ParameterizedInstanceTemplate class#

class laygo2.object.template.ParameterizedInstanceTemplate(libname, cellname, bbox_func=None, pins_func=None)[source]#

Bases: Template

The ParameterizedInstanceTemplate class implements a template for generating instances with varying size (bounding box) and pin configurations based on input parameters, such as instances mapped to Cadence Virtuoso’s pcells or Pycells.

Public Data Attributes:

libname

The libname of the instance to be generated.

cellname

The cellname of the instance to be generated.
Inherited from Template

name

Template name.

Public Methods:

__init__(libname, cellname[, bbox_func, ...])

Constructor of ParameterizedInstanceTemplate class.

bbox([params])

Bounding box of the template object.

pins([params])

Return pin dictionary of ParameterizedInstanceTemplate object.

generate([name, shape, pitch, transform, ...])

Generate an Instance object corresponding to the template and its input parameters.
Inherited from Template

__init__([name])

The constructor function.

__str__()

Return a string representation of this template's information.

summarize()

Return the summary of the template information.

height([params])

int: Return the height of the template.

width([params])

int: Return the width of the template.

size([params])

int: Return the size of the template.

bbox([params])

numpy.ndarray: (Abstract method) the physical bounding box of the template.

pins([params])

dict: (Abstract method) Dictionary storing the pins of the template.

generate([name, shape, pitch, transform, ...])

instance: (Abstract method) Generate an instance from the template.
__init__(libname, cellname, bbox_func=None, pins_func=None)[source]#

Constructor of ParameterizedInstanceTemplate class.

Parameters:

  • libname (str) – The library name.

  • cellname (str) – The cell name of the template.

  • bbox_func (callable) – The function that computes the bounding box of the template from its input parameters.

  • pins_func (callable) – The function that returns a dictionary that contains its pin objects for its input parameters.

Return type:

laygo2.object.template.ParameterizedInstanceTemplate

Example

>>> import numpy as np
>>> from laygo2.object.template import ParameterizedInstanceTemplate
>>> from laygo2.object.physical import Pin
>>> # bbox computation function.
>>> def pcell_bbox_func(params):
        return np.array([[0, 0], [100 * params["mult"], 100]])
>>> # pin generation function.
>>> def pcell_pins_func(params):
>>>     template_pins = dict()
>>>     for i in range(params["mult"]):
>>>         template_pins["in" + str(i)] = Pin(
>>>             xy=[[i * 100 + 0, 0], [i * 100 + 10, 10]],
>>>             layer=["M1", "drawing"],
>>>             netname="in" + str(i),
>>>         )
>>>         template_pins["out" + str(i)] = Pin(
>>>             xy=[[i * 100 + 90, 90], [i * 100 + 90, 100]],
>>>             layer=["M1", "drawing"],
>>>             netname="out" + str(i),
>>>         )
>>>     return template_pins
>>> # Create a template
>>> pcell_temp = ParameterizedInstanceTemplate(
>>>     libname="mylib",
>>>     cellname="mypcelltemplate",
>>>     bbox_func=pcell_bbox_func,
>>>     pins_func=pcell_pins_func,
>>> )
>>> # Generate an instance for input parameters.
>>> pcell_inst_params = {"mult": 4}
>>> pcell_inst = pcell_temp.generate(
>>>    name="mypcellinst",
>>>    transform="R0",
>>>    params=pcell_inst_params,
>>> )
>>> # display
>>> print(pcell_temp)
    <laygo2.object.template.ParameterizedInstanceTemplate object at 0x000001B1BA91D9C0>
    name: mypcelltemplate,
    class: ParameterizedInstanceTemplate,
>>> print(pcell_inst)
    xy: [0, 0],
    params: {'mult': 4},
    size: [400, 100],
    shape: None,
    pitch: [400, 100],
    transform: R0,
    pins: {'in0': <laygo2.object.physical.Pin object at 0x000001B1BA91FCA0>,
           'out0': <laygo2.object.physical.Pin object at 0x000001B1BA91FC70>,
           'in1': <laygo2.object.physical.Pin object at 0x000001B1BA91FC10>,
           'out1': <laygo2.object.physical.Pin object at 0x000001B1BA91E8C0>,
           'in2': <laygo2.object.physical.Pin object at 0x000001B1BA91E890>,
           'out2': <laygo2.object.physical.Pin object at 0x000001B1BA91FBE0>,
           'in3': <laygo2.object.physical.Pin object at 0x000001B1BA91E7D0>,
           'out3': <laygo2.object.physical.Pin object at 0x000001B1BA91E710>},
_images/object_template_ParameterizedInstanceTemplate_init.png
bbox(params=None)[source]#

Bounding box of the template object.

