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 |
|---|---|---|---|---|---|---|
ARFlow | ARFlow-master/transforms/sep_transforms.py | import numpy as np
import torch
# from scipy.misc import imresize
from skimage.transform import resize as imresize
class ArrayToTensor(object):
"""Converts a numpy.ndarray (H x W x C) to a torch.FloatTensor of shape (C x H x W)."""
def __call__(self, array):
assert (isinstance(array, np.ndarray))
... | 832 | 26.766667 | 91 | py |
ARFlow | ARFlow-master/transforms/ar_transforms/interpolation.py | ## Portions of Code from, copyright 2018 Jochen Gast
from __future__ import absolute_import, division, print_function
import torch
from torch import nn
import torch.nn.functional as tf
def _bchw2bhwc(tensor):
return tensor.transpose(1,2).transpose(2,3)
def _bhwc2bchw(tensor):
return tensor.transpose(2,3).... | 6,104 | 37.15625 | 101 | py |
ARFlow | ARFlow-master/transforms/ar_transforms/sp_transfroms.py | # Part of the code from https://github.com/visinf/irr/blob/master/augmentations.py
import torch
import torch.nn as nn
from transforms.ar_transforms.interpolation import Interp2
from transforms.ar_transforms.interpolation import Meshgrid
import numpy as np
def denormalize_coords(xx, yy, width, height):
""" scale ... | 12,154 | 34.437318 | 89 | py |
ARFlow | ARFlow-master/transforms/ar_transforms/ap_transforms.py | import numpy as np
import torch
from torchvision import transforms as tf
from PIL import ImageFilter
def get_ap_transforms(cfg):
transforms = [ToPILImage()]
if cfg.cj:
transforms.append(ColorJitter(brightness=cfg.cj_bri,
contrast=cfg.cj_con,
... | 2,275 | 30.611111 | 85 | py |
ARFlow | ARFlow-master/transforms/ar_transforms/oc_transforms.py | import numpy as np
import torch
# from skimage.color import rgb2yuv
import cv2
from fast_slic.avx2 import SlicAvx2 as Slic
from skimage.segmentation import slic as sk_slic
def run_slic_pt(img_batch, n_seg=200, compact=10, rd_select=(8, 16), fast=True): # Nx1xHxW
"""
:param img: Nx3xHxW 0~1 float32
:para... | 1,952 | 29.046154 | 91 | py |
ARFlow | ARFlow-master/losses/flow_loss.py | import torch.nn as nn
import torch.nn.functional as F
from .loss_blocks import SSIM, smooth_grad_1st, smooth_grad_2nd, TernaryLoss
from utils.warp_utils import flow_warp
from utils.warp_utils import get_occu_mask_bidirection, get_occu_mask_backward
class unFlowLoss(nn.modules.Module):
def __init__(self, cfg):
... | 4,395 | 37.226087 | 88 | py |
ARFlow | ARFlow-master/losses/get_loss.py | from .flow_loss import unFlowLoss
def get_loss(cfg):
if cfg.type == 'unflow':
loss = unFlowLoss(cfg)
else:
raise NotImplementedError(cfg.type)
return loss
| 184 | 19.555556 | 43 | py |
ARFlow | ARFlow-master/losses/loss_blocks.py | import torch
import torch.nn as nn
import torch.nn.functional as F
# Crecit: https://github.com/simonmeister/UnFlow/blob/master/src/e2eflow/core/losses.py
def TernaryLoss(im, im_warp, max_distance=1):
patch_size = 2 * max_distance + 1
def _rgb_to_grayscale(image):
grayscale = image[:, 0, :, :] * 0.29... | 3,197 | 30.98 | 87 | py |
myriad | myriad-main/setup.py | from setuptools import setup, find_packages
setup(
name='myriad',
packages=find_packages(),
license='Apache 2.0',
author='Nikolaus H. R. Howe, Simon Dufort-Labbé, Nitarshan Rajkumar',
)
| 195 | 20.777778 | 71 | py |
myriad | myriad-main/run.py | # (c) 2021 Nikolaus Howe
import numpy as np
import random
from jax.config import config
from myriad.experiments.e2e_sysid import run_endtoend
from myriad.experiments.mle_sysid import run_mle_sysid
from myriad.experiments.node_e2e_sysid import run_node_endtoend
from myriad.experiments.node_mle_sysid import run_node_ml... | 2,407 | 26.363636 | 83 | py |
myriad | myriad-main/tests/tests.py | # (c) Nikolaus Howe 2021
from scipy.integrate import odeint
import jax.numpy as jnp
import numpy as np
import sys
import unittest
from run import run_trajectory_opt
from myriad.config import IntegrationMethod, NLPSolverType, OptimizerType, QuadratureRule, SystemType
from myriad.custom_types import State, Control, Tim... | 7,521 | 26.654412 | 104 | py |
myriad | myriad-main/tests/system_tests.py | # (c) Nikolaus Howe 2021
