CSDM¶

class csdmpy.CSDM(filename='', version=None, description='', **kwargs)[source]¶

Bases: object

Create an instance of a CSDM class.

This class is based on the root CSDM object of the core scientific dataset (CSD) model. The class is a composition of the DependentVariable and Dimension instances, where an instance of the DependentVariable class describes a \(p\)-component dependent variable, and an instance of the Dimension class describes a dimension of a \(d\)-dimensional space. Additional attributes of this class are listed below.

Attributes Summary

`version`	Version number of the CSD model on file.
`description`	Description of the dataset.
`read_only`	If True, the data-file is serialized as read only, otherwise, False.
`tags`	List of tags attached to the dataset.
`timestamp`	Timestamp from when the file was last serialized.
`geographic_coordinate`	Geographic coordinate, if present, from where the file was last serialized.
`dimensions`	Tuple of the Dimension instances.
`x`	Alias for the dimensions attribute.
`dependent_variables`	Tuple of the DependentVariable instances.
`y`	Alias for the dependent_variables attribute.
`application`	Application metadata dictionary of the CSDM object.
`data_structure`	Json serialized string describing the CSDM class instance.
`filename`	Local file address of the current file.

Methods summary

`dict`	Serialize the CSDM instance as a python dictionary.
`to_dict`	Alias to the dict() method of the class.
`dumps`	Serialize the CSDM instance as a JSON data-exchange string.
`astype`	Return a copy of the CSDM object by converting the numeric type of each dependent variables components to the given value.
`to_list`	Return the dimension coordinates and dependent variable components as a list of numpy arrays.
`save`	Serialize the CSDM instance as a JSON data-exchange file.
`copy`	Create a copy of the current CSDM instance.
`split`	View of the dependent-variables as individual csdm objects.
`reshape`	Reshape the csdm object to shape.
`transpose`	Return a transpose of the CSDM object.
`fft`	Perform a FFT along the given dimension=axis, for linear dimension, assuming Nyquist-Shannon relation.
`to_positive_inc`	Convert the csdm object with negative increment dimensions to positive increments.

Numpy compatible attributes summary

`real`	Return a csdm object with only the real part of the dependent variable components.
`imag`	Return a csdm object with only the imaginary part of the dependent variable components.
`shape`	Return the count along each dimension of the csdm object.
`size`	Return the size of the dependent_variable components.
`T`	Return a csdm object with a transpose of the dataset.

Numpy compatible method summary

`max`	Return a csdm object of maximum dependent variable along a given axis.s
`min`	Return a csdm object of minimum dependent variable component along a given axis.
`clip`	Clip the dependent variable components between the min and max values.
`conj`	Return a complex conjugate of the csdm object.
`round`	Rounds a csdm object to the given decimals.
`sum`	Return a csdm object sum over a given axis.
`mean`	Return a csdm object mean over a given axis.
`var`	Return a csdm object variance over a given axis.
`std`	Return a csdm object standard deviation over a given axis.
`prod`	Return a csdm object product over a given axis.

Attributes documentation

version¶: Version number of the CSD model on file.

description¶

Description of the dataset. The default value is an empty string.

Example

>>> print(data.description)
A simulated sine curve.

Returns: A string of UTF-8 allows characters describing the dataset.
Raises: TypeError – When the assigned value is not a string.

read_only¶

If True, the data-file is serialized as read only, otherwise, False.

By default, the CSDM object loads a copy of the .csdf(e) file, irrespective of the value of the read_only attribute. The value of this attribute may be toggled at any time after the file import. When serializing the .csdf(e) file, if the value of the read_only attribute is found True, the file will be serialized as read only.

tags¶: List of tags attached to the dataset.

timestamp¶

Timestamp from when the file was last serialized. Attribute is real only.

The timestamp stamp is a string representation of the Coordinated Universal Time (UTC) formatted according to the iso-8601 standard.

Raises: AttributeError – When the attribute is modified.

geographic_coordinate¶

Geographic coordinate, if present, from where the file was last serialized. This attribute is read-only.

The geographic coordinates correspond to the location where the file was last serialized. If present, the geographic coordinates are described with three attributes, the required latitude and longitude, and an optional altitude.

Raises: AttributeError – When the attribute is modified.

dimensions¶: Tuple of the Dimension instances.

x¶: Alias for the dimensions attribute.

dependent_variables¶: Tuple of the DependentVariable instances.

y¶: Alias for the dependent_variables attribute.

application¶

Application metadata dictionary of the CSDM object.

