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
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z2n-periodogram | z2n-periodogram-master/z2n/stats.py | #! /usr/bin/python
# -*- coding: utf-8 -*-
# Other libraries
import click
import numpy as np
from numba import jit
from tqdm import trange
from scipy import optimize
from scipy.stats import norm
import matplotlib.pyplot as plt
@jit(forceobj=True, parallel=True, fastmath=True)
def exposure(series) -> None:
"""
... | 9,648 | 22.824691 | 76 | py |
z2n-periodogram | z2n-periodogram-master/z2n/prompt.py | #! /usr/bin/python
# -*- coding: utf-8 -*-
# Generic/Built-in
import psutil
import shelve
import pathlib
import threading
# Other Libraries
import click
import numpy as np
from click_shell import shell
import matplotlib.pyplot as mplt
# Owned Libraries
from z2n import file
from z2n import stats
from z2n import __doc... | 11,094 | 34.790323 | 88 | py |
z2n-periodogram | z2n-periodogram-master/z2n/file.py | #! /usr/bin/python
# -*- coding: utf-8 -*-
# Generic/Built-in
import pathlib
# Other Libraries
import click
import numpy as np
from astropy.io import fits
from astropy.table import Table
def load_file(series, ext) -> int:
"""
Open file and store time series.
Parameters
----------
series : Serie... | 17,730 | 34.820202 | 86 | py |
z2n-periodogram | z2n-periodogram-master/z2n/plot.py | #! /usr/bin/python
# -*- coding: utf-8 -*-
# Generic/Built-in
import psutil
import pathlib
# Other Libraries
import click
import numpy as np
import matplotlib.pyplot as plt
# Owned Libraries
from z2n import stats
from z2n.series import Series
class Plot:
"""
A class to represent the plot of a time series.
... | 15,571 | 39.978947 | 88 | py |
z2n-periodogram | z2n-periodogram-master/z2n/__init__.py | #! /usr/bin/python
# -*- coding: utf-8 -*-
__version__ = '2.0.6'
__license__ = 'MIT'
__author__ = 'Yohan Alexander'
__copyright__ = 'Copyright (C) 2020, Z2n Software, by Yohan Alexander.'
__description__ = 'A package for interative periodograms analysis.'
__maintainer__ = 'Yohan Alexander'
__email__ = 'yohanfranca@gma... | 501 | 32.466667 | 71 | py |
z2n-periodogram | z2n-periodogram-master/z2n/series.py | #! /usr/bin/python
# -*- coding: utf-8 -*-
# Generic/Built-in
import sys
import copy
import psutil
import pathlib
import tempfile
# Other Libraries
import h5py
import click
import termtables
import numpy as np
import matplotlib.pyplot as plt
# Owned Libraries
from z2n import file
from z2n import stats
class Series... | 17,816 | 34.281188 | 84 | py |
bmm | bmm-master/setup.py |
import setuptools
NAME = 'bmm'
DESCRIPTION = 'Bayesian Map-matching'
with open('README.md') as f:
long_description = f.read()
with open('requirements.txt') as f:
install_requires = f.read().splitlines()
METADATA = dict(
name="bmm",
version='1.3',
url='http://github.com/SamDuffield/bmm',
aut... | 742 | 22.21875 | 50 | py |
bmm | bmm-master/bmm/__init__.py |
"""bmm: Bayesian Map-matching"""
from bmm.src.inference.smc import initiate_particles
from bmm.src.inference.smc import update_particles
from bmm.src.inference.smc import offline_map_match
from bmm.src.inference.smc import _offline_map_match_fl
from bmm.src.inference.smc import updates
from bmm.src.inference.sample... | 1,060 | 28.472222 | 63 | py |
bmm | bmm-master/bmm/src/tools/edges.py | ########################################################################################################################
# Module: edges.py
# Description: Some tools including interpolation along a proportion of a given edge, selecting edges within a distance
# of a point and discretisation of an edge for ... | 13,894 | 38.251412 | 121 | py |
bmm | bmm-master/bmm/src/tools/plot.py | ########################################################################################################################
# Module: plot.py
# Description: Plot cam_graph, inferred route and/or polyline.
#
# Web: https://github.com/SamDuffield/bmm
##########################################################################... | 5,372 | 35.55102 | 120 | py |
bmm | bmm-master/bmm/src/inference/sample.py | ########################################################################################################################
# Module: inference/sample.py
# Description: Generate route and polyline from map-matching model.
#
# Web: https://github.com/SamDuffield/bmm
#########################################################... | 6,711 | 45.937063 | 120 | py |
bmm | bmm-master/bmm/src/inference/model.py | ########################################################################################################################
