repo stringlengths 2 99 | file stringlengths 13 225 | code stringlengths 0 18.3M | file_length int64 0 18.3M | avg_line_length float64 0 1.36M | max_line_length int64 0 4.26M | extension_type stringclasses 1
value |
|---|---|---|---|---|---|---|
PyBDSF | PyBDSF-master/bdsf/collapse.py | """Module collapse
Defines operation Op_collapse which collapses 3D image. Calculates and
stores mean and rms (normal and clipped) per channel anyway for further
use, even if weights are unity.
"""
from __future__ import absolute_import
import numpy as N
from .image import *
from . import _cbdsm
#_cbdsm.init_numpy()
... | 11,493 | 36.562092 | 114 | py |
PyBDSF | PyBDSF-master/bdsf/const.py | """Constants
Some universal constants
"""
import math
pi=math.pi
fwsig=2.35482
rad=180.0/pi
c=2.99792458e8
bolt=1.3806505e-23
sq2=math.sqrt(2)
| 147 | 8.866667 | 24 | py |
PyBDSF | PyBDSF-master/bdsf/readimage.py | """Module readimage.
Defines operation Op_readimage which initializes image and WCS
The current implementation tries to reduce input file to 2D if
possible, as this makes more sense atm. One more important thing
to note -- in its default configuration pyfits will read data
in non-native format, so we have to convert ... | 25,341 | 40.13961 | 119 | py |
PyBDSF | PyBDSF-master/bdsf/spectralindex.py | """Module Spectral index.
This module calculates spectral indices for Gaussians and sources for a multichannel cube.
"""
from __future__ import print_function
from __future__ import absolute_import
import numpy as N
from .image import Op
from . import mylogger
from copy import deepcopy as cp
from . import functio... | 29,798 | 46.602236 | 146 | py |
PyBDSF | PyBDSF-master/bdsf/image.py | """Module image.
Instances of class Image are a primary data-holders for all PyBDSF
operations. They store the image itself together with some meta-information
(such as headers), options for processing modules and all data generated during
processing. A few convenience methods are also defined here for interactive
use... | 7,542 | 34.580189 | 88 | py |
PyBDSF | PyBDSF-master/bdsf/wavelet_atrous.py | """Compute a-trous wavelet transform of the gaussian residual image.
Do source extraction on this if asked.
"""
from __future__ import print_function
from __future__ import absolute_import
import numpy as N
from .image import *
from . import mylogger
import os
from . import has_pl
if has_pl:
import matplotlib.pypl... | 30,509 | 40.966988 | 170 | py |
PyBDSF | PyBDSF-master/bdsf/mylogger.py | """ WARNING, ERROR, and CRITICAL are always output to screen and to log file.
INFO and USERINFO always go to the log file. DEBUG goes to log file if debug is
True. USERINFO goes to screen only if quiet is False.
Use as follows:
mylog = mylogger.logging.getLogger("name")
mylog.info('info') --> print to logfile, but n... | 4,331 | 30.852941 | 79 | py |
PyBDSF | PyBDSF-master/bdsf/polarisation.py | """Module polarisation.
This module finds the Q, U, and V fluxes, the total, linear, and circular
polarisation fractions and the linear polarisation angle of each source identified
by gaul2srl. The position angle is defined from North, with positive angles
towards East.
"""
from __future__ import absolute_import
fro... | 30,916 | 46.2737 | 145 | py |
PyBDSF | PyBDSF-master/bdsf/cleanup.py | """
Does miscellaneous jobs at the end, which assumes all other tasks are run.
"""
from __future__ import absolute_import
import numpy as N
import os
from .image import *
from . import mylogger
from . import has_pl
if has_pl:
import matplotlib.pyplot as pl
import matplotlib.cm as cm
from . import funct... | 1,688 | 29.160714 | 102 | py |
PyBDSF | PyBDSF-master/bdsf/islands.py | """Module islands.
Defines operation Op_islands which does island detection.
Current implementation uses scipy.ndimage operations for island detection.
While it's implemented to work for images of arbitrary dimensionality,
the bug in the current version of scipy (0.6) often causes crashes
(or just wrong results) for 3... | 18,339 | 41.258065 | 148 | py |
PyBDSF | PyBDSF-master/bdsf/opts.py | """PyBDSF options
Options are essentially user-controllable parameters passed into PyBDSF
operations, and allow for end-users to control the exact details of how
calculations are done.
