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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sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/__init__.py | """Public-facing objects."""
from . import estimation, utilities, grids, interpolate, misc, hetblocks
from .blocks.simple_block import simple
from .blocks.het_block import het
from .blocks.solved_block import solved
from .blocks.combined_block import combine, create_model
from .blocks.support.simple_displacement impo... | 2,209 | 45.041667 | 115 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/interpolate.py | from .utilities.interpolate import *
| 37 | 18 | 36 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/classes/steady_state_dict.py | from copy import deepcopy
from .result_dict import ResultDict
from ..utilities.misc import dict_diff
from ..utilities.ordered_set import OrderedSet
from ..utilities.bijection import Bijection
import numpy as np
from numbers import Real
from typing import Any, Dict, Union
Array = Any
class SteadyStateDict(ResultDict... | 626 | 27.5 | 98 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/classes/jacobian_dict.py | import copy
import warnings
import numpy as np
from ..utilities.misc import factor, factored_solve
from ..utilities.ordered_set import OrderedSet
from ..utilities.bijection import Bijection
from .impulse_dict import ImpulseDict
from .sparse_jacobians import IdentityMatrix, SimpleSparse, make_matrix
from typing import ... | 13,815 | 38.25 | 125 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/classes/result_dict.py | import copy
from ..utilities.bijection import Bijection
class ResultDict:
def __init__(self, data, internals=None):
if isinstance(data, ResultDict):
if internals is not None:
raise ValueError(f'Supplying {type(self).__name__} and also internals to constructor not allowed')
... | 2,557 | 31.379747 | 132 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/classes/sparse_jacobians.py | import numpy as np
from numba import njit
import copy
class IdentityMatrix:
"""Simple identity matrix class, cheaper than using actual np.eye(T) matrix,
use to initialize Jacobian of a variable wrt itself"""
__array_priority__ = 10_000
def sparse(self):
"""Equivalent SimpleSparse representatio... | 10,126 | 34.041522 | 106 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/classes/__init__.py | from .steady_state_dict import SteadyStateDict, UserProvidedSS
from .impulse_dict import ImpulseDict
from .jacobian_dict import JacobianDict, FactoredJacobianDict
from .sparse_jacobians import IdentityMatrix, SimpleSparse
| 222 | 43.6 | 62 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/classes/impulse_dict.py | """ImpulseDict class for manipulating impulse responses."""
import numpy as np
from .result_dict import ResultDict
from ..utilities.ordered_set import OrderedSet
from ..utilities.bijection import Bijection
from .steady_state_dict import SteadyStateDict
class ImpulseDict(ResultDict):
def __init__(self, data, int... | 4,427 | 37.172414 | 169 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/examples/krusell_smith.py | from sequence_jacobian import grids, simple, create_model, hetblocks
hh = hetblocks.hh_sim.hh
'''Part 1: Blocks'''
@simple
def firm(K, L, Z, alpha, delta):
r = alpha * Z * (K(-1) / L) ** (alpha-1) - delta
w = (1 - alpha) * Z * (K(-1) / L) ** alpha
Y = Z * K(-1) ** alpha * L ** (1 - alpha)
return r, w... | 3,386 | 32.205882 | 107 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/examples/hank.py | import numpy as np
from sequence_jacobian import grids, simple, create_model, hetblocks
hh = hetblocks.hh_labor.hh
'''Part 1: Blocks'''
@simple
def firm(Y, w, Z, pi, mu, kappa):
L = Y / Z
Div = Y - w * L - mu/(mu-1)/(2*kappa) * (1+pi).apply(np.log)**2 * Y
return L, Div
@simple
def monetary(pi, rstar,... | 2,880 | 26.179245 | 95 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/examples/rbc.py | from sequence_jacobian import simple, create_model
'''Part 1: Blocks'''
@simple
def firm(K, L, Z, alpha, delta):
r = alpha * Z * (K(-1) / L) ** (alpha-1) - delta
w = (1 - alpha) * Z * (K(-1) / L) ** alpha
Y = Z * K(-1) ** alpha * L ** (1 - alpha)
return r, w, Y
@simple
