code stringlengths 114 1.05M | path stringlengths 3 312 | quality_prob float64 0.5 0.99 | learning_prob float64 0.2 1 | filename stringlengths 3 168 | kind stringclasses 1
value |
|---|---|---|---|---|---|
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import tensorflow as tf
import numpy as np
import random
import time
from .ops import average_gradients, _variable_with_weight_decay, _variable_on_cpu
import phenograph
from sklearn.cluster import KMeans
def ... | /scScope_cpu-0.1.5.tar.gz/scScope_cpu-0.1.5/scscope/large_scale_processing.py | 0.773131 | 0.416797 | large_scale_processing.py | pypi |
import tensorflow as tf
def _variable_with_weight_decay(name, shape, stddev, wd):
"""
Helper to create an initialized Variable with weight decay.
Note that the Variable is initialized with a truncated normal distribution.
A weight decay is added only if one is specified.
Args:
name: nam... | /scScope-0.1.5.tar.gz/scScope-0.1.5/scscope/ops.py | 0.844409 | 0.578865 | ops.py | pypi |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import tensorflow as tf
import numpy as np
import random
import time
from .ops import average_gradients, _variable_with_weight_decay, _variable_on_cpu
import phenograph
from sklearn.cluster import KMeans
def ... | /scScope-0.1.5.tar.gz/scScope-0.1.5/scscope/large_scale_processing.py | 0.773131 | 0.416797 | large_scale_processing.py | pypi |
# scSplit [](https://doi.org/10.5281/zenodo.3464622)
### Genotype-free demultiplexing of pooled single-cell RNA-seq, using a hidden state model for identifying genetically distinct samples within a mixed population.
#### It has been tested on up ... | /scSplit-1.0.8.2.tar.gz/scSplit-1.0.8.2/README.md | 0.812533 | 0.781164 | README.md | pypi |
import torch
import random
import numpy as np
import pandas as pd
from tqdm import tqdm
from torch.optim import Adam
import torch.nn.functional as F
from torch.utils.data import DataLoader
from .model import simdatset, AutoEncoder, device
from .utils import showloss
def reproducibility(seed=1):
torch.manual_seed(... | /scTAPE-1.1.2-py3-none-any.whl/TAPE/train.py | 0.667581 | 0.422624 | train.py | pypi |
import os
import anndata
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from sklearn.preprocessing import MinMaxScaler, StandardScaler
#### NEEDED FILES
# 1. GeneLength.txt
def counts2FPKM(counts, genelen):
genelen = pd.read_csv(genelen, sep=',')
genelen['Transcri... | /scTAPE-1.1.2-py3-none-any.whl/TAPE/utils.py | 0.439988 | 0.431464 | utils.py | pypi |
import anndata
import pandas as pd
from .simulation import generate_simulated_data
from .utils import ProcessInputData
from .train import train_model, predict, reproducibility
from .model import scaden, AutoEncoder
def Deconvolution(necessary_data, real_bulk, sep='\t', variance_threshold=0.98,
scaler... | /scTAPE-1.1.2-py3-none-any.whl/TAPE/deconvolution.py | 0.711431 | 0.557424 | deconvolution.py | pypi |
import json
import time
from pathlib import Path
from typing import Optional, Union
import inspect
import numpy as np
import pandas as pd
from scipy import sparse
from scTenifold.core._networks import *
from scTenifold.core._QC import sc_QC
from scTenifold.core._norm import cpm_norm
from scTenifold.core._decompositio... | /scTenifoldpy-0.1.3.tar.gz/scTenifoldpy-0.1.3/scTenifold/core/_base.py | 0.761583 | 0.159872 | _base.py | pypi |
from typing import Sequence
import numpy as np
import pandas as pd
import scipy
from scTenifold.core._utils import timer
from tensorly.decomposition import parafac, parafac2, parafac_power_iteration
from tensorly import decomposition
import tensorly as tl
__all__ = ["tensor_decomp"]
@timer
def tensor_decomp(network... | /scTenifoldpy-0.1.3.tar.gz/scTenifoldpy-0.1.3/scTenifold/core/_decomposition.py | 0.899431 | 0.315749 | _decomposition.py | pypi |
import pandas as pd
from warnings import warn
def sc_QC(X: pd.DataFrame,
min_lib_size: float = 1000,
remove_outlier_cells: bool = True,
min_percent: float = 0.05,
max_mito_ratio: float = 0.1,
min_exp_avg: float = 0,
min_exp_sum: float = 0) -> pd.DataFrame:
... | /scTenifoldpy-0.1.3.tar.gz/scTenifoldpy-0.1.3/scTenifold/core/_QC.py | 0.87674 | 0.668752 | _QC.py | pypi |
import re
from pathlib import Path
import zipfile
from warnings import warn
from scipy.sparse.csr import csr_matrix
import pandas as pd
__all__ = ["read_mtx", "read_folder"]
def _get_mtx_body(rows, decode=None, print_header=True):
find_header_btn, row_ptr = False, 0
while not find_header_btn:
m = r... | /scTenifoldpy-0.1.3.tar.gz/scTenifoldpy-0.1.3/scTenifold/data/_io.py | 0.407805 | 0.291989 | _io.py | pypi |
from typing import Dict, Union, List
import zipfile
import gzip
from io import BytesIO
import re
from pathlib import Path
import requests
import pandas as pd
from ._io import read_mtx
_valid_ds_names = ["AD", "Nkx2_KO", "aging", "cetuximab", "dsRNA", "morphine"]
_repo_url = "https://raw.githubusercontent.com/{owne... | /scTenifoldpy-0.1.3.tar.gz/scTenifoldpy-0.1.3/scTenifold/data/_get.py | 0.645902 | 0.219599 | _get.py | pypi |
from functools import partial
from warnings import warn
from typing import Optional, List
import pandas as pd
import numpy as np
def _check_features(df,
features):
