)[源代码]: Replaces the current Listeners with specified argument. Paremeters ———-

class fdi.dataset.listener.ListnerSet(data=None, *args, **kwds)[源代码]

基类：fdi.dataset.serializable.Serializable, fdi.dataset.eq.DeepcmpEqual, collections.UserList

Mutable collection of Listeners of an EvenSender.

参数: data: default is None for a list.

__init__(data=None, *args, **kwds)[源代码]

参数: data: default is None for a list.

equals(obj, verbose=False)[源代码]: compares with another one. :参数: Returns

geturns(remove=None)[源代码]: Returns the current urns. :参数: Returns

seturns(urns)[源代码]: Replaces the current urn with specified argument.

string(level=0, alist=False, **kwds)

返回

LIST[TUPLE(OBJ)] or STRXS
A list of member-repre tuples or a string of all depending on alist.

toString(level=0, alist=False, **kwds)[源代码]

返回

LIST[TUPLE(OBJ)] or STRXS
A list of member-repre tuples or a string of all depending on alist.

property urns

class fdi.dataset.listener.MetaDataListener(*args, **kwds)[源代码]

基类：fdi.dataset.listener.EventListener

Listener for events occuring in MetaData. Available types:

* PARAMETER_ADDED
* PARAMETER_REMOVED
* PARAMETER_CHANGED

Possible causes: not null (for PARAMETER_CHANGED, if parameter internally changed) null (for PARAMETER_CHANGED, when set is called with a previous existing parameter, and rest)

Warning: The listener handler must be a class attribute in order to create an object hard reference. See DatasetBaseListener.

__init__(*args, **kwds)[源代码]

class fdi.dataset.listener.ParameterListener(**kwds)[源代码]

基类：fdi.dataset.listener.EventListener

Listener for events occuring in a Parameter. Available types:

* DESCRIPTION_CHANGED
* UNIT_CHANGED
* VALUE_CHANGED
* UNKOWN_ATTRIBUTE_CHANGED

Cause is always null.

Warning: The listener handler must be a class attribute in order to create an object hard reference. See DatasetBaseListener.

__init__(**kwds)[源代码]

class fdi.dataset.listener.ProductListener(**kwds)[源代码]

基类：fdi.dataset.listener.EventListener

Listener for events occuring in Product. Available types:

* METADATA_CHANGED
* DATASET_ADDED
* DATASET_REMOVED
* DATASET_CHANGED

Possible causes:

* not null (METADATA_CHANGED, DATASET_CHANGED)
* null (METADATA_CHANGED, DATASET_REMOVED, DATASET_CHANGED)

Warning: The listener handler must be a class attribute in order to create an object hard reference. See DatasetBaseListener.

__init__(**kwds)[源代码]

fdi.dataset.mediawrapper module

class fdi.dataset.mediawrapper.MediaWrapper(data=None, unit=None, description=None, typ_='image/png', source=None, typecode=None, version=None, zInfo=None, alwaysMeta=True, **kwds)[源代码]

基类：fdi.dataset.arraydataset.ArrayDataset

A MediaWrapper contains raw, usually binary, data in specific format.

Initializes media data wrapped in ArrayDataset.

typ_: www style string that follows Content-Type: `. Default is `imagw/png.

__init__(data=None, unit=None, description=None, typ_='image/png', source=None, typecode=None, version=None, zInfo=None, alwaysMeta=True, **kwds)[源代码]

Initializes media data wrapped in ArrayDataset.

typ_: www style string that follows Content-Type: `. Default is `imagw/png.

fdi.dataset.mediawrapper_datamodel module

fdi.dataset.messagequeue module

class fdi.dataset.messagequeue.MqttRelayListener(topics=None, host=None, port=None, username=None, passwd=None, callback=None, clean_session=None, client_id=None, userdata=None, qos=1, **kwds)[源代码]

基类：fdi.dataset.listener.EventListener

Generic interface for sending anything heard to an MQTT message queue.

Starts a MQTT message queue and forward everything in the arguement list to the MQ serialized.

host, port, username, passwd: if any is not provided, it is looked up in `config[‘mqtt’].