The doc string should give a short description of the option, followed by a
line break ('\n') then a long, detailed description. The ... | 103,331 | 65.537025 | 116 | py |
PyBDSF | PyBDSF-master/bdsf/sourcecounts.py | """Sourcecounts
s is flux in Jy and n is number > s per str
"""
import numpy as N
s=N.array([ 9.9999997e-05, 0.00010328281, 0.00010667340, 0.00011017529, 0.00011379215, 0.00011752774, 0.00012138595, \
0.00012537083, 0.00012948645, 0.00013373725, 0.00013812761, 0.00014266209, 0.00014734542, 0.00015218249, 0.000157178... | 12,587 | 104.781513 | 123 | py |
PyBDSF | PyBDSF-master/bdsf/functions.py | # some functions
from __future__ import print_function
from __future__ import absolute_import
try:
# For Python 2
basestring = basestring
except NameError:
basestring = str
def poly(c,x):
""" y = Sum { c(i)*x^i }, i=0,len(c)"""
import numpy as N
y=N.zeros(len(x))
for i in range(len(c)):
... | 80,495 | 32.950232 | 141 | py |
PyBDSF | PyBDSF-master/bdsf/psf_vary.py | from __future__ import print_function
from __future__ import absolute_import
import numpy as N
from .image import *
from . import mylogger
from copy import deepcopy as cp
from . import has_pl
if has_pl:
import matplotlib.pyplot as pl
import scipy
import scipy.signal as S
from . import _cbdsm
from . import function... | 49,211 | 44.821229 | 176 | py |
PyBDSF | PyBDSF-master/bdsf/pybdsf.py | """Interactive PyBDSF shell.
This module initializes the interactive PyBDSF shell, which is a customized
IPython enviroment. It should be called from the terminal prompt using the
command "pybdsf".
"""
from __future__ import print_function
import bdsf
from bdsf.image import Image
import pydoc
import sys
import inspect... | 29,572 | 38.378162 | 83 | py |
PyBDSF | PyBDSF-master/bdsf/plotresults.py | """Plotting module
This module is used to display fits results.
"""
from __future__ import print_function
from __future__ import absolute_import
from .image import *
from . import has_pl
if has_pl:
import matplotlib.pyplot as pl
import matplotlib.cm as cm
import matplotlib.patches as mpatches
from matp... | 29,396 | 38.672065 | 137 | py |
PyBDSF | PyBDSF-master/bdsf/tc.py | """Defines some basic facilities for handling typed values.
It's quite basic and limited implementation tailored specifically for
use in the PyBDSM user-options and derived properties. For a user
option, one can define a group that is used when listing the options to
the screen. For a property (e.g., flux density), o... | 20,582 | 29.092105 | 77 | py |
PyBDSF | PyBDSF-master/bdsf/_version.py | """Version module.
This module simply stores the version number, as well as a changelog.
"""
# Version number
__version__ = '1.11.0a1'
# Changelog
def changelog():
"""
PyBDSF Changelog.
-----------------------------------------------------------------------
2023/05/22 - Version 1.10.3
2023/05/0... | 29,263 | 39.985994 | 85 | py |
PyBDSF | PyBDSF-master/bdsf/gausfit.py | """Module gausfit.
This module does multi-gaussian fits for all detected islands.
At the moment fitting algorithm is quite simple -- we just add
gaussians one-by-one as long as there are pixels with emission
in the image, and do post-fitting flagging of the extracted
gaussians.
The fitting itself is implemented by th... | 48,011 | 43.414431 | 138 | py |
PyBDSF | PyBDSF-master/bdsf/multi_proc.py | """Multiprocessing module to handle parallelization.
This module can optionally update a statusbar and can divide tasks
between cores using weights (so that each core gets a set of tasks with
the same total weight).
Adapted from a module by Brian Refsdal at SAO, available at AstroPython
(http://www.astropython.org/sn... | 7,753 | 31.041322 | 83 | py |
PyBDSF | PyBDSF-master/bdsf/threshold.py | """Module threshold.
Defines operation Op_threshold. If the option 'thresh' is defined
as 'fdr' then the value of thresh_pix is estimated using the
False Detection Rate algorithm (using the user defined value
of fdr_alpha). If thresh is None, then the false detection
probability is first calculated, and if the number ... | 4,603 | 38.689655 | 113 | py |
PyBDSF | PyBDSF-master/bdsf/__init__.py | """Initialize PyBDSF namespace.
Import all standard operations, define default chain of
operations and provide function 'execute', which can
execute chain of operations properly. Also define the
'process_image' convienence function that can take
options as arguments rather than as a dictionary (as
required by 'execute... | 9,534 | 35.957364 | 118 | py |
PyBDSF | PyBDSF-master/bdsf/gaul2srl.py |
"""Module gaul2srl
This will group gaussians in an island into sources. Will code callgaul2srl.f here, though
it could probably be made more efficient.
img.sources is a list of source objects, which are instances of the class Source
(with attributes the same as in .srl of fbdsm).
img.sources[n] is a source.
source.g... | 34,935 | 49.927114 | 142 | py |
PyBDSF | PyBDSF-master/bdsf/interface.py | """Interface module.
The interface module handles all functions typically needed by the user in an
interactive environment such as IPython. Many are also used by the
custom IPython shell defined in pybdsf.
"""
from __future__ import print_function
from __future__ import absolute_import
try:
# For Python 2, use r... | 47,513 | 40.244792 | 125 | py |
PyBDSF | PyBDSF-master/bdsf/make_residimage.py | """Module make_residimage.
