from pct.nodes import PCTNode
from pct.functions import WeightedSum, Constant
from pct.hierarchy import PCTHierarchy--------------------------------------------------------------------------- ModuleNotFoundError Traceback (most recent call last) Cell In[2], line 1 ----> 1 from pct.nodes import PCTNode 2 from pct.functions import WeightedSum, Constant 3 from pct.hierarchy import PCTHierarchy ModuleNotFoundError: No module named 'pct'
Create a hierarchy by defining the number of rows (levels) and columns.
pre=Constant(5, name='precon')
namespace=pre.namespace
post=Constant(10, name='postcon', namespace=namespace)
hpct = PCTHierarchy(3,3, pre=[pre], post=[post], history=True, clear_names=False, links="dense", namespace=namespace)
hpct.hierarchy[[<pct.nodes.PCTNode>,
<pct.nodes.PCTNode>,
<pct.nodes.PCTNode>],
[<pct.nodes.PCTNode>,
<pct.nodes.PCTNode>,
<pct.nodes.PCTNode>],
[<pct.nodes.PCTNode>,
<pct.nodes.PCTNode>,
<pct.nodes.PCTNode>]]print(hpct.get_summary())**************************
PRE: 5.000
L0C0 0.000 0.000 0.000 0.000
L0C1 0.000 0.000 0.000 0.000
L0C2 0.000 0.000 0.000 0.000
L1C0 0.000 0.000 0.000 0.000
L1C1 0.000 0.000 0.000 0.000
L1C2 0.000 0.000 0.000 0.000
L2C0 0.000 0.000 0.000 0.000
L2C1 0.000 0.000 0.000 0.000
L2C2 0.000 0.000 0.000 0.000
POST: 10.000
print(hpct.get_parameters_list())[[[[5]], [[10]]], [[[[1, 1, 1]], [[0]], [[1]]], [[[1, 1, 1]], [[0]], [[1]]], [[[1, 1, 1]], [[0]], [[1]]]], [[[[1, 1, 1]], [[1, 1, 1]], [[1]]], [[[1, 1, 1]], [[1, 1, 1]], [[1]]], [[[1, 1, 1]], [[1, 1, 1]], [[1]]]], [[[[0]], [[1, 1, 1]], [[1]]], [[[0]], [[1, 1, 1]], [[1]]], [[[0]], [[1, 1, 1]], [[1]]]]]print(hpct.get_grid())[3, 3, 3]hpct.change_namespace()hpct.summary()**************************
pcthierarchy PCTHierarchy [3, 3, 3] ccff3ef2-036f-11f0-9f08-04d9f58727ab
--------------------------
PRE: precon Constant | 5
Level 0 Cols 3
level0col0 PCTNode ccff3ef2-036f-11f0-9f08-04d9f58727ab
----------------------------
REF: weighted_sum WeightedSum | weights [1, 1, 1] | 0 | links proportional3 proportional4 proportional5
PER: variable Variable | 0
COM: subtract Subtract | 0 | links weighted_sum variable
OUT: proportional Proportional | gain 1 | 0 | links subtract
----------------------------
level0col1 PCTNode ccff3ef2-036f-11f0-9f08-04d9f58727ab
----------------------------
REF: weighted_sum1 WeightedSum | weights [1, 1, 1] | 0 | links proportional3 proportional4 proportional5
PER: variable1 Variable | 0
COM: subtract1 Subtract | 0 | links weighted_sum1 variable1
OUT: proportional1 Proportional | gain 1 | 0 | links subtract1
----------------------------
level0col2 PCTNode ccff3ef2-036f-11f0-9f08-04d9f58727ab
----------------------------
REF: weighted_sum2 WeightedSum | weights [1, 1, 1] | 0 | links proportional3 proportional4 proportional5
PER: variable2 Variable | 0
COM: subtract2 Subtract | 0 | links weighted_sum2 variable2
OUT: proportional2 Proportional | gain 1 | 0 | links subtract2
----------------------------
Level 1 Cols 3
level1col0 PCTNode ccff3ef2-036f-11f0-9f08-04d9f58727ab
----------------------------
REF: weighted_sum4 WeightedSum | weights [1, 1, 1] | 0 | links proportional6 proportional7 proportional8
PER: weighted_sum3 WeightedSum | weights [1, 1, 1] | 0 | links variable variable1 variable2
COM: subtract3 Subtract | 0 | links weighted_sum4 weighted_sum3
OUT: proportional3 Proportional | gain 1 | 0 | links subtract3
----------------------------
level1col1 PCTNode ccff3ef2-036f-11f0-9f08-04d9f58727ab
----------------------------
REF: weighted_sum6 WeightedSum | weights [1, 1, 1] | 0 | links proportional6 proportional7 proportional8
PER: weighted_sum5 WeightedSum | weights [1, 1, 1] | 0 | links variable variable1 variable2
COM: subtract4 Subtract | 0 | links weighted_sum6 weighted_sum5
OUT: proportional4 Proportional | gain 1 | 0 | links subtract4
----------------------------
level1col2 PCTNode ccff3ef2-036f-11f0-9f08-04d9f58727ab
----------------------------
REF: weighted_sum8 WeightedSum | weights [1, 1, 1] | 0 | links proportional6 proportional7 proportional8
PER: weighted_sum7 WeightedSum | weights [1, 1, 1] | 0 | links variable variable1 variable2
COM: subtract5 Subtract | 0 | links weighted_sum8 weighted_sum7
OUT: proportional5 Proportional | gain 1 | 0 | links subtract5
----------------------------
Level 2 Cols 3
level2col0 PCTNode ccff3ef2-036f-11f0-9f08-04d9f58727ab
----------------------------
REF: constant Constant | 0
PER: weighted_sum9 WeightedSum | weights [1, 1, 1] | 0 | links weighted_sum3 weighted_sum5 weighted_sum7
COM: subtract6 Subtract | 0 | links constant weighted_sum9
OUT: proportional6 Proportional | gain 1 | 0 | links subtract6
----------------------------
level2col1 PCTNode ccff3ef2-036f-11f0-9f08-04d9f58727ab
----------------------------
REF: constant1 Constant | 0
PER: weighted_sum10 WeightedSum | weights [1, 1, 1] | 0 | links weighted_sum3 weighted_sum5 weighted_sum7
COM: subtract7 Subtract | 0 | links constant1 weighted_sum10
OUT: proportional7 Proportional | gain 1 | 0 | links subtract7
----------------------------
level2col2 PCTNode ccff3ef2-036f-11f0-9f08-04d9f58727ab
----------------------------
REF: constant2 Constant | 0
PER: weighted_sum11 WeightedSum | weights [1, 1, 1] | 0 | links weighted_sum3 weighted_sum5 weighted_sum7