__init__(topics=None, host=None, port=None, username=None, passwd=None, callback=None, clean_session=None, client_id=None, userdata=None, qos=1, **kwds)[源代码]

Starts a MQTT message queue and forward everything in the arguement list to the MQ serialized.

host, port, username, passwd: if any is not provided, it is looked up in `config[‘mqtt’].

targetChanged(*args, **kwargs)[源代码]: Informs that an event has happened in a target of any type.

class fdi.dataset.messagequeue.MqttRelaySender(topics=None, host=None, port=None, username=None, passwd=None, callback=None, clean_session=None, client_id=None, userdata=None, qos=1, **kwds)[源代码]

基类：fdi.dataset.listener.EventSender

Gets MQTT messages and forwards to listeners.

Starts a MQTT message queue and forward everything in the arguement list to the MQ serialized.

host, port, username, passwd: if any is not provided, it is looked up in `config[‘mqtt’].

__init__(topics=None, host=None, port=None, username=None, passwd=None, callback=None, clean_session=None, client_id=None, userdata=None, qos=1, **kwds)[源代码]

Starts a MQTT message queue and forward everything in the arguement list to the MQ serialized.

host, port, username, passwd: if any is not provided, it is looked up in `config[‘mqtt’].

fdi.dataset.messagequeue.on_message(client, userdata, msg)[源代码]

fdi.dataset.metadata module

class fdi.dataset.metadata.AbstractParameter(value=None, description='UNKNOWN', **kwds)[源代码]

基类：fdi.dataset.annotatable.Annotatable, fdi.dataset.copyable.Copyable, fdi.dataset.eq.DeepcmpEqual, fdi.dataset.listener.DatasetEventSender, fdi.dataset.serializable.Serializable

Parameter is the interface for all named attributes in the MetaData container.

A Parameter is a variable with associated information about its description, unit, type, valid ranges, default, format code etc. Type can be numeric, string, datetime, vector.

Often a parameter shows a property. So a parameter in the metadata of a dataset or product is often called a property.

Default value=None, description=’UNKNOWN’

Constructed with no argument results in a parameter of None value and ‘UNKNOWN’ description ‘’. With a signle argument: arg -> value, ‘UNKNOWN’ as default-> description. With two positional arguments: arg1-> value, arg2-> description. Type is set according to value’s. Unsuported parameter types will get a NotImplementedError.

__init__(value=None, description='UNKNOWN', **kwds)[源代码]: Constructed with no argument results in a parameter of None value and ‘UNKNOWN’ description ‘’. With a signle argument: arg -> value, ‘UNKNOWN’ as default-> description. With two positional arguments: arg1-> value, arg2-> description. Type is set according to value’s. Unsuported parameter types will get a NotImplementedError.

accept(visitor)[源代码]: Adds functionality to classes of this type.

getValue()[源代码]: Gets the value of this parameter as an Object.

getValueAsString()[源代码]: Value as string for building the string representation of the parameter.

hash()[源代码]

hash and equality derived only from the value of the parameter.

because Python does not allow overriding __eq__ without setting hash to None.

setValue(value)[源代码]: Replaces the current value of this parameter.

string(level=0, alist=False, **kwds): alist: returns a dictionary string representation of parameter attributes.

toString(level=0, alist=False, **kwds)[源代码]: alist: returns a dictionary string representation of parameter attributes.

property value: for property getter

fdi.dataset.metadata.Default_Extra_Param_Width = 10: Attribute | Defining Module | Holder Variable |

‘description’ | Annotatable | description |

‘typ_’ | Typed | _type |

‘unit’ | Quantifiable | ‘_unit’ |

‘typecode’ | Typecoded | ‘_typecode’ |

class fdi.dataset.metadata.MetaData(copy=None, defaults=None, **kwds)[源代码]

基类：fdi.dataset.listener.ParameterListener, fdi.dataset.composite.Composite, fdi.dataset.copyable.Copyable, fdi.dataset.listener.DatasetEventSender

A container of named Parameters. A MetaData object can have one or more parameters, each of them stored against a unique name. The order of adding parameters to this container is important, that is: the keySet() method will return a set of labels of the parameters in the sequence as they were added. Note that replacing a parameter with the same name, will keep the order.