valid_features = set(df.index) & set(features)
if len(features) != len(valid_features):
warn(f"Found {len(features) -... | /scTenifoldpy-0.1.3.tar.gz/scTenifoldpy-0.1.3/scTenifold/cell_cycle/UCell.py | 0.81409 | 0.355467 | UCell.py | pypi |
from typing import Optional, Dict, List
import argparse
from pathlib import Path
import numpy as np
import pandas as pd
from scanpy.tools import score_genes
from scTenifold.data._sim import *
def adobo_score(X,
genes,
n_bins: int = 25,
n_ctrl: int = 50,
... | /scTenifoldpy-0.1.3.tar.gz/scTenifoldpy-0.1.3/scTenifold/cell_cycle/scoring.py | 0.724773 | 0.371678 | scoring.py | pypi |
from sklearn.decomposition import PCA
from sklearn.manifold import TSNE, Isomap, MDS, SpectralEmbedding, LocallyLinearEmbedding
import umap
from sklearn.preprocessing import StandardScaler
import pandas as pd
from enum import Enum
__all__ = ["prepare_PCA_dfs", "prepare_embedding_dfs"]
class Reducer(Enum):
TSNE =... | /scTenifoldpy-0.1.3.tar.gz/scTenifoldpy-0.1.3/scTenifold/plotting/_dim_reduction.py | 0.803019 | 0.446495 | _dim_reduction.py | pypi |
from typing import Tuple, Optional
import seaborn as sns
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import networkx as nx
from scipy.stats import chi2
from scTenifold.plotting._dim_reduction import *
def plot_network_graph(network: np.ndarray,
weight_thres=0.1,
... | /scTenifoldpy-0.1.3.tar.gz/scTenifoldpy-0.1.3/scTenifold/plotting/_plotting.py | 0.944498 | 0.646209 | _plotting.py | pypi |
from control import step_response as st, impulse_response, initial_response, forced_response
from matplotlib import pyplot as plt
def step(sys, T=None,xylim=None, X0=0.0, input=None, output=None, transpose=False, return_x=False, squeeze=True,grid=False):
"""
Step response of a linear system
If the system ... | /sca-fiuna-0.2.1.1.tar.gz/sca-fiuna-0.2.1.1/sca/graph.py | 0.912231 | 0.798776 | graph.py | pypi |
import cmath
from control.matlab import TransferFunction
from control.xferfcn import tf
def phase(V):
"""
function phase:
receive one or vector of complex numbers and return the vector of phase
angle respect the origin on radian
num: complex single or vector of complex
def: single number or ... | /sca-fiuna-0.2.1.1.tar.gz/sca-fiuna-0.2.1.1/sca/funclib.py | 0.558568 | 0.850033 | funclib.py | pypi |
import spidev
from utils.constant import Constant
_STANDARD_GRAVITY = 9.80665 # m/s^2
# 32 bit SPI commands to interact with device
_READ_ACC_X = Constant(0x040000F7)
_READ_ACC_Y = Constant(0x080000FD)
_READ_ACC_Z = Constant(0x0C0000FB)
_SW_RESET = Constant(0xB4002098)
_WHO_AM_I = Constant(0x40000091)
_SELF_TEST = ... | /sca3300-1.0.1-py3-none-any.whl/sca3300.py | 0.706798 | 0.417568 | sca3300.py | pypi |
import enum
import re
# status modes
MODE_SUCCESS = 0x0
MODE_FAILURE = 0x1
MODE_PENDING = 0x2
# status domain separators
DOMAIN_GENERIC = 0x0
DOMAIN_BE = 0x1
DOMAIN_FE = 0x2
class MWStatus(enum.IntEnum):
def encode(mode, domain, value):
return ((mode & 0x3) << 30) | ((domain & 0x3) << 28) | ((value & 0... | /sca3s_cli-1.0.6-py3-none-any.whl/sca3s_cli/classes/middleware_status.py | 0.52902 | 0.21686 | middleware_status.py | pypi |
import multiprocessing
import os
from collections import defaultdict
from pathlib import Path
import colorama
import h5py
import numpy as np
from tensorflow.keras.utils import to_categorical # nopep8 pylint: disable=import-error
from tqdm import tqdm
from termcolor import cprint
from .aes import AES
colorama.ini... | /aes/data.py | 0.502686 | 0.247407 | data.py | pypi |
import os
from collections import defaultdict, namedtuple
from multiprocessing import Pool
from pathlib import Path
import colorama
import h5py
import numpy as np
import tensorflow as tf
from tensorflow.keras.utils import to_categorical # nopep8 pylint: disable=import-error
from termcolor import cprint
from .aes i... | /aes/combined_data.py | 0.660063 | 0.23875 | combined_data.py | pypi |
import numpy as np
from termcolor import cprint
import tensorflow
from .aes import AES
from scaaml.utils import hex_display, hex_display_recovered_key
from scaaml.aes.combined_data import shard_to_dict
from tqdm import tqdm
def pred2byte(attack_point, pt, prediction_index):
"""Recover the byte value
Args:
... | /aes/attack.py | 0.849628 | 0.403773 | attack.py | pypi |
import abc
import dataclasses
import logging
import typing
import scopeton.scope
from dataclasses_json import dataclass_json
import yaml
# @dataclasses.dataclass
# @dataclass_json
from scopeton.decorators import Inject
class ArgsConfig:
lib_path: str
upgrade: bool
v: bool
pm_file: str
def __str... | /scad_pm-0.23.tar.gz/scad_pm-0.23/scad_pm_mod/config.py | 0.673729 | 0.175361 | config.py | pypi |
import sys
import numpy as np
import pandas as pd
from scipy.interpolate import interp1d
sys.path.append('')
from scada_data_analysis.utils.binning_function import binning_func
from scada_data_analysis.modules.power_curve_preprocessing import PowerCurveFiltering
class ExpectedPower:
def __init__(self, turbine_l... | /scada_data_analysis-1.0.7.tar.gz/scada_data_analysis-1.0.7/scada_data_analysis/modules/expected_power.py | 0.614857 | 0.571677 | expected_power.py | pypi |
import os
import pandas as pd
import matplotlib.pyplot as plt
import sys