COM: subtract8 Subtract | 0 | links constant2 weighted_sum11
OUT: proportional8 Proportional | gain 1 | 0 | links subtract8
----------------------------
POST: postcon Constant | 10
**************************#FunctionsList.getInstance().report()Create a hierarchy from a configuration.
config = hpct.get_config()
print(config){'type': 'PCTHierarchy', 'name': 'pcthierarchy', 'pre': {'pre0': {'type': 'Constant', 'name': 'precon', 'value': 5, 'links': {}}}, 'levels': {'level0': {'level': 0, 'nodes': {'col0': {'col': 0, 'node': {'type': 'PCTNode', 'name': 'level0col0', 'refcoll': {'0': {'type': 'WeightedSum', 'name': 'weighted_sum', 'value': 0, 'links': {0: 'proportional3', 1: 'proportional4', 2: 'proportional5'}, 'weights': [1, 1, 1]}}, 'percoll': {'0': {'type': 'Variable', 'name': 'variable', 'value': 0, 'links': {}}}, 'comcoll': {'0': {'type': 'Subtract', 'name': 'subtract', 'value': 0, 'links': {0: 'weighted_sum', 1: 'variable'}}}, 'outcoll': {'0': {'type': 'Proportional', 'name': 'proportional', 'value': 0, 'links': {0: 'subtract'}, 'gain': 1}}}}, 'col1': {'col': 1, 'node': {'type': 'PCTNode', 'name': 'level0col1', 'refcoll': {'0': {'type': 'WeightedSum', 'name': 'weighted_sum1', 'value': 0, 'links': {0: 'proportional3', 1: 'proportional4', 2: 'proportional5'}, 'weights': [1, 1, 1]}}, 'percoll': {'0': {'type': 'Variable', 'name': 'variable1', 'value': 0, 'links': {}}}, 'comcoll': {'0': {'type': 'Subtract', 'name': 'subtract1', 'value': 0, 'links': {0: 'weighted_sum1', 1: 'variable1'}}}, 'outcoll': {'0': {'type': 'Proportional', 'name': 'proportional1', 'value': 0, 'links': {0: 'subtract1'}, 'gain': 1}}}}, 'col2': {'col': 2, 'node': {'type': 'PCTNode', 'name': 'level0col2', 'refcoll': {'0': {'type': 'WeightedSum', 'name': 'weighted_sum2', 'value': 0, 'links': {0: 'proportional3', 1: 'proportional4', 2: 'proportional5'}, 'weights': [1, 1, 1]}}, 'percoll': {'0': {'type': 'Variable', 'name': 'variable2', 'value': 0, 'links': {}}}, 'comcoll': {'0': {'type': 'Subtract', 'name': 'subtract2', 'value': 0, 'links': {0: 'weighted_sum2', 1: 'variable2'}}}, 'outcoll': {'0': {'type': 'Proportional', 'name': 'proportional2', 'value': 0, 'links': {0: 'subtract2'}, 'gain': 1}}}}}}, 'level1': {'level': 1, 'nodes': {'col0': {'col': 0, 'node': {'type': 'PCTNode', 'name': 'level1col0', 'refcoll': {'0': {'type': 'WeightedSum', 'name': 'weighted_sum4', 'value': 0, 'links': {0: 'proportional6', 1: 'proportional7', 2: 'proportional8'}, 'weights': [1, 1, 1]}}, 'percoll': {'0': {'type': 'WeightedSum', 'name': 'weighted_sum3', 'value': 0, 'links': {0: 'variable', 1: 'variable1', 2: 'variable2'}, 'weights': [1, 1, 1]}}, 'comcoll': {'0': {'type': 'Subtract', 'name': 'subtract3', 'value': 0, 'links': {0: 'weighted_sum4', 1: 'weighted_sum3'}}}, 'outcoll': {'0': {'type': 'Proportional', 'name': 'proportional3', 'value': 0, 'links': {0: 'subtract3'}, 'gain': 1}}}}, 'col1': {'col': 1, 'node': {'type': 'PCTNode', 'name': 'level1col1', 'refcoll': {'0': {'type': 'WeightedSum', 'name': 'weighted_sum6', 'value': 0, 'links': {0: 'proportional6', 1: 'proportional7', 2: 'proportional8'}, 'weights': [1, 1, 1]}}, 'percoll': {'0': {'type': 'WeightedSum', 'name': 'weighted_sum5', 'value': 0, 'links': {0: 'variable', 1: 'variable1', 2: 'variable2'}, 'weights': [1, 1, 1]}}, 'comcoll': {'0': {'type': 'Subtract', 'name': 'subtract4', 'value': 0, 'links': {0: 'weighted_sum6', 1: 'weighted_sum5'}}}, 'outcoll': {'0': {'type': 'Proportional', 'name': 'proportional4', 'value': 0, 'links': {0: 'subtract4'}, 'gain': 1}}}}, 'col2': {'col': 2, 'node': {'type': 'PCTNode', 'name': 'level1col2', 'refcoll': {'0': {'type': 'WeightedSum', 'name': 'weighted_sum8', 'value': 0, 'links': {0: 'proportional6', 1: 'proportional7', 2: 'proportional8'}, 'weights': [1, 1, 1]}}, 'percoll': {'0': {'type': 'WeightedSum', 'name': 'weighted_sum7', 'value': 0, 'links': {0: 'variable', 1: 'variable1', 2: 'variable2'}, 'weights': [1, 1, 1]}}, 'comcoll': {'0': {'type': 'Subtract', 'name': 'subtract5', 'value': 0, 'links': {0: 'weighted_sum8', 1: 'weighted_sum7'}}}, 'outcoll': {'0': {'type': 'Proportional', 'name': 'proportional5', 'value': 0, 'links': {0: 'subtract5'}, 'gain': 1}}}}}}, 'level2': {'level': 2, 'nodes': {'col0': {'col': 0, 'node': {'type': 'PCTNode', 'name': 'level2col0', 'refcoll': {'0': {'type': 'Constant', 'name': 'constant', 'value': 0, 'links': {}}}, 'percoll': {'0': {'type': 'WeightedSum', 'name': 'weighted_sum9', 'value': 