2014-09-02 17:03:50 +00:00
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#!/usr/bin/env python3
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# KLL Compiler Containers
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#
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KLL Compiler Re-Write
This was many months of efforts in re-designing how the KLL compiler should work.
The major problem with the original compiler was how difficult it was to extend language wise.
This lead to many delays in KLL 0.4 and 0.5 being implemented.
The new design is a multi-staged compiler, where even tokenization occurs over multiple stages.
This allows individual parsing and token regexes to be expressed more simply without affect other expressions.
Another area of change is the concept of Contexts.
In the original KLL compiler the idea of a cache assigned was "hacked" on when I realized the language was "broken" (after nearly finishing the compiler).
Since assignment order is generally considered not to matter for keymappings, I created a "cached" assignment where the whole file is read into a sub-datastructure, then apply to the master datastructure.
Unfortunately, this wasn't really all that clear, so it was annoying to work with.
To remedy this, I created KLL Contexts, which contain information about a group of expressions.
Not only can these groups can be merged with other Contexts, they have historical data about how they were generated allowing for errors very late in processing to be pin-pointed back to the offending kll file.
Backends work nearly the same as they did before.
However, all call-backs for capability evaluations have been removed.
This makes the interface much cleaner as Contexts can only be symbolically merged now.
(Previously datastructures did evaluation merges where the ScanCode or Capability was looked up right before passing to the backend, but this required additional information from the backend).
Many of the old parsing and tokenization rules have been reused, along with the hid_dict.py code.
The new design takes advantage of processor pools to handle multithreading where it makes sense.
For example, all specified files are loaded into ram simulatenously rather than sparingly reading from.
The reason for this is so that each Context always has all the information it requires at all times.
kll
- Program entry point (previously kll.py)
- Very small now, does some setting up of command-line args
- Most command-line args are specified by the corresponding processing stage
common/channel.py
- Pixel Channel container classes
common/context.py
- Context container classes
- As is usual with other files, blank classes inherit a base class
- These blank classes are identified by the class name itself to handle special behaviour
- And if/when necessary functions are re-implemented
- MergeConext class facilitates merging of contexts while maintaining lineage
common/expression.py
- Expression container classes
* Expression base class
* AssignmentExpression
* NameAssociationExpression
* DataAssociationExpression
* MapExpression
- These classes are used to store expressions after they have finished parsing and tokenization
common/file.py
- Container class for files being read by the KLL compiler
common/emitter.py
- Base class for all KLL emitters
- TextEmitter for dealing with text file templates
common/hid_dict.py
- Slightly modified version of kll_lib/hid_dict.py
common/id.py
- Identification container classes
- Used to indentify different types of elements used within the KLL language
common/modifier.py
- Container classes for animation and pixel change functions
common/organization.py
- Data structure merging container classes
- Contains all the sub-datastructure classes as well
- The Organization class handles the merge orchestration and expression insertion
common/parse.py
- Parsing rules for funcparserlib
- Much of this file was taken from the original kll.py
- Many changes to support the multi-stage processing and support KLL 0.5
common/position.py
- Container class dealing with physical positions
common/schedule.py
- Container class dealing with scheduling and timing events
common/stage.py
- Contains ControlStage and main Stage classes
* CompilerConfigurationStage
* FileImportStage
* PreprocessorStage
* OperationClassificationStage
* OperationSpecificsStage
* OperationOrganizationStage
* DataOrganziationStage
* DataFinalizationStage
* DataAnalysisStage
* CodeGenerationStage
* ReportGenerationStage
- Each of these classes controls the life-cycle of each stage
- If multi-threading is desired, it must be handled within the class
* The next stage will not start until the current stage is finished
- Errors are handled such that as many errors as possible are recorded before forcing an exit
* The exit is handled at the end of each stage if necessary
- Command-line arguments for each stage can be defined if necessary (they are given their own grouping)
- Each stage can pull variables and functions from other stages if necessary using a name lookup
* This means you don't have to worry about over-arching datastructures
emitters/emitters.py
- Container class for KLL emitters
- Handles emitter setup and selection
emitters/kiibohd/kiibohd.py
- kiibohd .h file KLL emitter
- Re-uses some backend code from the original KLL compiler
funcparserlib/parser.py
- Added debug mode control
examples/assignment.kll
examples/defaultMapExample.kll
examples/example.kll
examples/hhkbpro2.kll
examples/leds.kll
examples/mapping.kll
examples/simple1.kll
examples/simple2.kll
examples/simpleExample.kll
examples/state_scheduling.kll
- Updating/Adding rules for new compiler and KLL 0.4 + KLL 0.5 support
2016-09-02 06:48:13 +00:00
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# Copyright (C) 2014-2016 by Jacob Alexander
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2014-09-02 17:03:50 +00:00
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#
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# This file is free software: you can redistribute it and/or modify
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# it under the terms of the GNU General Public License as published by
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# the Free Software Foundation, either version 3 of the License, or
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# (at your option) any later version.