import sys
import unittest
from myriad.config import IntegrationMethod, NLPSolverType, OptimizerType, SystemType
from myriad.useful_scripts import run_setup
from run import run_trajectory_opt
hp, cfg = run_setup(sys.argv, gin_path='../myriad/gin-configs/default.gin')
class SystemTests(unitt... | 950 | 26.171429 | 85 | py |
myriad | myriad-main/tests/test_smoke.py | import random
import unittest
import jax
import numpy as np
from myriad.config import Config, SystemType, HParams, OptimizerType
from myriad.trajectory_optimizers import get_optimizer
from myriad.systems import IndirectFHCS
from myriad.plotting import plot_result
# import os
# os.environ['KMP_DUPLICATE_LIB_OK'] = 'T... | 2,495 | 36.253731 | 117 | py |
myriad | myriad-main/myriad/custom_types.py | # (c) Nikolaus Howe 2021
import jax.numpy as jnp
from typing import Callable, Mapping, Optional, Union
Batch = jnp.ndarray
Control = Union[float, jnp.ndarray]
Controls = jnp.ndarray
Cost = float
Dataset = jnp.ndarray
Defect = jnp.ndarray
DParams = Mapping[str, Union[float, jnp.ndarray]]
DState = Union[float, jnp.nda... | 663 | 25.56 | 68 | py |
myriad | myriad-main/myriad/plotting.py | # (c) 2021 Nikolaus Howe
import jax.numpy as jnp
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.offsetbox import AnchoredText
from typing import Dict, Optional, Tuple
from myriad.config import SystemType, IntegrationMethod, OptimizerType, HParams
from myriad.systems import state_... | 8,641 | 32.496124 | 125 | py |
myriad | myriad-main/myriad/probing_numerical_instability.py | # (c) 2021 Nikolaus Howe
import numpy as np
import jax
import jax.numpy as jnp
import matplotlib.pyplot as plt
import pickle as pkl
from jax import lax
from typing import Callable, Tuple
from myriad.custom_types import State, States, Control, Controls, DState
from myriad.utils import integrate, integrate_time_indepen... | 7,453 | 30.451477 | 116 | py |
myriad | myriad-main/myriad/utils.py | # (c) 2021 Nikolaus Howe
from __future__ import annotations
import jax
import jax.numpy as jnp
import numpy as np
import time
import typing
if typing.TYPE_CHECKING:
from myriad.neural_ode.create_node import NeuralODE
from myriad.config import HParams, Config
from jax import jit, lax, vmap
from typing import Call... | 18,600 | 39.088362 | 133 | py |
myriad | myriad-main/myriad/useful_scripts.py | # (c) 2021 Nikolaus Howe
from __future__ import annotations
import jax.numpy as jnp
import numpy as np
import pickle as pkl
import simple_parsing
from jax.flatten_util import ravel_pytree
from jax.config import config
from pathlib import Path
from typing import Tuple
from myriad.config import HParams, Config
from my... | 11,496 | 36.087097 | 118 | py |
myriad | myriad-main/myriad/config.py | # (c) 2021 Nikolaus Howe
from typing import Tuple
import jax
from dataclasses import dataclass
from enum import Enum
from myriad.systems import SystemType
class OptimizerType(Enum):
"""Parser argument. Optimizing strategy used to solve the OCP"""
# _settings_ = NoAlias
COLLOCATION = "COLLOCATION"
SHOOTING ... | 4,564 | 34.115385 | 150 | py |
myriad | myriad-main/myriad/defaults.py | # (c) 2021 Nikolaus Howe
from myriad.systems import SystemType
learning_rates = {
SystemType.PENDULUM: {
'eta_x': 1e-1,
'eta_v': 1e-3
},
SystemType.CANCERTREATMENT: { # works for single shooting, 50 controls
'eta_x': 1e-1,
'eta_v': 1e-3
},
SystemType.CARTPOLE: {
'eta_x': 1e-2,
'eta_... | 1,883 | 19.258065 | 85 | py |
myriad | myriad-main/myriad/study_scripts.py | # (c) 2021 Nikolaus Howe
import jax.numpy as jnp
import matplotlib
import matplotlib.pyplot as plt
import pickle as pkl
from jax.config import config
from pathlib import Path
from myriad.defaults import param_guesses
from myriad.neural_ode.create_node import NeuralODE
from myriad.experiments.mle_sysid import run_mle_... | 7,920 | 32.706383 | 113 | py |
myriad | myriad-main/myriad/__init__.py | """
This library implements in [JAX](https://github.com/google/jax) various real-world environments,
neural ODEs for system identification, and trajectory optimizers for solving the optimal control problem.
