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6253fd3589121d8417376f870abbc8f350d20d9489200f79a309df1f5c73b734
Python
189
6
from __future__ import absolute_import from . import app x = app.MainWindow() #x.objectsPane.open('/home/arthur/forcebalance/studies/001_water_tutorial/1.netforce_torque.in') x.mainloop()
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Python
190
5
import gl gl.resetdefaults() gl.meshload('/Users/chris/afni/pial/lh.sphere') gl.overlayload('/Users/chris/afni/pial/lh.HCP-MMP1.annot') gl.atlas2node('/Users/chris/afni/pial/mynodes.node');
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Python
190
7
import numpy as np #ratios = [0, 15.0, 9.0, 3.0, 2.0, 1.5] default_ratio = 0 #ratios[0] intro_ratios = [9.0] #[ratios[2]] final_ratios = [4.0] #[ratios[3]] hard_ratios = [2.5] #[ratios[4]]
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Python
190
4
L,R = 0,1 COR,INCOR,EARLY_L,EARLY_R,NULL,KILLED = 1,0,2,3,4,5 EARLY = [EARLY_L, EARLY_R] PHASE_INTRO, PHASE_STIM, PHASE_DELAY, PHASE_LICK, PHASE_REWARD, PHASE_ITI, PHASE_END = 0,1,2,3,4,5,6
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Python
191
6
import pandas as pd df = pd.read_csv(snakemake.input.subclonality, sep="\t") df.loc[df["Subclonality"] == snakemake.wildcards.clone].to_csv( snakemake.output[0], sep="\t", index=False )
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Python
191
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""" Atom and bond features for GNN models. For an introduction to the theory behind this module, see :ref:`featurization_theory` """ from ._base import Feature __all__ = [ "Feature", ]
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Python
191
7
""" Structures for managing molecule graphs """ from ._dgl.molecule import DGLMolecule from ._dgl.batch import DGLMoleculeBatch from ._graph.molecule import GraphMolecule, GraphMoleculeBatch
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Python
192
6
from PyInstaller.utils.hooks import collect_submodules from PyInstaller.utils.hooks import collect_data_files hiddenimports = collect_submodules("scipy") datas = collect_data_files("scipy")
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Python
193
6
""" Copright © 2023 Howard Hughes Medical Institute, Authored by Carsen Stringer and Atika Syeda. """ " Test Facemap neural prediction output " # TODO: Add tests for neural prediction output
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Python
194
6
from PyInstaller.utils.hooks import collect_submodules from PyInstaller.utils.hooks import collect_data_files hiddenimports = collect_submodules("gevent") datas = collect_data_files("gevent")
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Python
195
6
from PyInstaller.utils.hooks import collect_submodules from PyInstaller.utils.hooks import collect_data_files hiddenimports = collect_submodules("antspyx") datas = collect_data_files("antspyx")
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Python
195
6
from PyInstaller.utils.hooks import collect_submodules from PyInstaller.utils.hooks import collect_data_files hiddenimports = collect_submodules("nibabel") datas = collect_data_files("nibabel")
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Python
195
6
from gufe import LigandAtomMapping from kartograf import KartografAtomMapper from . import lomap_scorers from .ligandatommapper import LigandAtomMapper from .lomap_mapper import LomapAtomMapper
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Python
195
6
from PyInstaller.utils.hooks import collect_submodules from PyInstaller.utils.hooks import collect_data_files hiddenimports = collect_submodules("sklearn") datas = collect_data_files("sklearn")
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Python
195
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from utils.schema_test_tools import test_local test_local(path_to_schema_dir='config/dumps/', schema_file='neo4j2owl_config_schema.json', path_to_test_dir='config/dumps/')
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Python
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from .cost_TS import CostsTS from .cost_FC import CostsFC from .cost_FC import CostsFixedFC from .cost_Mean import CostsMean from .cost_PSD import CostsPSD from .cost_PSD import CostsFixedPSD
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Python
196
6
from PyInstaller.utils.hooks import collect_submodules from PyInstaller.utils.hooks import collect_data_files hiddenimports = collect_submodules("rtutils") datas = collect_data_files("rtutils")
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Python
196
6
from PyInstaller.utils.hooks import collect_submodules from PyInstaller.utils.hooks import collect_data_files hiddenimports = collect_submodules("pydicom") datas = collect_data_files("pydicom")
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Python
197
8
""" Authors: Zheng Wang, John Griffiths, Andrew Clappison, Hussain Ather Neural Mass Model fitting module for functions used in the model """ import torch from torch.nn.parameter import Parameter