sys.path.append('')
from scada_data_analysis.utils.binning_function import binning_func
class PowerCurveFiltering:
"""
This class returns two subsets of the original SCADA data representing normal and abnormal operations
"""
... | /scada_data_analysis-1.0.7.tar.gz/scada_data_analysis-1.0.7/scada_data_analysis/modules/power_curve_preprocessing.py | 0.508544 | 0.48054 | power_curve_preprocessing.py | pypi |
# scadnano Python package
[](https://scadnano-python-package.readthedocs.io/en/latest/?b... | /scadnano-0.18.1.tar.gz/scadnano-0.18.1/README.md | 0.893356 | 0.904229 | README.md | pypi |
import warnings
warnings.simplefilter(action='ignore')
import argparse, os
import numpy as np
import pandas as pd
from pandas.api.types import is_string_dtype, is_numeric_dtype
from sklearn.model_selection import train_test_split
from sklearn.utils import shuffle
from scaespy import scAEspy
from _version import __vers... | /scaespy-1.2.1-py3-none-any.whl/cli/scaespy.py | 0.648466 | 0.243474 | scaespy.py | pypi |
import argparse
import datetime
import logging
import os
import re
import shlex
import subprocess
import sys
import textwrap
import time
logging.basicConfig(level=logging.INFO)
RE_YEARRANGE = re.compile(r"(\d{4})-(\d{4})", re.ASCII)
REPOROOT = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..", "..")... | /scal-2.1.0.tar.gz/scal-2.1.0/bin/lib/autoautoscl/__main__.py | 0.471953 | 0.252183 | __main__.py | pypi |
from __future__ import (nested_scopes, generators, division, absolute_import, with_statement,
print_function, unicode_literals)
import logging
import optparse
from foursquare.source_code_analysis.exception import SourceCodeAnalysisException
from foursquare.source_code_analysis.scala.scala_imp... | /scala-source-tools-0.14.tar.gz/scala-source-tools-0.14/foursquare/source_code_analysis/scala/scala_import_rewriter.py | 0.666605 | 0.184235 | scala_import_rewriter.py | pypi |
from __future__ import (nested_scopes, generators, division, absolute_import, with_statement,
print_function, unicode_literals)
class ScalaSymbolPath(object):
""""A dotted path of identifiers."""
def __init__(self, path_string):
"""Object is immutable."""
self.path_string = path_s... | /scala-source-tools-0.14.tar.gz/scala-source-tools-0.14/foursquare/source_code_analysis/scala/scala_imports.py | 0.900233 | 0.263274 | scala_imports.py | pypi |
from __future__ import (nested_scopes, generators, division, absolute_import, with_statement,
print_function, unicode_literals)
import re
from foursquare.source_code_analysis.exception import SourceCodeAnalysisException
from foursquare.source_code_analysis.scala.scala_imports import ScalaImpo... | /scala-source-tools-0.14.tar.gz/scala-source-tools-0.14/foursquare/source_code_analysis/scala/scala_import_parser.py | 0.724675 | 0.152821 | scala_import_parser.py | pypi |
from __future__ import annotations
import json
import logging
import os
import re
import secrets
import string
import shutil
from datetime import datetime
from typing import Any, Dict, List, MutableSequence, Optional, Tuple, Union, overload
import ipinfo
import requests
from requests.models import Response
from scala... | /scala_wrapper-0.0.6-py3-none-any.whl/scala_wrapper/content_manager/__init__.py | 0.849144 | 0.297746 | __init__.py | pypi |
from __future__ import annotations
import json
import logging
import os
import shutil
from datetime import datetime
from typing import Any, Dict, List, MutableSequence, Optional, Union, overload
import ipinfo
import requests
from requests.models import Response
from scala_wrapper.utils import typedef
def get_id(val... | /scala_wrapper-0.0.6-py3-none-any.whl/scala/content_manager/__init__.py | 0.741206 | 0.171061 | __init__.py | pypi |
Cuckoo filters
--------------
A Cuckoo filter is a data structure for probabilistic set-membership
queries with a low false positive probability (FPP). As an improvement
over the classic Bloom filter, items can be added or removed into
Cuckoo filters at will. A Cuckoo filter also utilizes space more
efficiently.
Cuck... | /scalable-cuckoo-filter-1.1.tar.gz/scalable-cuckoo-filter-1.1/README.md | 0.614857 | 0.879147 | README.md | pypi |
import yaml
from marshmallow import Schema, fields, EXCLUDE, validates_schema
from marshmallow.exceptions import ValidationError
class ExcludeUnknownSchema(Schema):
""" Remove unknown keys from loaded dictionary
"""
class Meta:
""" Exclude unknown properties.
"""
unknown = EXCLUDE
... | /scalable-pypeline-1.2.3.tar.gz/scalable-pypeline-1.2.3/pypeline/pipeline_config_schema.py | 0.827654 | 0.262074 | pipeline_config_schema.py | pypi |
import re
import os
import logging
import pkg_resources
import yaml
from yaml.loader import SafeLoader
from marshmallow import Schema, fields, pre_load, EXCLUDE, INCLUDE,\
validates_schema
from marshmallow.validate import OneOf
from marshmallow.exceptions import ValidationError
from pypeline.utils.module_utils impo... | /scalable-pypeline-1.2.3.tar.gz/scalable-pypeline-1.2.3/pypeline/sermos_yaml.py | 0.615666 | 0.182881 | sermos_yaml.py | pypi |
import os
from boto3 import Session
import logging
logger = logging.getLogger(__name__)
class KeyGenerator(object):
""" Common functions for key generators.