It calculates residual image from the list of gaussians and shapelets
"""
from __future__ import absolute_import
import numpy as N
from scipy import stats # for skew and kurtosis
from .image import *
from .shapelets import *
from . import mylogger
class Op_make_residimage(Op):
"""Crea... | 9,400 | 40.052402 | 120 | py |
PyBDSF | PyBDSF-master/bdsf/shapefit.py | """Module shapelets
This will do all the shapelet analysis of islands in an image
"""
from __future__ import absolute_import
from .image import *
from .islands import *
from .shapelets import *
from . import mylogger
from . import statusbar
from . import multi_proc as mp
import itertools
try:
from itertools impor... | 6,326 | 38.792453 | 117 | py |
PyBDSF | PyBDSF-master/bdsf/output.py | """Module output.
Defines functions that write the results of source detection in a
variety of formats. These are then used as methods of Image objects
and/or are called by the outlist operation if output_all is True.
"""
from __future__ import print_function
from __future__ import absolute_import
from .image import ... | 49,335 | 40.147623 | 130 | py |
PyBDSF | PyBDSF-master/bdsf/preprocess.py | """Module preprocess
Calculates some basic statistics of the image and sets up processing
parameters for PyBDSM.
"""
from __future__ import absolute_import
import numpy as N
from . import _cbdsm
from .image import *
from math import pi, sqrt, log
from . import const
from . import functions as func
from . import mylog... | 6,799 | 37.418079 | 116 | py |
PyBDSF | PyBDSF-master/bdsf/statusbar.py | """Display an animated statusbar"""
from __future__ import absolute_import
import sys
import os
from . import functions as func
class StatusBar():
# class variables:
# max: number of total items to be completed
# pos: number of completed items
# spin_pos: current position in array of busy_chars
#... | 3,257 | 31.58 | 187 | py |
PyBDSF | PyBDSF-master/bdsf/rmsimage.py | """Module rmsimage.
Defines operation Op_rmsimage which calculates mean and
rms maps.
The current implementation will handle both 2D and 3D images,
where for 3D case it will calculate maps for each plane (=
Stokes images).
"""
from __future__ import absolute_import
import numpy as N
import scipy.ndimage as nd
from .... | 47,148 | 43.818441 | 129 | py |
PyBDSF | PyBDSF-master/bdsf/shapelets.py | """Module shapelets.
nmax => J = 0..nmax; hence nmax+1 orders calculated.
ordermax = nmax+1; range(ordermax) has all the values of n
Order n => J=n, where J=0 is the gaussian.
"""
from __future__ import print_function
from __future__ import absolute_import
import numpy as N
try:
from astropy.io import fits as py... | 13,371 | 33.552972 | 108 | py |
PyBDSF | PyBDSF-master/bdsf/nat/__init__.py | # Adapted for numpy/ma/cdms2 by convertcdms.py
"""---------------------------------------------------------------------------------------------
INTRODUCTION TO NGMATH
The ngmath library is a collection of interpolators and approximators for one-dimensional, two-dimensional
and three-dimensional da... | 88,775 | 47.19544 | 242 | py |
PyBDSF | PyBDSF-master/natgrid/setup.py | #!/usr/bin/env python
from numpy.distutils.core import setup, Extension
import glob,sys
sources=glob.glob('Src/*.c')
setup (name = "natgrid",
version='1.0',
description = "natgrid",
url = "http://cdat.sf.net",
packages = [''],
package_dir = {'': 'Lib'},
include_dirs = ['Inclu... | 404 | 22.823529 | 58 | py |
PyBDSF | PyBDSF-master/natgrid/Test/test_natgrid.py | # Adapted for numpy/ma/cdms2 by convertcdms.py
"""Documentation for module natgridtest: an automatic test for natgrid, an interface to the ngmath NATGRID
TESTING
Typing
cdat natgridtest.py
generates some testing of the natgridmodule using analytical functions a... | 51,193 | 45.120721 | 133 | py |