"""
# from .config import *
# from .nlp_solvers import *
# from .trajectory_optimizers import *
# from .plotting ... | 1,043 | 40.76 | 105 | py |
myriad | myriad-main/myriad/neural_ode/data_generators.py | # # (c) 2021 Nikolaus Howe
# from __future__ import annotations # for nicer typing
#
# import typing
#
# if typing.TYPE_CHECKING:
# pass
# import jax
# import jax.numpy as jnp
# import numpy as np
# import time
#
# from typing import Optional
#
# from myriad.config import Config, HParams, SamplingApproach
# from myr... | 8,950 | 39.502262 | 124 | py |
myriad | myriad-main/myriad/neural_ode/node_training.py | # (c) Nikolaus Howe 2021
from __future__ import annotations
import haiku as hk
import jax
import jax.numpy as jnp
import optax
import typing
if typing.TYPE_CHECKING:
from myriad.neural_ode.create_node import NeuralODE
from jax.flatten_util import ravel_pytree
from tqdm import trange
from typing import Callable, Op... | 8,523 | 41.40796 | 116 | py |
myriad | myriad-main/myriad/neural_ode/__init__.py | 0 | 0 | 0 | py | |
myriad | myriad-main/myriad/neural_ode/create_node.py | # (c) 2021 Nikolaus Howe
from pathlib import Path
import haiku as hk
import jax
import jax.numpy as jnp
import optax
import pickle as pkl
from dataclasses import dataclass
from jax import config
from typing import Optional
from myriad.config import HParams, Config, SamplingApproach
from myriad.trajectory_optimizers ... | 7,428 | 40.044199 | 115 | py |
myriad | myriad-main/myriad/nlp_solvers/__init__.py | # (c) 2021 Nikolaus Howe
import jax
import jax.numpy as jnp
import time
from cyipopt import minimize_ipopt
from scipy.optimize import minimize
from typing import Dict
from myriad.config import Config, HParams, NLPSolverType
from myriad.defaults import learning_rates
from myriad.utils import get_state_trajectory_and_c... | 3,500 | 34.363636 | 110 | py |
myriad | myriad-main/myriad/nlp_solvers/extra_gradient.py | # (c) 2021 Nikolaus Howe
import jax.numpy as jnp
from jax import jit, grad
from tensorboardX import SummaryWriter # for parameter tuning
writer = SummaryWriter()
def extra_gradient(fun, x0, method, constraints, bounds, jac, options):
del method, jac
print("we're trying exgd with steps:", options['maxiter'])
... | 2,531 | 29.878049 | 106 | py |
myriad | myriad-main/myriad/systems/base.py | # (c) 2021 Nikolaus Howe
from abc import ABC
from dataclasses import dataclass
from typing import Mapping, Optional
import jax.numpy as jnp
from myriad.custom_types import Control, Controls, Cost, DState, Params, State, States
@dataclass
class FiniteHorizonControlSystem(object):
"""
Abstract class describing a ... | 6,308 | 33.47541 | 121 | py |
myriad | myriad-main/myriad/systems/__init__.py | # (c) 2021 Nikolaus Howe
from enum import Enum
from typing import Union
from .base import FiniteHorizonControlSystem, IndirectFHCS
from myriad.systems.classical_control.cartpole import CartPole
from myriad.systems.classical_control.mountain_car import MountainCar
from myriad.systems.classical_control.pendulum import P... | 5,439 | 43.590164 | 104 | py |
myriad | myriad-main/myriad/systems/neural_ode/node_system.py | # (c) 2021 Nikolaus Howe
from __future__ import annotations
import typing
if typing.TYPE_CHECKING:
from myriad.neural_ode.create_node import NeuralODE
import jax.numpy as jnp
from myriad.systems.base import FiniteHorizonControlSystem
from myriad.custom_types import Control, Cost, DState, Params, State, Timestep
... | 1,363 | 30.72093 | 106 | py |
myriad | myriad-main/myriad/systems/neural_ode/__init__.py | 0 | 0 | 0 | py | |
myriad | myriad-main/myriad/systems/miscellaneous/tumour.py | import jax.numpy as jnp
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
from myriad.custom_types import Params
from myriad.systems import FiniteHorizonControlSystem
class Tumour(FiniteHorizonControlSystem):
"""
Tumour anti-angiogenesis model, from [Practical Methods for Optimal Control ... | 4,802 | 35.386364 | 205 | py |
myriad | myriad-main/myriad/systems/miscellaneous/seir.py | import jax.numpy as jnp
from myriad.systems import FiniteHorizonControlSystem
class SEIR(FiniteHorizonControlSystem):
"""
SEIR epidemic model for COVID-19, inspired by [Perkins and Espana, 2020](https://link.springer.com/article/10.1007/s11538-020-00795-y).