0, 'links': {0: 'weighted_sum3', 1: 'weighted_sum5', 2: 'weighted_sum7'}, 'weights': [1, 1, 1]}}, 'comcoll': {'0': {'type': 'Subtract', 'name': 'subtract6', 'value': 0, 'links': {0: 'constant', 1: 'weighted_sum9'}}}, 'outcoll': {'0': {'type': 'Proportional', 'name': 'proportional6', 'value': 0, 'links': {0: 'subtract6'}, 'gain': 1}}}}, 'col1': {'col': 1, 'node': {'type': 'PCTNode', 'name': 'level2col1', 'refcoll': {'0': {'type': 'Constant', 'name': 'constant1', 'value': 0, 'links': {}}}, 'percoll': {'0': {'type': 'WeightedSum', 'name': 'weighted_sum10', 'value': 0, 'links': {0: 'weighted_sum3', 1: 'weighted_sum5', 2: 'weighted_sum7'}, 'weights': [1, 1, 1]}}, 'comcoll': {'0': {'type': 'Subtract', 'name': 'subtract7', 'value': 0, 'links': {0: 'constant1', 1: 'weighted_sum10'}}}, 'outcoll': {'0': {'type': 'Proportional', 'name': 'proportional7', 'value': 0, 'links': {0: 'subtract7'}, 'gain': 1}}}}, 'col2': {'col': 2, 'node': {'type': 'PCTNode', 'name': 'level2col2', 'refcoll': {'0': {'type': 'Constant', 'name': 'constant2', 'value': 0, 'links': {}}}, 'percoll': {'0': {'type': 'WeightedSum', 'name': 'weighted_sum11', 'value': 0, 'links': {0: 'weighted_sum3', 1: 'weighted_sum5', 2: 'weighted_sum7'}, 'weights': [1, 1, 1]}}, 'comcoll': {'0': {'type': 'Subtract', 'name': 'subtract8', 'value': 0, 'links': {0: 'constant2', 1: 'weighted_sum11'}}}, 'outcoll': {'0': {'type': 'Proportional', 'name': 'proportional8', 'value': 0, 'links': {0: 'subtract8'}, 'gain': 1}}}}}}}, 'post': {'post0': {'type': 'Constant', 'name': 'postcon', 'value': 10, 'links': {}}}}# h = PCTHierarchy.from_config(config, namespace=namespace)
h = PCTHierarchy.from_config(config)assert h.get_config() == hpct.get_config()The hierarchy details can be viewed as a summary.
hpct.get_node(2,0).get_function('reference').set_value(1)
hpct.get_node(2,1).get_function('reference').set_value(1)
hpct.get_node(2,2).get_function('reference').set_value(1)
for level in range(3):
for col in range(3):
hpct.get_node(level,col).get_function('output').set_property('gain', 10)
hpct.summary()**************************
pcthierarchy PCTHierarchy [3, 3, 3] ccff3ef2-036f-11f0-9f08-04d9f58727ab
--------------------------
PRE: precon Constant | 5
Level 0 Cols 3
level0col0 PCTNode ccff3ef2-036f-11f0-9f08-04d9f58727ab
----------------------------
REF: weighted_sum WeightedSum | weights [1, 1, 1] | 0 | links proportional3 proportional4 proportional5
PER: variable Variable | 0
COM: subtract Subtract | 0 | links weighted_sum variable
OUT: proportional Proportional | gain 10 | 0 | links subtract
----------------------------
level0col1 PCTNode ccff3ef2-036f-11f0-9f08-04d9f58727ab
----------------------------
REF: weighted_sum1 WeightedSum | weights [1, 1, 1] | 0 | links proportional3 proportional4 proportional5
PER: variable1 Variable | 0
COM: subtract1 Subtract | 0 | links weighted_sum1 variable1
OUT: proportional1 Proportional | gain 10 | 0 | links subtract1
----------------------------
level0col2 PCTNode ccff3ef2-036f-11f0-9f08-04d9f58727ab
----------------------------
REF: weighted_sum2 WeightedSum | weights [1, 1, 1] | 0 | links proportional3 proportional4 proportional5
PER: variable2 Variable | 0
COM: subtract2 Subtract | 0 | links weighted_sum2 variable2
OUT: proportional2 Proportional | gain 10 | 0 | links subtract2
----------------------------
Level 1 Cols 3
level1col0 PCTNode ccff3ef2-036f-11f0-9f08-04d9f58727ab
----------------------------
REF: weighted_sum4 WeightedSum | weights [1, 1, 1] | 0 | links proportional6 proportional7 proportional8
PER: weighted_sum3 WeightedSum | weights [1, 1, 1] | 0 | links variable variable1 variable2
COM: subtract3 Subtract | 0 | links weighted_sum4 weighted_sum3
OUT: proportional3 Proportional | gain 10 | 0 | links subtract3
----------------------------
level1col1 PCTNode ccff3ef2-036f-11f0-9f08-04d9f58727ab
----------------------------
REF: weighted_sum6 WeightedSum | weights [1, 1, 1] | 0 | links proportional6 proportional7 proportional8
PER: weighted_sum5 WeightedSum | weights [1, 1, 1] | 0 | links variable variable1 variable2
COM: subtract4 Subtract | 0 | links weighted_sum6 weighted_sum5
OUT: proportional4 Proportional | gain 10 | 0 | links subtract4
----------------------------
level1col2 PCTNode ccff3ef2-036f-11f0-9f08-04d9f58727ab
----------------------------
REF: weighted_sum8 WeightedSum | weights [1, 1, 1] | 0 | links proportional6 proportional7 proportional8