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#
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# This file is distributed in the hope that it will be useful,
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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# GNU General Public License for more details.
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#
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# You should have received a copy of the GNU General Public License
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# along with this file. If not, see <http://www.gnu.org/licenses/>.
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### Imports ###
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2014-09-10 00:49:46 +00:00
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import copy
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2014-09-02 17:03:50 +00:00
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### Decorators ###
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KLL Compiler Re-Write
This was many months of efforts in re-designing how the KLL compiler should work.
The major problem with the original compiler was how difficult it was to extend language wise.
This lead to many delays in KLL 0.4 and 0.5 being implemented.
The new design is a multi-staged compiler, where even tokenization occurs over multiple stages.
This allows individual parsing and token regexes to be expressed more simply without affect other expressions.
Another area of change is the concept of Contexts.
In the original KLL compiler the idea of a cache assigned was "hacked" on when I realized the language was "broken" (after nearly finishing the compiler).
Since assignment order is generally considered not to matter for keymappings, I created a "cached" assignment where the whole file is read into a sub-datastructure, then apply to the master datastructure.
Unfortunately, this wasn't really all that clear, so it was annoying to work with.
To remedy this, I created KLL Contexts, which contain information about a group of expressions.
Not only can these groups can be merged with other Contexts, they have historical data about how they were generated allowing for errors very late in processing to be pin-pointed back to the offending kll file.
Backends work nearly the same as they did before.
However, all call-backs for capability evaluations have been removed.
This makes the interface much cleaner as Contexts can only be symbolically merged now.
(Previously datastructures did evaluation merges where the ScanCode or Capability was looked up right before passing to the backend, but this required additional information from the backend).
Many of the old parsing and tokenization rules have been reused, along with the hid_dict.py code.
The new design takes advantage of processor pools to handle multithreading where it makes sense.
For example, all specified files are loaded into ram simulatenously rather than sparingly reading from.
The reason for this is so that each Context always has all the information it requires at all times.
kll
- Program entry point (previously kll.py)
- Very small now, does some setting up of command-line args
- Most command-line args are specified by the corresponding processing stage
common/channel.py
- Pixel Channel container classes
common/context.py
- Context container classes
- As is usual with other files, blank classes inherit a base class
- These blank classes are identified by the class name itself to handle special behaviour
- And if/when necessary functions are re-implemented
- MergeConext class facilitates merging of contexts while maintaining lineage
common/expression.py
- Expression container classes
* Expression base class
* AssignmentExpression
* NameAssociationExpression
* DataAssociationExpression
* MapExpression
- These classes are used to store expressions after they have finished parsing and tokenization
common/file.py
- Container class for files being read by the KLL compiler
common/emitter.py
- Base class for all KLL emitters
- TextEmitter for dealing with text file templates
common/hid_dict.py
- Slightly modified version of kll_lib/hid_dict.py
common/id.py
- Identification container classes
- Used to indentify different types of elements used within the KLL language
common/modifier.py
- Container classes for animation and pixel change functions
common/organization.py
- Data structure merging container classes
- Contains all the sub-datastructure classes as well
- The Organization class handles the merge orchestration and expression insertion
common/parse.py
- Parsing rules for funcparserlib
- Much of this file was taken from the original kll.py
- Many changes to support the multi-stage processing and support KLL 0.5
common/position.py
- Container class dealing with physical positions
common/schedule.py
- Container class dealing with scheduling and timing events
common/stage.py
- Contains ControlStage and main Stage classes
* CompilerConfigurationStage
* FileImportStage
* PreprocessorStage
* OperationClassificationStage
* OperationSpecificsStage
* OperationOrganizationStage
* DataOrganziationStage
* DataFinalizationStage
* DataAnalysisStage
* CodeGenerationStage
* ReportGenerationStage
- Each of these classes controls the life-cycle of each stage
- If multi-threading is desired, it must be handled within the class
* The next stage will not start until the current stage is finished
- Errors are handled such that as many errors as possible are recorded before forcing an exit
* The exit is handled at the end of each stage if necessary
- Command-line arguments for each stage can be defined if necessary (they are given their own grouping)
- Each stage can pull variables and functions from other stages if necessary using a name lookup
* This means you don't have to worry about over-arching datastructures
emitters/emitters.py
- Container class for KLL emitters
- Handles emitter setup and selection
emitters/kiibohd/kiibohd.py
- kiibohd .h file KLL emitter
- Re-uses some backend code from the original KLL compiler
funcparserlib/parser.py
- Added debug mode control
examples/assignment.kll
examples/defaultMapExample.kll
examples/example.kll
examples/hhkbpro2.kll
examples/leds.kll
examples/mapping.kll
examples/simple1.kll
examples/simple2.kll
examples/simpleExample.kll
examples/state_scheduling.kll
- Updating/Adding rules for new compiler and KLL 0.4 + KLL 0.5 support
2016-09-02 06:48:13 +00:00
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## Print Decorator Variables
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2014-09-02 17:03:50 +00:00
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ERROR = '\033[5;1;31mERROR\033[0m:'
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### Parsing ###
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2014-09-17 00:01:40 +00:00
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KLL Compiler Re-Write
This was many months of efforts in re-designing how the KLL compiler should work.