# Module: inference/model.py
# Description: Objects and functions relating to the map-matching state-space model.
#
# Web: https://github.com/SamDuffield/bmm
#########################################... | 16,786 | 46.420904 | 124 | py |
bmm | bmm-master/bmm/src/inference/resampling.py | ########################################################################################################################
# Module: inference/resampling.py
# Description: Resampling schemes for converting weighted particles (series of positions/edges/distances) to
# unweighted. Notably multinomial resamplin... | 22,840 | 46.192149 | 120 | py |
bmm | bmm-master/bmm/src/inference/backward.py | ########################################################################################################################
# Module: inference/backward.py
# Description: Implementation of backward simulation for particle smoothing.
#
# Web: https://github.com/SamDuffield/bmm
##############################################... | 18,714 | 47.86423 | 120 | py |
bmm | bmm-master/bmm/src/inference/parameters.py | ########################################################################################################################
# Module: inference/parameters.py
# Description: Expectation maximisation to infer maximum likelihood hyperparameters.
#
# Web: https://github.com/SamDuffield/bmm
####################################... | 13,538 | 45.208191 | 120 | py |
bmm | bmm-master/bmm/src/inference/proposal.py | ########################################################################################################################
# Module: inference/proposal.py
# Description: Proposal mechanisms to extend particles (series of positions/edges/distances) and re-weight
# in light of a newly received observation.
#
#... | 18,595 | 44.802956 | 120 | py |
bmm | bmm-master/bmm/src/inference/particles.py | ########################################################################################################################
# Module: inference/particles.py
# Description: Class to store map-matching particles.
#
# Web: https://github.com/SamDuffield/bmm
####################################################################... | 5,927 | 35.592593 | 120 | py |
bmm | bmm-master/bmm/src/inference/smc.py | ########################################################################################################################
# Module: inference/smc.py
# Description: Implementation of sequential Monte Carlo map-matching. Both offline and online.
#
# Web: https://github.com/SamDuffield/bmm
#################################... | 28,889 | 45.97561 | 120 | py |
bmm | bmm-master/tests/test_smc.py | ########################################################################################################################
# Module: tests/test_smc.py
# Description: Tests for SMC implementation.
#
# Web: https://github.com/SamDuffield/bayesian-traffic
#####################################################################... | 6,752 | 46.893617 | 120 | py |
bmm | bmm-master/tests/test_resampling.py | ########################################################################################################################
# Module: tests/test_resampling.py
# Description: Tests for resampling schemes.
#
# Web: https://github.com/SamDuffield/bayesian-traffic
##############################################################... | 2,864 | 40.521739 | 120 | py |
bmm | bmm-master/tests/test_MMParticles.py | ########################################################################################################################
# Module: tests/test_MMParticles.py
# Description: Tests for MMParticles class.
#
# Web: https://github.com/SamDuffield/bayesian-traffic
##############################################################... | 2,205 | 30.070423 | 120 | py |
bmm | bmm-master/simulations/sanity_check.py |
import numpy as np
import pandas as pd
import osmnx as ox
import json
import bmm
# Download and project graph
graph = ox.graph_from_place('London, UK')
graph = ox.project_graph(graph)
# Generate synthetic route and polyline
generated_route, generated_polyline = bmm.sample_route(graph, timestamps=15, num_obs=20)
# ... | 609 | 24.416667 | 96 | py |
bmm | bmm-master/simulations/porto/max_rejections_compare.py | import os
import json
import numpy as np
import osmnx as ox
import pandas as pd
import matplotlib.pyplot as plt
import bmm
from . import utils
seed = 0
np.random.seed(seed)
timestamps = 15
n_samps = np.array([50, 100, 150, 200])
lag = 3
mr_max = 20
# max_rejections = np.arange(0, mr_max + 1, step=int(mr_max/5))
ma... | 6,552 | 36.878613 | 115 | py |
bmm | bmm-master/simulations/porto/bulk_map_match.py | import os
import json
import numpy as np
import osmnx as ox
import pandas as pd
import bmm
porto_sim_dir = os.getcwd()
graph_path = porto_sim_dir + '/portotaxi_graph_portugal-140101.osm._simple.graphml'
graph = ox.load_graphml(graph_path)
test_route_data_path = '' # Download from https://archive.ics.uci.edu/ml/dat... | 1,851 | 28.870968 | 146 | py |
bmm | bmm-master/simulations/porto/utils.py | import functools
import gc
import json
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import bmm
def read_data(path, chunksize=None):
data_reader = pd.read_csv(path, chunksize=10)
data_columns = data_reader.get_chunk().columns
polyline_converters = {col_name: json.loads for col_n... | 5,822 | 31.171271 | 109 | py |
bmm | bmm-master/simulations/porto/parameter_training.py | ########################################################################################################################