This model is an adaptation of SEIR models, specific... | 4,207 | 35.591304 | 137 | py |
myriad | myriad-main/myriad/systems/miscellaneous/rocket_landing.py | # (c) 2021 Nikolaus Howe
import jax
import jax.numpy as jnp
from typing import Optional
from myriad.custom_types import Control, Cost, DState, Params, State, Timestep
from myriad.systems import FiniteHorizonControlSystem
class RocketLanding(FiniteHorizonControlSystem):
"""
Simulate a starship landing! Inspired ... | 4,647 | 36.184 | 154 | py |
myriad | myriad-main/myriad/systems/miscellaneous/__init__.py | 0 | 0 | 0 | py | |
myriad | myriad-main/myriad/systems/miscellaneous/van_der_pol.py | import jax.numpy as jnp
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
from myriad.custom_types import Params
from myriad.systems import FiniteHorizonControlSystem
class VanDerPol(FiniteHorizonControlSystem):
"""
Driven Van der Pol oscillator, from [CasADi](http://casadi.sourceforge.ne... | 2,496 | 29.82716 | 113 | py |
myriad | myriad-main/myriad/systems/classical_control/cartpole.py | # (c) 2021 Nikolaus Howe
import jax.numpy as jnp
from typing import Optional
from myriad.systems.base import FiniteHorizonControlSystem
from myriad.custom_types import Control, Cost, DState, Params, State, Timestep
class CartPole(FiniteHorizonControlSystem):
"""
Cart-pole swing-up, from [(Kelly, 2017)](https://... | 5,799 | 39.277778 | 127 | py |
myriad | myriad-main/myriad/systems/classical_control/mountain_car.py | # (c) 2021 Nikolaus Howe
import jax
import jax.numpy as jnp
from typing import Optional
from myriad.custom_types import Control, Cost, DState, Params, State, Timestep
from myriad.systems.base import FiniteHorizonControlSystem
def hill_function(x: float) -> float:
# return jnp.max(jnp.array([-3 * x - jnp.pi, -1/3 ... | 5,788 | 31.706215 | 175 | py |
myriad | myriad-main/myriad/systems/classical_control/pendulum.py | # (c) 2021 Nikolaus Howe
# inspired by https://github.com/openai/gym/blob/master/gym/envs/classic_control/pendulum.py
# and https://github.com/locuslab/mpc.pytorch/blob/07f43da67581b783f4f230ca97b0efbc421773af/mpc/env_dx/pendulum.py
import jax
import jax.numpy as jnp
from typing import Optional
from myriad.systems.... | 5,848 | 30.446237 | 156 | py |
myriad | myriad-main/myriad/systems/classical_control/__init__.py | 0 | 0 | 0 | py | |
myriad | myriad-main/myriad/systems/lenhart/mould_fungicide.py | from typing import Union, Optional
import gin
import jax.numpy as jnp
import matplotlib.pyplot as plt
import seaborn as sns
from myriad.custom_types import Params
from myriad.systems import IndirectFHCS
@gin.configurable
class MouldFungicide(IndirectFHCS):
"""
Taken from: Optimal Control Applied to Biological... | 3,084 | 37.5625 | 113 | py |
myriad | myriad-main/myriad/systems/lenhart/simple_case.py | from typing import Union, Optional, Dict
import gin
import jax.numpy as jnp
import matplotlib.pyplot as plt
import seaborn as sns
from myriad.systems import IndirectFHCS
@gin.configurable
class SimpleCase(IndirectFHCS):
"""
Taken from: Optimal Control Applied to Biological Models, Lenhart & Workman (Chapter 5... | 2,217 | 34.206349 | 112 | py |
myriad | myriad-main/myriad/systems/lenhart/cancer_treatment.py | import gin
import jax.numpy as jnp
from typing import Optional, Union
from myriad.custom_types import Params
from myriad.systems import IndirectFHCS
@gin.configurable
class CancerTreatment(IndirectFHCS):
"""
Taken from: Optimal Control Applied to Biological Models, Lenhart & Workman (Chapter 10, Lab 5)
... | 4,085 | 43.413043 | 120 | py |
myriad | myriad-main/myriad/systems/lenhart/simple_case_with_bounds.py | from typing import Union, Optional
import gin
import jax.numpy as jnp
import matplotlib.pyplot as plt
import seaborn as sns
from myriad.systems import IndirectFHCS
@gin.configurable
class SimpleCaseWithBounds(IndirectFHCS):
"""
Taken from: Optimal Control Applied to Biological Models, Lenhart & Workman (Chapt... | 2,409 | 35.515152 | 112 | py |
myriad | myriad-main/myriad/systems/lenhart/predator_prey.py | import gin
import jax.numpy as jnp
from typing import Union, Optional
from myriad.custom_types import Params
from myriad.systems import IndirectFHCS
@gin.configurable
class PredatorPrey(IndirectFHCS):
# TODO: there is an error when trying to plot with PredatorPrey
"""
Taken from: Optimal Control Applied to ... | 5,190 | 36.615942 | 132 | py |
myriad | myriad-main/myriad/systems/lenhart/bacteria.py | from typing import Union, Optional
import gin
import jax.numpy as jnp
from myriad.custom_types import Params
from myriad.systems import IndirectFHCS
@gin.configurable
class Bacteria(IndirectFHCS):
"""Taken from: Optimal Control Applied to Biological Models, Lenhart & Workman (Chapter 7, Lab 3)
This environm... | 4,287 | 43.666667 | 120 | py |
myriad | myriad-main/myriad/systems/lenhart/harvest.py | import gin