Table_Widths = [{'name': 15, 'value': 18, 'unit': 6, 'type': 8, 'valid': 17, 'default': 15, 'code': 4, 'description': 17}]

__init__(copy=None, defaults=None, **kwds)[源代码]

accept(visitor)[源代码]: Hook for adding functionality to meta data object through visitor pattern.

clear()[源代码]: Removes all the key - parameter mappings.

remove(name)[源代码]: add eventhandling

set(name, newParameter)[源代码]

Saves the parameter and adds eventhandling.

In a parameter name, dot or other invalid characters (when the name is used as a property name) is ignored.

Raises TypeError if not given Parameter (sub) class object.

string(level=0, tablefmt='grid', tablefmt1='simple', tablefmt2='rst', extra=False, param_widths=None, width=0, **kwds)

return string representation of metada.

level: 0 is the most detailed, 2 is the least, tablefmt: format string in packae tabulate, for level==0, tablefmt1 for level1, tablefmt2: format of 2D table data. param_widths: controls how the attributes of every parameter are displayed in the table cells. If is set to -1, there is no cell-width limit. For finer control set a dictionary of parameter attitute names and how many characters wide its tsble cell is, 0 for ommiting the attributable. Default is MetaData.Table_Widths[0]. e.g.

``{‘name’: 8, ‘value’: 17, ‘unit’: 7, ‘type’: 8,: ‘valid’: 20, ‘default’: 17, ‘code’: 4, ‘description’: 15}``

toString(level=0, tablefmt='grid', tablefmt1='simple', tablefmt2='rst', extra=False, param_widths=None, width=0, **kwds)[源代码]

return string representation of metada.

level: 0 is the most detailed, 2 is the least, tablefmt: format string in packae tabulate, for level==0, tablefmt1 for level1, tablefmt2: format of 2D table data. param_widths: controls how the attributes of every parameter are displayed in the table cells. If is set to -1, there is no cell-width limit. For finer control set a dictionary of parameter attitute names and how many characters wide its tsble cell is, 0 for ommiting the attributable. Default is MetaData.Table_Widths[0]. e.g.

``{‘name’: 8, ‘value’: 17, ‘unit’: 7, ‘type’: 8,: ‘valid’: 20, ‘default’: 17, ‘code’: 4, ‘description’: 15}``

class fdi.dataset.metadata.Parameter(value=None, description='UNKNOWN', typ_='', default=None, valid=None, **kwds)[源代码]

基类：fdi.dataset.metadata.AbstractParameter, fdi.dataset.typed.Typed

Parameter is the interface for all named attributes in the MetaData container. It can have a value and a description. Default arguments: typ_=’’, default=None, valid=None. value=default, description=’UNKNOWN’

invoked with no argument results in a parameter of: None value and ‘UNKNOWN’ description ‘’. typ_ DataTypes[‘’], which is None. With a signle argument: arg -> value, ‘UNKNOWN’-> description. ParameterTypes-> typ_, hex values have integer typ_. Unsuported parameter types will get a NotImplementedError.
f With two positional arguments: arg1-> value, arg2-> description. ParameterTypes[‘’]-> typ_.: Unsuported parameter types will get a NotImplementedError. With three positional arguments: arg1 casted to DataTypes[arg3]-> value, arg2-> description. arg3-> typ_. Unsuported parameter types will get a NotImplementedError. Incompatible value and typ_ will get a TypeError. Parameters ———-

__init__(value=None, description='UNKNOWN', typ_='', default=None, valid=None, **kwds)[源代码]

invoked with no argument results in a parameter of: None value and ‘UNKNOWN’ description ‘’. typ_ DataTypes[‘’], which is None. With a signle argument: arg -> value, ‘UNKNOWN’-> description. ParameterTypes-> typ_, hex values have integer typ_. Unsuported parameter types will get a NotImplementedError.
f With two positional arguments: arg1-> value, arg2-> description. ParameterTypes[‘’]-> typ_.: Unsuported parameter types will get a NotImplementedError. With three positional arguments: arg1 casted to DataTypes[arg3]-> value, arg2-> description. arg3-> typ_. Unsuported parameter types will get a NotImplementedError. Incompatible value and typ_ will get a TypeError. Parameters ———-

accept(visitor)[源代码]: Adds functionality to classes of this type.

checked(value)[源代码]

Checks input value against self.type.