# Module: parameter_inference.py
# Description: Tune hyperparameters using some Porto taxi data.
#
# Web: https://github.com/SamDuffield/bmm
##########################################################... | 1,652 | 33.4375 | 120 | py |
bmm | bmm-master/simulations/porto/total_variation_compare.py | import os
import json
import numpy as np
import osmnx as ox
import pandas as pd
import bmm
from . import utils
seed = 0
np.random.seed(seed)
timestamps = 15
ffbsi_n_samps = int(1e3)
fl_n_samps = np.array([50, 100, 150, 200])
lags = np.array([0, 3, 10])
max_rejections = 30
initial_truncation = None
num_repeats = 20... | 8,082 | 41.319372 | 117 | py |
bmm | bmm-master/simulations/cambridge/utils.py | import functools
import gc
import numpy as np
import osmnx as ox
from networkx import write_gpickle, read_gpickle
import bmm
def download_cambridge_graph(save_path):
cambridge_ll_bbox = [52.245, 52.150, 0.220, 0.025]
raw_graph = ox.graph_from_bbox(*cambridge_ll_bbox,
trun... | 933 | 21.238095 | 57 | py |
bmm | bmm-master/simulations/cambridge/simulated_parameter_training.py | import numpy as np
import os
from .utils import sample_route, download_cambridge_graph, load_graph
import bmm
np.random.seed(0)
# Load cam_graph
graph_path = os.getcwd() + '/cambridge_projected_simple.graphml'
if not os.path.exists(graph_path):
download_cambridge_graph(graph_path)
# Load networkx cam_graph
ca... | 3,048 | 36.641975 | 114 | py |
bmm | bmm-master/simulations/cambridge/single_route_ffbsi.py | import json
import numpy as np
import matplotlib.pyplot as plt
import os
from utils import download_cambridge_graph, load_graph
import bmm
# Setup
seed = 0
np.random.seed(seed)
# Model parameters
time_interval = 100
route_length = 4
gps_sd = 10
num_inter_cut_off = 10
# Inference parameters
n_samps = 1000
max_re... | 3,504 | 31.155963 | 114 | py |
bmm | bmm-master/docs/conf.py | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If ex... | 2,323 | 34.753846 | 79 | py |
STEP | STEP-master/src/utils.py | import numpy as np
def get_neighbor_finder(data, uniform, max_node_idx=None):
max_node_idx = max(data.sources.max(), data.destinations.max()) if max_node_idx is None else max_node_idx
adj_list = [[] for _ in range(max_node_idx + 1)]
for source, destination, edge_idx, timestamp in zip(data.sources, data.de... | 7,050 | 44.490323 | 163 | py |
STEP | STEP-master/src/train_gnn.py | import pytorch_lightning as pyl
import torch
import torch.nn.functional as F
import numpy as np
import datasets as dataset
import torch.utils.data
import sklearn
from option import args
from model.tgat import TGAT
class ModelLightning(pyl.LightningModule):
def __init__(self, config, backbone):
super().__... | 3,844 | 28.128788 | 122 | py |
STEP | STEP-master/src/option.py | import argparse
parser = argparse.ArgumentParser(description='Denoise')
parser.add_argument('--dir_data', type=str, default='../dataset')
parser.add_argument('--data_set', type=str, default='wikipedia')
parser.add_argument('--output_edge_txt', type=str, default='./result/edge_pred.txt')
parser.add_argument('--mask_e... | 1,480 | 45.28125 | 108 | py |
STEP | STEP-master/src/datasets_edge.py | import torch
import torch.utils.data
import os
import numpy as np
import random
import pandas as pd
class Data:
def __init__(self, sources, destinations, timestamps, edge_idxs, labels):
self.sources = sources
self.destinations = destinations
self.timestamps = timestamps
self.edge_i... | 3,073 | 26.693694 | 92 | py |
STEP | STEP-master/src/datasets.py | import torch
import torch.utils.data
import os
import numpy as np
from option import args
import random
import pandas as pd
from utils import get_neighbor_finder, masked_get_neighbor_finder
from operator import itemgetter
class Data:
def __init__(self, sources, destinations, timestamps, edge_idxs, labels):
... | 9,798 | 39.159836 | 130 | py |
STEP | STEP-master/src/build_dataset_graph.py | from option import args
import pandas as pd
import numpy as np
def preprocess(data_name):
u_list, i_list, ts_list, label_list = [], [], [], []
feat_l = []
idx_list = []
with open(data_name) as f:
s = next(f)
for idx, line in enumerate(f):
e = line.strip().split(',')
u = int(e[0])
i ... | 1,891 | 23.894737 | 76 | py |
STEP | STEP-master/src/eval_gnn.py | import pytorch_lightning as pyl
import torch
import torch.nn.functional as F
import numpy as np
import datasets as dataset
import torch.utils.data
import sklearn
from option import args
from model.tgat import TGAT
class ModelLightning(pyl.LightningModule):
def __init__(self, config, backbone):
super().__... | 4,116 | 29.272059 | 122 | py |
STEP | STEP-master/src/edge_pruning.py | import pytorch_lightning as pyl
import torch
import torch.nn.functional as F
import numpy as np
import datasets_edge as dataset
import torch.utils.data
import sklearn
from option import args
from model.precom_model import Precom_Model
class ModelLightning(pyl.LightningModule):
def __init__(self, config, backbone):... | 4,096 | 29.125 | 122 | py |
STEP | STEP-master/src/train_gsn.py | import pytorch_lightning as pyl
import torch
import datasets as dataset
import torch.utils.data
from option import args
from model.tgat import TGAT