The major problem with the original compiler was how difficult it was to extend language wise.
This lead to many delays in KLL 0.4 and 0.5 being implemented.
The new design is a multi-staged compiler, where even tokenization occurs over multiple stages.
This allows individual parsing and token regexes to be expressed more simply without affect other expressions.
Another area of change is the concept of Contexts.
In the original KLL compiler the idea of a cache assigned was "hacked" on when I realized the language was "broken" (after nearly finishing the compiler).
Since assignment order is generally considered not to matter for keymappings, I created a "cached" assignment where the whole file is read into a sub-datastructure, then apply to the master datastructure.
Unfortunately, this wasn't really all that clear, so it was annoying to work with.
To remedy this, I created KLL Contexts, which contain information about a group of expressions.
Not only can these groups can be merged with other Contexts, they have historical data about how they were generated allowing for errors very late in processing to be pin-pointed back to the offending kll file.
Backends work nearly the same as they did before.
However, all call-backs for capability evaluations have been removed.
This makes the interface much cleaner as Contexts can only be symbolically merged now.
(Previously datastructures did evaluation merges where the ScanCode or Capability was looked up right before passing to the backend, but this required additional information from the backend).
Many of the old parsing and tokenization rules have been reused, along with the hid_dict.py code.
The new design takes advantage of processor pools to handle multithreading where it makes sense.
For example, all specified files are loaded into ram simulatenously rather than sparingly reading from.
The reason for this is so that each Context always has all the information it requires at all times.
kll
- Program entry point (previously kll.py)
- Very small now, does some setting up of command-line args
- Most command-line args are specified by the corresponding processing stage
common/channel.py
- Pixel Channel container classes
common/context.py
- Context container classes
- As is usual with other files, blank classes inherit a base class
- These blank classes are identified by the class name itself to handle special behaviour
- And if/when necessary functions are re-implemented
- MergeConext class facilitates merging of contexts while maintaining lineage
common/expression.py
- Expression container classes
* Expression base class
* AssignmentExpression
* NameAssociationExpression
* DataAssociationExpression
* MapExpression
- These classes are used to store expressions after they have finished parsing and tokenization
common/file.py
- Container class for files being read by the KLL compiler
common/emitter.py
- Base class for all KLL emitters
- TextEmitter for dealing with text file templates
common/hid_dict.py
- Slightly modified version of kll_lib/hid_dict.py
common/id.py
- Identification container classes
- Used to indentify different types of elements used within the KLL language
common/modifier.py
- Container classes for animation and pixel change functions
common/organization.py
- Data structure merging container classes
- Contains all the sub-datastructure classes as well
- The Organization class handles the merge orchestration and expression insertion
common/parse.py
- Parsing rules for funcparserlib
- Much of this file was taken from the original kll.py
- Many changes to support the multi-stage processing and support KLL 0.5
common/position.py
- Container class dealing with physical positions
common/schedule.py
- Container class dealing with scheduling and timing events
common/stage.py
- Contains ControlStage and main Stage classes
* CompilerConfigurationStage
* FileImportStage
* PreprocessorStage
* OperationClassificationStage
* OperationSpecificsStage
* OperationOrganizationStage
* DataOrganziationStage
* DataFinalizationStage
* DataAnalysisStage
* CodeGenerationStage
* ReportGenerationStage
- Each of these classes controls the life-cycle of each stage
- If multi-threading is desired, it must be handled within the class
* The next stage will not start until the current stage is finished
- Errors are handled such that as many errors as possible are recorded before forcing an exit
* The exit is handled at the end of each stage if necessary
- Command-line arguments for each stage can be defined if necessary (they are given their own grouping)
- Each stage can pull variables and functions from other stages if necessary using a name lookup
* This means you don't have to worry about over-arching datastructures
emitters/emitters.py
- Container class for KLL emitters
- Handles emitter setup and selection
emitters/kiibohd/kiibohd.py
- kiibohd .h file KLL emitter
- Re-uses some backend code from the original KLL compiler