def household(K, L, w, eis, f... | 1,345 | 27.041667 | 90 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/examples/__init__.py | """Example models""" | 20 | 20 | 20 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/examples/two_asset.py | import numpy as np
from sequence_jacobian import simple, solved, combine, create_model, grids, hetblocks
hh = hetblocks.hh_twoasset.hh
'''Part 1: Blocks'''
@simple
def pricing(pi, mc, r, Y, kappap, mup):
nkpc = kappap * (mc - 1 / mup) + Y(+1) / Y * (1 + pi(+1)).apply(np.log) \
/ (1 + r(+1)) - (1 + pi... | 5,688 | 29.751351 | 111 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/hetblocks/hh_twoasset.py | import numpy as np
from numba import guvectorize
from ..blocks.het_block import het
from .. import interpolate
def hh_init(b_grid, a_grid, z_grid, eis):
Va = (0.6 + 1.1 * b_grid[:, np.newaxis] + a_grid) ** (-1 / eis) * np.ones((z_grid.shape[0], 1, 1))
Vb = (0.5 + b_grid[:, np.newaxis] + 1.2 * a_grid) ** (-1 ... | 7,161 | 38.351648 | 102 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/hetblocks/hh_labor.py | '''Standard Incomplete Market model with Endogenous Labor Supply'''
import numpy as np
from numba import vectorize, njit
from ..blocks.het_block import het
from .. import interpolate
def hh_init(a_grid, we, r, eis, T):
fininc = (1 + r) * a_grid + T[:, np.newaxis] - a_grid[0]
coh = (1 + r) * a_grid[np.newaxi... | 2,678 | 30.151163 | 109 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/hetblocks/hh_sim.py | '''Standard Incomplete Market model'''
import numpy as np
from ..blocks.het_block import het
from .. import interpolate, misc, grids
'''Core HetBlock'''
def hh_init(a_grid, y, r, eis):
coh = (1 + r) * a_grid[np.newaxis, :] + y[:, np.newaxis]
Va = (1 + r) * (0.1 * coh) ** (-1 / eis)
return Va
@het(exog... | 1,283 | 26.319149 | 90 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/hetblocks/__init__.py | '''Heterogeneous agent blocks'''
from . import hh_labor, hh_sim, hh_twoasset
| 77 | 25 | 43 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/utilities/discretize.py | """Grids and Markov chains"""
import numpy as np
from scipy.stats import norm
def asset_grid(amin, amax, n):
# find maximum ubar of uniform grid corresponding to desired maximum amax of asset grid
ubar = np.log(1 + np.log(1 + amax - amin))
# make uniform grid
u_grid = np.linspace(0, ubar, n)
... | 5,371 | 32.575 | 245 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/utilities/differentiate.py | """Numerical differentiation"""
from .misc import make_tuple
def numerical_diff(func, ssinputs_dict, shock_dict, h=1E-4, y_ss_list=None):
"""Differentiate function numerically via forward difference, i.e. calculate
f'(xss)*shock = (f(xss + h*shock) - f(xss))/h
for small h. (Variable names inspired by a... | 2,191 | 37.45614 | 115 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/utilities/optimized_routines.py | """Njitted routines to speed up some steps in backward iteration or aggregation"""
import numpy as np
from numba import njit
@njit
def setmin(x, xmin):
"""Set 2-dimensional array x where each row is ascending equal to equal to max(x, xmin)."""
ni, nj = x.shape
for i in range(ni):
for j in range(n... | 1,188 | 26.022727 | 104 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/utilities/bijection.py | from .ordered_set import OrderedSet
class Bijection:
def __init__(self, map):
# identity always implicit, remove if there explicitly
self.map = {k: v for k, v in map.items() if k != v}
invmap = {}
for k, v in map.items():
if v in invmap:
raise ValueError(... | 2,910 | 32.45977 | 86 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/utilities/ordered_set.py | from typing import Iterable
class OrderedSet:
"""Ordered set implemented as dict (where key insertion order is preserved) mapping all to None.
Operations on multiple ordered sets (e.g. union) order all members of first argument first, then
second argument. If a member is in both, order is as early as ... | 3,740 | 22.677215 | 100 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/utilities/misc.py | """Assorted other utilities"""
import numpy as np
import scipy.linalg
from numba import njit, guvectorize
def make_tuple(x):
"""If not tuple or list, make into tuple with one element.