"""
def __init__(self):
super(KeyGenerator, self).__init__()
self.hidden_files = ('.DS_Store', '.git', 'Icon', '.Dropbox')
def ... | /scalable-pypeline-1.2.3.tar.gz/scalable-pypeline-1.2.3/pypeline/generators.py | 0.561335 | 0.158369 | generators.py | pypi |
import logging
import networkx as nx
from typing import List, Union
logger = logging.getLogger(__name__)
def get_execution_graph(
config: dict,
adjacency_key: str = 'dagAdjacency',
task_definitions_key: str = 'taskDefinitions') -> nx.DiGraph:
""" Generate a directed graph based on a pipel... | /scalable-pypeline-1.2.3.tar.gz/scalable-pypeline-1.2.3/pypeline/utils/graph_utils.py | 0.847021 | 0.592195 | graph_utils.py | pypi |
import pandas as pd
import rich
from rich.progress import Progress
from .exceptions import DataValidationError
from .exporter import Exporter
from .loader import Loader
from .steps import Step
from .validations import DataValidation
class DataPipeline:
def __init__(
self,
steps: list[Step],
... | /scalde_data_factory-0.0.1-py3-none-any.whl/data_factory/pipeline.py | 0.616936 | 0.259843 | pipeline.py | pypi |
import os
import numpy as np
import pandas as pd
import scipy
from scipy.sparse import issparse
import torch
from torch.utils.data import Dataset
from torch.utils.data.sampler import Sampler
from torch.utils.data import DataLoader
from anndata import AnnData
import scanpy as sc
import episcanpy as epi
from sklearn.pr... | /scale_atac-1.1.0-py3-none-any.whl/scale/dataset.py | 0.460046 | 0.318426 | dataset.py | pypi |
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn import init
from torch.optim.lr_scheduler import MultiStepLR, ExponentialLR, ReduceLROnPlateau
import time
import math
import numpy as np
from tqdm import tqdm, trange
from itertools import repeat
from sklearn.mixture import GaussianMixtu... | /scale_atac-1.1.0-py3-none-any.whl/scale/model.py | 0.914958 | 0.358129 | model.py | pypi |
import numpy as np
import pandas as pd
import scipy as sp
def jsd(p, q, base=np.e):
"""
Jensen Shannon_divergence
"""
## convert to np.array
p, q = np.asarray(p), np.asarray(q)
## normalize p, q to probabilities
p, q = p/p.sum(), q/q.sum()
m = 1./2*(p + q)
return sp.stats.entrop... | /scale_atac-1.1.0-py3-none-any.whl/scale/specifity.py | 0.635336 | 0.536434 | specifity.py | pypi |
import json
import logging
from abc import ABC, abstractmethod
from dataclasses import dataclass
from typing import Generic, Sequence, TypeVar
from launch_api.core import Service
from launch_api.types import I, JsonVal, O
logger = logging.getLogger("service")
__all__: Sequence[str] = (
# re-export
"Service",... | /scale_launch-0.3.3-py3-none-any.whl/launch/clientlib/service.py | 0.844329 | 0.207536 | service.py | pypi |
from dataclasses import dataclass
from logging import Logger
from typing import List, Sequence
import numpy as np
from launch_api.loader import Loader, LoaderSpec
from launch_api.model import B, Model
from launch_api.model_service.types import InferenceService, Processor
from launch_api.types import I, O
__all__: Seq... | /scale_launch-0.3.3-py3-none-any.whl/launch/clientlib/model_service/implementation.py | 0.858259 | 0.167151 | implementation.py | pypi |
from dataclasses import dataclass
from logging import Logger
from typing import List, Sequence
import numpy as np
from launch_api.batching.types import B, BatchableService, Batcher, Model
from launch_api.loader import Loader, LoaderSpec
from launch_api.types import I, O
__all__: Sequence[str] = (
"BatchableServic... | /scale_launch-0.3.3-py3-none-any.whl/launch/clientlib/batching/implementation.py | 0.86196 | 0.187411 | implementation.py | pypi |
import numpy as np
import json
import os
from scale_lidar_io import LidarScene, Transform
from .view_utils import open_viewer, open_new_viewer
from .awsHandler import get_secret, get_db_connection, get_signed_url
from bson.objectid import ObjectId
from pyquaternion import Quaternion
import base64
import requests
from .... | /scale_lidar_io_debug-0.2.0.tar.gz/scale_lidar_io_debug-0.2.0/scale_lidar_io_debug/scene.py | 0.429429 | 0.190385 | scene.py | pypi |
import numpy as np
import ujson
class JSONBinaryEncoder:
block_size = 4
def fill_block(self, data, fill=b'\00'):
return data + fill * (self.block_size - len(data) % self.block_size)
def encode_object(self, obj, keys=None, items=None, buffer=None, **params):
keys = keys or []
item... | /scale_lidar_io_debug-0.2.0.tar.gz/scale_lidar_io_debug-0.2.0/scale_lidar_io_debug/JSONBinaryEncoder.py | 0.496338 | 0.236737 | JSONBinaryEncoder.py | pypi |
from abc import ABCMeta, abstractmethod
import numpy as np
import open3d as o3d
import pandas as pd
from laspy.file import File
_FIELDS = ["x", "y", "z", "i", "d"]
class Importer:
"""Points importer/helper"""
class Base(metaclass=ABCMeta):
"""Abstract importer class to be inherited for data type sp... | /scale_lidar_io-1.2.5-py3-none-any.whl/scale_lidar_io/connectors.py | 0.900248 | 0.279432 | connectors.py | pypi |
import zipfile
from multiprocessing.pool import ThreadPool
from functools import partial
from io import BytesIO
from typing import MutableMapping, List, Dict
from tqdm import tqdm
import numpy as np
import pandas as pd
import ujson
from scaleapi.tasks import Task, TaskType
from .camera import LidarCamera
from .image ... | /scale_lidar_io-1.2.5-py3-none-any.whl/scale_lidar_io/scene.py | 0.887747 | 0.308125 | scene.py | pypi |
import pandas as pd
import ujson
import matplotlib.pyplot as plt
from matplotlib.widgets import Slider, Button
import numpy as np
from io import BytesIO
from pyquaternion import Quaternion
from typing import Any
from scipy.spatial.transform import Rotation as R
import open3d as o3d
from .camera import LidarCamera
fro... | /scale_lidar_io-1.2.5-py3-none-any.whl/scale_lidar_io/frame.py | 0.875548 | 0.476762 | frame.py | pypi |
import numpy as np
import transforms3d as t3d
from pyquaternion import Quaternion
class Transform:
"""Transform object represent a rigid transformation matrix (rotation and translation).
Transform is a 4x4 matrix, although it could be instance using (16,1), (3,4), (3,3) or (3,1) matrixes.