funcparserlib/parser.py
- Added debug mode control
examples/assignment.kll
examples/defaultMapExample.kll
examples/example.kll
examples/hhkbpro2.kll
examples/leds.kll
examples/mapping.kll
examples/simple1.kll
examples/simple2.kll
examples/simpleExample.kll
examples/state_scheduling.kll
- Updating/Adding rules for new compiler and KLL 0.4 + KLL 0.5 support
2016-09-02 06:48:13 +00:00
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## Containers
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2014-09-17 00:01:40 +00:00
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2015-08-16 04:29:18 +00:00
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class ScanCode:
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# Container for ScanCodes
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#
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# scancode - Non-interconnect adjusted scan code
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# interconnect_id - Unique id for the interconnect node
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def __init__( self, scancode, interconnect_id ):
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self.scancode = scancode
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self.interconnect_id = interconnect_id
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def __eq__( self, other ):
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return self.dict() == other.dict()
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def __repr__( self ):
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return repr( self.dict() )
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def dict( self ):
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return {
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'ScanCode' : self.scancode,
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'Id' : self.interconnect_id,
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}
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# Calculate the actual scancode using the offset list
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def offset( self, offsetList ):
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if self.interconnect_id > 0:
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return self.scancode + offsetList[ self.interconnect_id - 1 ]
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else:
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return self.scancode
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class ScanCodeStore:
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# Unique lookup for ScanCodes
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def __init__( self ):
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self.scancodes = []
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def __getitem__( self, name ):
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# First check if this is a ScanCode object
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if isinstance( name, ScanCode ):
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# Do a reverse lookup
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for idx, scancode in enumerate( self.scancodes ):
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if scancode == name:
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return idx
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# Could not find scancode
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return None
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# Return scancode using unique id
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return self.scancodes[ name ]
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# Attempt add ScanCode to list, return unique id
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def append( self, new_scancode ):
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# Iterate through list to make sure this is a unique ScanCode
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for idx, scancode in enumerate( self.scancodes ):
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if new_scancode == scancode:
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return idx
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# Unique entry, add to the list
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self.scancodes.append( new_scancode )
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return len( self.scancodes ) - 1
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2014-09-02 17:03:50 +00:00
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class Capabilities:
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# Container for capabilities dictionary and convenience functions
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def __init__( self ):
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self.capabilities = dict()