PER: weighted_sum7 WeightedSum | weights [1, 1, 1] | 0 | links variable variable1 variable2
COM: subtract5 Subtract | 0 | links weighted_sum8 weighted_sum7
OUT: proportional5 Proportional | gain 10 | 0 | links subtract5
----------------------------
Level 2 Cols 3
level2col0 PCTNode ccff3ef2-036f-11f0-9f08-04d9f58727ab
----------------------------
REF: constant Constant | 1
PER: weighted_sum9 WeightedSum | weights [1, 1, 1] | 0 | links weighted_sum3 weighted_sum5 weighted_sum7
COM: subtract6 Subtract | 0 | links constant weighted_sum9
OUT: proportional6 Proportional | gain 10 | 0 | links subtract6
----------------------------
level2col1 PCTNode ccff3ef2-036f-11f0-9f08-04d9f58727ab
----------------------------
REF: constant1 Constant | 1
PER: weighted_sum10 WeightedSum | weights [1, 1, 1] | 0 | links weighted_sum3 weighted_sum5 weighted_sum7
COM: subtract7 Subtract | 0 | links constant1 weighted_sum10
OUT: proportional7 Proportional | gain 10 | 0 | links subtract7
----------------------------
level2col2 PCTNode ccff3ef2-036f-11f0-9f08-04d9f58727ab
----------------------------
REF: constant2 Constant | 1
PER: weighted_sum11 WeightedSum | weights [1, 1, 1] | 0 | links weighted_sum3 weighted_sum5 weighted_sum7
COM: subtract8 Subtract | 0 | links constant2 weighted_sum11
OUT: proportional8 Proportional | gain 10 | 0 | links subtract8
----------------------------
POST: postcon Constant | 10
**************************The hierarchy details can be viewed as a configuration. That configuration can be used to create a hierarchy, as shown above.
hpct.get_config(){'type': 'PCTHierarchy',
'name': 'pcthierarchy',
'pre': {'pre0': {'type': 'Constant',
'name': 'precon',
'value': 5,
'links': {}}},
'levels': {'level0': {'level': 0,
'nodes': {'col0': {'col': 0,
'node': {'type': 'PCTNode',
'name': 'level0col0',
'refcoll': {'0': {'type': 'WeightedSum',
'name': 'weighted_sum',
'value': 0,
'links': {0: 'proportional3', 1: 'proportional4', 2: 'proportional5'},
'weights': [1, 1, 1]}},
'percoll': {'0': {'type': 'Variable',
'name': 'variable',
'value': 0,
'links': {}}},
'comcoll': {'0': {'type': 'Subtract',
'name': 'subtract',
'value': 0,
'links': {0: 'weighted_sum', 1: 'variable'}}},
'outcoll': {'0': {'type': 'Proportional',
'name': 'proportional',
'value': 0,
'links': {0: 'subtract'},
'gain': 10}}}},
'col1': {'col': 1,
'node': {'type': 'PCTNode',
'name': 'level0col1',
'refcoll': {'0': {'type': 'WeightedSum',
'name': 'weighted_sum1',
'value': 0,
'links': {0: 'proportional3', 1: 'proportional4', 2: 'proportional5'},
'weights': [1, 1, 1]}},
'percoll': {'0': {'type': 'Variable',
'name': 'variable1',
'value': 0,
'links': {}}},
'comcoll': {'0': {'type': 'Subtract',
'name': 'subtract1',
'value': 0,
'links': {0: 'weighted_sum1', 1: 'variable1'}}},
'outcoll': {'0': {'type': 'Proportional',
'name': 'proportional1',
'value': 0,
'links': {0: 'subtract1'},
'gain': 10}}}},
'col2': {'col': 2,
'node': {'type': 'PCTNode',
'name': 'level0col2',
'refcoll': {'0': {'type': 'WeightedSum',
'name': 'weighted_sum2',
'value': 0,
'links': {0: 'proportional3', 1: 'proportional4', 2: 'proportional5'},
'weights': [1, 1, 1]}},
'percoll': {'0': {'type': 'Variable',
'name': 'variable2',
'value': 0,
'links': {}}},
'comcoll': {'0': {'type': 'Subtract',
'name': 'subtract2',
'value': 0,
'links': {0: 'weighted_sum2', 1: 'variable2'}}},
'outcoll': {'0': {'type': 'Proportional',
'name': 'proportional2',
'value': 0,
'links': {0: 'subtract2'},
'gain': 10}}}}}},
'level1': {'level': 1,
'nodes': {'col0': {'col': 0,
'node': {'type': 'PCTNode',
'name': 'level1col0',
'refcoll': {'0': {'type': 'WeightedSum',
'name': 'weighted_sum4',
'value': 0,
'links': {0: 'proportional6', 1: 'proportional7', 2: 'proportional8'},
'weights': [1, 1, 1]}},
'percoll': {'0': {'type': 'WeightedSum',
'name': 'weighted_sum3',
'value': 0,
'links': {0: 'variable', 1: 'variable1', 2: 'variable2'},
'weights': [1, 1, 1]}},
'comcoll': {'0': {'type': 'Subtract',
'name': 'subtract3',
'value': 0,
'links': {0: 'weighted_sum4', 1: 'weighted_sum3'}}},
'outcoll': {'0': {'type': 'Proportional',
'name': 'proportional3',
'value': 0,
'links': {0: 'subtract3'},
'gain': 10}}}},
'col1': {'col': 1,
'node': {'type': 'PCTNode',
'name': 'level1col1',
'refcoll': {'0': {'type': 'WeightedSum',
'name': 'weighted_sum6',
'value': 0,
'links': {0: 'proportional6', 1: 'proportional7', 2: 'proportional8'},
'weights': [1, 1, 1]}},
'percoll': {'0': {'type': 'WeightedSum',
'name': 'weighted_sum5',
'value': 0,