If value is none, returns it; else if type is not set, return value after setting type; If value’s type is a subclass of self’s type, return the value; If value’s and self’s types are both subclass of Number, returns value casted in self’s type.

property default

getDefault()[源代码]: Returns the default related to this object.

getValid()[源代码]: Returns the valid related to this object.

isValid()[源代码]

setDefault(default)[源代码]

Sets the default of this object.

Default is set directly if type is not set or default is None. If the type of default is not getType(), TypeError is raised.

setType(typ_)[源代码]

Replaces the current type of this parameter.

Default will be casted if not the same. Unsuported parameter types will get a NotImplementedError.

setValid(valid)[源代码]

Sets the valid of this object.

If valid is None or empty, set as None, else save in a way so the tuple keys can be serialized with JSON. [[[rangelow, ranehi], state1], [[range2low, r..]..]..]

setValue(value)[源代码]

Replaces the current value of this parameter.

If value is None set it to None (#TODO: default?) If given/current type is ‘’ and arg value’s type is in DataTypes both value and type are updated to the suitable one in DataTypeNames; or else TypeError is raised. If value type is not a subclass of given/current type, or

Incompatible value and type will get a TypeError.

split(into=None)[源代码]

split a multiple binary bit-masked parameters according to masks.

into: dictionary mapping bit-masks to the sub-name of the parameter. return: a dictionary mapping name of new parameters to its value.

string(level=0, alist=False, **kwds): alist: returns a dictionary string representation of parameter attributes.

toString(level=0, alist=False, **kwds)[源代码]: alist: returns a dictionary string representation of parameter attributes.

property valid

validate(value=Invalid)[源代码]

checks if a match the rule set.

value: will be checked against the ruleset. Default is self._valid. returns: (valid value, rule name) for discrete and range rules. {mask: (valid val, rule name, mask_height, mask_width), …} for binary masks rules. (INVALID, ‘Invalid’) if no matching is found. (value, ‘Default’) if rule set is empty.

fdi.dataset.metadata.make_jsonable(valid)[源代码]

fdi.dataset.metadata.parameterDataClasses(tt)[源代码]: maps machine type names to class objects

fdi.dataset.metadataholder module

class fdi.dataset.metadataholder.MetaDataHolder(meta=None, **kwds)[源代码]

基类：object

Object holding meta data.

Adds MetaData to the class. with defaults set to self.zInfo[‘metadata’].

__init__(meta=None, **kwds)[源代码]: Adds MetaData to the class. with defaults set to self.zInfo[‘metadata’].

getMeta()[源代码]: Returns the current MetaData container of this object. Cannot become a python property because setMeta is in Attributable

hasMeta()[源代码]: whether the metadata holder is present. During initialization subclass of MetaDataHolder may need to know if the metadata holder has been put in place with is method.

setMeta(meta)[源代码]

fdi.dataset.ndprint module

fdi.dataset.ndprint.ndprint(data, trans=True, maxElem=9223372036854775807, tablefmt3='plain', **kwds)[源代码]

makes a formated string of an N-dimensional array for printing.

The fastest changing index is the innerest list. E.g. A 2 by 3 matrix is [[1,2],[3,4],[5,6]] written as:

1 2 3 4 5 6

But if the matrix is a table, the cells in a column change the fastest,

and the columns are written vertically. So to print a matrix as a table, whose columns are the innerest list, set trans = True (default) then the matrix needs to be printed transposed:

1 3 5 2 4 6

tablefmt3: control 2d array printing. Default ‘plain’.

fdi.dataset.ndprint.padstr(s, w, just='left', pad=' ')[源代码]

fdi.dataset.numericparameter module

class fdi.dataset.numericparameter.BooleanParameter(value=None, description='UNKNOWN', default=None, valid=None, **kwds)[源代码]

基类：fdi.dataset.metadata.Parameter

A Parameter that has a boolean as the value.