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def __getitem__( self, name ):
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return self.capabilities[ name ]
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def __setitem__( self, name, contents ):
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self.capabilities[ name ] = contents
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def __repr__( self ):
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return "Capabilities => {0}\nIndexed Capabilities => {1}".format( self.capabilities, sorted( self.capabilities, key = self.capabilities.get ) )
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# Total bytes needed to store arguments
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def totalArgBytes( self, name ):
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totalBytes = 0
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# Iterate over the arguments, summing the total bytes
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2014-09-07 03:56:46 +00:00
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for arg in self.capabilities[ name ][ 1 ]:
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totalBytes += int( arg[ 1 ] )
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2014-09-02 17:03:50 +00:00
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return totalBytes
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# Name of the capability function
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def funcName( self, name ):
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2014-09-07 03:56:46 +00:00
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return self.capabilities[ name ][ 0 ]
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2014-09-02 17:03:50 +00:00
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# Only valid while dictionary keys are not added/removed
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def getIndex( self, name ):
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return sorted( self.capabilities, key = self.capabilities.get ).index( name )
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def getName( self, index ):
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return sorted( self.capabilities, key = self.capabilities.get )[ index ]
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def keys( self ):
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return sorted( self.capabilities, key = self.capabilities.get )
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class Macros:
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# Container for Trigger Macro : Result Macro correlation
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# Layer selection for generating TriggerLists
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#
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# Only convert USB Code list once all the ResultMacros have been accumulated (does a macro reduction; not reversible)
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# Two staged list for ResultMacros:
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# 1) USB Code/Non-converted (may contain capabilities)
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# 2) Capabilities
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def __init__( self ):
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# Default layer (0)
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self.layer = 0
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2015-08-16 04:29:18 +00:00
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# Unique ScanCode Hash Id Lookup
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self.scanCodeStore = ScanCodeStore()
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2014-09-02 17:03:50 +00:00
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# Macro Storage
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2014-09-06 19:35:22 +00:00
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self.macros = [ dict() ]
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2014-09-10 00:49:46 +00:00
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# Base Layout Storage
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self.baseLayout = None
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self.layerLayoutMarkers = []
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2014-09-07 03:56:46 +00:00
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# Correlated Macro Data
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self.resultsIndex = dict()
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self.triggersIndex = dict()
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self.resultsIndexSorted = []
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self.triggersIndexSorted = []
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self.triggerList = []