'links': {0: 'variable', 1: 'variable1', 2: 'variable2'},
'weights': [1, 1, 1]}},
'comcoll': {'0': {'type': 'Subtract',
'name': 'subtract4',
'value': 0,
'links': {0: 'weighted_sum6', 1: 'weighted_sum5'}}},
'outcoll': {'0': {'type': 'Proportional',
'name': 'proportional4',
'value': 0,
'links': {0: 'subtract4'},
'gain': 10}}}},
'col2': {'col': 2,
'node': {'type': 'PCTNode',
'name': 'level1col2',
'refcoll': {'0': {'type': 'WeightedSum',
'name': 'weighted_sum8',
'value': 0,
'links': {0: 'proportional6', 1: 'proportional7', 2: 'proportional8'},
'weights': [1, 1, 1]}},
'percoll': {'0': {'type': 'WeightedSum',
'name': 'weighted_sum7',
'value': 0,
'links': {0: 'variable', 1: 'variable1', 2: 'variable2'},
'weights': [1, 1, 1]}},
'comcoll': {'0': {'type': 'Subtract',
'name': 'subtract5',
'value': 0,
'links': {0: 'weighted_sum8', 1: 'weighted_sum7'}}},
'outcoll': {'0': {'type': 'Proportional',
'name': 'proportional5',
'value': 0,
'links': {0: 'subtract5'},
'gain': 10}}}}}},
'level2': {'level': 2,
'nodes': {'col0': {'col': 0,
'node': {'type': 'PCTNode',
'name': 'level2col0',
'refcoll': {'0': {'type': 'Constant',
'name': 'constant',
'value': 1,
'links': {}}},
'percoll': {'0': {'type': 'WeightedSum',
'name': 'weighted_sum9',
'value': 0,
'links': {0: 'weighted_sum3', 1: 'weighted_sum5', 2: 'weighted_sum7'},
'weights': [1, 1, 1]}},
'comcoll': {'0': {'type': 'Subtract',
'name': 'subtract6',
'value': 0,
'links': {0: 'constant', 1: 'weighted_sum9'}}},
'outcoll': {'0': {'type': 'Proportional',
'name': 'proportional6',
'value': 0,
'links': {0: 'subtract6'},
'gain': 10}}}},
'col1': {'col': 1,
'node': {'type': 'PCTNode',
'name': 'level2col1',
'refcoll': {'0': {'type': 'Constant',
'name': 'constant1',
'value': 1,
'links': {}}},
'percoll': {'0': {'type': 'WeightedSum',
'name': 'weighted_sum10',
'value': 0,
'links': {0: 'weighted_sum3', 1: 'weighted_sum5', 2: 'weighted_sum7'},
'weights': [1, 1, 1]}},
'comcoll': {'0': {'type': 'Subtract',
'name': 'subtract7',
'value': 0,
'links': {0: 'constant1', 1: 'weighted_sum10'}}},
'outcoll': {'0': {'type': 'Proportional',
'name': 'proportional7',
'value': 0,
'links': {0: 'subtract7'},
'gain': 10}}}},
'col2': {'col': 2,
'node': {'type': 'PCTNode',
'name': 'level2col2',
'refcoll': {'0': {'type': 'Constant',
'name': 'constant2',
'value': 1,
'links': {}}},
'percoll': {'0': {'type': 'WeightedSum',
'name': 'weighted_sum11',
'value': 0,
'links': {0: 'weighted_sum3', 1: 'weighted_sum5', 2: 'weighted_sum7'},
'weights': [1, 1, 1]}},
'comcoll': {'0': {'type': 'Subtract',
'name': 'subtract8',
'value': 0,
'links': {0: 'constant2', 1: 'weighted_sum11'}}},
'outcoll': {'0': {'type': 'Proportional',
'name': 'proportional8',
'value': 0,
'links': {0: 'subtract8'},
'gain': 10}}}}}}},
'post': {'post0': {'type': 'Constant',
'name': 'postcon',
'value': 10,
'links': {}}}}Get the output function, which will be the output function of the last node, or the last item of the post-processor functions, if present.
link = hpct.get_output_function()
print(link.get_config()){'type': 'Constant', 'name': 'postcon', 'value': 10, 'links': {}}The hierarhcy can also be viewed graphically as a network of connected nodes.
import osimport networkx as nx
ahpct = PCTHierarchy(2,2, links="dense")
test = 2
if test==1:
g = ahpct.graph()
pos=graphviz_layout(g, prog='dot')
nx.draw(g, pos=pos, with_labels=True, font_size=12, font_weight='bold', node_color='red', node_size=500)
if test ==2:
g = ahpct.graph()
pos = nx.multipartite_layout(g, subset_key="layer", align='horizontal')
pos['constant1'][0]+=0.2
c = pos['constant1'][0]
print(c)
nx.draw(g, pos=pos, with_labels=True, font_weight='bold', node_color='red', node_size=750, arrowsize=25)
if test ==3:
if os.name=='nt':
ahpct.draw(file="ahpct.png", node_size=1500, figsize=(10,10))# with_labels=True, font_weight='bold', node_color='red', node_size=500, arrowsize=25, align='vertical'0.7454545454545454The hierachy can be run once by calling itself. The verbose flag will print the computations to the screen.
hpct(verbose=True)5.000
level0col0 0.000 0.000 0.000 0.000
level0col1 0.000 0.000 0.000 0.000
level0col2 0.000 0.000 0.000 0.000
level1col0 0.000 0.000 0.000 0.000
level1col1 0.000 0.000 0.000 0.000
level1col2 0.000 0.000 0.000 0.000
level2col0 1.000 0.000 1.000 10.000
level2col1 1.000 0.000 1.000 10.000
level2col2 1.000 0.000 1.000 10.000
10.000 10A hierarchy can be executed with the “run()” method, providing the number of iterations to run.