class ModelLightning(pyl.LightningModule):
def __init__(self, config, backbone):
super().__init__()
self.config = config
self.backbone = backb... | 4,863 | 31.426667 | 95 | py |
STEP | STEP-master/src/modules/time_encoding.py | import torch
import numpy as np
class TimeEncode(torch.nn.Module):
# Time Encoding proposed by TGAT
def __init__(self, dimension):
super(TimeEncode, self).__init__()
self.dimension = dimension
self.w = torch.nn.Linear(1, dimension)
self.w.weight = torch.nn.Parameter((torch.from_numpy(1 / 10 ** n... | 802 | 28.740741 | 99 | py |
STEP | STEP-master/src/modules/utils.py | import numpy as np
import torch
from sklearn.metrics import roc_auc_score
import math
import time
class MergeLayer(torch.nn.Module):
def __init__(self, dim1, dim2, dim3, dim4):
super().__init__()
self.layer_norm = torch.nn.LayerNorm(dim1 + dim2)
self.fc1 = torch.nn.Linear(dim1 + dim2, dim3)
self.fc2 ... | 1,731 | 26.935484 | 67 | py |
STEP | STEP-master/src/modules/temporal_attention.py | import torch
import torch_scatter as scatter
from torch import nn
from modules.utils import MergeLayer
class TemporalAttentionLayer2(torch.nn.Module):
"""
Temporal attention layer. Return the temporal embedding of a node given the node itself,
its neighbors and the edge timestamps.
"""
def __init__(self, ... | 6,626 | 43.47651 | 161 | py |
STEP | STEP-master/src/modules/embedding_module.py | import torch
from torch import nn
import numpy as np
import math
from modules.temporal_attention import TemporalAttentionLayer2
class EmbeddingModule(nn.Module):
def __init__(self, time_encoder, n_layers,
node_features_dims, edge_features_dims, time_features_dim, hidden_dim, dropout):
super(Embed... | 7,015 | 42.57764 | 113 | py |
STEP | STEP-master/src/model/tgat.py | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch_scatter as scatter
from modules.utils import MergeLayer_output, Feat_Process_Layer
from modules.embedding_module import get_embedding_module
from modules.time_encoding import TimeEncode
from model.gsn import Graph_sampling_network
from mode... | 5,947 | 48.983193 | 125 | py |
STEP | STEP-master/src/model/gsn.py | import torch
import torch.nn.functional as F
import torch_scatter as scatter
class Graph_sampling_network(torch.nn.Module):
def __init__(self, dim, batch_size, mask_ratio=0.5):
super(Graph_sampling_network, self).__init__()
self.mask_act = 'sigmoid'
self.mask_ratio = mask_ratio
sel... | 4,736 | 37.201613 | 136 | py |
STEP | STEP-master/src/model/gpn.py | import torch
from modules.utils import MergeLayer_output, Feat_Process_Layer
class Graph_pruning_network(torch.nn.Module):
def __init__(self, input_dim, hidden_dim, drop_out):
super(Graph_pruning_network, self).__init__()
self.edge_dim = input_dim
self.dims = hidden_dim
self.dropou... | 1,839 | 34.384615 | 128 | py |
SIT | SIT-master/tree_util.py | import numpy as np
import math
import matplotlib.pyplot as plt
import ipdb
import torch
def rotation_matrix(thea):
return np.array([
[np.cos(thea), -1 * np.sin(thea)],
[np.sin(thea), np.cos(thea)]
])
def generating_tree(seq, dir_list, split_interval=4, degree=3):
# seq [N n seq_len 2]
... | 6,747 | 33.080808 | 109 | py |
SIT | SIT-master/dataset.py | import pickle
import numpy as np
from torch.utils import data
from util import get_train_test_data, data_augmentation
from tree_util import tree_build, tree_label
class DatasetETHUCY(data.Dataset):
def __init__(self, data_path, dataset_name, batch_size, is_test, end_centered=True,
data_flip=Fals... | 1,893 | 34.074074 | 140 | py |
SIT | SIT-master/run.py | import argparse
from dataset import DatasetETHUCY
import util
import logging
import torch
from model.trajectory_model import TrajectoryModel
from torch.optim import Adam, lr_scheduler
import os
logging.basicConfig(format='%(asctime)s - %(levelname)s - %(name)s - %(message)s',
datefmt='%m/%d/%Y %H... | 6,964 | 36.446237 | 115 | py |
SIT | SIT-master/util.py | from typing import Dict
import os
import subprocess
import random
import pickle
import torch
import numpy as np
import argparse
class Args:
dataset = None
epoch = None
lr = None
lr_scheduler = None
lr_milestones = None
lr_gamma = None
obs_len = None
pred_len = None
train_batch_size... | 6,257 | 29.231884 | 125 | py |
SIT | SIT-master/model/component.py | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
class Activation_Fun(nn.Module):
def __init__(self, act_name):
super(Activation_Fun, self).__init__()
if act_name == 'relu':
self.act = nn.ReLU()
if act_name == 'prelu':
self.act = nn.P... | 2,946 | 31.384615 | 118 | py |
SIT | SIT-master/model/trajectory_model.py |
import torch
import torch.nn as nn
from model.component import MLP
from model.component import SelfAttention
from util import ModelArgs
class TrajectoryModel(nn.Module):
def __init__(self, args: ModelArgs):
super(TrajectoryModel, self).__init__()
in_dim = args.in_dim
obs_len = args.obs... | 6,157 | 33.022099 | 111 | py |
MCEq | MCEq-master/setup.py | import sys
from os.path import join, dirname, abspath
from setuptools import setup, Extension
from distutils.command import build_ext
def get_export_symbols(self, ext):
"""From https://bugs.python.org/issue35893"""
parts = ext.name.split(".")