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self.maxScanCode = []
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2014-09-17 00:01:40 +00:00
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self.firstScanCode = []
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2015-08-16 04:29:18 +00:00
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self.interconnectOffset = []
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2014-09-07 03:56:46 +00:00
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2014-09-08 04:32:36 +00:00
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# USBCode Assignment Cache
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self.assignmentCache = []
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2014-09-06 19:35:22 +00:00
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def __repr__( self ):
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return "{0}".format( self.macros )
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2014-09-02 17:03:50 +00:00
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2014-09-10 00:49:46 +00:00
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def completeBaseLayout( self ):
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# Copy base layout for later use when creating partial layers and add marker
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self.baseLayout = copy.deepcopy( self.macros[ 0 ] )
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self.layerLayoutMarkers.append( copy.deepcopy( self.baseLayout ) ) # Not used for default layer, just simplifies coding
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def removeUnmarked( self ):
|
|
|
|
# Remove all of the unmarked mappings from the partial layer
|
|
|
|
for trigger in self.layerLayoutMarkers[ self.layer ].keys():
|
|
|
|
del self.macros[ self.layer ][ trigger ]
|
|
|
|
|
2014-09-08 06:22:07 +00:00
|
|
|
def addLayer( self ):
|
|
|
|
# Increment layer count, and append another macros dictionary
|
|
|
|
self.layer += 1
|
2014-09-10 00:49:46 +00:00
|
|
|
self.macros.append( copy.deepcopy( self.baseLayout ) )
|
|
|
|
|
|
|
|
# Add a layout marker for each layer
|
|
|
|
self.layerLayoutMarkers.append( copy.deepcopy( self.baseLayout ) )
|
2014-09-02 17:03:50 +00:00
|
|
|
|
|
|
|
# Use for ScanCode trigger macros
|
|
|
|
def appendScanCode( self, trigger, result ):
|
2014-09-06 19:35:22 +00:00
|
|
|
if not trigger in self.macros[ self.layer ]:
|
|
|
|
self.replaceScanCode( trigger, result )
|
|
|
|
else:
|
|
|
|
self.macros[ self.layer ][ trigger ].append( result )
|
|
|
|
|
|
|
|
# Remove the given trigger/result pair
|
|
|
|
def removeScanCode( self, trigger, result ):
|
|
|
|
# Remove all instances of the given trigger/result pair
|
|
|
|
while result in self.macros[ self.layer ][ trigger ]:
|
|
|
|
self.macros[ self.layer ][ trigger ].remove( result )
|
|
|
|
|
|
|
|
# Replaces the given trigger with the given result
|
|
|
|
# If multiple results for a given trigger, clear, then add
|
|
|
|
def replaceScanCode( self, trigger, result ):
|
|
|
|
self.macros[ self.layer ][ trigger ] = [ result ]
|
|
|
|
|
2014-09-10 00:49:46 +00:00
|
|
|
# Mark layer scan code, so it won't be removed later
|
2014-09-17 01:14:06 +00:00
|
|
|
# Also check to see if it hasn't already been removed before
|
|
|
|
if not self.baseLayout is None and trigger in self.layerLayoutMarkers[ self.layer ]:
|
2014-09-10 00:49:46 +00:00
|
|
|
del self.layerLayoutMarkers[ self.layer ][ trigger ]
|
|
|
|
|
2014-09-06 19:35:22 +00:00
|
|
|
# Return a list of ScanCode triggers with the given USB Code trigger
|
|
|
|
def lookupUSBCodes( self, usbCode ):
|
|
|
|
scanCodeList = []
|
|
|
|
|
|
|
|
# Scan current layer for USB Codes
|
2014-09-02 17:03:50 +00:00
|
|
|
for macro in self.macros[ self.layer ].keys():
|
2014-09-08 04:32:36 +00:00
|
|
|
if usbCode in self.macros[ self.layer ][ macro ]:
|
2014-09-06 19:35:22 +00:00
|
|
|
scanCodeList.append( macro )
|
|
|
|
|
2015-02-28 04:26:01 +00:00
|
|
|
if len(scanCodeList) == 0:
|
|
|
|
if len(usbCode) > 1 or len(usbCode[0]) > 1:
|
|
|
|
for combo in usbCode:
|
|
|
|
comboCodes = list()
|
|
|
|
for key in combo:
|
|
|
|
scanCode = self.lookupUSBCodes(((key,),))
|
|
|
|
comboCodes.append(scanCode[0][0][0])
|
|
|
|
scanCodeList.append(tuple(code for code in comboCodes))
|
|
|
|
scanCodeList = [tuple(scanCodeList)]
|
|
|
|
|
2014-09-06 19:35:22 +00:00
|
|
|
return scanCodeList
|
2014-09-02 17:03:50 +00:00
|
|
|
|
2015-09-30 07:04:30 +00:00
|
|
|
# Check whether we should do soft replacement
|
|
|
|
def softReplaceCheck( self, scanCode ):
|
|
|
|
# First check if not the default layer
|
|
|
|
if self.layer == 0:
|
|
|
|
return True
|
|
|
|
|
|
|
|
# Check if current layer is set the same as the BaseMap
|
|
|
|
if not self.baseLayout is None and scanCode in self.layerLayoutMarkers[ self.layer ]:
|
|
|
|
return False
|
|
|
|
|
|
|
|
# Otherwise, allow replacement
|
|
|