import jax.numpy as jnp
from typing import Union, Optional
from myriad.systems import IndirectFHCS
@gin.configurable
class Harvest(IndirectFHCS):
"""
Taken from: Optimal Control Applied to Biological Models, Lenhart & Workman (Chapter 11, Lab 6)
The model was was adapted from Wayne M. Getz. Optimal... | 2,859 | 38.722222 | 112 | py |
myriad | myriad-main/myriad/systems/lenhart/bear_populations.py | import gin
import jax.numpy as jnp
from typing import Union, Optional
from myriad.custom_types import Params
from myriad.systems import IndirectFHCS
@gin.configurable
class BearPopulations(IndirectFHCS):
"""
Taken from: Optimal Control Applied to Biological Models, Lenhart & Workman (Chapter 15, Lab 9)
... | 6,332 | 42.675862 | 178 | py |
myriad | myriad-main/myriad/systems/lenhart/invasive_plant.py | import gin
import jax.numpy as jnp
import matplotlib.pyplot as plt
from typing import Union, Optional
from myriad.systems import IndirectFHCS
@gin.configurable
class InvasivePlant(IndirectFHCS):
"""
Taken from: Optimal Control Applied to Biological Models, Lenhart & Workman (Chapter 24, Lab 14)
This probl... | 5,532 | 39.985185 | 151 | py |
myriad | myriad-main/myriad/systems/lenhart/epidemic_seirn.py | import gin
import jax.numpy as jnp
from typing import Union, Optional
from myriad.systems import IndirectFHCS
@gin.configurable
class EpidemicSEIRN(IndirectFHCS): # TODO : Add R calculation at the end
"""
Taken from: Optimal Control Applied to Biological Models, Lenhart & Workman (Chapter 13, Lab 7)
... | 5,092 | 44.473214 | 149 | py |
myriad | myriad-main/myriad/systems/lenhart/hiv_treatment.py | import gin
import jax.numpy as jnp
from typing import Union, Optional
from myriad.custom_types import Params
from myriad.systems import IndirectFHCS
@gin.configurable
class HIVTreatment(IndirectFHCS):
"""
Taken from: Optimal Control Applied to Biological Models, Lenhart & Workman (Chapter 14, Lab 8)
Model... | 5,535 | 40.939394 | 163 | py |
myriad | myriad-main/myriad/systems/lenhart/__init__.py | 0 | 0 | 0 | py | |
myriad | myriad-main/myriad/systems/lenhart/bioreactor.py | import gin
import jax.numpy as jnp
from typing import Union, Optional
from myriad.custom_types import Params
from myriad.systems import IndirectFHCS
@gin.configurable
class Bioreactor(IndirectFHCS): # TODO: Add resolution for z state after optimization
"""
Taken from: Optimal Control Applied to Biological ... | 4,278 | 40.95098 | 133 | py |
myriad | myriad-main/myriad/systems/lenhart/timber_harvest.py | from typing import Union, Optional
import gin
import jax.numpy as jnp
import matplotlib.pyplot as plt
import seaborn as sns
from myriad.custom_types import Params
from myriad.systems import IndirectFHCS
@gin.configurable
class TimberHarvest(IndirectFHCS):
"""
Taken from: Optimal Control Applied to Biological ... | 4,409 | 41.403846 | 118 | py |
myriad | myriad-main/myriad/systems/lenhart/glucose.py | import gin
import jax.numpy as jnp
from typing import Union, Optional
from myriad.custom_types import Params
from myriad.systems import IndirectFHCS
@gin.configurable
class Glucose(IndirectFHCS):
"""
Taken from: Optimal Control Applied to Biological Models, Lenhart & Workman (Chapter 16, Lab 10)
Model is ... | 4,719 | 36.165354 | 121 | py |
myriad | myriad-main/myriad/trajectory_optimizers/forward_backward_sweep.py | # (c) 2021 Nikolaus Howe
import jax.numpy as jnp
from jax.flatten_util import ravel_pytree
# from jax.ops import index_update
# from ipopt import minimize_ipopt
from scipy.optimize import minimize
from dataclasses import dataclass
from typing import Callable, Dict, Tuple, Union
from myriad.config import Config, HPara... | 6,006 | 36.779874 | 117 | py |
myriad | myriad-main/myriad/trajectory_optimizers/base.py | # (c) 2021 Nikolaus Howe
from __future__ import annotations
import typing
if typing.TYPE_CHECKING:
from myriad.config import Config, HParams
# from myriad.config import
import jax
import jax.numpy as jnp
import numpy as np
from jax import vmap
from jax.flatten_util import ravel_pytree
# from ipopt import minimize... | 5,442 | 37.330986 | 149 | py |
myriad | myriad-main/myriad/trajectory_optimizers/__init__.py | # (c) 2021 Nikolaus Howe
from typing import Union
from myriad.trajectory_optimizers.base import TrajectoryOptimizer, IndirectMethodOptimizer
from myriad.trajectory_optimizers.collocation.trapezoidal import TrapezoidalCollocationOptimizer
from myriad.trajectory_optimizers.collocation.hermite_simpson import HermiteSimps... | 1,523 | 46.625 | 103 | py |
myriad | myriad-main/myriad/trajectory_optimizers/shooting.py | # (c) 2021 Nikolaus Howe
import jax
import jax.numpy as jnp
import numpy as np
from jax.flatten_util import ravel_pytree
from myriad.config import Config, HParams, IntegrationMethod
from myriad.custom_types import Control, Params, Timestep