# print('parts', parts)
if parts[-1] == "__init__":
... | 3,622 | 31.936364 | 118 | py |
MCEq | MCEq-master/mceq_config.py | from __future__ import print_function
import sys
import platform
import os.path as path
import warnings
base_path = path.dirname(path.abspath(__file__))
#: Debug flag for verbose printing, 0 silences MCEq entirely
debug_level = 1
#: Override debug prinput for functions listed here (just give the name,
#: "get_solution... | 14,601 | 33.601896 | 99 | py |
MCEq | MCEq-master/docs/conf.py | # -*- coding: utf-8 -*-
#
# Matrix Cascade Equation (MCEq) documentation build configuration file, created by
# sphinx-quickstart on Fri Nov 21 10:13:38 2014.
#
# 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
# au... | 9,553 | 31.386441 | 83 | py |
MCEq | MCEq-master/MCEq/core.py | import os
import six
from time import time
import numpy as np
import mceq_config as config
from MCEq.misc import normalize_hadronic_model_name, info
from MCEq.particlemanager import ParticleManager
import MCEq.data
class MCEqRun(object):
"""Main class for handling the calculation.
This class is the main user... | 54,114 | 40.626923 | 104 | py |
MCEq | MCEq-master/MCEq/particlemanager.py |
import six
from math import copysign
import numpy as np
import mceq_config as config
from MCEq.misc import info, print_in_rows, getAZN
from particletools.tables import PYTHIAParticleData
info(5, 'Initialization of PYTHIAParticleData object')
_pdata = PYTHIAParticleData()
backward_compatible_namestr = {
'nu_mu': ... | 45,993 | 38.244027 | 91 | py |
MCEq | MCEq-master/MCEq/misc.py |
from __future__ import print_function
from collections import namedtuple
import numpy as np
import mceq_config as config
#: Energy grid (centers, bind widths, dimension)
energy_grid = namedtuple("energy_grid", ("c", "b", "w", "d"))
#: Matrix with x_lab=E_child/E_parent values
_xmat = None
def normalize_hadronic_mod... | 6,702 | 27.402542 | 79 | py |
MCEq | MCEq-master/MCEq/data.py |
import six
import numpy as np
import h5py
from collections import defaultdict
import mceq_config as config
from os.path import join, isfile
from .misc import normalize_hadronic_model_name, info
# TODO: Convert this to some functional generic class. Very erro prone to
# enter stuff by hand
equivalences = {
'SIBYLL... | 35,586 | 35.954309 | 89 | py |
MCEq | MCEq-master/MCEq/charm_models.py | # -*- coding: utf-8 -*-
"""
:mod:`MCEq.charm_models` --- charmed particle production
========================================================
This module includes classes for custom charmed particle
production. Currently only the MRS model is implemented
as the class :class:`MRS_charm`. The abstract class
:class:`Char... | 11,491 | 32.602339 | 81 | py |
MCEq | MCEq-master/MCEq/version.py | __version__ = '1.2.6'
| 22 | 10.5 | 21 | py |
MCEq | MCEq-master/MCEq/__init__.py | 0 | 0 | 0 | py | |
MCEq | MCEq-master/MCEq/solvers.py |
import numpy as np
import mceq_config as config
from MCEq.misc import info
def solv_numpy(nsteps, dX, rho_inv, int_m, dec_m, phi, grid_idcs):
""":mod:`numpy` implementation of forward-euler integration.