PyBDSF | PyBDSF-master/doc/source/conf.py | # -*- coding: utf-8 -*-
#
# PyBDSF documentation build configuration file, created by
# sphinx-quickstart on Thu Jan 19 13:27:03 2012.
#
# This file is execfile()d with the current directory set to its containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
#
# All ... | 9,149 | 30.6609 | 83 | py |
confident-sinkhorn-allocation | confident-sinkhorn-allocation-master/load_data_clean.py | # -*- coding: utf-8 -*-
"""
Created on Wed Nov 17 21:11:58 2021
@author: Vu Nguyen
"""
import pandas as pd
from sklearn import preprocessing
import numpy as np
from sklearn.datasets import load_iris,load_breast_cancer,load_digits
import pickle
import os
path ='./vector_data/'
#======================================... | 3,686 | 27.804688 | 115 | py |
confident-sinkhorn-allocation | confident-sinkhorn-allocation-master/setup.py | from setuptools import setup, find_packages
setup(
name='csa',
version='1.0',
packages=find_packages(),
include_package_data = True,
description='Confident Sinkhorn Allocation',
install_requires=[
"colorama>=0.4.5",
"cycler>=0.11.0",
"fonttools>=4.33.3",
"joblib>... | 741 | 23.733333 | 48 | py |
confident-sinkhorn-allocation | confident-sinkhorn-allocation-master/load_multi_label_data.py | # -*- coding: utf-8 -*-
"""
Created on Thu Feb 3 14:25:12 2022
@author: Vu Nguyen
"""
#import arff
from scipy.io import arff
import pandas as pd
from sklearn.preprocessing import OneHotEncoder
import pickle
def load_yeast_multilabel(folder=''):
# temp = arff.loadarff(open('vector_data/yeast-train.arff', 'r'))
... | 2,733 | 24.082569 | 69 | py |
confident-sinkhorn-allocation | confident-sinkhorn-allocation-master/load_data.py | # -*- coding: utf-8 -*-
"""
Created on Wed Nov 17 21:11:58 2021
@author: Vu Nguyen
"""
import pandas as pd
from sklearn import preprocessing
import numpy as np
from sklearn.datasets import load_iris,load_breast_cancer,load_digits
import pickle
import os
path ='./vector_data/'
#======================================... | 3,540 | 27.556452 | 115 | py |
confident-sinkhorn-allocation | confident-sinkhorn-allocation-master/__init__.py | #from algorithm import *
#from utilities import * | 49 | 24 | 24 | py |
confident-sinkhorn-allocation | confident-sinkhorn-allocation-master/utilities/utils.py | # -*- coding: utf-8 -*-
"""
Created on Wed Mar 16 20:14:22 2022
@author: Vu Nguyen
"""
import pickle
import numpy as np
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler
def str2num(s, encoder):
return encoder[s]
def append_acc_early_termination(AccList, NumIte... | 8,280 | 39.004831 | 148 | py |
confident-sinkhorn-allocation | confident-sinkhorn-allocation-master/utilities/__init__.py | 0 | 0 | 0 | py | |
confident-sinkhorn-allocation | confident-sinkhorn-allocation-master/run_experiments/run_ups.py | import sys
#sys.path.insert(0,'..')
sys.path.append('..')
from tqdm import tqdm
import numpy as np
import os
import argparse
import logging
import pickle
from algorithm.pseudo_labeling import Pseudo_Labeling
#from algorithm.flexmatch import FlexMatch
from algorithm.ups import UPS
#from algorithm.csa import CSA
from ... | 4,544 | 38.181034 | 175 | py |
confident-sinkhorn-allocation | confident-sinkhorn-allocation-master/run_experiments/plot_results.py |
import sys
import os
sys.path.append('../')
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
import numpy as np
import matplotlib.pyplot as plt
#from algorithm.pseudo_labeling import Pseudo_Labeling
from algorithm.pseudo_labeling import Pseudo_Labeling
from algorithm.flexmatch impo... | 4,373 | 32.906977 | 159 | py |
confident-sinkhorn-allocation | confident-sinkhorn-allocation-master/run_experiments/run_pseudo_labeling.py | import sys
#sys.path.insert(0,'..')
sys.path.append('..')
import numpy as np
import os
import argparse
import logging
import pickle
from tqdm import tqdm
from algorithm.pseudo_labeling import Pseudo_Labeling
#from algorithm.flexmatch import FlexMatch
#from algorithm.ups import UPS
#from algorithm.csa import CSA
fro... | 4,272 | 36.814159 | 171 | py |
confident-sinkhorn-allocation | confident-sinkhorn-allocation-master/run_experiments/run_sla.py | import sys
import os
sys.path.insert(0,'..')
sys.path.append("../algorithm")
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
import numpy as np
import argparse
import logging
import pickle
from tqdm import tqdm
from algorithm.pseudo_labeling import Pseudo_Labeling
#from confident_si... | 4,557 | 38.293103 | 171 | py |
confident-sinkhorn-allocation | confident-sinkhorn-allocation-master/run_experiments/run_flexmatch.py | import sys
sys.path.append('..')
import numpy as np
import os
import argparse
import logging
import pickle
from tqdm import tqdm
from algorithm.pseudo_labeling import Pseudo_Labeling
from algorithm.flexmatch import FlexMatch
#from algorithm.ups import UPS
#from algorithm.csa import CSA
from utilities.utils import g... | 4,104 | 37.364486 | 171 | py |
confident-sinkhorn-allocation | confident-sinkhorn-allocation-master/run_experiments/run_csa.py | import sys
import os
sys.path.insert(0,'..')