from myriad.systems import FiniteHorizonControlSystem
from myriad.utils import... | 11,796 | 41.283154 | 120 | py |
myriad | myriad-main/myriad/trajectory_optimizers/collocation/hermite_simpson.py | # (c) 2021 Nikolaus Howe
import jax.numpy as jnp
import numpy as np
from jax import vmap
from jax.flatten_util import ravel_pytree
from typing import Tuple
from myriad.config import Config, HParams
from myriad.custom_types import Control, Controls, Cost, DState, DStates, Params, State, States, Timestep
from myriad.sy... | 15,045 | 41.744318 | 118 | py |
myriad | myriad-main/myriad/trajectory_optimizers/collocation/__init__.py | 0 | 0 | 0 | py | |
myriad | myriad-main/myriad/trajectory_optimizers/collocation/trapezoidal.py | # (c) 2021 Nikolaus Howe
import jax.numpy as jnp
import numpy as np
from jax import vmap
from jax.flatten_util import ravel_pytree
from myriad.config import Config, HParams
from myriad.custom_types import Control, Cost, DState, Params, State, Timestep, DStates
from myriad.trajectory_optimizers.base import TrajectoryO... | 8,760 | 40.719048 | 110 | py |
myriad | myriad-main/myriad/experiments/e2e_sysid.py | # (c) 2021 Nikolaus Howe
import jax
import jax.numpy as jnp
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import optax
import pickle as pkl
from pathlib import Path
from typing import Tuple
from myriad.config import HParams, Config, SystemType, NLPSolverType
from myriad.custom_types import Para... | 17,345 | 37.892377 | 116 | py |
myriad | myriad-main/myriad/experiments/node_mle_sysid.py | # (c) Nikolaus Howe 2021
from __future__ import annotations
import csv
import jax
import jax.numpy as jnp
import numpy as np
import pickle as pkl
from pathlib import Path
from myriad.config import Config, HParams, IntegrationMethod
from myriad.neural_ode.create_node import NeuralODE
from myriad.neural_ode.node_train... | 8,692 | 42.034653 | 115 | py |
myriad | myriad-main/myriad/experiments/__init__.py | 0 | 0 | 0 | py | |
myriad | myriad-main/myriad/experiments/mle_sysid.py | # (c) 2021 Nikolaus Howe
from __future__ import annotations
import csv
import jax
import jax.numpy as jnp
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import optax
import pickle as pkl
from pathlib import Path
from typing import Dict, Tuple, Union
from myriad.config import Config, HParams, In... | 12,626 | 36.247788 | 119 | py |
myriad | myriad-main/myriad/experiments/node_e2e_sysid.py | # (c) 2021 Nikolaus Howe
import jax
import jax.numpy as jnp
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import optax
import pickle as pkl
from pathlib import Path
from typing import Tuple
from myriad.config import HParams, Config, NLPSolverType
from myriad.defaults import learning_rates, para... | 18,018 | 38.342795 | 118 | py |
plotspec | plotspec-master/h2.py | from pdb import set_trace as stop #Use stop() for debugging
#from scipy import *
from pylab import *
from matplotlib.backends.backend_pdf import PdfPages #For outputting a pdf with multiple pages (or one page)
from mpl_toolkits.mplot3d import Axes3D #For making 3D plots
from astropy.modeling import models, fitting #Im... | 160,758 | 64.243101 | 323 | py |
plotspec | plotspec-master/run_plotspec_test.py | #Test script for plotspec.py library to demonstrate what library can do
from plotspec import * #Import plotspec library
import h2 #Import H2 library
#~~~~~~~~~~~~~~~~~~~~SCIENCE TARGET INFORMATION~~~~~~~~~~~~~~~~~~~~~~~~~~~~
save.name('NGC 7027')
date = 20141023 #Date of observation
frameno = 51 #Frame number for sci... | 3,188 | 78.725 | 348 | py |
plotspec | plotspec-master/plotspec_demo.py | #2D demo - IGRINS Conference 2015 in Korea
#by Kyle Kaplan
#~~~~~~~~~~~~~~~~~~~~IMPORT LIBRARIES~~~~~~~~~~~~~~~~~~~~~~~~~~~
from plotspec import * #Import plotspec library
import h2 #Import H2 library
#~~~~~~~~~~~~~~~~~~~~SCIENCE TARGET INFORMATION~~~~~~~~~~~~~~~~~~~~~~~~~~~~
##M 1-11
save.name('Demo')
date = 20141204 ... | 3,923 | 73.037736 | 240 | py |
plotspec | plotspec-master/datacube_demo.py | #Test demo script for make_datacube.py library
from scipy import *
import make_datacube as cubelib #Import library to make datacubes
workdir = '/Volumes/IGRINS_Data/datacube_demo/' #Set to where you want to save resulting fits files
vrange = [-10.0,10.0] #Velocity range
#Demo of saving files from datacube
cube = cub... | 812 | 61.538462 | 158 | py |
plotspec | plotspec-master/plotspec.py |
#This library will eventually be the ultimate IGRINS emission line viewability/analysis code
#
#start as test_new_plotspec.py
#Set matplotlib backend to get around freezing plot windows, first try the one TkAgg
import matplotlib
#Import libraries
import os #Import OS library for checking and creating directories
i... | 227,893 | 69.446368 | 314 | py |
plotspec | plotspec-master/ds9.py | #Python library for accessing DS9 and XPA.