Args:
nsteps (int): number of integration steps
dX (numpy.array[nsteps]): vector of step-size... | 12,678 | 34.317549 | 96 | py |
MCEq | MCEq-master/MCEq/tests/test_densities.py | import numpy as np
def test_corsika_atm():
from MCEq.geometry.density_profiles import CorsikaAtmosphere
# Depth at surface and density at X=100 g/cm2
cka_surf_100 = [
(1036.099233683902, 0.00015623258808300557),
(1033.8094962133184, 0.00015782685585891685),
(1055.861981113731, 0.0... | 2,689 | 37.985507 | 99 | py |
MCEq | MCEq-master/MCEq/tests/test_msis.py | from __future__ import print_function
result_expected = \
"""6.665177E+05 1.138806E+08 1.998211E+07 4.022764E+05 3.557465E+03 4.074714E-15 3.475312E+04 4.095913E+06 2.667273E+04 1.250540E+03 1.241416E+03
3.407293E+06 1.586333E+08 1.391117E+07 3.262560E+05 1.559618E+03 5.001846E-15 4.854208E+04 4.380967E+06 6.956682E+... | 11,398 | 49.438053 | 146 | py |
MCEq | MCEq-master/MCEq/tests/test_mceq.py | from __future__ import print_function
import mceq_config as config
from MCEq.core import MCEqRun
import crflux.models as pm
import numpy as np
import pytest
import sys
if sys.platform.startswith("win") and sys.maxsize <= 2**32:
pytest.skip("Skip model test on 32-bit Windows.", allow_module_level=True)
def forma... | 2,845 | 29.276596 | 109 | py |
MCEq | MCEq-master/MCEq/geometry/density_profiles.py | from abc import ABCMeta, abstractmethod
from six import with_metaclass
from os.path import join
import numpy as np
from MCEq.misc import theta_rad
from MCEq.misc import info
import mceq_config as config
class EarthsAtmosphere(with_metaclass(ABCMeta)):
"""
Abstract class containing common methods on atmospher... | 50,633 | 33.562457 | 115 | py |
MCEq | MCEq-master/MCEq/geometry/nrlmsise00_mceq.py | from MCEq.misc import info
import six
import MCEq.geometry.nrlmsise00.nrlmsise00 as cmsis
class NRLMSISE00Base(object):
def __init__(self):
# Cache altitude value of last call
self.last_alt = None
self.inp = cmsis.nrlmsise_input()
self.output = cmsis.nrlmsise_output()
self... | 6,859 | 34 | 79 | py |
MCEq | MCEq-master/MCEq/geometry/geometry.py |
import sys
import numpy as np
from MCEq.misc import theta_rad
import mceq_config as config
class EarthGeometry(object):
r"""A model of the Earth's geometry, approximating it
by a sphere. The figure below illustrates the meaning of the parameters.
.. figure:: graphics/geometry.*
:scale: 30 %
... | 7,994 | 33.61039 | 82 | py |
MCEq | MCEq-master/MCEq/geometry/__init__.py | 0 | 0 | 0 | py | |
MCEq | MCEq-master/MCEq/geometry/corsikaatm/corsikaatm.py | from ctypes import (cdll, Structure, c_int, c_double, POINTER)
import os
import sysconfig
base = os.path.dirname(os.path.abspath(__file__))
suffix = sysconfig.get_config_var('EXT_SUFFIX')
# Some Python 2.7 versions don't define EXT_SUFFIX
if suffix is None and 'SO' in sysconfig.get_config_vars():
suffix = syscon... | 1,406 | 32.5 | 74 | py |
MCEq | MCEq-master/MCEq/geometry/corsikaatm/__init__.py | 0 | 0 | 0 | py | |
MCEq | MCEq-master/MCEq/geometry/nrlmsise00/nrlmsise00.py | '''
Ctypes interface for struct-based interface to the C-version of NRLMSISE-00.
This C version of NRLMSISE-00 is written by Dominik Brodowski
'''
from ctypes import (cdll, Structure, c_int, c_double, pointer, byref, POINTER)
import os
import sysconfig
base = os.path.dirname(os.path.abspath(__file__))
suffix = sysc... | 1,581 | 33.391304 | 78 | py |
MCEq | MCEq-master/MCEq/geometry/nrlmsise00/__init__.py | 0 | 0 | 0 | py | |
qemu | qemu-master/python/setup.py | #!/usr/bin/env python3
"""
QEMU tooling installer script
Copyright (c) 2020-2021 John Snow for Red Hat, Inc.
"""
import setuptools
from setuptools.command import bdist_egg
import sys
import pkg_resources
class bdist_egg_guard(bdist_egg.bdist_egg):
"""
Protect against bdist_egg from being executed
This p... | 989 | 23.146341 | 86 | py |
qemu | qemu-master/python/qemu/qmp/error.py | """
QMP Error Classes
This package seeks to provide semantic error classes that are intended
to be used directly by clients when they would like to handle particular
semantic failures (e.g. "failed to connect") without needing to know the
enumeration of possible reasons for that failure.
QMPError serves as the ancest... | 1,701 | 32.372549 | 76 | py |
qemu | qemu-master/python/qemu/qmp/legacy.py | """
(Legacy) Sync QMP Wrapper
This module provides the `QEMUMonitorProtocol` class, which is a
synchronous wrapper around `QMPClient`.