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Python
198
7
#!/usr/bin/env python # -*- coding: utf-8 -*- ############################################################################### METADATA_UNPROCESSED = "unprocessed" METADATA_PROCESSED = "processed"
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Python
199
6
from PyInstaller.utils.hooks import collect_submodules from PyInstaller.utils.hooks import collect_data_files hiddenimports = collect_submodules("distutils") datas = collect_data_files("distutils")
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Python
199
7
import numpy as np from .mle_modification import MLEModification class MLEFunctional: def __init__(self, x, cdf=None, xmin=None, xmax=None): self.modification = MLEModification(cdf, xmin, xmax)
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Python
199
8
import pandas as pd gene_info=pd.read_csv('/data1/bigbrain/phate_testing/gene_info.csv') ex = gene_info[['gene.symbol']] ex.to_csv('/data1/bigbrain/phate_testing/all_gene_lists.csv',index=False)
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Python
200
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from framework.core.config import ExperimentConfig # noqa: F401 from framework.core.data import Batch, GraphData, ModelOutput # noqa: F401 from framework.core.registry import REGISTRY # noqa: F401
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Python
202
8
import gl gl.resetdefaults() gl.meshload('BrainMesh_ICBM152.rh.mz3') gl.overlayload('motor_4t95mesh.mz3') gl.overlaycolorname(1, 'red') gl.shaderxray(1.0, 0.3) gl.azimuthelevation(110, 15) gl.meshcurv()
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Python
203
6
from PyInstaller.utils.hooks import collect_submodules from PyInstaller.utils.hooks import collect_data_files hiddenimports = collect_submodules("statsmodels") datas = collect_data_files("statsmodels")
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Python
204
8
import gl gl.resetdefaults() gl.meshload('BrainMesh_ICBM152Right.mz3') gl.overlayload('motor_4t95mesh.mz3') gl.overlaycolorname(1, 'red') gl.shaderxray(1.0, 0.3) gl.azimuthelevation(110, 15) gl.meshcurv()
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Python
205
6
from PyInstaller.utils.hooks import collect_submodules from PyInstaller.utils.hooks import collect_data_files hiddenimports = collect_submodules("scikit-learn") datas = collect_data_files("scikit-learn")
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Python
205
15
from abc import ABC, abstractmethod class distribution_continuous(ABC): @abstractmethod def cdf(self, x): pass @abstractmethod def pdf(self, y): pass @abstractstaticmethod def fit(s): pass
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Python
207
12
""" Import tests """ import cinnabar import pytest import sys def test_cinnabar_imported(): """Sample test, will always pass so long as import statement worked""" assert "cinnabar" in sys.modules
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Python
209
14
""" Import tests """ import sys import pytest import cinnabar def test_cinnabar_imported(): """Sample test, will always pass so long as import statement worked""" assert "cinnabar" in sys.modules
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Python
210
9
"""YAMMBS: Yet Another Molecular Mechanics Benchmarking Suite.""" from importlib.metadata import version from yammbs._store import MoleculeStore __all__ = ("MoleculeStore",) __version__ = version("yammbs")
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Python
212
9
from .element_change import ( filter_atoms_h_only_h_mapped, filter_element_changes, ) from .ring_changes import ( filter_ringsize_changes, filter_ringbreak_changes, filter_whole_rings_only, )
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Python
213
10
import gl import sys print(sys.version) print(sys.path) print(gl.__doc__) for key in dir( gl ): if not key.startswith('_'): x = getattr( gl, key ).__doc__ print(key+' (built-in function): ') print(x)
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Python
218
12
from setuptools import setup, find_packages setup( name='multimodal_decoding', version='0.1', packages=find_packages(), url='', license='', author='', author_email='', description='' )
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Python
218
8
import gl gl.resetdefaults() gl.meshload('BrainMesh_ICBM152Left_smoothed.mz3') gl.meshcurv() gl.shadername('hidecurves') gl.overlayload('CIT168.mz3') gl.shaderforbackgroundonly(1) gl.shaderadjust('curvthreshhi', 0.44)
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Python
219
12
#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Fri Feb 7 11:17:06 2025 @author: saiful """ import pandas as pd df = pd.read_csv("/data/saiful/ePPI/alphafold_eppi_embeddings/eppi_enzym_info_all.csv")
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Python
221
11