>>> print(data.application)
None

By default, the application attribute is an empty object, that is, the application metadata stored by the previous application is ignored upon file import.

The application metadata may, however, be retained with a request via the load() method. This feature may be useful to related applications where application metadata might contain additional information. The attribute may be updated with a python dictionary.

The application attribute is where an application can place its own metadata as a python dictionary object containing application specific metadata, using a reverse domain name notation string as the attribute key, for example,

Example

>>> data.application = {
...     "com.example.myApp" : {
...         "myApp_key": "myApp_metadata"
...      }
... }
>>> print(data.application)
{'com.example.myApp': {'myApp_key': 'myApp_metadata'}}

Returns: Python dictionary object with the application metadata.

data_structure¶

Json serialized string describing the CSDM class instance.

The data_structure attribute is only intended for a quick preview of the dataset. This JSON serialized string from this attribute avoids displaying large datasets. Do not use the value of this attribute to save the data to a file, instead use the save() methods of the instance.

Raises: AttributeError – When modified.

filename¶: Local file address of the current file.

Numpy compatible attributes documentation

real¶: Return a csdm object with only the real part of the dependent variable components.

imag¶: Return a csdm object with only the imaginary part of the dependent variable components.

shape¶: Return the count along each dimension of the csdm object.

size¶: Return the size of the dependent_variable components.

T¶: Return a csdm object with a transpose of the dataset.

Methods documentation

dict(update_timestamp=False, read_only=False)[source]¶

Serialize the CSDM instance as a python dictionary.

Parameters

update_timestamp (bool) – If True, timestamp is updated to current time.
read_only (bool) – If true, the read_only flag is set true.

Example

>>> data.dict()['csdm']['version']
'1.0'

to_dict(update_timestamp=False, read_only=False)[source]¶: Alias to the dict() method of the class.

dumps(update_timestamp=False, read_only=False, **kwargs)[source]¶

Serialize the CSDM instance as a JSON data-exchange string.

Parameters

update_timestamp (bool) – If True, timestamp is updated to current time.
read_only (bool) – If true, the file is serialized as read_only.

Example

>>> data.dumps()[:63] # first 63 characters
'{"csdm": {"version": "1.0", "timestamp": "1994-11-05T13:15:30Z"'

save(filename='', read_only=False, output_device=None, indent=0)[source]¶

Serialize the CSDM instance as a JSON data-exchange file.

There are two types of file serialization extensions, .csdf and .csdfe. In the CSD model, when every instance of the DependentVariable objects from a CSDM class has an internal subtype, the corresponding CSDM instance is serialized with a .csdf file extension. If any single DependentVariable instance has an external subtype, the CSDM instance is serialized with a .csdfe file extension. The two different file extensions are used to alert the end-user of the possible deserialization error associated with the .csdfe file extensions had the external data file becomes inaccessible.

In csdmpy, however, irrespective of the dependent variable subtypes from the serialized JSON file, by default, all instances of DependentVariable class are treated an internal after import. Therefore, when serialized, the CSDM object should be stored as a .csdf file.

To store a file as a .csdfe file, the user much set the value of the encoding attribute from the dependent variables to raw. In which case, a binary file named filename_i.dat will be generated where \(i\) is the \(i^\text{th}\) dependent variable. The parameter filename is an argument of this method.

Note

Only dependent variables with encoding="raw" will be serialized to a binary file.

Parameters

filename (str) – The filename of the serialized file.
read_only (bool) – If true, the file is serialized as read_only.
output_device (object) – Object where the data is written. If provided, the argument filename become irrelevant.

Example

>>> data.save('my_file.csdf')

to_list()[source]¶

Return the dimension coordinates and dependent variable components as a list of numpy arrays. For multiple dependent variables, the components of each dependent variable is appended in the order of the dependent variables.

For example,

A 2D{1} will be packed as \([x_{0}, x_{1}, y_{0,0}]\)
A 2D{3} will be packed as \([x_{0}, x_{1}, y_{0,0}, y_{0,1}, y_{0,2}]\)
A 1D{1,2} will be packed as \([x_{0}, y_{0,0}, y_{1,0}, y_{1,1}]\)

where \(x_i\) represents the \(i^\text{th}\) dimension and \(y_{i,j}\) represents the \(j^\text{th}\) component of the \(i^\text{th}\) dependent variable.

astype(numeric_type)[source]¶

Return a copy of the CSDM object by converting the numeric type of each dependent variables components to the given value.