#Written by Kyle Kaplan March 2014.
import pyds9
#import subprocess
#from subprocess import call, PIPE #Allow python to access command line
#from subprocess import check_output #Allow python to access command line and return result to a variable
import time #To put in delays
... | 3,086 | 33.685393 | 139 | py |
plotspec | plotspec-master/make_datacube.py | #Library for making and processing the IGRINS datacube
from pylab import *
from scipy.ndimage import zoom, binary_closing #For resizing images
from astropy.io import fits, ascii #Use astropy for processing fits files, ASCII text files
from astropy.convolution import interpolate_replace_nans
#from astropy.convolution im... | 34,400 | 80.907143 | 372 | py |
plotspec | plotspec-master/line_lists/make_OH_line_list.py | #simple script for making a plotspec.py compatible OH line list based on the OH line list from http://www.gemini.edu/sciops/instruments/nir/wavecal/index.html
from pylab import *
line_data = loadtxt('OH_raw_rousselot_2000.dat') #Read in data from original line list
bright_lines = line_data[:,1] > 1e-1 #Find only brigh... | 680 | 67.1 | 158 | py |
SkeletonGCL | SkeletonGCL-main/main.py | #!/usr/bin/env python
from __future__ import print_function
import argparse
import inspect
import os
import pickle
import random
import shutil
import sys
import time
from collections import OrderedDict
import traceback
from sklearn.metrics import confusion_matrix
import csv
import numpy as np
import glob
# torch
impo... | 23,323 | 38.2 | 180 | py |
SkeletonGCL | SkeletonGCL-main/torchlight/setup.py | from setuptools import find_packages, setup
setup(
name='torchlight',
version='1.0',
description='A mini framework for pytorch',
packages=find_packages(),
install_requires=[])
| 197 | 21 | 47 | py |
SkeletonGCL | SkeletonGCL-main/torchlight/torchlight/util.py | #!/usr/bin/env python
import argparse
import os
import sys
import traceback
import time
import pickle
from collections import OrderedDict
import yaml
import h5py
import numpy as np
import torch
import torch.nn as nn
import torch.optim as optim
from torch.autograd import Variable
# from torchpack.runner.hooks import Pav... | 6,649 | 32.756345 | 117 | py |
SkeletonGCL | SkeletonGCL-main/torchlight/torchlight/__init__.py | from .util import IO
from .util import str2bool
from .util import str2dict
from .util import DictAction
from .util import import_class
from .gpu import visible_gpu
from .gpu import occupy_gpu
from .gpu import ngpu
| 214 | 22.888889 | 30 | py |
SkeletonGCL | SkeletonGCL-main/torchlight/torchlight/gpu.py | import os
import torch
def visible_gpu(gpus):
"""
set visible gpu.
can be a single id, or a list
return a list of new gpus ids
"""
gpus = [gpus] if isinstance(gpus, int) else list(gpus)
os.environ['CUDA_VISIBLE_DEVICES'] = ','.join(list(map(str, gpus)))
return list(range(... | 750 | 19.861111 | 71 | py |
SkeletonGCL | SkeletonGCL-main/graph/ntu_rgb_d.py | import sys
import numpy as np
sys.path.extend(['../'])
from graph import tools
num_node = 25
self_link = [(i, i) for i in range(num_node)]
inward_ori_index = [(1, 2), (2, 21), (3, 21), (4, 3), (5, 21), (6, 5), (7, 6),
(8, 7), (9, 21), (10, 9), (11, 10), (12, 11), (13, 1),
(14, ... | 1,146 | 32.735294 | 78 | py |
SkeletonGCL | SkeletonGCL-main/graph/ucla.py | import sys
import numpy as np
sys.path.extend(['../'])
from graph import tools
num_node = 20
self_link = [(i, i) for i in range(num_node)]
inward_ori_index = [(1, 2), (2, 3), (4, 3), (5, 3), (6, 5), (7, 6),
(8, 7), (9, 3), (10, 9), (11, 10), (12, 11), (13, 1),
(14, 13), (15, 14... | 1,105 | 30.6 | 78 | py |
SkeletonGCL | SkeletonGCL-main/graph/tools.py | import numpy as np
def get_sgp_mat(num_in, num_out, link):
A = np.zeros((num_in, num_out))
for i, j in link:
A[i, j] = 1
A_norm = A / np.sum(A, axis=0, keepdims=True)
return A_norm
def edge2mat(link, num_node):
A = np.zeros((num_node, num_node))
for i, j in link:
A[j, i] = 1
... | 2,193 | 26.425 | 71 | py |
SkeletonGCL | SkeletonGCL-main/graph/__init__.py | from . import tools
from . import ntu_rgb_d
from . import ucla
| 64 | 12 | 23 | py |
SkeletonGCL | SkeletonGCL-main/model/agcn.py | import math
import numpy as np
import torch
import torch.nn as nn
from torch.autograd import Variable
def import_class(name):
components = name.split('.')