Wrapping with this allows user to write, e.g.:
"return r" rather than "return (r,)"
"policy='a'" rather than "policy... | 5,204 | 27.135135 | 170 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/utilities/graph.py | """Topological sort and related code"""
from .ordered_set import OrderedSet
from .bijection import Bijection
class DAG:
"""Represents "blocks" that each have inputs and outputs, where output-input relationships between
blocks form a DAG. Fundamental DAG object intended to underlie CombinedBlock and CombinedExt... | 7,229 | 36.46114 | 118 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/utilities/multidim.py | import numpy as np
def multiply_ith_dimension(Pi, i, X):
"""If Pi is a matrix, multiply Pi times the ith dimension of X and return"""
X = X.swapaxes(0, i)
shape = X.shape
X = X.reshape((shape[0], -1))
# iterate forward using Pi
X = Pi @ X
# reverse steps
X = X.reshape((Pi.shape[0], *... | 1,039 | 24.365854 | 80 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/utilities/function.py | import re
import inspect
import numpy as np
from .ordered_set import OrderedSet
from . import graph
# TODO: fix this, have it twice (main version in misc) due to circular import problem
# let's make everything point to here for input_list, etc. so that this is unnecessary
def make_tuple(x):
"""If not tuple or lis... | 10,065 | 36.007353 | 150 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/utilities/__init__.py | """Utilities relating to: interpolation, forward step/transition, grids and Markov chains, solvers, sorting, etc."""
from . import (bijection, differentiate, discretize, drawdag, function, graph, interpolate,
misc, multidim, optimized_routines, ordered_set, solvers)
| 284 | 56 | 116 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/utilities/drawdag.py | import warnings
from sequence_jacobian.blocks.solved_block import SolvedBlock
from sequence_jacobian.blocks.het_block import HetBlock
"""
Adrien's DAG Graph routine, updated for SSJ v1.0
Requires installing graphviz package and executables
https://www.graphviz.org/
On a mac this can be done as follows:
1) Download m... | 4,348 | 41.637255 | 137 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/utilities/solvers.py | """Simple nonlinear solvers"""
import numpy as np
import warnings
def newton_solver(f, x0, y0=None, tol=1E-9, maxcount=100, backtrack_c=0.5, verbose=True):
"""Simple line search solver for root x satisfying f(x)=0 using Newton direction.
Backtracks if input invalid or improvement is not at least half the pr... | 5,160 | 33.871622 | 104 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/utilities/interpolate.py | """Efficient linear interpolation exploiting monotonicity.
Interpolates increasing query points xq against increasing data points x.
- interpolate_y: (x, xq, y) -> yq
get interpolated values of yq at xq
- interpolate_coord: (x, xq) -> (xqi, xqpi)
get representation xqi, xqpi of xq interpo... | 6,714 | 28.069264 | 99 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/blocks/combined_block.py | """CombinedBlock class and the combine function to generate it"""
from .block import Block
from .auxiliary_blocks.jacobiandict_block import JacobianDictBlock
from .support.parent import Parent
from ..classes import ImpulseDict, JacobianDict
from ..utilities.graph import DAG, find_intermediate_inputs
def combine(bloc... | 5,540 | 44.04878 | 137 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/blocks/solved_block.py | from .block import Block
from .simple_block import simple
from .support.parent import Parent
from ..classes import FactoredJacobianDict
from ..utilities.ordered_set import OrderedSet
def solved(unknowns, targets, solver=None, solver_kwargs={}, name=""):
"""Convenience @solved(unknowns=..., targets=...) decorator ... | 4,847 | 47.48 | 142 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/blocks/block.py | """Primitives to provide clarity and structure on blocks/models work"""
import numpy as np
from numbers import Real
from typing import Any, Dict, Union, Tuple, Optional, List
from copy import deepcopy
from .support.steady_state import provide_solver_default, solve_for_unknowns, compute_target_values
from .support.par... | 19,172 | 51.528767 | 194 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/blocks/stage_block.py | from typing import List, Optional
import numpy as np
import copy
from .block import Block
from .het_block import HetBlock
from ..classes import SteadyStateDict, JacobianDict, ImpulseDict
from ..utilities.ordered_set import OrderedSet
from ..utilities.function import ExtendedFunction, CombinedExtendedFunction
from ..ut... | 24,305 | 42.481216 | 141 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/blocks/simple_block.py | """Class definition of a simple block"""