Parameters: numeric_type – A numpy dtype or a string with a valid numeric type

Example

>>> data_32 = data_64.astype('float32')  

copy()[source]¶

Create a copy of the current CSDM instance.

Returns: A CSDM instance.

Example

>>> data2 = data.copy()

split()[source]¶

View of the dependent-variables as individual csdm objects.

Returns: A list of CSDM objects, each with one dependent variable. The objects are returned as a view.

Example

>>> # data contains two dependent variables
>>> d1, d2 = data.split()  

transpose()[source]¶: Return a transpose of the CSDM object.

fft(axis=0)[source]¶

Perform a FFT along the given dimension=axis, for linear dimension, assuming Nyquist-Shannon relation.

Parameters: axis – dimension index along which the FFT is performed.

The FFT method uses the complex_fft attribute of the Dimension object to decide whether a forward or inverse Fourier transform is performed. If the value of the complex_fft is True, an inverse FFT is performed, otherwise a forward FFT.

For FFT process, this function is equivalent to performing

phase = np.exp(-2j * np.pi * coordinates_offset * reciprocal_coordinates)
x_fft = sp.fft.fftshift(sp.fft.fft(x)) * phase

over all components for every dependent variable.

Similarly, for inverse FFT process, this function is equivalent to performing

phase = np.exp(2j * np.pi * reciprocal_coordinates_offset * coordinates)
x = sp.fft.ifft(sp.fft.ifftshift(x_fft * phase))

over all components for every dependent variable.

Returns: A CSDM object with the Fourier Transform data.

reshape(shape)[source]¶

Reshape the csdm object to shape.

Parameters: shape – A list of dimension objects or integers.

to_positive_inc()[source]¶

Convert the csdm object with negative increment dimensions to positive increments.

Parameters: csdm_obj – CSDM object

Numpy compatible method documentation

max(axis=None)[source]¶

Return a csdm object of maximum dependent variable along a given axis.s

Parameters: axis – An integer or None or a tuple of m integers corresponding to the dimension index/indices along which the operation is performed. If None, the output is over all dimensions per dependent variable.
Returns: A CSDM object with m dimensions removed, or a numpy array when dimension is None.

Example

>>> data.max()
<Quantity 0.95105654>

min(axis=None)[source]¶

Return a csdm object of minimum dependent variable component along a given axis.

Parameters: axis – An integer or None or a tuple of m integers corresponding to the dimension index/indices along which the operation is performed. If None, the output is over all dimensions per dependent variable.
Returns: A CSDM object with m dimensions removed, or a list when axis is None.

clip(min=None, max=None)[source]¶

Clip the dependent variable components between the min and max values.

Parameters

min – The minimum clip value.
max – The maximum clip value.

Returns

A CSDM object with values clipped between min and max.

conj()[source]¶: Return a complex conjugate of the csdm object.

round(decimals=0)[source]¶: Rounds a csdm object to the given decimals.

sum(axis=None)[source]¶

Return a csdm object sum over a given axis.

Parameters: axis – An integer or None or a tuple of m integers corresponding to the dimension index/indices along which the operation is performed. If None, the output is over all dimensions per dependent variable.
Returns: A CSDM object with m dimensions removed, or a list when axis is None.

mean(axis=None)[source]¶

Return a csdm object mean over a given axis.

Parameters: axis – An integer or None or a tuple of m integers corresponding to the dimension index/indices along which the operation is performed. If None, the output is over all dimensions per dependent variable.
Returns: A CSDM object with m dimensions removed, or a list when axis is None.

var(axis=None)[source]¶

Return a csdm object variance over a given axis.

Parameters: axis – An integer or None or a tuple of m integers corresponding to the dimension index/indices along which the operation is performed. If None, the output is over all dimensions per dependent variable.
Returns: A CSDM object with m dimensions removed, or a list when axis is None.

std(axis=None)[source]¶

Return a csdm object standard deviation over a given axis.

Parameters: axis – An integer or None or a tuple of m integers corresponding to the dimensions index/indices along which the operation is performed. If None, the output is over all dimensions per dependent variable.
Returns: A CSDM object with m dimensions removed, or a list when axis is None.

prod(axis=None)[source]¶

Return a csdm object product over a given axis.

Parameters: axis – An integer or None or a tuple of m integers corresponding to the dimension index/indices along which the operation is performed. If None, the output is over all dimensions per dependent variable.
Returns: A CSDM object with m dimensions removed, or a list when axis is None.