import base64 from pyroaring import BitMap def serialize_bitmap(bitmap: BitMap) -> str: return base64.b64encode(bitmap.serialize()).decode("ascii") def bitmap_count(bitmap: BitMap) -> int: return len(bitmap)
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Python
221
10
import numpy as np import os, os.path import logging def test_openmm_platforms(): """Testing comparison of platforms.""" from openmmtools.scripts import test_openmm_platforms # test_openmm_platforms.main()
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Python
222
10
from sybil import Sybil from sybil.parsers.rest import PythonCodeBlockParser pytest_collect_file = Sybil( name="tests", parsers=[ PythonCodeBlockParser(), ], patterns=["*.py", "*.rst"], ).pytest()
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Python
223
9
from PyInstaller.utils.hooks import collect_submodules hiddenimports = [ "PySide6.QtCore", "PySide6.QtGui", "PySide6.QtWidgets", "PySide6.QtWebEngineWidgets", # only include the ones you actually use ]
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Python
228
8
from util import now,now2 def add_to_saver_buffer(buf, source, data, ts=None, ts2=None, columns=None): if ts is None: ts = now() if ts2 is None: ts2 = now2() buf.put([source, data, ts, ts2, columns])
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Python
230
8
from numpy.testing import assert_allclose from openff.nagl.features._utils import one_hot_encode def test_one_hot_encode(): encoding = one_hot_encode("b", ["a", "b", "c"]).numpy() assert_allclose(encoding, [[0, 1, 0]])
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Python
232
12
from .core import * from .codec import * def ToASCII(label): return encode(label) def ToUnicode(label): return decode(label) def nameprep(s): raise NotImplementedError('IDNA 2008 does not utilise nameprep protocol')
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Python
232
10
import sys from pathlib import Path PROJECT_ROOT = Path(__file__).resolve().parents[1] SRC_ROOT = PROJECT_ROOT / "src" for path in (PROJECT_ROOT, SRC_ROOT): if str(path) not in sys.path: sys.path.insert(0, str(path))
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Python
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""" Model architectures and factory """ from .model import CustomModelCheckpoint, ModelBuilder, ModelLoader from .model_factory import ModelFactory __all__ = ["ModelFactory", "ModelBuilder", "ModelLoader", "CustomModelCheckpoint"]
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Python
235
11
import os import random import numpy as np import tensorflow as tf def set_global_seed(seed: int = 42) -> None: os.environ["PYTHONHASHSEED"] = str(seed) random.seed(seed) np.random.seed(seed) tf.random.set_seed(seed)
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Python
237
9
# pylint:disable='import-error' from nemsi import Morphology from bsb.morphologies import Morphology as _Morpho def convert_swc(data): m = Morphology.from_swc_data(data) data = m.to_swc() return _Morpho.from_swc_data(data)
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Python
238
9
import unittest from shapely.geometry import Point from shapely.validation import explain_validity class ValidationTestCase(unittest.TestCase): def test_valid(self): assert explain_validity(Point(0, 0)) == "Valid Geometry"
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Python
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stim_phase_durs = [ [[1.],None], [[2.,2.8,3.8],[.4,.3,.3]] ] default_stim_phase_duration = [[3.8, 1.5],[.85,.15]] delay_phase_durs = [ [[.200], None], [[.200],None] ] default_delay_phase_duration = [[.200],None] long_delay = [[1.3],None]
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Python
239
7
from PyInstaller.utils.hooks import collect_submodules from PyInstaller.utils.hooks import collect_data_files, copy_metadata hiddenimports = collect_submodules("gdown") datas = copy_metadata("gdown") datas += collect_data_files("gdown")
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Python
239
6
# Copyright Jonathan Hartley 2013. BSD 3-Clause license, see LICENSE file. from .initialise import init, deinit, reinit, colorama_text from .ansi import Fore, Back, Style, Cursor from .ansitowin32 import AnsiToWin32 __version__ = '0.4.4'
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Python
243
12
import pickle def save_pkl(filename, save_object): writer = open(filename,'wb') pickle.dump(save_object, writer) writer.close() def load_pkl(filename): loader = open(filename,'rb') file = pickle.load(loader) loader.close() return file
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Python
244
7
from pyphi import config import marshall_intrinsic_units with config.override(VALIDATE_SUBSYSTEM_STATES=False): marshall_intrinsic_units.run_binary_units_micro_example() marshall_intrinsic_units.summarize_binary_units_micro_example()
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Python
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9