import numpy as np
from copy import deepcopy
from .support.simple_displacement import ignore, Displace, AccumulatedDerivative
from .block import Block
from ..classes import SteadyStateDict, ImpulseDict, JacobianDict, SimpleSparse
from ..utilities import misc
from ..utilities.f... | 4,046 | 36.12844 | 103 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/blocks/het_block.py | import copy
import numpy as np
from typing import Optional, Dict
from .block import Block
from .. import utilities as utils
from ..classes import SteadyStateDict, ImpulseDict, JacobianDict
from ..utilities.function import ExtendedFunction, CombinedExtendedFunction
from ..utilities.ordered_set import OrderedSet
from ..... | 22,237 | 44.016194 | 155 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/blocks/__init__.py | """Block-construction tools""" | 30 | 30 | 30 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/blocks/support/stages.py | from typing import List, Optional
import numpy as np
import copy
# from sequence_jacobian.blocks.support.het_support import DiscreteChoice
from sequence_jacobian.blocks.support.law_of_motion import DiscreteChoice
from ...utilities.function import ExtendedFunction, CombinedExtendedFunction
from ...utilities.ordered_set... | 12,458 | 35.970326 | 115 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/blocks/support/law_of_motion.py | import numpy as np
from . import het_compiled
from ...utilities.interpolate import interpolate_coord_robust, interpolate_coord
from ...utilities.multidim import batch_multiply_ith_dimension, multiply_ith_dimension
from typing import Optional, Sequence, Any, List, Tuple, Union
import copy
class LawOfMotion:
"""Abst... | 5,451 | 33.506329 | 119 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/blocks/support/parent.py | from copy import deepcopy
class Parent:
# see tests in test_parent_block.py
def __init__(self, blocks, name=None):
# dict from names to immediate kid blocks themselves
# dict from descendants to the names of kid blocks through which to access them
# "descendants" of a block include its... | 2,775 | 32.047619 | 128 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/blocks/support/het_compiled.py | import numpy as np
from numba import njit
@njit
def forward_policy_1d(D, x_i, x_pi):
nZ, nX = D.shape
Dnew = np.zeros_like(D)
for iz in range(nZ):
for ix in range(nX):
i = x_i[iz, ix]
pi = x_pi[iz, ix]
d = D[iz, ix]
Dnew[iz, i] += d * pi
... | 3,292 | 30.361905 | 107 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/blocks/support/__init__.py | """Other classes and helpers to aid standard block functionality: .steady_state, .impulse_linear, .impulse_nonlinear,
.jacobian"""
| 131 | 43 | 117 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/blocks/support/het_support.py | import numpy as np
from . import het_compiled
from ...utilities.discretize import stationary as general_stationary
from ...utilities.interpolate import interpolate_coord_robust, interpolate_coord
from ...utilities.multidim import batch_multiply_ith_dimension, multiply_ith_dimension
from ...utilities.misc import logsum
... | 9,956 | 34.816547 | 113 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/blocks/support/simple_displacement.py | """Displacement handler classes used by SimpleBlock for .ss, .td, and .jac evaluation to have Dynare-like syntax"""
import numpy as np
import numbers
from warnings import warn
from ...utilities.misc import numeric_primitive
def ignore(x):
if isinstance(x, int):
return IgnoreInt(x)
elif isinstance(x, ... | 35,010 | 48.380818 | 127 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/blocks/support/steady_state.py | """Various lower-level functions to support the computation of steady states"""
import warnings
import numpy as np
import scipy.optimize as opt
from numbers import Real
from functools import partial
from ...utilities import misc, solvers
def instantiate_steady_state_mutable_kwargs(dissolve, block_kwargs, solver_kwa... | 18,934 | 50.734973 | 145 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/blocks/auxiliary_blocks/jacobiandict_block.py | """A simple wrapper for JacobianDicts to be embedded in DAGs"""
from ..block import Block
from ...classes import ImpulseDict, JacobianDict
class JacobianDictBlock(JacobianDict, Block):
"""A wrapper for nested dicts/JacobianDicts passed directly into DAGs to ensure method compatibility"""
def __init__(self, ne... | 1,166 | 47.625 | 128 | py |
sequence-jacobian | sequence-jacobian-master/src/sequence_jacobian/blocks/auxiliary_blocks/__init__.py | """Auxiliary Block types for building a coherent backend for Block handling"""
| 79 | 39 | 78 | py |
sequence-jacobian | sequence-jacobian-master/tests/conftest.py | """Fixtures used by tests."""