Its design closely resembles that of the original QEMUMonitorProtocol
class, originally written by Luiz Capitulino. It is provided here for
compatibility with scripts inside the QEMU ... | 10,193 | 30.079268 | 79 | py |
qemu | qemu-master/python/qemu/qmp/events.py | """
QMP Events and EventListeners
Asynchronous QMP uses `EventListener` objects to listen for events. An
`EventListener` is a FIFO event queue that can be pre-filtered to listen
for only specific events. Each `EventListener` instance receives its own
copy of events that it hears, so events may be consumed without fear... | 22,625 | 30.512535 | 78 | py |
qemu | qemu-master/python/qemu/qmp/message.py | """
QMP Message Format
This module provides the `Message` class, which represents a single QMP
message sent to or from the server.
"""
import json
from json import JSONDecodeError
from typing import (
Dict,
Iterator,
Mapping,
MutableMapping,
Optional,
Union,
)
from .error import ProtocolError... | 6,355 | 29.266667 | 91 | py |
qemu | qemu-master/python/qemu/qmp/qmp_tui.py | # Copyright (c) 2021
#
# Authors:
# Niteesh Babu G S <niteesh.gs@gmail.com>
#
# This work is licensed under the terms of the GNU LGPL, version 2 or
# later. See the COPYING file in the top-level directory.
"""
QMP TUI
QMP TUI is an asynchronous interface built on top the of the QMP library.
It is the successor of QM... | 22,153 | 32.926493 | 79 | py |
qemu | qemu-master/python/qemu/qmp/qmp_client.py | """
QMP Protocol Implementation
This module provides the `QMPClient` class, which can be used to connect
and send commands to a QMP server such as QEMU. The QMP class can be
used to either connect to a listening server, or used to listen and
accept an incoming connection from that server.
"""
import asyncio
import lo... | 22,564 | 33.397866 | 78 | py |
qemu | qemu-master/python/qemu/qmp/util.py | """
Miscellaneous Utilities
This module provides asyncio utilities and compatibility wrappers for
Python 3.6 to provide some features that otherwise become available in
Python 3.7+.
Various logging and debugging utilities are also provided, such as
`exception_summary()` and `pretty_traceback()`, used primarily for
ad... | 6,229 | 27.318182 | 78 | py |
qemu | qemu-master/python/qemu/qmp/protocol.py | """
Generic Asynchronous Message-based Protocol Support
This module provides a generic framework for sending and receiving
messages over an asyncio stream. `AsyncProtocol` is an abstract class
that implements the core mechanisms of a simple send/receive protocol,
and is designed to be extended.
In this package, it is... | 38,478 | 35.164474 | 79 | py |
qemu | qemu-master/python/qemu/qmp/models.py | """
QMP Data Models
This module provides simplistic data classes that represent the few
structures that the QMP spec mandates; they are used to verify incoming
data to make sure it conforms to spec.
"""
# pylint: disable=too-few-public-methods
from collections import abc
import copy
from typing import (
Any,
... | 4,442 | 29.22449 | 76 | py |
qemu | qemu-master/python/qemu/qmp/__init__.py | """
QEMU Monitor Protocol (QMP) development library & tooling.
This package provides a fairly low-level class for communicating
asynchronously with QMP protocol servers, as implemented by QEMU, the
QEMU Guest Agent, and the QEMU Storage Daemon.
`QMPClient` provides the main functionality of this package. All errors
r... | 1,545 | 24.766667 | 71 | py |
qemu | qemu-master/python/qemu/qmp/qmp_shell.py | #
# Copyright (C) 2009-2022 Red Hat Inc.
#
# Authors:
# Luiz Capitulino <lcapitulino@redhat.com>
# John Snow <jsnow@redhat.com>
#
# This work is licensed under the terms of the GNU LGPL, version 2 or
# later. See the COPYING file in the top-level directory.
#
"""
Low-level QEMU shell on top of QMP.
usage: qmp-shell... | 19,800 | 31.407529 | 79 | py |
qemu | qemu-master/python/qemu/utils/qom_common.py | """
QOM Command abstractions.
"""
##
# Copyright John Snow 2020, for Red Hat, Inc.
# Copyright IBM, Corp. 2011
#
# Authors:
# John Snow <jsnow@redhat.com>
# Anthony Liguori <aliguori@amazon.com>
#
# This work is licensed under the terms of the GNU GPL, version 2 or later.
# See the COPYING file in the top-level direc... | 4,995 | 27.386364 | 79 | py |
qemu | qemu-master/python/qemu/utils/qemu_ga_client.py | """
QEMU Guest Agent Client
Usage:
Start QEMU with:
# qemu [...] -chardev socket,path=/tmp/qga.sock,server=on,wait=off,id=qga0 \
-device virtio-serial \
-device virtserialport,chardev=qga0,name=org.qemu.guest_agent.0
Run the script:
$ qemu-ga-client --address=/tmp/qga.sock <command> [args...]
or
$ export QGA... | 9,490 | 28.29321 | 77 | py |
qemu | qemu-master/python/qemu/utils/qom.py | """
QEMU Object Model testing tools.
usage: qom [-h] {set,get,list,tree,fuse} ...