mod = __import__(components[0])
for comp in components[1:]:
mod = getattr(mod, comp)
return mod
def conv_branch_init(conv, branches):
... | 6,153 | 32.086022 | 138 | py |
SkeletonGCL | SkeletonGCL-main/model/loss.py | from importlib_metadata import requires
import torch
import torch.nn as nn
from torch import einsum, positive
import math
import random
class InfoNCEGraph(nn.Module):
def __init__(self, in_channels=128, out_channels=256, mem_size=512, positive_num=128, negative_num=512, T=0.8, class_num=60, label_all=[]):
... | 3,455 | 45.702703 | 143 | py |
SkeletonGCL | SkeletonGCL-main/model/__init__.py | 0 | 0 | 0 | py | |
SkeletonGCL | SkeletonGCL-main/model/baseline.py | import math
import numpy as np
import torch
import torch.nn as nn
from torch.autograd import Variable
def import_class(name):
components = name.split('.')
mod = __import__(components[0])
for comp in components[1:]:
mod = getattr(mod, comp)
return mod
def conv_branch_init(conv, branches):
... | 6,316 | 31.06599 | 110 | py |
SkeletonGCL | SkeletonGCL-main/model/ctrgcn.py | import math
import pdb
import numpy as np
import torch
import torch.nn as nn
from torch.autograd import Variable
def import_class(name):
components = name.split('.')
mod = __import__(components[0])
for comp in components[1:]:
mod = getattr(mod, comp)
return mod
def conv_branch_init(conv, bra... | 13,345 | 35.664835 | 132 | py |
SkeletonGCL | SkeletonGCL-main/feeders/feeder_ucla.py | import numpy as np
import pickle
import json
import random
import math
from torch.utils.data import Dataset
class Feeder(Dataset):
def __init__(self, data_path, label_path, repeat=1, random_choose=False, random_shift=False, random_move=False,
window_size=-1, normalization=False, debug=False, use_... | 94,902 | 603.477707 | 61,388 | py |
SkeletonGCL | SkeletonGCL-main/feeders/tools.py | import random
import matplotlib.pyplot as plt
import numpy as np
import pdb
import torch
import torch.nn.functional as F
def valid_crop_resize(data_numpy,valid_frame_num,p_interval,window):
# input: C,T,V,M
C, T, V, M = data_numpy.shape
begin = 0
end = valid_frame_num
valid_size = end - begin
... | 8,189 | 33.851064 | 150 | py |
SkeletonGCL | SkeletonGCL-main/feeders/bone_pairs.py | ntu_pairs = (
(1, 2), (2, 21), (3, 21), (4, 3), (5, 21), (6, 5),
(7, 6), (8, 7), (9, 21), (10, 9), (11, 10), (12, 11),
(13, 1), (14, 13), (15, 14), (16, 15), (17, 1), (18, 17),
(19, 18), (20, 19), (22, 23), (21, 21), (23, 8), (24, 25),(25, 12)
)
| 262 | 36.571429 | 70 | py |
SkeletonGCL | SkeletonGCL-main/feeders/feeder_ntu.py | import numpy as np
import torch
from torch.utils.data import Dataset
from feeders import tools
class Feeder(Dataset):
def __init__(self, data_path, label_path=None, p_interval=1, split='train', random_choose=False, random_shift=False,
random_move=False, random_rot=False, window_size=-1, normalizat... | 5,311 | 41.496 | 120 | py |
SkeletonGCL | SkeletonGCL-main/feeders/__init__.py | from . import tools
from . import feeder_ucla
from . import feeder_ntu | 70 | 22.666667 | 25 | py |
covid19model | covid19model-master/Python/src/dataset.py | import yaml
import pandas as pd
import numpy as np
from src.util import poly, dt_to_dec
from scipy.stats import gamma as gamma_scipy
from numpy.random import gamma as gamma_np
from statsmodels.distributions.empirical_distribution import ECDF
class HierarchicalDataset:
"""Base Dataset class containing attributes r... | 9,851 | 38.408 | 128 | py |
covid19model | covid19model-master/Python/src/util.py | import numpy as np
from datetime import datetime
def poly(x, p):
"""
Thanks to https://stackoverflow.com/questions/41317127/python-equivalent-to-r-poly-function
"""
x = np.array(x)
X = np.transpose(np.vstack((x**k for k in range(p+1))))
return np.linalg.qr(X)[0][:,1:]
def dt_to_dec(dt):
""... | 726 | 37.263158 | 119 | py |
STDEN | STDEN-main/stden_train.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import argparse
import yaml
from lib.utils import load_graph_data
from model.stden_supervisor import STDENSupervisor
import numpy as np
import torch
def main(args):
with open(args.config_filename) as f... | 1,156 | 29.447368 | 108 | py |
STDEN | STDEN-main/stden_eval.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import argparse
import yaml
from lib.utils import load_graph_data
from model.stden_supervisor import STDENSupervisor
import numpy as np
import torch
def main(args):
with open(args.config_filename) as f... | 1,577 | 34.863636 | 108 | py |
STDEN | STDEN-main/model/diffeq_solver.py | import torch
import torch.nn as nn
import time
from torchdiffeq import odeint
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
class DiffeqSolver(nn.Module):
def __init__(self, odefunc, method, latent_dim,
odeint_rtol = 1e-4, odeint_atol = 1e-5):
nn.Module.__init__(self... | 1,877 | 37.326531 | 119 | py |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.