"""ubergraph-agent package.""" import importlib_metadata try: __version__ = importlib_metadata.version(__name__) except importlib_metadata.PackageNotFoundError: # package is not installed __version__ = "0.0.0" # pragma: no cover
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Python
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13
""" GO Annotation Review agent module for reviewing GO standard annotations. """ from pathlib import Path THIS_DIR = Path(__file__).parent DOCUMENTS_DIR = THIS_DIR / "documents" __all__ = [ # Constants "THIS_DIR", "DOCUMENTS_DIR", ]
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Python
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8
# This code is part of OpenFE and is licensed under the MIT license. # For details, see https://github.com/OpenFreeEnergy/openfe """ The MCS class from Lomap shamelessly wrapped and used here to match our API. """ from lomap import LomapAtomMapper
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Python
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7
# This code is part of OpenFE and is licensed under the MIT license. # For details, see https://github.com/OpenFreeEnergy/openfe from .relative_alchemical_network_planner import ( RHFEAlchemicalNetworkPlanner, RBFEAlchemicalNetworkPlanner, )
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Python
251
7
import time def now(): return time.clock() #Platform-dependent, on windows has high precision. no correspondence to "real" time of day #return time.time() # Platform-invariant, but low resolution on windows def now2(): return time.time()
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Python
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10
"Architectures for convolutional layers" from ._base import BaseGCNStack, _GCNStackMeta from ._sage import SAGEConvStack from ._gin import GINConvStack __all__ = ["BaseGCNStack", "SAGEConvStack", "GINConvStack"] # TODO: eventually migrate out DGL?
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Python
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9
# Use TypedDict for metadata from typing_extensions import TypedDict MetadataDict = TypedDict("Metadata", {"difficulty": str, "type": str}) def metadata(difficulty: str, type: str) -> MetadataDict: return {"difficulty": difficulty, "type": type}
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Python
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#!/usr/bin/env python # -*- coding: utf-8 -*- from os import path import json def load_atlas(name): fname = f"{path.dirname(__file__)}/atlas/{name}.json" with open(fname) as f: return json.load(f) if __name__ == '__main__': pass
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Python
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"""For when pip wants to check the date or time. """ import datetime def today_is_later_than(year, month, day): # type: (int, int, int) -> bool today = datetime.date.today() given = datetime.date(year, month, day) return today > given
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Python
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import pytest from truesight.dataset.gsm8k import GSM8kGenerator @pytest.mark.asyncio async def test_basic(): generator = GSM8kGenerator( preference_prompt="hello", model_id="gpt-4o-2024-08-06", ) await generator.generate(5)
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Python
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""" Hi-Compass Predicting Module This module provides functionality for Hi-C prediction from genomic features. """ from .PredictDataset import PredictDataset from .PredictModel import PredictModel __all__ = [ 'PredictDataset', 'PredictModel', ]
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Python
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"""Test the tracking models.""" from absl.testing import parameterized from tensorflow.python.framework import test_util as tf_test_util from keras import keras_parameterized from tensorflow.keras import backend as K from deepcell.model_zoo import tracking
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Python
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from PyInstaller.utils.hooks import collect_submodules from PyInstaller.utils.hooks import collect_data_files, copy_metadata hiddenimports = collect_submodules("raidionicsseg") datas = copy_metadata("raidionicsseg") datas += collect_data_files("raidionicsseg")
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Python
263
8
# This code is part of OpenFE and is licensed under the MIT license. # For details, see https://github.com/OpenFreeEnergy/openfe from .plugins import OFECommandPlugin from . import commands from importlib.metadata import version __version__ = version("openfe")
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Python
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#!/usr/bin/env python # -*- coding: utf-8 -*- from __future__ import print_function, division, absolute_import, unicode_literals from pylab import * def pylab_eval(expr, **variables): return eval(expr, None, variables) if __name__ == '__main__': pass