Set up a parameter whose value is a boolean

__init__(value=None, description='UNKNOWN', default=None, valid=None, **kwds)[源代码]: Set up a parameter whose value is a boolean

setDefault(default)[源代码]: accept any type that bool Vector does.

setValue(value)[源代码]: accept any type that bool does.

class fdi.dataset.numericparameter.NumericParameter(value=None, description='UNKNOWN', typ_='', default=None, unit=None, valid=None, typecode=None, **kwds)[源代码]

基类：fdi.dataset.metadata.Parameter, fdi.dataset.quantifiable.Quantifiable

A Parameter that has a number as the value, a unit, and a typecode.

Set up a parameter whose value is a or a list of numbers.

typ_: type of the parameter value.

__init__(value=None, description='UNKNOWN', typ_='', default=None, unit=None, valid=None, typecode=None, **kwds)[源代码]

Set up a parameter whose value is a or a list of numbers.

typ_: type of the parameter value.

setDefault(default)[源代码]: accept any type that a Vector does.

setValue(value)[源代码]: accept any type that a Vector does.

fdi.dataset.odict module

class fdi.dataset.odict.ODict(*args, **kwds)[源代码]

基类：collections.UserDict, fdi.dataset.serializable.Serializable, fdi.dataset.eq.DeepcmpEqual

Ordered dict that is not a subclass of dict and with a better __str__.

__init__(*args, **kwds)[源代码]

get(name)[源代码]: Raise a KeyError to change the default behavior of colections.Mapping to quietly return a None when a key is not found in the dict.

hash()[源代码]

string(level=0, keyval=None, **kwds)

level

default=0,

keyval

default=`None`. If set to a string, ODict class name is not shown and a label of given string is shown with each key as ‘label key:

‘.

tablefmt: =’rst’, tablefmt1=’simple’, tablefmt2=’simple’, matprint=None, trans=True, heavy=True

toString(level=0, keyval=None, **kwds)[源代码]

level

default=0,

keyval

default=`None`. If set to a string, ODict class name is not shown and a label of given string is shown with each key as ‘label key:

‘.

tablefmt: =’rst’, tablefmt1=’simple’, tablefmt2=’simple’, matprint=None, trans=True, heavy=True

fdi.dataset.product module

class fdi.dataset.product.Product(description='UNKNOWN', typ_='Product', level='ALL', creator='UNKNOWN', creationDate=FineTime(Unknown), rootCause='UNKNOWN', version='0.8', FORMATV='1.6.0.10', startDate=FineTime(Unknown), endDate=FineTime(Unknown), instrument='UNKNOWN', modelName='UNKNOWN', mission='_AGS', zInfo=None, **kwds)[源代码]

基类：fdi.dataset.baseproduct.BaseProduct

Product class schema 1.6 inheriting [‘BaseProduct’].

Automatically generated from fdi/dataset/resources/Product.yml on 2021-12-13 09:38:07.593902.

Description: Project level product

Generally a Product (inheriting BaseProduct) has project-wide attributes and can be extended to define a plethora of specialized products.

Initializes instances with more metadata as attributes, set to default values.

Put description keyword argument here to allow e.g. BaseProduct(“foo”) and description=’foo’

__init__(description='UNKNOWN', typ_='Product', level='ALL', creator='UNKNOWN', creationDate=FineTime(Unknown), rootCause='UNKNOWN', version='0.8', FORMATV='1.6.0.10', startDate=FineTime(Unknown), endDate=FineTime(Unknown), instrument='UNKNOWN', modelName='UNKNOWN', mission='_AGS', zInfo=None, **kwds)[源代码]

Initializes instances with more metadata as attributes, set to default values.

Put description keyword argument here to allow e.g. BaseProduct(“foo”) and description=’foo’

property endDate

property instrument

property mission

property modelName

property startDate

fdi.dataset.quantifiable module

class fdi.dataset.quantifiable.Quantifiable(unit=None, typecode=None, **kwds)[源代码]

基类：fdi.dataset.typecoded.Typecoded

A Quantifiable object is a numeric object that has a unit. $ x.unit = ELECTRON_VOLTS $ print x.unit eV [1.60218E-19 J]

Has a unit and a typecode (as in array.array.typecodes).