#sys.path.append('..')
sys.path.append("../algorithm")
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
import numpy as np
import os
import argparse
import logging
import pickle
from tqdm import tqdm
from algorithm.pseudo_labeling import P... | 4,521 | 37.649573 | 171 | py |
confident-sinkhorn-allocation | confident-sinkhorn-allocation-master/algorithm/flexmatch.py | # -*- coding: utf-8 -*-
"""
Created on Mon Nov 15 14:19:22 2021
@author: Vu Nguyen
"""
import numpy as np
from tqdm import tqdm
from sklearn.metrics import accuracy_score
from xgboost import XGBClassifier
from scipy import stats
from .pseudo_labeling import Pseudo_Labeling
# FlexMatch Strategy for Pseudo-Labeling... | 8,767 | 42.405941 | 151 | py |
confident-sinkhorn-allocation | confident-sinkhorn-allocation-master/algorithm/pseudo_labeling.py |
import numpy as np
from tqdm import tqdm
from sklearn.metrics import accuracy_score
from xgboost import XGBClassifier
import matplotlib.pyplot as plt
from sklearn.multioutput import MultiOutputClassifier
import copy
import sklearn
class Pseudo_Labeling(object):
# implementation of the master class for pseudo... | 16,406 | 38.439904 | 144 | py |
confident-sinkhorn-allocation | confident-sinkhorn-allocation-master/algorithm/__init__.py | 0 | 0 | 0 | py | |
confident-sinkhorn-allocation | confident-sinkhorn-allocation-master/algorithm/csa.py | # -*- coding: utf-8 -*-
"""
Created on Mon Nov 15 14:19:22 2021
@author: Vu Nguyen
"""
import numpy as np
from tqdm import tqdm
from sklearn.metrics import accuracy_score
from xgboost import XGBClassifier
import matplotlib.pyplot as plt
from scipy import stats
import time
from .pseudo_labeling import Pseudo_Labe... | 16,573 | 38.368171 | 155 | py |
confident-sinkhorn-allocation | confident-sinkhorn-allocation-master/algorithm/ups.py | # -*- coding: utf-8 -*-
"""
Created on Mon Nov 15 14:19:22 2021
@author: Vu Nguyen
"""
import numpy as np
from tqdm import tqdm
from sklearn.metrics import accuracy_score
from xgboost import XGBClassifier
import matplotlib.pyplot as plt
from .pseudo_labeling import Pseudo_Labeling
# UPS: ==========================... | 7,123 | 42.175758 | 135 | py |
Unimer | Unimer-master/lr_scheduler_wrapper.py | # coding=utf8
from typing import Dict, Any
from overrides import overrides
from torch.optim.lr_scheduler import MultiStepLR
from allennlp.training.learning_rate_schedulers import LearningRateScheduler
class PyTorchMultiStepLearningRateSchedulerWrapper(LearningRateScheduler):
def __init__(self, lr_scheduler: Mu... | 816 | 27.172414 | 76 | py |
Unimer | Unimer-master/evaluations.py | # coding=utf-8
import re
import numpy as np
from grammars.utils import action_sequence_to_logical_form
def evaluate_grammar_based_prediction(instance, prediction, grammar, preprocessor, postprocessor=None):
meta_field = instance['meta_field']
question = meta_field['question']
truth_logical_form = meta_fi... | 8,052 | 38.282927 | 112 | py |
Unimer | Unimer-master/custom_trainer.py | # coding=utf8
import math
import time
import torch
import logging
from typing import Dict, List, Tuple, Optional, Iterable, Union, Callable, NoReturn
from allennlp.data import Instance
from allennlp.data.iterators.data_iterator import TensorDict, DataIterator
from allennlp.models import Model
from allennlp.training.ch... | 13,380 | 46.282686 | 119 | py |
Unimer | Unimer-master/nni_main.py | # coding=utf-8
import os
import re
import time
import json
import shutil
import subprocess
from absl import app
from absl import flags
from pprint import pprint
import nni
# Data
flags.DEFINE_integer('cuda_device', 0, 'cuda_device')
flags.DEFINE_string('train_data', os.path.join('data', 'geo', 'geo_funql_train.tsv'),... | 3,358 | 33.628866 | 142 | py |
Unimer | Unimer-master/model_builder.py | # coding=utf8
import numpy
import torch
from typing import Dict, List, Callable
from overrides import overrides
from allennlp.modules.seq2seq_encoders import PytorchSeq2SeqWrapper
from allennlp.training.metrics import Metric
from allennlp.models.model import Model
from allennlp.data.vocabulary import Vocabulary
from a... | 15,631 | 50.084967 | 120 | py |
Unimer | Unimer-master/__init__.py | 0 | 0 | 0 | py | |
Unimer | Unimer-master/run_parser.py | # coding=utf-8
import re
import os
import json
import copy
import random
import torch
import itertools
from typing import Dict, Any
from overrides import overrides
from absl import app
from absl import flags
import numpy as np
import torch
import torch.optim as optim
from torch.optim.lr_scheduler import MultiStepLR
fr... | 21,059 | 46.432432 | 120 | py |