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from PyInstaller.utils.hooks import collect_submodules from PyInstaller.utils.hooks import collect_data_files, copy_metadata hiddenimports = collect_submodules("raidionicsrads") datas = copy_metadata("raidionicsrads") datas += collect_data_files("raidionicsrads")
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"""Builtin Datasets""" from .dynamic_nuclear_net import ( DynamicNuclearNetSample, DynamicNuclearNetSegmentation, DynamicNuclearNetTracking ) from .tissue_net import TissueNet, TissueNetSample from .spot_net import ( SpotNet, SpotNetExampleData )
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from gufe import LigandAtomMapping from .ligandatommapper import LigandAtomMapper from .lomap_mapper import LomapAtomMapper from .perses_mapper import PersesAtomMapper from kartograf import KartografAtomMapper from . import perses_scorers from . import lomap_scorers
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import gl gl.resetdefaults() gl.meshload('BrainMesh_ICBM152.rh.mz3') gl.overlayload('motor_4t95mesh.mz3') gl.overlaycolorname(1, 'red') gl.shaderxray(0.9, 0.5) gl.azimuthelevation(110, 15) gl.meshcurv() gl.shadername('MatCap'); gl.shadermatcap('MetalShiny');
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import gl gl.resetdefaults() gl.meshload('BrainMesh_ICBM152Right.mz3') gl.overlayload('motor_4t95vol.nii.gz') gl.overlayminmax(1,2,12) gl.overlaycolorname(2, 'Red-Yellow') gl.azimuthelevation(110, 15) gl.shadername('MatCap'); gl.meshcurv() gl.overlaytranslucent(2, 1)
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import gl gl.resetdefaults() #opacity adjusts whether overlays are translucent (0) opacity = 50 pth = '/Users/chris/Downloads/sf/' gl.meshload('BrainMesh_ICBM152_smoothed.mz3') gl.overlayload(pth+'region.mz3') gl.overlayload(pth+'stat.mz3') gl.overlayoverlapoverwrite(0)
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#!/usr/bin/env python from forcebalance.molecule import * from forcebalance.nifty import _exec #Run calculation _exec("psi4 -n 8 eth.psi4in eth.psi4out") #Get ouptut and write qdata.txt file mol_out = Molecule("eth.psi4out") mol_out.write("qdata.txt", ftype="qdata")
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from datasets import load_dataset COT_SUFFIX = "Provide your reasoning in <think> tags. Write your final answer in <answer> tags. Only give the numeric value as your answer." COT_PROMPT_TEMPLATE = "{question} " + COT_SUFFIX DATASET = load_dataset("openai/gsm8k", "main")
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#!/usr/bin/env python from __future__ import print_function import numpy as np QM_MM = np.loadtxt('EnergyCompare.txt') QM_Wt = np.zeros_like(QM_MM[:,3]) + 1.0 QM_Wt /= np.sum(QM_Wt) D = QM_MM[:,0]-QM_MM[:,1] D -= np.mean(D) D /= 4.184 D = np.abs(D) print(np.dot(D,QM_Wt))
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# compute mutual information score import numpy as np from sklearn.metrics import mutual_info_score def calc_MI(x, y, bins): c_xy = np.histogram2d(x, y, bins)[0] mi = mutual_info_score(None, None, contingency=c_xy) return mi py_mi = calc_MI(veci, vecj, nbins)
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#!/usr/bin/env python # -*- coding: utf-8 -*- import os.path as path __author__ = 'herrlich10 <herrlich10@gmail.com>' with open(path.join(path.dirname(path.realpath(__file__)), '__version__')) as f: __version__ = f.readline().strip() if __name__ == '__main__': pass
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__all__ = [] from . import _ml from ._ml import * from . import _venn from ._venn import * from . import _std from ._std import * from . import _graphs from ._graphs import * __all__ += _ml.__all__ __all__ += _venn.__all__ __all__ += _std.__all__ __all__ += _graphs.__all__
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import sys import PyInstaller.__main__ # Set recursion limit early sys.setrecursionlimit(10000) print("Recursion limit before build:", sys.getrecursionlimit()) PyInstaller.__main__.run([ '--log-level=INFO', '--noconfirm', '--clean', 'assets/main_arm.spec' ])
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channel_config = { "colors" : ["gcamp", "isos"], #needs to stay in this order "gcamp" : {1 : {"_4701", "_470A" ,"_465A"}, 2 : {"_4702", "_470B", "_465B"}}, "isos" : {1 : {"_4051", "_405A"}, 2 : {"_4052", "_405B"}}}
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from setuptools import setup, find_packages # Read dependencies from requirements.txt with open("requirements.txt") as f: requirements = f.read().splitlines() setup( name="seege_", version="0.1.0", packages=find_packages(), install_requires=requirements, )
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""" ===== Geo ===== Welcome to Geo - an example template / easter egg. Theme courtesy of the wonderful Geo for Bootstrap theme: http://code.divshot.com/geo-bootstrap/ """ import os template_parent = "original" template_dir = os.path.dirname(__file__) base_fn = "base.html"