hpct1 = PCTHierarchy(3,3, pre=[pre], post=[post], history=True, links="dense")
namespace=hpct1.namespace
hpct1.get_node(2,0).get_function('reference').set_value(1)
hpct1.get_node(2,1).get_function('reference').set_value(1)
hpct1.get_node(2,2).get_function('reference').set_value(1)
for level in range(3):
for col in range(3):
hpct1.get_node(level,col).get_function('output').set_property('gain', 10)
hpct1.run(10)10If the hierarchy is created with the “history” flag equal to True, the data can be retrieved for each node. The node is accessed by specifying the row and column within the hierarchy.
print(hpct1.get_node(1,1).history.data)
assert hpct1.get_node(1,1).history.data == {'refcoll': {'weighted_sum6': [0.0, 30.0, 30.0, 30.0, 30.0, 30.0, 30.0, 30.0, 30.0, 30.0]}, 'percoll': {'weighted_sum5': [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]}, 'comcoll': {'subtract4': [0.0, 30.0, 30.0, 30.0, 30.0, 30.0, 30.0, 30.0, 30.0, 30.0]}, 'outcoll': {'proportional4': [0.0, 300.0, 300.0, 300.0, 300.0, 300.0, 300.0, 300.0, 300.0, 300.0]}}{'refcoll': {'weighted_sum6': [0, 30, 30, 30, 30, 30, 30, 30, 30, 30]}, 'percoll': {'weighted_sum5': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]}, 'comcoll': {'subtract4': [0, 30, 30, 30, 30, 30, 30, 30, 30, 30]}, 'outcoll': {'proportional4': [0, 300, 300, 300, 300, 300, 300, 300, 300, 300]}}Save a hierarchy to file.
import jsonhpct1.save("hpct.json")Create a hierarchy from file.
#loaded = PCTHierarchy.load("hpct.json", clear=False, namespace=namespace)
loaded = PCTHierarchy.load("hpct.json", clear=False)
loaded.summary()**************************
pcthierarchy PCTHierarchy [3, 3, 3] ceb3566b-036f-11f0-894f-04d9f58727ab
--------------------------
PRE: precon Constant | 5
Level 0 Cols 3
level0col0 PCTNode ceb3566b-036f-11f0-894f-04d9f58727ab
----------------------------
REF: weighted_sum WeightedSum | weights [1, 1, 1] | 900 | links proportional3 proportional4 proportional5
PER: variable Variable | 0
COM: subtract Subtract | 900 | links weighted_sum variable
OUT: proportional Proportional | gain 10 | 9000 | links subtract
----------------------------
level0col1 PCTNode ceb3566b-036f-11f0-894f-04d9f58727ab
----------------------------
REF: weighted_sum1 WeightedSum | weights [1, 1, 1] | 900 | links proportional3 proportional4 proportional5
PER: variable1 Variable | 0
COM: subtract1 Subtract | 900 | links weighted_sum1 variable1
OUT: proportional1 Proportional | gain 10 | 9000 | links subtract1
----------------------------
level0col2 PCTNode ceb3566b-036f-11f0-894f-04d9f58727ab
----------------------------
REF: weighted_sum2 WeightedSum | weights [1, 1, 1] | 900 | links proportional3 proportional4 proportional5
PER: variable2 Variable | 0
COM: subtract2 Subtract | 900 | links weighted_sum2 variable2
OUT: proportional2 Proportional | gain 10 | 9000 | links subtract2
----------------------------
Level 1 Cols 3
level1col0 PCTNode ceb3566b-036f-11f0-894f-04d9f58727ab
----------------------------
REF: weighted_sum4 WeightedSum | weights [1, 1, 1] | 30 | links proportional6 proportional7 proportional8
PER: weighted_sum3 WeightedSum | weights [1, 1, 1] | 0 | links variable variable1 variable2
COM: subtract3 Subtract | 30 | links weighted_sum4 weighted_sum3
OUT: proportional3 Proportional | gain 10 | 300 | links subtract3
----------------------------
level1col1 PCTNode ceb3566b-036f-11f0-894f-04d9f58727ab
----------------------------
REF: weighted_sum6 WeightedSum | weights [1, 1, 1] | 30 | links proportional6 proportional7 proportional8
PER: weighted_sum5 WeightedSum | weights [1, 1, 1] | 0 | links variable variable1 variable2
COM: subtract4 Subtract | 30 | links weighted_sum6 weighted_sum5
OUT: proportional4 Proportional | gain 10 | 300 | links subtract4
----------------------------
level1col2 PCTNode ceb3566b-036f-11f0-894f-04d9f58727ab
----------------------------
REF: weighted_sum8 WeightedSum | weights [1, 1, 1] | 30 | links proportional6 proportional7 proportional8
PER: weighted_sum7 WeightedSum | weights [1, 1, 1] | 0 | links variable variable1 variable2
COM: subtract5 Subtract | 30 | links weighted_sum8 weighted_sum7
OUT: proportional5 Proportional | gain 10 | 300 | links subtract5
----------------------------
Level 2 Cols 3
level2col0 PCTNode ceb3566b-036f-11f0-894f-04d9f58727ab
----------------------------
REF: constant Constant | 1
PER: weighted_sum9 WeightedSum | weights [1, 1, 1] | 0 | links weighted_sum3 weighted_sum5 weighted_sum7
COM: subtract6 Subtract | 1 | links constant weighted_sum9
OUT: proportional6 Proportional | gain 10 | 10 | links subtract6
----------------------------
level2col1 PCTNode ceb3566b-036f-11f0-894f-04d9f58727ab
----------------------------
REF: constant1 Constant | 1
PER: weighted_sum10 WeightedSum | weights [1, 1, 1] | 0 | links weighted_sum3 weighted_sum5 weighted_sum7
COM: subtract7 Subtract | 1 | links constant1 weighted_sum10
OUT: proportional7 Proportional | gain 10 | 10 | links subtract7
----------------------------
level2col2 PCTNode ceb3566b-036f-11f0-894f-04d9f58727ab
----------------------------
REF: constant2 Constant | 1
PER: weighted_sum11 WeightedSum | weights [1, 1, 1] | 0 | links weighted_sum3 weighted_sum5 weighted_sum7
COM: subtract8 Subtract | 1 | links constant2 weighted_sum11
OUT: proportional8 Proportional | gain 10 | 10 | links subtract8
----------------------------
POST: postcon Constant | 10
**************************import networkx as nx
import matplotlib.pyplot as plt# https://matplotlib.org/3.1.0/gallery/color/named_colors.html
loaded.draw(with_edge_labels=True, color_mapping={'w':'aqua','c':'limegreen','s':'goldenrod', 'p':'red', 'v':'silver'})
Build a hierarchy by adding nodes and functions manually.