Unimer | Unimer-master/text2sql_data.py | # coding=utf8
"""
Parsing data from https://github.com/jkkummerfeld/text2sql-data/tree/master/data
"""
import os
import json
import copy
def get_sql_data(basepath, raw_data_path):
with open(raw_data_path, 'r') as f:
data = json.load(f)
question_based_train_dataset, question_based_dev_dataset, questio... | 2,982 | 41.014085 | 121 | py |
Unimer | Unimer-master/hyperparameters/read_hyperparameter.py | # coding=utf8
import json
import argparse
from pprint import pprint
def main(path):
with open(path, 'r', encoding='utf8') as f:
for line in f:
results = json.loads(json.loads(line))
pprint(results)
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_... | 456 | 20.761905 | 74 | py |
Unimer | Unimer-master/neural_models/recombination_seq2seq_copy.py | # coding=utf8
from typing import Dict, List, Tuple
import numpy
from overrides import overrides
import torch
import torch.nn.functional as F
from torch.nn.modules.linear import Linear
from torch.nn.modules.rnn import LSTMCell
from allennlp.common.util import START_SYMBOL, END_SYMBOL
from allennlp.data.vocabulary imp... | 29,535 | 47.182708 | 137 | py |
Unimer | Unimer-master/neural_models/seq2seq_model.py | # coding=utf8
import torch
from overrides import overrides
from typing import Dict, List, Tuple
from allennlp.training.metrics import Metric
from allennlp.models.model import Model
from allennlp.data.vocabulary import Vocabulary
from allennlp.nn import util
from allennlp.modules import Attention, TextFieldEmbedder, Se... | 3,441 | 37.244444 | 98 | py |
Unimer | Unimer-master/neural_models/utils.py | # coding=utf8
import numpy
import torch
from typing import List
def has_nan(x: torch.Tensor) -> bool:
return torch.isnan(x).any()
def matrix_cosine_similarity(x: torch.Tensor, y: torch.Tensor, eps: float=1e-8):
"""
:param x (batch_size, length_1, dim)
:param y (batch_size, length_2, dim)
:retur... | 1,279 | 31.820513 | 80 | py |
Unimer | Unimer-master/neural_models/GNN.py | # coding=utf8
import numpy
import torch
import torch.nn as nn
from allennlp.models.model import Model
from allennlp.data.tokenizers import Token
from allennlp.common.util import START_SYMBOL, END_SYMBOL
from allennlp.data.vocabulary import Vocabulary
from allennlp.modules import Embedding
from allennlp.modules.text_fi... | 33,952 | 50.057143 | 122 | py |
Unimer | Unimer-master/neural_models/GNN2.py | # coding=utf8
import numpy
import torch
import torch.nn as nn
from allennlp.models.model import Model
from allennlp.data.tokenizers import Token
from allennlp.common.util import START_SYMBOL, END_SYMBOL
from allennlp.data.vocabulary import Vocabulary
from allennlp.modules import Embedding
from allennlp.modules.text_fi... | 34,001 | 50.130827 | 122 | py |
Unimer | Unimer-master/neural_models/__init__.py | # coding=utf-8
| 16 | 4.666667 | 14 | py |
Unimer | Unimer-master/neural_models/grammar_based_models.py | # coding=utf8
import numpy
import torch
import torch.nn as nn
from typing import Dict, List
from overrides import overrides
from allennlp.training.metrics import Metric
from allennlp.models.model import Model
from allennlp.data.vocabulary import Vocabulary
from allennlp.nn import util
from allennlp.modules.text_field_... | 3,744 | 42.546512 | 134 | py |
Unimer | Unimer-master/neural_models/recombination_seq2seq.py | # coding=utf8
import numpy
import torch
from typing import Dict, Tuple, Union, List, Any
from allennlp.models import SimpleSeq2Seq
from allennlp.data.vocabulary import Vocabulary
from allennlp.modules import TextFieldEmbedder, Seq2SeqEncoder, Attention, SimilarityFunction
from allennlp.nn import util, InitializerAppli... | 11,830 | 47.093496 | 122 | py |
Unimer | Unimer-master/neural_models/modules/grammar_decoder.py | # coding=utf-8
import torch
import copy
import numpy as np
import torch.nn as nn
import torch.nn.functional as F
from overrides import overrides
from allennlp.modules import Embedding
from typing import Tuple, List, Dict
from .. import utils as nn_utils
class LSTMGrammarDecoder(nn.Module):
def __init__(self,
... | 14,904 | 44.166667 | 137 | py |
Unimer | Unimer-master/neural_models/modules/gnn_multi_head_attention.py | # coding=utf8
import math
import torch
import numpy as np
import torch.nn as nn
from allennlp.nn import util
from torch.nn import Parameter
import torch.nn.functional as F
from torch.nn.init import xavier_uniform_
class GNNMatrixMultiHeadAttention(nn.Module):
def __init__(self, d_model: int, nhead: int, nlabels... | 17,043 | 40.77451 | 134 | py |
Unimer | Unimer-master/neural_models/modules/gnn_encoder.py | # coding=utf8
import copy