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import pytest from openff.nagl.label.dataset import LabelledDataset @pytest.fixture(scope="function") def small_dataset(tmp_path): smiles = ["C", "CC"] dataset = LabelledDataset.from_smiles( tmp_path, smiles, mapped=False ) return dataset
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import gl gl.resetdefaults() gl.meshload('BrainMesh_ICBM152.rh.mz3') gl.overlayload('motor_4t95mesh.mz3') gl.overlaycolorname(1, 'red') gl.shaderxray(0.9, 0.5) gl.azimuthelevation(110, 15) gl.shadername('MatCap'); gl.shadermatcap('Cortex'); gl.meshcurv() gl.overlaytranslucent(2, 1)
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"""Config classes for defining optimizers""" import typing from openff.nagl._base.base import ImmutableModel class OptimizerConfig(ImmutableModel): """The configuration for the optimizer to use during training""" optimizer: typing.Literal["Adam"] learning_rate: float
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from pathlib import Path from dotenv import load_dotenv import pytest import os, certifi os.environ["SSL_CERT_FILE"] = certifi.where() @pytest.fixture(scope="session", autouse=True) def load_env(): """Load environment variables from .env file for all tests.""" load_dotenv()
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import gl gl.resetdefaults() gl.meshload('BrainMesh_ICBM152Right.mz3') gl.overlayload('motor_4t95mesh.mz3') gl.overlaycolorname(1, 'red') gl.shaderxray(0.9, 0.5) gl.azimuthelevation(110, 15) gl.shadername('MatCap'); gl.shadermatcap('Cortex'); gl.meshcurv() gl.overlaytranslucent(2, 1)
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"""Benchmarks for OpenFF protein force fields""" # Add imports here # Handle versioneer from ._version import get_versions from .proteinbenchmark import * versions = get_versions() __version__ = versions["version"] __git_revision__ = versions["full-revisionid"] del get_versions, versions
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def get_mem_mb(wildcards, attempt): """ To adjust resources in the rules attemps = reiterations + 1 Max number attemps = 8 """ mem_avail = [2, 4, 8, 16, 64, 128, 256] # print(mem_avail[attempt-1] * 1000, attempt, mem_avail) return mem_avail[attempt - 1] * 1000
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from .logging import setup_logging from .kfold import train_kfold,kfold_split_dataset from .eval_vis import plot_kfold_comparison, plot_training_curves __all__ = [ 'setup_logging', 'train_kfold', 'kfold_split_dataset', 'plot_kfold_comparison', 'plot_training_curves' ]
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""" ========= gathered ========= This theme extends 'default'. Unlike 'default', it organizes all sections under the 'Detailed Statistics' header, rather than grouping them by module. """ import os template_dir = os.path.dirname(__file__) template_parent = "original" base_fn = "base.html"
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import numpy as np test_int_types = [int, np.int16, np.int32, np.int64] class MultiGeometryTestCase: def subgeom_access_test(self, cls, geoms): geom = cls(geoms) for t in test_int_types: for i, g in enumerate(geoms): assert geom.geoms[t(i)] == g
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# This code is part of OpenFE and is licensed under the MIT license. # For details, see https://github.com/OpenFreeEnergy/openfe from . import custom_typing from .optional_imports import requires_package from .remove_oechem import without_oechem_backend from .system_probe import log_system_probe
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import sys import numpy as np MC_file=sys.argv[1] FD_file=sys.argv[2] mc_data = np.loadtxt(MC_file) fd_data = mc_data[1:, :] - mc_data[0:-1, :] fd_data[:, :3] *= 35 fd_data = np.abs(fd_data) fd_data = fd_data.sum(axis=1) fd_data = np.insert(fd_data, 0, 0) np.savetxt(FD_file, fd_data, fmt="%.7f")
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from config import * from analog_reader import AnalogReader from valve import Valve from light import Light from opto import Opto from audio import Speaker from cameras import default_cam_params, PSEye from communications import SICommunicator from mp285 import MP285 from actuator import LActuator
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#!/usr/local/bin/python2.0 import os, sys from string import * argv=sys.argv argc=len(argv) raw = map(split, open(argv[1]).readlines()) for line in raw: print line[-1], m=1 for token in line[:-1]: if atof(token) != 0: print "%d:%s"%(m,token), m=m+1 print
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"""Metrics have been moved to deepcell_toolbox.metrics.""" from deepcell_toolbox.metrics import PixelMetrics from deepcell_toolbox.metrics import ObjectMetrics from deepcell_toolbox.metrics import Metrics from deepcell_toolbox.metrics import split_stack from deepcell_toolbox.metrics import match_nodes