|
return True
|
|
|
|
|
2014-09-08 04:32:36 +00:00
|
|
|
# Cache USBCode Assignment
|
|
|
|
def cacheAssignment( self, operator, scanCode, result ):
|
|
|
|
self.assignmentCache.append( [ operator, scanCode, result ] )
|
|
|
|
|
|
|
|
# Assign cached USBCode Assignments
|
|
|
|
def replayCachedAssignments( self ):
|
|
|
|
# Iterate over each item in the assignment cache
|
|
|
|
for item in self.assignmentCache:
|
|
|
|
# Check operator, and choose the specified assignment action
|
|
|
|
# Append Case
|
|
|
|
if item[0] == ":+":
|
|
|
|
self.appendScanCode( item[1], item[2] )
|
|
|
|
|
|
|
|
# Remove Case
|
|
|
|
elif item[0] == ":-":
|
|
|
|
self.removeScanCode( item[1], item[2] )
|
|
|
|
|
|
|
|
# Replace Case
|
2015-09-30 07:04:30 +00:00
|
|
|
elif item[0] == ":" or item[0] == "::":
|
2014-09-08 04:32:36 +00:00
|
|
|
self.replaceScanCode( item[1], item[2] )
|
|
|
|
|
|
|
|
# Clear assignment cache
|
|
|
|
self.assignmentCache = []
|
|
|
|
|
2014-09-07 03:56:46 +00:00
|
|
|
# Generate/Correlate Layers
|
|
|
|
def generate( self ):
|
|
|
|
self.generateIndices()
|
|
|
|
self.sortIndexLists()
|
2015-08-16 04:29:18 +00:00
|
|
|
self.generateOffsetTable()
|
2014-09-07 03:56:46 +00:00
|
|
|
self.generateTriggerLists()
|
|
|
|
|
|
|
|
# Generates Index of Results and Triggers
|
|
|
|
def generateIndices( self ):
|
|
|
|
# Iterate over every trigger result, and add to the resultsIndex and triggersIndex
|
|
|
|
for layer in range( 0, len( self.macros ) ):
|
|
|
|
for trigger in self.macros[ layer ].keys():
|
|
|
|
# Each trigger has a list of results
|
|
|
|
for result in self.macros[ layer ][ trigger ]:
|
|
|
|
# Only add, with an index, if result hasn't been added yet
|
|
|
|
if not result in self.resultsIndex:
|
|
|
|
self.resultsIndex[ result ] = len( self.resultsIndex )
|
|
|
|
|
|
|
|
# Then add a trigger for each result, if trigger hasn't been added yet
|
|
|
|
triggerItem = tuple( [ trigger, self.resultsIndex[ result ] ] )
|
|
|
|
if not triggerItem in self.triggersIndex:
|
|
|
|
self.triggersIndex[ triggerItem ] = len( self.triggersIndex )
|
|
|
|
|
|
|
|
# Sort Index Lists using the indices rather than triggers/results
|
|
|
|
def sortIndexLists( self ):
|
|
|
|
self.resultsIndexSorted = [ None ] * len( self.resultsIndex )
|
|
|
|
# Iterate over the resultsIndex and sort by index
|
|
|
|
for result in self.resultsIndex.keys():
|
|
|
|
self.resultsIndexSorted[ self.resultsIndex[ result ] ] = result
|
|
|
|
|
|
|
|
self.triggersIndexSorted = [ None ] * len( self.triggersIndex )
|
|
|
|
# Iterate over the triggersIndex and sort by index
|
|
|
|
for trigger in self.triggersIndex.keys():
|
|
|
|
self.triggersIndexSorted[ self.triggersIndex[ trigger ] ] = trigger
|
|
|
|
|
2015-08-16 04:29:18 +00:00
|
|
|
# Generates list of offsets for each of the interconnect ids
|
|
|
|
def generateOffsetTable( self ):
|
|
|
|
idMaxScanCode = [ 0 ]
|
|
|
|
|
|
|
|
# Iterate over each layer to get list of max scancodes associated with each interconnect id
|
|
|
|
for layer in range( 0, len( self.macros ) ):
|
|
|
|
# Iterate through each trigger/sequence in the layer
|
|
|
|
for sequence in self.macros[ layer ].keys():
|
|
|
|
# Iterate over the trigger to locate the ScanCodes
|
|
|
|
for combo in sequence:
|
|
|
|
# Iterate over each scancode id in the combo
|
|
|
|
for scancode_id in combo:
|
|
|
|
# Lookup ScanCode
|
|
|
|
scancode_obj = self.scanCodeStore[ scancode_id ]
|
|
|
|
|
|
|
|
# Extend list if not large enough
|
|
|
|
if scancode_obj.interconnect_id >= len( idMaxScanCode ):
|
|
|
|
idMaxScanCode.extend( [ 0 ] * ( scancode_obj.interconnect_id - len( idMaxScanCode ) + 1 ) )
|
|
|
|
|
|
|
|
# Determine if the max seen id for this interconnect id
|
|
|
|
if scancode_obj.scancode > idMaxScanCode[ scancode_obj.interconnect_id ]:
|
|
|
|
idMaxScanCode[ scancode_obj.interconnect_id ] = scancode_obj.scancode
|
|
|
|
|
|
|
|
# Generate interconnect offsets
|
|
|
|
self.interconnectOffset = [ idMaxScanCode[0] + 1 ]
|
|
|
|
for index in range( 1, len( idMaxScanCode ) ):
|
|
|
|
self.interconnectOffset.append( self.interconnectOffset[ index - 1 ] + idMaxScanCode[ index ] )
|
|
|
|
|
2014-09-07 03:56:46 +00:00
|
|
|
# Generates Trigger Lists per layer using index lists
|
|
|
|
def generateTriggerLists( self ):
|
|
|
|
for layer in range( 0, len( self.macros ) ):
|
|
|
|
# Set max scancode to 0xFF (255)
|
|
|
|
# But keep track of the actual max scancode and reduce the list size
|
|
|
|
self.triggerList.append( [ [] ] * 0xFF )
|
|
|
|
self.maxScanCode.append( 0x00 )
|
|
|
|
|
2014-09-09 06:51:44 +00:00
|
|
|
# Iterate through trigger macros to locate necessary ScanCodes and corresponding triggerIndex
|
|
|
|
for trigger in self.macros[ layer ].keys():
|
|
|
|
for variant in range( 0, len( self.macros[ layer ][ trigger ] ) ):
|
|
|
|
# Identify result index
|
|
|
|
resultIndex = self.resultsIndex[ self.macros[ layer ][ trigger ][ variant ] ]
|
|
|
|
|
|
|
|
# Identify trigger index
|