**Note**: not a... | /scale_lidar_io-1.2.5-py3-none-any.whl/scale_lidar_io/transform.py | 0.951897 | 0.865281 | transform.py | pypi |
import numpy as np
import requests
from scaleapi.tasks import Task, TaskType
import ujson
from .scene import LidarScene
from .helper import parse_xyz, get_api_client, get_default_template
class LidarAnnotationTask(Task):
"""Lidar annotation Task object"""
scene: LidarScene = None
def __init__(self, par... | /scale_lidar_io-1.2.5-py3-none-any.whl/scale_lidar_io/task.py | 0.744192 | 0.262704 | task.py | pypi |
from collections import defaultdict
import numpy as np
from pyquaternion import Quaternion
from typing import List
from google.protobuf.json_format import MessageToDict
from .lidar_frame_1_pb2 import CameraImage, LidarFrame
from .transform import Transform
# Protobuf Helpers
def create_scene_from_protobufs(scene, ... | /scale_lidar_io-1.2.5-py3-none-any.whl/scale_lidar_io/protobuf_helper.py | 0.842831 | 0.300803 | protobuf_helper.py | pypi |
import shutil
import numpy as np
import tempfile
from PIL import Image, ImageEnhance
from .helper import s3_smart_upload, scale_file_upload
class LidarImage:
"""LidarImage objects represent an image with a LidarCamera reference.
LidarImage properties:
- camera: Camera id
- image_path: Image path
... | /scale_lidar_io-1.2.5-py3-none-any.whl/scale_lidar_io/image.py | 0.793986 | 0.352982 | image.py | pypi |
from .scene import LidarScene
from .transform import Transform
from .frame import LidarFrame
from .camera import LidarCamera
from .image import LidarImage
from .helper import (
s3_smart_upload,
format_lidar_point,
format_point,
format_quaternion,
scale_file_upload,
get_signed_url
)
from io impo... | /scale_lidar_io-1.2.5-py3-none-any.whl/scale_lidar_io/nucleus_scene.py | 0.838151 | 0.265113 | nucleus_scene.py | pypi |
import random
import cv2
import numpy as np
from PIL import Image, ImageDraw
from .color_utils import map_colors
from .transform import Transform
class LidarCamera:
"""Camera object that contains all the camera information
Camera properties:
- id = camera id/Name/Identifier, type: int, str
... | /scale_lidar_io-1.2.5-py3-none-any.whl/scale_lidar_io/camera.py | 0.876522 | 0.522994 | camera.py | pypi |
from typing import Dict, Optional, Union
from llmengine.api_engine import DEFAULT_TIMEOUT, APIEngine
from llmengine.data_types import (
CancelFineTuneResponse,
CreateFineTuneRequest,
CreateFineTuneResponse,
GetFineTuneEventsResponse,
GetFineTuneResponse,
ListFineTunesResponse,
)
class FineTun... | /scale_llm_engine-0.0.0b8-py3-none-any.whl/llmengine/fine_tuning.py | 0.953221 | 0.860252 | fine_tuning.py | pypi |
from io import BufferedReader
from llmengine.api_engine import DEFAULT_TIMEOUT, APIEngine
from llmengine.data_types import (
DeleteFileResponse,
GetFileContentResponse,
GetFileResponse,
ListFilesResponse,
UploadFileResponse,
)
class File(APIEngine):
"""
File API. This API is used to uploa... | /scale_llm_engine-0.0.0b8-py3-none-any.whl/llmengine/file.py | 0.768038 | 0.541227 | file.py | pypi |
import json
# LLM Engine Errors
class ValidationError(Exception):
def __init__(self, message: str):
super().__init__(message)
# API Inference Errors
class BadRequestError(Exception):
"""
Corresponds to HTTP 400. Indicates that the request had inputs that were invalid. The user should not
att... | /scale_llm_engine-0.0.0b8-py3-none-any.whl/llmengine/errors.py | 0.684053 | 0.16378 | errors.py | pypi |
import datetime
from enum import Enum
from typing import Any, Dict, List, Literal, Optional, Union
from pydantic import BaseModel, Field, HttpUrl
CpuSpecificationType = Union[str, int, float]
StorageSpecificationType = Union[str, int, float] # TODO(phil): we can make this more specific.
class LLMInferenceFramework... | /scale_llm_engine-0.0.0b8-py3-none-any.whl/llmengine/data_types.py | 0.672117 | 0.170266 | data_types.py | pypi |
from typing import Dict, List, Optional
from llmengine.api_engine import DEFAULT_TIMEOUT, APIEngine, assert_self_hosted
from llmengine.data_types import (
CreateLLMEndpointRequest,
CreateLLMEndpointResponse,
DeleteLLMEndpointResponse,
GetLLMEndpointResponse,
GpuType,
ListLLMEndpointsResponse,
... | /scale_llm_engine-0.0.0b8-py3-none-any.whl/llmengine/model.py | 0.91482 | 0.397938 | model.py | pypi |
from typing import AsyncIterable, Iterator, Union
from llmengine.api_engine import APIEngine
from llmengine.data_types import (
CompletionStreamResponse,
CompletionStreamV1Request,
CompletionSyncResponse,
CompletionSyncV1Request,
)
class Completion(APIEngine):
"""
Completion API. This API is ... | /scale_llm_engine-0.0.0b8-py3-none-any.whl/llmengine/completion.py | 0.923351 | 0.762579 | completion.py | pypi |
# Nucleus
https://dashboard.scale.com/nucleus
Aggregate metrics in ML are not good enough. To improve production ML, you need to understand their qualitative failure modes, fix them by gathering more data, and curate diverse scenarios.