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn import MultiheadAttention
from .gnn_multi_head_attention import GNNMatrixMultiHeadAttention, GNNVectorMultiHeadAttention, \
GNNVectorContinuousMultiHeadAttention, GNNVectorMultiHeadAttention2
def _get_clone... | 20,183 | 48.349633 | 179 | py |
Unimer | Unimer-master/neural_models/modules/grammar_copy_decoder_2.py | # coding=utf-8
import torch
import copy
import numpy as np
import torch.nn as nn
import torch.nn.functional as F
from overrides import overrides
from allennlp.modules import Embedding
from typing import Tuple, List, Dict
from .. import utils as nn_utils
class LSTMGrammarCopyDecoder(nn.Module):
def __init__(self... | 20,773 | 46.429224 | 150 | py |
Unimer | Unimer-master/neural_models/modules/grammar_copy_decoder.py | # coding=utf-8
import torch
import copy
import numpy as np
import torch.nn as nn
import torch.nn.functional as F
from overrides import overrides
from allennlp.modules import Embedding
from typing import Tuple, List, Dict
from .. import utils as nn_utils
class LSTMGrammarCopyDecoder(nn.Module):
def __init__(self... | 20,697 | 46.363844 | 150 | py |
Unimer | Unimer-master/executions/compare_funql_prolog_denotations.py | # codint=uf8
import re
def read_logical_forms(path):
ql_dict = dict()
with open(path, 'r') as f:
for line in f:
line = line.strip()
splits = line.split('\t')
ql_dict[splits[0]] = splits[1]
return ql_dict
def process_prolog_denotation(denotation):
assert d... | 2,670 | 30.05814 | 83 | py |
Unimer | Unimer-master/executions/geo/get_sql_denotations.py | # coding=utf8
from sql.evaluator import get_result
def evaluate(path):
questions, logical_forms = list(), list()
with open(path, 'r') as f:
for line in f:
line = line.strip()
splits = line.split('\t')
q, l = splits[0], splits[1]
questions.append(q)
... | 922 | 27.84375 | 63 | py |
Unimer | Unimer-master/executions/geo/get_prolog_denotations.py | # coding=utf8
import os
import re
import json
import argparse
import subprocess
pattern = re.compile('(\d+)(\[.*\])')
script_template = """
:-compile('%s').
:-compile('%s').
%s
:-halt.
"""
def evaluate(path):
questions, logical_forms = list(), list()
with open(path, 'r') as f:
for line in f:
... | 2,091 | 28.464789 | 94 | py |
Unimer | Unimer-master/executions/geo/evaluate_sql.py | # coding=utf8
import os
import re
import json
import argparse
from sql.evaluator import compare_sqls
def evaluate(path, timeout=120):
with open(path, 'r') as f:
predictions = json.load(f)
total = len(predictions)
correct = 0
for pidx, p in enumerate(predictions):
truth = p['truth... | 790 | 24.516129 | 87 | py |
Unimer | Unimer-master/executions/geo/evaluate_lambda_calculus.py | # coding=utf8
import re
import os
import json
import shutil
import argparse
import subprocess
from lambda_calculus.transform_lambda_caculus import transform
import sys
sys.path += ['..', os.path.join('..', '..')]
pattern = re.compile('\(\"([p|t])\",(\d+),Just\s+(.*)\)')
failed_pattern = re.compile('\(\"([p|t])\",(\d... | 5,659 | 32.892216 | 103 | py |
Unimer | Unimer-master/executions/geo/evaluate_funql.py | # coding=utf8
import os
import re
import json
import argparse
import subprocess
pattern = re.compile("(\d+)'\s+([yn])'")
script_template = """
:-compile('%s').
:-compile('%s').
:-compile('%s').
:-use_module(library(time)).
%s
:-halt.
"""
def evaluate(path, timeout=120):
with open(path, 'r') as f:
pred... | 2,316 | 30.310811 | 251 | py |
Unimer | Unimer-master/executions/geo/evaluate_prolog.py | # coding=utf8
import re
import os
import json
import argparse
import subprocess
import sys
sys.path += ['..', '../../']
pattern = re.compile("(\d+)'\s+([yn])'")
script_template = """
:-compile('%s').
:-compile('%s').
:-compile('%s').
:-use_module(library(time)).
%s
:-halt.
"""
def tokenize(logical_form):
no... | 4,435 | 30.913669 | 243 | py |
Unimer | Unimer-master/executions/geo/get_lambda_calculus_denotations.py | # coding=utf8
import os
import re
import json
import shutil
import argparse
import subprocess
from geo.lambda_calculus.transform_lambda_caculus import transform
pattern = re.compile('\((\d+),Just\s+(.*)\)')
failed_pattern = re.compile('\((\d+),Nothing\)')
script_template = r"""
module Main where
import Lib
import G... | 2,902 | 28.323232 | 124 | py |
Unimer | Unimer-master/executions/geo/__init__.py | 0 | 0 | 0 | py | |
Unimer | Unimer-master/executions/geo/get_funql_denotations.py | # coding=utf8
import os
import re
import json
import argparse
import subprocess
pattern = re.compile('(\d+)(\[.*\])')
script_template = """
:-compile('%s').
:-compile('%s').
:-compile('%s').
%s
:-halt.