__init__(unit=None, typecode=None, **kwds)[源代码]: Has a unit and a typecode (as in array.array.typecodes).

getUnit()[源代码]: Returns the unit related to this object.

setUnit(unit)[源代码]: Sets the unit of this object.

property unit

fdi.dataset.readonlydict module

fdi.dataset.readonlydict.ReadOnlyDict: alias of fdi.dataset.readonlydict.frozendict

class fdi.dataset.readonlydict.bReadOnlyDict[源代码]

基类：dict

Dictionary that is read-only and returns all values of dict type to ReadOnlyDict type so they, too, cannot be modified.

Based on https://stackoverflow.com/a/61700719/13472124

clear(*args, **kwargs)

pop(*args, **kwargs)

popitem(*args, **kwargs)

setdefault(*args, **kwargs)

update(*args, **kwargs)

class fdi.dataset.readonlydict.frozendict(*args, **kw)[源代码]

基类：dict

Extended version of frozent dict.

This extended version of the code above will also “freeze” dictionaries and lists stored as values of the dictionary. If dictionaries/lists are found among the values, they will be handled recursively.

Oren Tirosh, Ero Carrera, Søren Løvborg

https://code.activestate.com/recipes/414283/

__init__(*args, **kw)[源代码]

property clear

property pop

property popitem

property setdefault

property update

fdi.dataset.readonlydict.make_readonly(d, excluded=None)[源代码]: Recursively make values of Mapping type at all levels read-only.

fdi.dataset.serializable module

class fdi.dataset.serializable.Serializable(*args, **kwds)[源代码]

基类：object

mh: Can be serialized. Has a _STID instance property to show its class information.

__init__(*args, **kwds)[源代码]

fits(*args, **kwds)[源代码]: Get a FITS representation.

serializable()[源代码]: Can be encoded with serializableEncoder

serialized(indent=None)[源代码]

tree(*args, **kwds)[源代码]: Get a directory-tree-like representation.

yaml(*args, **kwds)[源代码]: Get a YAML representation.

class fdi.dataset.serializable.SerializableEncoder(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, sort_keys=False, indent=None, separators=None, default=None)[源代码]

基类：json.encoder.JSONEncoder

can encode parameter and product etc such that they can be recovered with deserialize(). Python 3 treats string and unicode as unicode, encoded with utf-8, byte blocks as bytes, encoded with utf-8. Python 2 treats string as str and unicode as unicode, encoded with utf-8, byte blocks as str, encoded with utf-8

Constructor for JSONEncoder, with sensible defaults.

If skipkeys is false, then it is a TypeError to attempt encoding of keys that are not str, int, float or None. If skipkeys is True, such items are simply skipped.

If ensure_ascii is true, the output is guaranteed to be str objects with all incoming non-ASCII characters escaped. If ensure_ascii is false, the output can contain non-ASCII characters.

If check_circular is true, then lists, dicts, and custom encoded objects will be checked for circular references during encoding to prevent an infinite recursion (which would cause an OverflowError). Otherwise, no such check takes place.

If allow_nan is true, then NaN, Infinity, and -Infinity will be encoded as such. This behavior is not JSON specification compliant, but is consistent with most JavaScript based encoders and decoders. Otherwise, it will be a ValueError to encode such floats.

If sort_keys is true, then the output of dictionaries will be sorted by key; this is useful for regression tests to ensure that JSON serializations can be compared on a day-to-day basis.

If indent is a non-negative integer, then JSON array elements and object members will be pretty-printed with that indent level. An indent level of 0 will only insert newlines. None is the most compact representation.

If specified, separators should be an (item_separator, key_separator) tuple. The default is (’, ‘, ‘: ‘) if indent is None and (‘,’, ‘: ‘) otherwise. To get the most compact JSON representation, you should specify (‘,’, ‘:’) to eliminate whitespace.

If specified, default is a function that gets called for objects that can’t otherwise be serialized. It should return a JSON encodable version of the object or raise a TypeError.

default(obj)[源代码]

class fdi.dataset.serializable.SerializableEncoderAll(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, sort_keys=False, indent=None, separators=None, default=None)[源代码]