|
|
|
triggerIndex = self.triggersIndex[ tuple( [ trigger, resultIndex ] ) ]
|
|
|
|
|
|
|
|
# Iterate over the trigger to locate the ScanCodes
|
|
|
|
for sequence in trigger:
|
2015-08-16 04:29:18 +00:00
|
|
|
for combo_id in sequence:
|
|
|
|
combo = self.scanCodeStore[ combo_id ].offset( self.interconnectOffset )
|
2014-09-09 06:51:44 +00:00
|
|
|
# Append triggerIndex for each found scanCode of the Trigger List
|
|
|
|
# Do not re-add if triggerIndex is already in the Trigger List
|
|
|
|
if not triggerIndex in self.triggerList[ layer ][ combo ]:
|
|
|
|
# Append is working strangely with list pre-initialization
|
|
|
|
# Doing a 0 check replacement instead -HaaTa
|
|
|
|
if len( self.triggerList[ layer ][ combo ] ) == 0:
|
|
|
|
self.triggerList[ layer ][ combo ] = [ triggerIndex ]
|
|
|
|
else:
|
|
|
|
self.triggerList[ layer ][ combo ].append( triggerIndex )
|
|
|
|
|
|
|
|
# Look for max Scan Code
|
|
|
|
if combo > self.maxScanCode[ layer ]:
|
|
|
|
self.maxScanCode[ layer ] = combo
|
2014-09-07 03:56:46 +00:00
|
|
|
|
|
|
|
# Shrink triggerList to actual max size
|
|
|
|
self.triggerList[ layer ] = self.triggerList[ layer ][ : self.maxScanCode[ layer ] + 1 ]
|
|
|
|
|
2014-09-17 00:01:40 +00:00
|
|
|
# Calculate first scan code for layer, useful for uC implementations trying to save RAM
|
|
|
|
firstScanCode = 0
|
|
|
|
for triggerList in range( 0, len( self.triggerList[ layer ] ) ):
|
|
|
|
firstScanCode = triggerList
|
|
|
|
|
|
|
|
# Break if triggerList has items
|
|
|
|
if len( self.triggerList[ layer ][ triggerList ] ) > 0:
|
|
|
|
break;
|
|
|
|
self.firstScanCode.append( firstScanCode )
|
|
|
|
|
2014-09-07 03:56:46 +00:00
|
|
|
# Determine overall maxScanCode
|
|
|
|
self.overallMaxScanCode = 0x00
|
|
|
|
for maxVal in self.maxScanCode:
|
|
|
|
if maxVal > self.overallMaxScanCode:
|
|
|
|
self.overallMaxScanCode = maxVal
|
|
|
|
|
2014-09-17 00:01:40 +00:00
|
|
|
|
|
|
|
class Variables:
|
|
|
|
# Container for variables
|
|
|
|
# Stores three sets of variables, the overall combined set, per layer, and per file
|
|
|
|
def __init__( self ):
|
2014-11-20 21:52:58 +00:00
|
|
|
# Dictionaries of variables
|
|
|
|
self.baseLayout = dict()
|
|
|
|
self.fileVariables = dict()
|
|
|
|
self.layerVariables = [ dict() ]
|
|
|
|
self.overallVariables = dict()
|
|
|
|
self.defines = dict()
|
2014-09-17 00:01:40 +00:00
|
|
|
|
2014-11-20 21:52:58 +00:00
|
|
|
self.currentFile = ""
|
|
|
|
self.currentLayer = 0
|
|
|
|
self.baseLayoutEnabled = True
|
|
|
|
|
|
|
|
def baseLayoutFinished( self ):
|
|
|
|
self.baseLayoutEnabled = False
|
2014-09-17 00:01:40 +00:00
|
|
|
|
|
|
|
def setCurrentFile( self, name ):
|
|
|
|
# Store using filename and current layer
|
2014-11-20 21:52:58 +00:00
|
|
|
self.currentFile = name
|
|
|
|
self.fileVariables[ name ] = dict()
|
|
|
|
|
|
|
|
# If still processing BaseLayout
|
|
|
|
if self.baseLayoutEnabled:
|
2015-02-16 21:29:26 +00:00
|
|
|
if '*LayerFiles' in self.baseLayout.keys():
|
|
|
|
self.baseLayout['*LayerFiles'] += [ name ]
|
|
|
|
else:
|
|
|
|
self.baseLayout['*LayerFiles'] = [ name ]
|
2014-11-20 21:52:58 +00:00
|
|
|
# Set for the current layer
|
|
|
|
else:
|
2015-02-16 21:29:26 +00:00
|
|
|
if '*LayerFiles' in self.layerVariables[ self.currentLayer ].keys():
|
|
|
|
self.layerVariables[ self.currentLayer ]['*LayerFiles'] += [ name ]
|
|
|
|
else:
|
|
|
|
self.layerVariables[ self.currentLayer ]['*LayerFiles'] = [ name ]
|
2014-09-17 00:01:40 +00:00
|
|
|
|
2014-11-20 21:52:58 +00:00
|
|
|
def incrementLayer( self ):
|
2014-09-17 00:01:40 +00:00
|
|
|
# Store using layer index
|
2014-11-20 21:52:58 +00:00
|
|
|
self.currentLayer += 1
|
|
|
|
self.layerVariables.append( dict() )
|
2014-09-17 00:01:40 +00:00
|
|
|
|
|
|
|
def assignVariable( self, key, value ):
|
2014-11-20 21:52:58 +00:00
|
|
|
# Overall set of variables
|
|
|
|
self.overallVariables[ key ] = value
|
|
|
|
|
2015-02-16 21:29:26 +00:00
|
|
|
# The Name variable is a special accumulation case
|
|
|
|
if key == 'Name':
|
|
|
|
# BaseLayout still being processed
|
|
|
|
if self.baseLayoutEnabled:
|
|
|
|
if '*NameStack' in self.baseLayout.keys():
|
|
|
|
self.baseLayout['*NameStack'] += [ value ]
|
|
|
|
else:
|
|
|
|
self.baseLayout['*NameStack'] = [ value ]
|
|
|
|
# Layers
|
|
|
|
else:
|
|
|
|
if '*NameStack' in self.layerVariables[ self.currentLayer ].keys():
|
|
|
|
self.layerVariables[ self.currentLayer ]['*NameStack'] += [ value ]
|
|
|
|
else:
|
|
|
|
self.layerVariables[ self.currentLayer ]['*NameStack'] = [ value ]
|
|
|
|
|
2014-11-20 21:52:58 +00:00
|
|
|
# If still processing BaseLayout
|
|
|
|
if self.baseLayoutEnabled:
|
|
|
|
self.baseLayout[ key ] = value
|
|
|
|
# Set for the current layer
|
|
|
|
else:
|
|
|
|
self.layerVariables[ self.currentLayer ][ key ] = value
|
|
|
|
|
|
|
|
# File context variables
|
|
|
|
self.fileVariables[ self.currentFile ][ key ] = value
|
2014-09-17 00:01:40 +00:00
|
|
|
|