"""
def evaluate(path):
questions, logical_forms = list(), list()
with open(path, 'r') as f:
for ... | 1,642 | 25.934426 | 92 | py |
Unimer | Unimer-master/executions/geo/sql/evaluator.py | # coding=utf8
import re
import mysql.connector
from pprint import pprint
db = mysql.connector.connect(
host="localhost",
user="root",
passwd="123456",
database="geo",
auth_plugin='mysql_native_password'
)
def normalize(sql):
s = re.sub(' +', ' ', sql)
s = s.replace('MAX (', 'MAX(')
... | 2,741 | 32.439024 | 690 | py |
Unimer | Unimer-master/executions/geo/lambda_calculus/parse_geobase.py | # coding=utf8
import re
def parse_state(path):
with open(path, 'r') as f:
for line in f:
line = line.strip()
if line.startswith('state('):
info = line[len('state('):-2]
# print(info)
infos = info.split(',')
for idx, c... | 7,848 | 37.665025 | 112 | py |
Unimer | Unimer-master/executions/geo/lambda_calculus/transform_lambda_caculus.py | # coding=utf8
import re
import json
entity_pattern = re.compile('\s([a-z|_|.]+?:[a-z]+)[\s|)]')
def process_logic_expression(haskell_lf, is_and):
if is_and:
target, replace_target, replace_result = "(and:<t*,t>", "and:<t*,t>", "and ["
else:
target, replace_target, replace_result = "(or:<t*,t... | 6,483 | 42.810811 | 122 | py |
Unimer | Unimer-master/executions/geo/lambda_calculus/__init__.py | # coding=utf8 | 13 | 13 | 13 | py |
Unimer | Unimer-master/executions/geo/lambda_calculus/create_evaluate_script.py | # coding=utf8
import os
import json
script_template = r"""
module Main where
import Lib
import Geobase
import Geofunctions
import System.Environment
import System.Timeout
main :: IO ()
main = do
putStrLn "Execute Lambda Calculus"
-- let predicted_result = (count_ (\x -> (and [(river x), (loc x "texas:s")])... | 1,605 | 26.689655 | 170 | py |
Unimer | Unimer-master/executions/atis/evaluate_sql.py | # coding=utf8
import os
import re
import json
import argparse
from sql.evaluator import compare_sqls
def evaluate(path, timeout=120):
with open(path, 'r') as f:
predictions = json.load(f)
total = len(predictions)
correct = 0
for pidx, p in enumerate(predictions):
truth = p['truth... | 956 | 24.184211 | 87 | py |
Unimer | Unimer-master/executions/atis/evaluate_lambda_calculus.py | # coding=utf8
import json
import argparse
from lambda_calculus.lc_evaluator import compare_lambda_calculus
def evaluate(path, timeout=600):
with open(path, 'r') as f:
predictions = json.load(f)
total = len(predictions)
correct = 0
for pidx, p in enumerate(predictions):
print(pidx)
... | 1,076 | 26.615385 | 87 | py |
Unimer | Unimer-master/executions/atis/evaluate_funql.py | # coding=utf8
import json
import argparse
from funql.evaluator import compare_funql
def evaluate(path, timeout=600):
with open(path, 'r') as f:
predictions = json.load(f)
total = len(predictions)
correct = 0
for pidx, p in enumerate(predictions):
print(pidx)
print(p['question... | 1,042 | 26.447368 | 87 | py |
Unimer | Unimer-master/executions/atis/__init__.py | 0 | 0 | 0 | py | |
Unimer | Unimer-master/executions/atis/funql/transform.py | # coding=utf
ENTITY_TYPE_MAP = {
"ac": "aircraft_code",
"al": "airline_code",
"ci": "city_name",
"ap": "airport_code",
"fn": "flight_number",
"cl": "class_description",
"ti": "time",
"pd": "day_period",
"mf": "manufacturer",
"mn": "month",
"da": "day",
"i": "integer",
... | 2,952 | 29.760417 | 102 | py |
Unimer | Unimer-master/executions/atis/funql/evaluator.py | # coding=utf8
import logging
from .query import *
from .transform import transform
def get_result(funql):
python_lf = transform(funql)
return_dict = dict()
try:
results = eval(python_lf)
except:
logging.error("Exception", exc_info=True)
return_dict['is_valid'] = False
else... | 2,277 | 30.638889 | 116 | py |
Unimer | Unimer-master/executions/atis/funql/__init__.py | 0 | 0 | 0 | py | |
Unimer | Unimer-master/executions/atis/funql/query.py | # coding=utf8
import re
import mysql.connector
from pprint import pprint
from .transform import transform
db = None
def get_connection():
global db
if db and db.is_connected():
return db
else:
db = mysql.connector.connect(
host="localhost",
user="root",
... | 80,393 | 34.651441 | 399 | py |
Unimer | Unimer-master/executions/atis/sql/evaluator.py | # coding=utf8
from multiprocessing import Process, Manager
import re
import mysql.connector
from pprint import pprint
class TimeoutException(Exception):
pass
def normalize(sql):
s = re.sub(' +', ' ', sql)
s = s.replace('MAX (', 'MAX(')
s = s.replace('MIN (', 'MIN(')
s = s.replace('AVG (', 'AVG(... | 3,401 | 29.648649 | 551 | py |
Unimer | Unimer-master/executions/atis/sql/__init__.py | 0 | 0 | 0 | py |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.