Create an empty hierarchy.
myhpct = PCTHierarchy()
namespace=myhpct.namespace
myhpct.summary(build=False)**************************
pcthierarchy PCTHierarchy [] cf9927d0-036f-11f0-8e9c-04d9f58727ab
--------------------------
PRE: None
POST: None
**************************Add a node. Then nodes at particular positions.
myhpct.add_node(PCTNode(namespace=namespace))
myhpct.add_node(PCTNode(namespace=namespace), level=1)
myhpct.add_node(PCTNode(namespace=namespace), level=0)
myhpct.summary(build=False)**************************
pcthierarchy PCTHierarchy [2, 1] cf9927d0-036f-11f0-8e9c-04d9f58727ab
--------------------------
PRE: None
Level 0 Cols 2
pctnode2 PCTNode cf9927d0-036f-11f0-8e9c-04d9f58727ab
----------------------------
REF: constant2 Constant | 0
PER: variable2 Variable | 0
COM: subtract2 Subtract | 0
OUT: proportional2 Proportional | gain 1 | 0
----------------------------
pctnode PCTNode cf9927d0-036f-11f0-8e9c-04d9f58727ab
----------------------------
REF: constant Constant | 0
PER: variable Variable | 0
COM: subtract Subtract | 0
OUT: proportional Proportional | gain 1 | 0
----------------------------
Level 1 Cols 1
pctnode1 PCTNode cf9927d0-036f-11f0-8e9c-04d9f58727ab
----------------------------
REF: constant1 Constant | 0
PER: variable1 Variable | 0
COM: subtract1 Subtract | 0
OUT: proportional1 Proportional | gain 1 | 0
----------------------------
POST: None
**************************Replace functions at particular positions in the hierarchy.
myhpct.insert_function(level=0, col=0, collection="perception", function=Proportional(3, name="prop2", namespace=namespace))
myhpct.insert_function(level=1, col=0, collection="perception", function=WeightedSum(weights=[1,1], name="wsum", namespace=namespace))
myhpct.insert_function(level=0, col=1, collection="reference", function=Proportional(1, name="passthru", namespace=namespace))Add pre and post processor functions.
myhpct.add_preprocessor(Constant(1, name="cons1", namespace=namespace))
myhpct.add_preprocessor(Proportional(5, name="prop1", namespace=namespace))
myhpct.add_postprocessor(Proportional(5, name="postprop1", namespace=namespace))
myhpct.add_postprocessor(Proportional(5, name="postprop2", namespace=namespace))Link the functions together.
myhpct.set_links("prop1", "cons1")
myhpct.set_links("prop2", "prop1")
myhpct.add_links("wsum", "prop2", "variable")
myhpct.set_links("passthru", "proportional1")
myhpct.set_links("postprop1", "proportional")
myhpct.set_links("postprop2", "postprop1")myhpct.get_node(0,0).get_function('reference').set_value(1)
myhpct.get_node(1,0).get_function('reference').set_value(1)
myhpct.get_node(0,0).get_function('output').set_property('gain', 10)
myhpct.get_node(0,1).get_function('output').set_property('gain', 10)
myhpct.get_node(1,0).get_function('output').set_property('gain', 10)
myhpct.summary(build=True)**************************
pcthierarchy PCTHierarchy [2, 1] cf9927d0-036f-11f0-8e9c-04d9f58727ab
--------------------------
PRE: cons1 Constant | 1
prop1 Proportional | gain 5 | 0 | links cons1
Level 0 Cols 2
pctnode2 PCTNode cf9927d0-036f-11f0-8e9c-04d9f58727ab
----------------------------
REF: constant2 Constant | 1
PER: prop2 Proportional | gain 3 | 0 | links prop1
COM: subtract2 Subtract | 0 | links constant2 prop2
OUT: proportional2 Proportional | gain 10 | 0 | links subtract2
----------------------------
pctnode PCTNode cf9927d0-036f-11f0-8e9c-04d9f58727ab
----------------------------
REF: passthru Proportional | gain 1 | 0 | links proportional1
PER: variable Variable | 0
COM: subtract Subtract | 0 | links passthru variable
OUT: proportional Proportional | gain 10 | 0 | links subtract
----------------------------
Level 1 Cols 1
pctnode1 PCTNode cf9927d0-036f-11f0-8e9c-04d9f58727ab
----------------------------
REF: constant1 Constant | 1
PER: wsum WeightedSum | weights [1, 1] | 0 | links prop2 variable
COM: subtract1 Subtract | 0 | links constant1 wsum
OUT: proportional1 Proportional | gain 10 | 0 | links subtract1
----------------------------
POST: postprop1 Proportional | gain 5 | 0 | links proportional
postprop2 Proportional | gain 5 | 0 | links postprop1
**************************myhpctconfig = myhpct.get_config()
#print(myhpctconfig)