Scale Nucleus helps you:
- Visualize your data
- Curate interesting slices withi... | /scale_nucleus-0.15.10b0.tar.gz/scale_nucleus-0.15.10b0/README.md | 0.675765 | 0.900267 | README.md | pypi |
import json
import os.path
from collections import Counter
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Sequence
from .annotation import is_local_path
from .camera_params import CameraParams
from .constants import (
BACKEND_REFERENCE_ID_KEY,
CAMERA_PARAMS_KEY,... | /scale_nucleus-0.15.10b0.tar.gz/scale_nucleus-0.15.10b0/nucleus/dataset_item.py | 0.844345 | 0.42931 | dataset_item.py | pypi |
from enum import Enum
from typing import TYPE_CHECKING, Dict, Optional
from .async_job import AsyncJob
from .camera_params import CameraParams
from .constants import CAMERA_PARAMS_KEY
if TYPE_CHECKING:
from . import NucleusClient
# Wording set to match with backend enum
class ExportMetadataType(Enum):
SCENE... | /scale_nucleus-0.15.10b0.tar.gz/scale_nucleus-0.15.10b0/nucleus/metadata_manager.py | 0.881761 | 0.18101 | metadata_manager.py | pypi |
import json
from collections import Counter
from typing import TYPE_CHECKING, Iterable, List, Optional, Sequence
from nucleus.annotation import Annotation, SegmentationAnnotation
from nucleus.async_utils import (
FileFormField,
FormDataContextHandler,
make_many_form_data_requests_concurrently,
)
from nucle... | /scale_nucleus-0.15.10b0.tar.gz/scale_nucleus-0.15.10b0/nucleus/annotation_uploader.py | 0.831725 | 0.305613 | annotation_uploader.py | pypi |
import json
import warnings
from abc import ABC
from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Union
from nucleus.constants import (
FRAME_RATE_KEY,
FRAMES_KEY,
IMAGE_LOCATION_KEY,
LENGTH_KEY,
METADATA_KEY,
NUM_SENSORS_KEY,
POINTCLOUD_L... | /scale_nucleus-0.15.10b0.tar.gz/scale_nucleus-0.15.10b0/nucleus/scene.py | 0.915219 | 0.444324 | scene.py | pypi |
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict
from .annotation import Point3D
from .constants import (
CAMERA_MODEL_KEY,
CX_KEY,
CY_KEY,
FX_KEY,
FY_KEY,
HEADING_KEY,
K1_KEY,
K2_KEY,
K3_KEY,
K4_KEY,
P1_KEY,
P2_KEY,
POSITION_KEY,
... | /scale_nucleus-0.15.10b0.tar.gz/scale_nucleus-0.15.10b0/nucleus/camera_params.py | 0.864253 | 0.326218 | camera_params.py | pypi |
import json
import os
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Sequence, Type, Union
from urllib.parse import urlparse
import numpy as np
from .constants import (
ANNOTATION_ID_KEY,
ANNOTATIONS_KEY,
BOX_TYPE,
CATEGORY_TYPE,
CUBOID_TYPE... | /scale_nucleus-0.15.10b0.tar.gz/scale_nucleus-0.15.10b0/nucleus/annotation.py | 0.835919 | 0.169509 | annotation.py | pypi |
import asyncio
import time
from dataclasses import dataclass
from typing import TYPE_CHECKING, BinaryIO, Callable, Sequence, Tuple
import aiohttp
import nest_asyncio
from tqdm import tqdm
from nucleus.constants import DEFAULT_NETWORK_TIMEOUT_SEC
from nucleus.errors import NucleusAPIError
from nucleus.retry_strategy i... | /scale_nucleus-0.15.10b0.tar.gz/scale_nucleus-0.15.10b0/nucleus/async_utils.py | 0.833392 | 0.201951 | async_utils.py | pypi |
from typing import List, Optional, Union
import requests
from nucleus.annotation import check_all_mask_paths_remote
from nucleus.annotation_uploader import PredictionUploader
from nucleus.async_job import AsyncJob
from nucleus.utils import (
format_prediction_response,
serialize_and_write_to_presigned_url,
)
... | /scale_nucleus-0.15.10b0.tar.gz/scale_nucleus-0.15.10b0/nucleus/model_run.py | 0.935516 | 0.254402 | model_run.py | pypi |
import io
import json
import uuid
from collections import defaultdict
from typing import IO, TYPE_CHECKING, Dict, List, Sequence, Type, Union
import requests
from requests.models import HTTPError
from nucleus.annotation import (
Annotation,
BoxAnnotation,
CategoryAnnotation,
CuboidAnnotation,
Key... | /scale_nucleus-0.15.10b0.tar.gz/scale_nucleus-0.15.10b0/nucleus/utils.py | 0.813942 | 0.166472 | utils.py | pypi |
from dataclasses import dataclass, field
from typing import Dict, List, Optional, Type, Union
from .annotation import (
BoxAnnotation,
CategoryAnnotation,
CuboidAnnotation,
Keypoint,
KeypointsAnnotation,
LineAnnotation,
Point,
Point3D,
PolygonAnnotation,
SceneCategoryAnnotation,... | /scale_nucleus-0.15.10b0.tar.gz/scale_nucleus-0.15.10b0/nucleus/prediction.py | 0.921012 | 0.427277 | prediction.py | pypi |
from typing import Any, Dict, List, Optional, Union
from .annotation import (
BoxAnnotation,
CategoryAnnotation,
CuboidAnnotation,
MultiCategoryAnnotation,
PolygonAnnotation,
SceneCategoryAnnotation,
SegmentationAnnotation,
)
from .constants import (
ANNOTATION_METADATA_SCHEMA_KEY,
... | /scale_nucleus-0.15.10b0.tar.gz/scale_nucleus-0.15.10b0/nucleus/payload_constructor.py | 0.835685 | 0.186687 | payload_constructor.py | pypi |
import time
from dataclasses import dataclass
from typing import Dict, List
import requests
from nucleus.constants import (
JOB_CREATION_TIME_KEY,
JOB_ID_KEY,
JOB_LAST_KNOWN_STATUS_KEY,
JOB_TYPE_KEY,
STATUS_KEY,
)
from nucleus.utils import replace_double_slashes
JOB_POLLING_INTERVAL = 5
@datacl... | /scale_nucleus-0.15.10b0.tar.gz/scale_nucleus-0.15.10b0/nucleus/async_job.py | 0.640748 | 0.228565 | async_job.py | pypi |
from typing import Dict, List, Optional, Union
import requests
from .async_job import AsyncJob
from .constants import METADATA_KEY, MODEL_TAGS_KEY, NAME_KEY, REFERENCE_ID_KEY
from .dataset import Dataset