Parameters:

params (dict) – A dictionary that contains input parameters corresponding to the bounding box to be computed.

Returns:

numpy.ndarray – coordinates corresponding to the input parameters.

Return type:

A 2x2 numpy array that contains the bounding box

Example

>>> import numpy as np
>>> from laygo2.object.template import ParameterizedInstanceTemplate
>>> from laygo2.object.physical import Pin
>>> # bbox computation function.
>>> def pcell_bbox_func(params):
        return np.array([[0, 0], [100 * params["mult"], 100]])
>>> # pin generation function.
>>> def pcell_pins_func(params):
>>>     template_pins = dict()
>>>     for i in range(params["mult"]):
>>>         template_pins["in" + str(i)] = Pin(
>>>             xy=[[i * 100 + 0, 0], [i * 100 + 10, 10]],
>>>             layer=["M1", "drawing"],
>>>             netname="in" + str(i),
>>>         )
>>>         template_pins["out" + str(i)] = Pin(
>>>             xy=[[i * 100 + 90, 90], [i * 100 + 90, 100]],
>>>             layer=["M1", "drawing"],
>>>             netname="out" + str(i),
>>>         )
>>>     return template_pins
>>> # Create a template
>>> pcell_temp = ParameterizedInstanceTemplate(
>>>     libname="mylib",
>>>     cellname="mypcelltemplate",
>>>     bbox_func=pcell_bbox_func,
>>>     pins_func=pcell_pins_func,
>>> )
>>> # Compute bbox for input parameters
>>> pcell_inst_params = {"mult": 4}
>>> pcell_temp.bbox(params=pcell_inst_params)
array([[  0,   0],
       [400, 100]])
_images/object_template_ParameterizedInstanceTemplate_bbox.png
generate(name=None, shape=None, pitch=None, transform='R0', netmap=None, params=None)[source]#

Generate an Instance object corresponding to the template and its input parameters.

Parameters:

  • name (str) – name of the instance to be generated.

  • shape (numpy.ndarray, optional.) – shape of the object to be generated.

  • pitch (numpy.ndarray, optional.) – pitch of the object to be generated.

  • transform (str, optional.) – transformation attribute of the entity to be generated.

  • netmap (dict, optional.) – dictionary containing netmap conversion information of pins.

  • params (dict, optional.) – dictionary having the entity attributes.

Returns:

laygo2.object.physical.Instance

Return type:

The generated Instance object

Example

>>> import numpy as np
>>> from laygo2.object.template import ParameterizedInstanceTemplate
>>> from laygo2.object.physical import Pin
>>> # bbox computation function.
>>> def pcell_bbox_func(params):
        return np.array([[0, 0], [100 * params["mult"], 100]])
>>> # pin generation function.
>>> def pcell_pins_func(params):
>>>     template_pins = dict()
>>>     for i in range(params["mult"]):
>>>         template_pins["in" + str(i)] = Pin(
>>>             xy=[[i * 100 + 0, 0], [i * 100 + 10, 10]],
>>>             layer=["M1", "drawing"],
>>>             netname="in" + str(i),
>>>         )
>>>         template_pins["out" + str(i)] = Pin(
>>>             xy=[[i * 100 + 90, 90], [i * 100 + 90, 100]],
>>>             layer=["M1", "drawing"],
>>>             netname="out" + str(i),
>>>         )
>>>     return template_pins
>>> # Create a template
>>> pcell_temp = ParameterizedInstanceTemplate(
>>>     libname="mylib",
>>>     cellname="mypcelltemplate",
>>>     bbox_func=pcell_bbox_func,
>>>     pins_func=pcell_pins_func,
>>> )
>>> # Generate an instance for input parameters.
>>> pcell_inst_params = {"mult": 4}
>>> pcell_inst = pcell_temp.generate(
>>>    name="mypcellinst",
>>>    transform="R0",
>>>    params=pcell_inst_params,
>>> )
>>> # display
>>> print(pcell_temp)
    <laygo2.object.template.ParameterizedInstanceTemplate object at 0x000001B1BA91D9C0>
    name: mypcelltemplate,
    class: ParameterizedInstanceTemplate,
>>> print(pcell_inst)
    xy: [0, 0],
    params: {'mult': 4},
    size: [400, 100],
    shape: None,
    pitch: [400, 100],
    transform: R0,
    pins: {'in0': <laygo2.object.physical.Pin object at 0x000001B1BA91FCA0>,
           'out0': <laygo2.object.physical.Pin object at 0x000001B1BA91FC70>,
           'in1': <laygo2.object.physical.Pin object at 0x000001B1BA91FC10>,
           'out1': <laygo2.object.physical.Pin object at 0x000001B1BA91E8C0>,
           'in2': <laygo2.object.physical.Pin object at 0x000001B1BA91E890>,
           'out2': <laygo2.object.physical.Pin object at 0x000001B1BA91FBE0>,
           'in3': <laygo2.object.physical.Pin object at 0x000001B1BA91E7D0>,
           'out3': <laygo2.object.physical.Pin object at 0x000001B1BA91E710>},
_images/object_template_ParameterizedInstanceTemplate_generate.png
height(params=None)#