Query and manipulate QOM data
optional arguments:
-h, --help show this help message and exit
QOM commands:
{set,get,list,tree,fuse}
set Set a QOM property value
get Get a QOM propert... | 7,580 | 26.667883 | 79 | py |
qemu | qemu-master/python/qemu/utils/accel.py | """
QEMU accel module:
This module provides utilities for discover and check the availability of
accelerators.
"""
# Copyright (C) 2015-2016 Red Hat Inc.
# Copyright (C) 2012 IBM Corp.
#
# Authors:
# Fam Zheng <famz@redhat.com>
#
# This work is licensed under the terms of the GNU GPL, version 2. See
# the COPYING fi... | 2,348 | 26.635294 | 75 | py |
qemu | qemu-master/python/qemu/utils/qom_fuse.py | """
QEMU Object Model FUSE filesystem tool
This script offers a simple FUSE filesystem within which the QOM tree
may be browsed, queried and edited using traditional shell tooling.
This script requires the 'fusepy' python package.
usage: qom-fuse [-h] [--socket SOCKET] <mount>
Mount a QOM tree as a FUSE filesystem... | 5,978 | 27.745192 | 78 | py |
qemu | qemu-master/python/qemu/utils/__init__.py | """
QEMU development and testing utilities
This package provides a small handful of utilities for performing
various tasks not directly related to the launching of a VM.
"""
# Copyright (C) 2021 Red Hat Inc.
#
# Authors:
# John Snow <jsnow@redhat.com>
# Cleber Rosa <crosa@redhat.com>
#
# This work is licensed under... | 5,382 | 32.02454 | 78 | py |
qemu | qemu-master/python/qemu/machine/machine.py | """
QEMU machine module:
The machine module primarily provides the QEMUMachine class,
which provides facilities for managing the lifetime of a QEMU VM.
"""
# Copyright (C) 2015-2016 Red Hat Inc.
# Copyright (C) 2012 IBM Corp.
#
# Authors:
# Fam Zheng <famz@redhat.com>
#
# This work is licensed under the terms of the... | 31,109 | 33.29989 | 79 | py |
qemu | qemu-master/python/qemu/machine/qtest.py | """
QEMU qtest library
qtest offers the QEMUQtestProtocol and QEMUQTestMachine classes, which
offer a connection to QEMU's qtest protocol socket, and a qtest-enabled
subclass of QEMUMachine, respectively.
"""
# Copyright (C) 2015 Red Hat Inc.
#
# Authors:
# Fam Zheng <famz@redhat.com>
#
# This work is licensed under... | 4,696 | 27.640244 | 75 | py |
qemu | qemu-master/python/qemu/machine/console_socket.py | """
QEMU Console Socket Module:
This python module implements a ConsoleSocket object,
which can drain a socket and optionally dump the bytes to file.
"""
# Copyright 2020 Linaro
#
# Authors:
# Robert Foley <robert.foley@linaro.org>
#
# This code is licensed under the GPL version 2 or later. See
# the COPYING file in... | 4,685 | 35.046154 | 72 | py |
qemu | qemu-master/python/qemu/machine/__init__.py | """
QEMU development and testing library.
This library provides a few high-level classes for driving QEMU from a
test suite, not intended for production use.
| QEMUQtestProtocol: send/receive qtest messages.
| QEMUMachine: Configure and Boot a QEMU VM
| +-- QEMUQtestMachine: VM class, with a qtest socket.
"""
# ... | 945 | 24.567568 | 71 | py |
qemu | qemu-master/python/tests/protocol.py | import asyncio
from contextlib import contextmanager
import os
import socket
from tempfile import TemporaryDirectory
import avocado
from qemu.qmp import ConnectError, Runstate
from qemu.qmp.protocol import AsyncProtocol, StateError
from qemu.qmp.util import asyncio_run, create_task
class NullProtocol(AsyncProtocol[... | 18,678 | 30.288107 | 80 | py |
qemu | qemu-master/target/hexagon/gen_analyze_funcs.py | #!/usr/bin/env python3
##
## Copyright(c) 2022-2023 Qualcomm Innovation Center, Inc. All Rights Reserved.
##
## This program is free software; you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 2 of the Licen... | 9,792 | 37.70751 | 80 | py |
qemu | qemu-master/target/hexagon/gen_helper_funcs.py | #!/usr/bin/env python3
##
## Copyright(c) 2019-2023 Qualcomm Innovation Center, Inc. All Rights Reserved.
##
## This program is free software; you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 2 of the Licen... | 12,876 | 35.68661 | 80 | py |
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