from .model_run import ModelRun
from .prediction import (
BoxPrediction,
CuboidPrediction,
PolygonPred... | /scale_nucleus-0.15.10b0.tar.gz/scale_nucleus-0.15.10b0/nucleus/model.py | 0.944542 | 0.513059 | model.py | pypi |
import json
from dataclasses import dataclass
from typing import TYPE_CHECKING, Any, Dict, Optional
import requests
from .constants import (
DATASET_ID_KEY,
METADATA_KEY,
OVERWRITE_KEY,
REFERENCE_ID_KEY,
)
if TYPE_CHECKING:
from . import Connection
@dataclass # pylint: disable=R0902
class Trac... | /scale_nucleus-0.15.10b0.tar.gz/scale_nucleus-0.15.10b0/nucleus/track.py | 0.930411 | 0.160661 | track.py | pypi |
from typing import Set
from .constants import (
DATASET_ID_KEY,
ERROR_CODES,
ERROR_ITEMS,
ERROR_PAYLOAD,
IGNORED_ITEMS,
NEW_ITEMS,
UPDATED_ITEMS,
)
from .dataset_item import DatasetItem
def json_list_to_dataset_item(item_list):
return [DatasetItem.from_json(item) for item in item_list... | /scale_nucleus-0.15.10b0.tar.gz/scale_nucleus-0.15.10b0/nucleus/upload_response.py | 0.856498 | 0.166777 | upload_response.py | pypi |
from typing import List
from nucleus.async_job import AsyncJob
from nucleus.connection import Connection
from .constants import EVAL_FUNCTION_KEY, SCENARIO_TEST_ID_KEY, EntityLevel
from .data_transfer_objects.eval_function import (
CreateEvalFunction,
EvalFunctionEntry,
GetEvalFunctions,
)
from .data_tran... | /scale_nucleus-0.15.10b0.tar.gz/scale_nucleus-0.15.10b0/nucleus/validate/client.py | 0.938343 | 0.370425 | client.py | pypi |
from typing import Any, Dict, List, Optional
from pydantic import validator
from ...pydantic_base import ImmutableModel
from ..constants import ThresholdComparison
class EvaluationCriterion(ImmutableModel):
"""
An Evaluation Criterion is defined as an evaluation function, threshold, and comparator.
It d... | /scale_nucleus-0.15.10b0.tar.gz/scale_nucleus-0.15.10b0/nucleus/validate/data_transfer_objects/eval_function.py | 0.825555 | 0.547101 | eval_function.py | pypi |
import abc
from typing import Any, Dict
from ..constants import ThresholdComparison
from ..data_transfer_objects.eval_function import (
EvalFunctionEntry,
EvaluationCriterion,
)
class EvalFunctionConfig(abc.ABC):
"""Abstract base class for concrete implementations of EvalFunctionsConfigs
Operating o... | /scale_nucleus-0.15.10b0.tar.gz/scale_nucleus-0.15.10b0/nucleus/validate/eval_functions/base_eval_function.py | 0.857141 | 0.251452 | base_eval_function.py | pypi |
import itertools
from typing import Callable, Dict, List, Optional, Union
from nucleus.validate.eval_functions.base_eval_function import (
EvalFunctionConfig,
)
from ...metrics.filtering import ListOfAndFilters, ListOfOrAndFilters
from ..data_transfer_objects.eval_function import EvalFunctionEntry
from ..errors i... | /scale_nucleus-0.15.10b0.tar.gz/scale_nucleus-0.15.10b0/nucleus/validate/eval_functions/available_eval_functions.py | 0.825976 | 0.407805 | available_eval_functions.py | pypi |
from typing import Optional, Union
from nucleus.validate.eval_functions.base_eval_function import (
EvalFunctionConfig,
)
from ....metrics.filtering import ListOfAndFilters, ListOfOrAndFilters
class SegmentationIOUConfig(EvalFunctionConfig):
def __call__(
self,
annotation_filters: Optional[
... | /scale_nucleus-0.15.10b0.tar.gz/scale_nucleus-0.15.10b0/nucleus/validate/eval_functions/config_classes/segmentation.py | 0.957596 | 0.479382 | segmentation.py | pypi |
import abc
from typing import List, Optional, Set, Tuple, Union
import numpy as np
from nucleus.annotation import AnnotationList, Segment, SegmentationAnnotation
from nucleus.metrics.base import MetricResult
from nucleus.metrics.filtering import ListOfAndFilters, ListOfOrAndFilters
from nucleus.prediction import Pred... | /scale_nucleus-0.15.10b0.tar.gz/scale_nucleus-0.15.10b0/nucleus/metrics/segmentation_metrics.py | 0.73678 | 0.54583 | segmentation_metrics.py | pypi |
import sys
from abc import abstractmethod
from typing import List, Optional, Union
import numpy as np
from nucleus.annotation import AnnotationList, BoxAnnotation, PolygonAnnotation
from nucleus.prediction import BoxPrediction, PolygonPrediction, PredictionList
from .base import Metric, ScalarResult
from .custom_typ... | /scale_nucleus-0.15.10b0.tar.gz/scale_nucleus-0.15.10b0/nucleus/metrics/polygon_metrics.py | 0.862279 | 0.474692 | polygon_metrics.py | pypi |
import logging
import sys
from functools import wraps
from typing import TYPE_CHECKING, Dict, List, Tuple
from nucleus.annotation import BoxAnnotation, PolygonAnnotation
from .base import ScalarResult
from .custom_types import BoxOrPolygonAnnotation, BoxOrPolygonPrediction
from .errors import PolygonAnnotationTypeErr... | /scale_nucleus-0.15.10b0.tar.gz/scale_nucleus-0.15.10b0/nucleus/metrics/polygon_utils.py | 0.655557 | 0.553385 | polygon_utils.py | pypi |
import sys
from abc import ABC, abstractmethod
from dataclasses import dataclass
from typing import Iterable, List, Optional, Union
from nucleus.annotation import AnnotationList
from nucleus.metrics.errors import EverythingFilteredError
from nucleus.metrics.filtering import (
ListOfAndFilters,
ListOfOrAndFilte... | /scale_nucleus-0.15.10b0.tar.gz/scale_nucleus-0.15.10b0/nucleus/metrics/base.py | 0.861989 | 0.519034 | base.py | pypi |
from functools import wraps
from typing import Dict, List, Tuple
import numpy as np
try:
from shapely.geometry import Polygon