int: Return the height of the template.

pins(params=None)[source]#

Return pin dictionary of ParameterizedInstanceTemplate object.

Parameters:

params (dict) – A dictionary that contains input parameters corresponding to the pin objects to be produced.

Returns:

dict – input parameters.

Return type:

A dictionary that contains pin object corresponding to the

Example

>>> import numpy as np
>>> from laygo2.object.template import ParameterizedInstanceTemplate
>>> from laygo2.object.physical import Pin
>>> # bbox computation function.
>>> def pcell_bbox_func(params):
        return np.array([[0, 0], [100 * params["mult"], 100]])
>>> # pin generation function.
>>> def pcell_pins_func(params):
>>>     template_pins = dict()
>>>     for i in range(params["mult"]):
>>>         template_pins["in" + str(i)] = Pin(
>>>             xy=[[i * 100 + 0, 0], [i * 100 + 10, 10]],
>>>             layer=["M1", "drawing"],
>>>             netname="in" + str(i),
>>>         )
>>>         template_pins["out" + str(i)] = Pin(
>>>             xy=[[i * 100 + 90, 90], [i * 100 + 90, 100]],
>>>             layer=["M1", "drawing"],
>>>             netname="out" + str(i),
>>>         )
>>>     return template_pins
>>> # Create a template
>>> pcell_temp = ParameterizedInstanceTemplate(
>>>     libname="mylib",
>>>     cellname="mypcelltemplate",
>>>     bbox_func=pcell_bbox_func,
>>>     pins_func=pcell_pins_func,
>>> )
>>> # Compute bbox for input parameters
>>> pcell_inst_params = {"mult": 4}
>>> pcell_temp.pins(params=pcell_inst_params)
    {'in0': <laygo2.object.physical.Pin object at 0x000001B1BA91F7C0>,
     'out0': <laygo2.object.physical.Pin object at 0x000001B1BA91E830>,
     'in1': <laygo2.object.physical.Pin object at 0x000001B1BA91DAB0>,
     'out1': <laygo2.object.physical.Pin object at 0x000001B1BA91E860>,
     'in2': <laygo2.object.physical.Pin object at 0x000001B1BA91E560>,
     'out2': <laygo2.object.physical.Pin object at 0x000001B1BA91E800>,
     'in3': <laygo2.object.physical.Pin object at 0x000001B1BA91E770>,
     'out3': <laygo2.object.physical.Pin object at 0x000001B1BA91EA40>}
_images/object_template_ParameterizedInstanceTemplate_pins.png
size(params=None)#

int: Return the size of the template.

summarize()#

Return the summary of the template information.

width(params=None)#

int: Return the width of the template.

_abc_impl = <_abc._abc_data object>#
_bbox = None#
_pins = None#
cellname = None#

The cellname of the instance to be generated.

Type:

str

libname = None#

The libname of the instance to be generated.

Type:

str

name = None#

Template name.

Type:

str

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