assert myhpctconfig == {'type': 'PCTHierarchy', 'name': 'pcthierarchy', 'pre': {'pre0': {'type': 'Constant', 'name': 'cons1', 'value': 1, 'links': {}}, 'pre1': {'type': 'Proportional', 'name': 'prop1', 'value': 0, 'links': {0: 'cons1'}, 'gain': 5}}, 'levels': {'level0': {'level': 0, 'nodes': {'col0': {'col': 0, 'node': {'type': 'PCTNode', 'name': 'pctnode2', 'refcoll': {'0': {'type': 'Constant', 'name': 'constant2', 'value': 1, 'links': {}}}, 'percoll': {'0': {'type': 'Proportional', 'name': 'prop2', 'value': 0, 'links': {0: 'prop1'}, 'gain': 3}}, 'comcoll': {'0': {'type': 'Subtract', 'name': 'subtract2', 'value': 0, 'links': {0: 'constant2', 1: 'prop2'}}}, 'outcoll': {'0': {'type': 'Proportional', 'name': 'proportional2', 'value': 0, 'links': {0: 'subtract2'}, 'gain': 10}}}}, 'col1': {'col': 1, 'node': {'type': 'PCTNode', 'name': 'pctnode', 'refcoll': {'0': {'type': 'Proportional', 'name': 'passthru', 'value': 0, 'links': {0: 'proportional1'}, 'gain': 1}}, 'percoll': {'0': {'type': 'Variable', 'name': 'variable', 'value': 0, 'links': {}}}, 'comcoll': {'0': {'type': 'Subtract', 'name': 'subtract', 'value': 0, 'links': {0: 'passthru', 1: 'variable'}}}, 'outcoll': {'0': {'type': 'Proportional', 'name': 'proportional', 'value': 0, 'links': {0: 'subtract'}, 'gain': 10}}}}}}, 'level1': {'level': 1, 'nodes': {'col0': {'col': 0, 'node': {'type': 'PCTNode', 'name': 'pctnode1', 'refcoll': {'0': {'type': 'Constant', 'name': 'constant1', 'value': 1, 'links': {}}}, 'percoll': {'0': {'type': 'WeightedSum', 'name': 'wsum', 'value': 0, 'links': {0: 'prop2', 1: 'variable'}, 'weights': [1.0, 1.0]}}, 'comcoll': {'0': {'type': 'Subtract', 'name': 'subtract1', 'value': 0, 'links': {0: 'constant1', 1: 'wsum'}}}, 'outcoll': {'0': {'type': 'Proportional', 'name': 'proportional1', 'value': 0, 'links': {0: 'subtract1'}, 'gain': 10}}}}}}}, 'post': {'post0': {'type': 'Proportional', 'name': 'postprop1', 'value': 0, 'links': {0: 'proportional'}, 'gain': 5}, 'post1': {'type': 'Proportional', 'name': 'postprop2', 'value': 0, 'links': {0: 'postprop1'}, 'gain': 5}}}Define the order in which the node will be processed.
myhpct.set_order(["pctnode2", "pctnode1", "pctnode"])Run the hierarchy once.
out = myhpct(verbose=True)
print(out)
assert out == -350001.000 5.000
pctnode2 1.000 15.000 -14.000 -140.000
pctnode1 1.000 15.000 -14.000 -140.000
pctnode -140.000 0.000 -140.000 -1400.000
-7000.000 -35000.000
-35000# config = {'type': 'Individual', 'name': 'pcthierarchy', 'pre': {'pre0': {'type': 'CartPoleV1', 'name': 'CartPoleV1', 'value': [0.03498833197860944, 0.20994561633454428, 0.012668159509212712, -0.2705237130920193, 0.047656152654718356], 'links': {0: 'Action1'}, 'env_name': 'CartPole-v1', 'reward': 1.0, 'done': False, 'info': {}}, 'pre1': {'type': 'IndexedParameter', 'name': 'ICV', 'value': 0.20994561633454428, 'links': {0: 'CartPoleV1'}, 'index': 1}, 'pre2': {'type': 'IndexedParameter', 'name': 'ICP', 'value': 0.03498833197860944, 'links': {0: 'CartPoleV1'}, 'index': 0}, 'pre3': {'type': 'IndexedParameter', 'name': 'IPV', 'value': -0.2705237130920193, 'links': {0: 'CartPoleV1'}, 'index': 3}, 'pre4': {'type': 'IndexedParameter', 'name': 'IPA', 'value': 0.012668159509212712, 'links': {0: 'CartPoleV1'}, 'index': 2}}, 'levels': {'level0': {'level': 0, 'nodes': {'col0': {'col': 0, 'node': {'type': 'PCTNode', 'name': 'L0C0', 'refcoll': {'0': {'type': 'EAConstant', 'name': 'RL0C0', 'value': 0, 'links': {}}}, 'percoll': {'0': {'type': 'EAWeightedSum', 'name': 'PL0C0', 'value': -0.2705237130920193, 'links': {0: 'ICV', 1: 'ICP', 2: 'IPV', 3: 'IPA'}, 'weights': [0, 0, 1, 0]}}, 'comcoll': {'0': {'type': 'Subtract', 'name': 'CL0C0', 'value': 0.2705237130920193, 'links': {0: 'RL0C0', 1: 'PL0C0'}}}, 'outcoll': {'0': {'type': 'EAProportional', 'name': 'OL0C0', 'value': -0.05046166000036782, 'links': {0: 'CL0C0'}, 'gain': -0.1865332226280776}}}}}}}, 'post': {'post0': {'type': 'EAWeightedSum', 'name': 'Action1', 'value': -0.005282911840894066, 'links': {0: 'OL0C0'}, 'weights': [0.10469159835121472]}}}
# ind = PCTHierarchy.from_config(config)from pct.errors import RootSumSquaredError, TotalError
er = RootSumSquaredError()
te = TotalError(error_response=er, limit=250,min=True)
te.add_error_data([1, 2])
print(te)
hpct = PCTHierarchy(1,1,error_collector=te)
hpct.run(steps=5, verbose=True)
err=te.error()
print(err)TotalError limit:250, limit_exceeded:False, : RootSumSquaredError error_response:2.23606797749979
[0]
level0col0 0.000 0.000 0.000 0.000
Current score=2.23606797749979
[1]
level0col0 0.000 0.000 0.000 0.000
Current score=2.23606797749979
[2]
level0col0 0.000 0.000 0.000 0.000
Current score=2.23606797749979
[3]
level0col0 0.000 0.000 0.000 0.000
Current score=2.23606797749979
[4]
level0col0 0.000 0.000 0.000 0.000
Current score=2.23606797749979
2.23606797749979