prompt stringlengths 19 879k | completion stringlengths 3 53.8k | api stringlengths 8 59 |
|---|---|---|
# Copyright 2019 Image Analysis Lab, German Center for Neurodegenerative Diseases (DZNE), Bonn
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2... | np.amin(ev2) | numpy.amin |
import numpy as np
from prlqr.systems.dynamical_system import DiscreteTimeDynamicalSystem, StateFeedbackLaw, NormalRandomControlLaw
from prlqr.analysis.stability_analysis import check_stability
class LinearSystem(DiscreteTimeDynamicalSystem):
def __init__(self, A, B, controller, settings):
self.A = A
... | np.linalg.pinv(X0) | numpy.linalg.pinv |
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.distributions import Categorical
from torchlib.common import FloatTensor
from torchlib.dataset.utils import create_data_loader
from torchlib.generative_model.made import MADE
class WarmUpModel(nn.Module):
def __init__... | np.concatenate(x2_temp, axis=0) | numpy.concatenate |
from hashlib import new
import numpy as np
import random
import numba as nb
import matplotlib.pyplot as plt
from numpy.core.defchararray import count
from numpy.matrixlib import defmatrix
# from numpy.testing._private.utils import rand
from agent import *
from grid import *
import time
from neighbor import neighbor
imp... | np.max(self.income_list) | numpy.max |
import numpy as np
import math
import time
import json
import os
from sklearn.neural_network import MLPClassifier
import controller as c
import utils as u
class Neuro_controller(c.Controller):
def __init__(self, config):
super(Neuro_controller, self).__init__("NEURO", config)
self.n_sonar = 0
... | np.asarray(weights[:cutoff[i]]) | numpy.asarray |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
The Phantom class is instantiated with a ground-truth phantom and corresponding material properties data. The get_projections method simulates data acquisition and returns radiographs for the specified theta values.
"""
import sys
import os
import numpy as np
impo... | np.asarray(df[3]) | numpy.asarray |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Oct 19 11:11:49 2017
@author: robertmarsland
"""
from __future__ import division
import numpy as np
import pandas as pd
from numpy.random import dirichlet
import numbers
#DEFAULT PARAMETERS FOR CONSUMER AND METABOLIC MATRICES, AND INITIAL ... | np.random.gamma(kc,scale=thetac,size=(assumptions['Sgen'],M)) | numpy.random.gamma |
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