cleanup readme and example
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README.md
125
README.md
@ -16,101 +16,98 @@ has deprived the man of both a schematic and a better connectivity tool.
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Requirements:
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Requirements:
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* python >= 3.9 (written and tested with 3.10)
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* python >= 3.9 (written and tested with 3.10)
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* numpy
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* numpy
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* pyclipper
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* klayout (python package only)
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Install with pip:
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Install with pip:
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```bash
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```bash
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pip3 install snarled
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pip install snarled
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```
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```
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Alternatively, install from git
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Alternatively, install from git
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```bash
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```bash
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pip3 install git+https://mpxd.net/code/jan/snarled.git@release
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pip install git+https://mpxd.net/code/jan/snarled.git@release
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```
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```
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## Example
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## Example
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See `examples/check.py`. Note that the example uses `masque` to load data.
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See `examples/check.py` (python interface) or `examples/run.sh` (command-line interface).
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Command line:
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```bash
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snarled connectivity.oas connectivity.txt -m layermap.txt
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```
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Python interface:
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```python3
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```python3
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from pprint import pformat
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from pprint import pformat
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from masque.file import gdsii, oasis
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import logging
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import snarled
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import snarled.interfaces.masque
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# Layer definitions
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import snarled
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connectivity = {
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from snarled.types import layer_t
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logging.basicConfig()
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logging.getLogger('snarled').setLevel(logging.INFO)
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connectivity = [
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((1, 0), (1, 2), (2, 0)), # M1 to M2 (via V12)
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((1, 0), (1, 2), (2, 0)), # M1 to M2 (via V12)
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((1, 0), (1, 3), (3, 0)), # M1 to M3 (via V13)
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((1, 0), (1, 3), (3, 0)), # M1 to M3 (via V13)
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((2, 0), (2, 3), (3, 0)), # M2 to M3 (via V23)
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((2, 0), (2, 3), (3, 0)), # M2 to M3 (via V23)
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]
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labels_map: dict[layer_t, layer_t] = {
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(1, 0): (1, 0),
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(2, 0): (2, 0),
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(3, 0): (3, 0),
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}
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}
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filename = 'connectivity.oas'
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cells, props = oasis.readfile('connectivity.oas')
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nets = snarled.trace_layout(filename, connectivity, topcell='top', labels_map=labels_map)
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topcell = cells['top']
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result = snarled.TraceAnalysis(nets)
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polys, labels = snarled.interfaces.masque.read_cell(topcell, connectivity)
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print('\n')
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nets_info = snarled.trace_connectivity(polys, labels, connectivity)
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print(result)
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print('\nFinal nets:')
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print([kk for kk in nets_info.nets if isinstance(kk.name, str)])
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print('\nShorted net sets:')
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for short in nets_info.get_shorted_nets():
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print('(' + ','.join([repr(nn) for nn in sorted(list(short))]) + ')')
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print('\nOpen nets:')
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print(pformat(dict(nets_info.get_open_nets())))
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```
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```
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this prints the following:
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this prints the following:
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```
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```
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Nets ['SignalD', 'SignalI'] are shorted on layer (1, 0) in poly:
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INFO:snarled.trace:Adding layer (3, 0)
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[[13000.0, -3000.0],
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INFO:snarled.trace:Adding layer (2, 3)
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[16000.0, -3000.0],
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INFO:snarled.trace:Adding layer (1, 3)
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[16000.0, -1000.0],
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INFO:snarled.trace:Adding layer (1, 2)
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[13000.0, -1000.0],
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INFO:snarled.trace:Adding layer (1, 0)
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[13000.0, 2000.0],
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INFO:snarled.trace:Adding layer (2, 0)
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[12000.0, 2000.0],
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[12000.0, -1000.0],
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[11000.0, -1000.0],
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[11000.0, -3000.0],
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[12000.0, -3000.0],
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[12000.0, -8000.0],
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[13000.0, -8000.0]]
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Nets ['SignalK', 'SignalK'] are shorted on layer (1, 0) in poly:
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[[18500.0, -8500.0], [28200.0, -8500.0], [28200.0, 1000.0], [18500.0, 1000.0]]
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Nets ['SignalC', 'SignalC'] are shorted on layer (1, 0) in poly:
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[[10200.0, 0.0], [-1100.0, 0.0], [-1100.0, -1000.0], [10200.0, -1000.0]]
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Nets ['SignalG', 'SignalH'] are shorted on layer (1, 0) in poly:
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[[10100.0, -2000.0], [5100.0, -2000.0], [5100.0, -3000.0], [10100.0, -3000.0]]
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Final nets:
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[SignalA, SignalC__0, SignalE, SignalG, SignalK__0, SignalK__2, SignalL]
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Shorted net sets:
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Trace analysis
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(SignalC__0,SignalC__1,SignalD,SignalI)
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=============
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(SignalK__0,SignalK__1)
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Nets
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(SignalG,SignalH)
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(groups of electrically connected labels)
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(SignalA,SignalB)
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SignalA,SignalB
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(SignalE,SignalF)
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SignalC,SignalD,SignalI
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SignalE,SignalF
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SignalG,SignalH
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SignalK
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SignalK
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SignalL
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Open nets:
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Opens
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{'SignalK': [SignalK__0, SignalK__2]}
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(2+ nets containing the same name)
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SignalK : 2 nets
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Shorts
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(2+ unique names for the same net)
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SignalA,SignalB
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SignalC,SignalD,SignalI
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SignalE,SignalF
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SignalG,SignalH
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=============
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```
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```
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## Code organization
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## Code organization
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- The main functionality is in `trace_connectivity`.
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- The primary functionality is in `trace`; specifically `trace.trace_layout()`.
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- Useful classes, namely `NetsInfo` and `NetName`, are in `snarled.tracker`.
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- `main` provides a command-line interface, supported by the functions in `utils`.
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- `snarled.interfaces` contains helper code for interfacing with other packages.
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## Caveats
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This package is slow, dumb, and the code is ugly. There's only a basic test case.
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If you know what you're doing, you could probably do a much better job of it.
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...but you *have* heard of it :)
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@ -1,8 +1,6 @@
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"""
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"""
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Example code for checking connectivity in a layout by using
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Example code for checking connectivity in a layout by using `snarled`
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`snarled` and `masque`.
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"""
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"""
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from pprint import pformat
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import logging
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import logging
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import snarled
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import snarled
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@ -12,13 +10,14 @@ from snarled.types import layer_t
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logging.basicConfig()
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logging.basicConfig()
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logging.getLogger('snarled').setLevel(logging.INFO)
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logging.getLogger('snarled').setLevel(logging.INFO)
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# How are the conductors connected to each other?
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connectivity = [
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connectivity = [
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((1, 0), (1, 2), (2, 0)), # M1 to M2 (via V12)
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((1, 0), (1, 2), (2, 0)), # M1 to M2 (via V12)
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((1, 0), (1, 3), (3, 0)), # M1 to M3 (via V13)
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((1, 0), (1, 3), (3, 0)), # M1 to M3 (via V13)
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((2, 0), (2, 3), (3, 0)), # M2 to M3 (via V23)
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((2, 0), (2, 3), (3, 0)), # M2 to M3 (via V23)
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]
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]
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# What labels should be loaded, and which geometry layers should they apply to?
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labels_map: dict[layer_t, layer_t] = {
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labels_map: dict[layer_t, layer_t] = {
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(1, 0): (1, 0),
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(1, 0): (1, 0),
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(2, 0): (2, 0),
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(2, 0): (2, 0),
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