except (ModuleNotFoundError, OSError):
from ..package_not_installed import PackageNotInstalled
Polygon = PackageNotInstalled
from nucleus.annotation import CuboidAnnotation
from... | /scale_nucleus-0.15.10b0.tar.gz/scale_nucleus-0.15.10b0/nucleus/metrics/cuboid_utils.py | 0.945951 | 0.69978 | cuboid_utils.py | pypi |
import copy
import enum
import functools
import logging
from enum import Enum
from typing import (
Callable,
Iterable,
List,
NamedTuple,
Optional,
Sequence,
Set,
Tuple,
Union,
)
from rich.console import Console
from rich.table import Table
from nucleus.annotation import (
Annot... | /scale_nucleus-0.15.10b0.tar.gz/scale_nucleus-0.15.10b0/nucleus/metrics/filtering.py | 0.757794 | 0.44059 | filtering.py | pypi |
import sys
from abc import abstractmethod
from typing import List, Optional, Union
from nucleus.annotation import AnnotationList, CuboidAnnotation
from nucleus.prediction import CuboidPrediction, PredictionList
from .base import Metric, ScalarResult
from .cuboid_utils import detection_iou, label_match_wrapper, recall... | /scale_nucleus-0.15.10b0.tar.gz/scale_nucleus-0.15.10b0/nucleus/metrics/cuboid_metrics.py | 0.842151 | 0.590396 | cuboid_metrics.py | pypi |
import abc
import logging
from enum import Enum
from typing import List, Optional, Union
import numpy as np
from nucleus.annotation import AnnotationList, SegmentationAnnotation
from nucleus.metrics.base import MetricResult
from nucleus.metrics.filtering import (
ListOfAndFilters,
ListOfOrAndFilters,
appl... | /scale_nucleus-0.15.10b0.tar.gz/scale_nucleus-0.15.10b0/nucleus/metrics/segmentation_to_poly_metrics.py | 0.883588 | 0.441974 | segmentation_to_poly_metrics.py | pypi |
from abc import abstractmethod
from dataclasses import dataclass
from typing import List, Optional, Set, Tuple, Union
from nucleus.annotation import AnnotationList, CategoryAnnotation
from nucleus.metrics.base import Metric, MetricResult, ScalarResult
from nucleus.metrics.filtering import ListOfAndFilters, ListOfOrAnd... | /scale_nucleus-0.15.10b0.tar.gz/scale_nucleus-0.15.10b0/nucleus/metrics/categorization_metrics.py | 0.894732 | 0.633439 | categorization_metrics.py | pypi |
from __future__ import annotations
from dataclasses import dataclass
from typing import Iterable, Protocol
import numpy as np
import numpy.typing as npt
from pyquaternion import Quaternion as PyQuaternion
from scipy.spatial.transform import Rotation as R
@dataclass
class Point3D:
x: float
y: float
z: flo... | /scale_sensor_fusion_io-0.3.2-py3-none-any.whl/scale_sensor_fusion_io/models/Pose.py | 0.972972 | 0.726256 | Pose.py | pypi |
import numpy as np
import pandas as pd
from scipy.spatial.transform import Rotation
from scipy.interpolate import interp1d
from typing import Union
from numpy.typing import ArrayLike
class CuboidPath(pd.DataFrame):
"""CuboidPath class representing a list of cuboids at given timestamps, extending pandas DataFrame... | /scale_sensor_fusion_io-0.3.2-py3-none-any.whl/scale_sensor_fusion_io/models/paths/cuboid_path.py | 0.949236 | 0.756987 | cuboid_path.py | pypi |
from __future__ import annotations
from functools import reduce
from typing import Iterator, Union, Optional
import numpy as np
import numpy.typing as npt
import pandas as pd
from numpy.typing import ArrayLike
from scipy.interpolate import interp1d
from scipy.spatial.transform import Rotation
IDENTITY = (0, 0, 0, 0,... | /scale_sensor_fusion_io-0.3.2-py3-none-any.whl/scale_sensor_fusion_io/models/paths/pose_path.py | 0.977252 | 0.681283 | pose_path.py | pypi |
from dataclasses import dataclass
from typing import List, Literal, Optional, Union
from enum import Enum
import scale_sensor_fusion_io.spec.sfs as SFS
SensorID = SFS.SensorID
AnnotationID = SFS.AnnotationID
PosePath = SFS.PosePath
PointsSensorPoints = SFS.PointsSensorPoints
PointsSensor = SFS.PointsSensor
Lidar... | /scale_sensor_fusion_io-0.3.2-py3-none-any.whl/scale_sensor_fusion_io/spec/v5/types.py | 0.917834 | 0.382545 | types.py | pypi |
from dataclasses import dataclass
from typing import List, Literal, Optional, Union
import numpy as np
import numpy.typing as npt
SensorID = Union[str, int]
AnnotationID = Union[str, int]
# Define PosePath dataclass
@dataclass
class PosePath:
timestamps: List[int]
values: List[List[float]] # x y z qx qy qz... | /scale_sensor_fusion_io-0.3.2-py3-none-any.whl/scale_sensor_fusion_io/spec/sfs/types.py | 0.919661 | 0.507446 | types.py | pypi |
from __future__ import annotations
from dataclasses import dataclass
from typing import Generic, List, Literal, Optional, Sequence, TypeVar, Union
import scale_sensor_fusion_io as sfio
from typing_extensions import TypeAlias
PathField: TypeAlias = Union[int, str]
PathInput: TypeAlias = Union[PathField, List[PathFiel... | /scale_sensor_fusion_io-0.3.2-py3-none-any.whl/scale_sensor_fusion_io/validation/error.py | 0.931275 | 0.324369 | error.py | pypi |
from dataclasses import InitVar
from typing import Type, Any, Optional, Union, Collection, TypeVar, Dict, Callable, Mapping, List, Tuple, get_type_hints
T = TypeVar("T", bound=Any)
def transform_value(
type_hooks: Mapping[Union[Type, object], Callable[[Any], Any]], cast: List[Type], target_type: Type, value: Any... | /scale_sensor_fusion_io-0.3.2-py3-none-any.whl/scale_sensor_fusion_io/validation/dacite_internal/types.py | 0.741861 | 0.268851 | types.py | pypi |
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