import pytest
from sequence_jacobian.examples import rbc, krusell_smith, hank, two_asset
@pytest.fixture(scope='session')
def rbc_dag():
return rbc.dag()
@pytest.fixture(scope='session')
def krusell_smith_dag():
return krusell_smith.dag()
@pytest.fixture(scope='session')
de... | 552 | 16.83871 | 74 | py |
sequence-jacobian | sequence-jacobian-master/tests/__init__.py | """All tests""" | 15 | 15 | 15 | py |
sequence-jacobian | sequence-jacobian-master/tests/robustness/test_steady_state.py | """Tests for steady_state with worse initial guesses, making use of the constrained solution functionality"""
import pytest
import numpy as np
# Filter out warnings when the solver is trying to search in bad regions
@pytest.mark.filterwarnings("ignore:.*invalid value encountered in.*:RuntimeWarning")
def test_hank_s... | 2,187 | 51.095238 | 109 | py |
sequence-jacobian | sequence-jacobian-master/tests/robustness/__init__.py | """Tests to check for code robustness, including error checking and attempts to use models with bad initializations."""
| 120 | 59.5 | 119 | py |
sequence-jacobian | sequence-jacobian-master/tests/base/test_remap.py | import numpy as np
from sequence_jacobian import simple, solved, combine
@simple
def matching(theta, ell, kappa):
f = theta / (1 + theta ** ell) ** (1 / ell)
qfill = f / theta
hiring_cost = kappa / qfill
return f, qfill, hiring_cost
@solved(unknowns={'h': (0, 1)}, targets=['jc_res'])
def job_creatio... | 1,605 | 31.77551 | 104 | py |
sequence-jacobian | sequence-jacobian-master/tests/base/test_two_asset.py | """Test the two asset HANK steady state computation"""
import numpy as np
from sequence_jacobian.hetblocks import hh_twoasset as hh
from sequence_jacobian import utilities as utils
def test_hank_ss():
A, B, UCE = hank_ss_singlerun()
assert np.isclose(A, 12.526539492650361)
assert np.isclose(B, 1.0840860... | 2,907 | 36.766234 | 98 | py |
sequence-jacobian | sequence-jacobian-master/tests/base/test_steady_state.py | """Test all models' steady state computations"""
import numpy as np
from sequence_jacobian.examples import rbc, krusell_smith, hank, two_asset
# def test_rbc_steady_state(rbc_dag):
# _, ss, *_ = rbc_dag
# ss_ref = rbc.rbc_ss()
# assert set(ss.keys()) == set(ss_ref.keys())
# for k in ss.keys():
# ... | 1,408 | 31.022727 | 78 | py |
sequence-jacobian | sequence-jacobian-master/tests/base/test_simple_block.py | """Test SimpleBlock functionality"""
import copy
import numpy as np
import pytest
from sequence_jacobian import simple
from sequence_jacobian.classes.steady_state_dict import SteadyStateDict
@simple
def F(K, L, Z, alpha):
Y = Z * K(-1)**alpha * L**(1-alpha)
FK = alpha * Y / K
FL = (1-alpha) * Y / L
... | 2,476 | 37.107692 | 120 | py |
sequence-jacobian | sequence-jacobian-master/tests/base/test_dchoice.py | '''
SIM model with labor force participation choice
- state space: (s, x, e, a)
- s is employment
- 0: employed, 1: unemployed, 2: out of labor force
- x is matching
- 0: matched, 1: unmatched
- e is labor productivity
- a is assets
'''
import numpy as np
from numba import njit
from seq... | 7,609 | 36.487685 | 160 | py |
sequence-jacobian | sequence-jacobian-master/tests/base/test_estimation.py | """Test all models' estimation calculations"""
''
import pytest
import numpy as np
from sequence_jacobian import estimation
# See test_determinacy.py for the to-do describing this suppression
@pytest.mark.filterwarnings("ignore:.*cannot be safely interpreted as an integer.*:DeprecationWarning")
def test_krusell_smit... | 1,474 | 31.065217 | 103 | py |
sequence-jacobian | sequence-jacobian-master/tests/base/test_jacobian.py | """Test all models' Jacobian calculations"""
import numpy as np
def test_ks_jac(krusell_smith_dag):
_, ss, ks_model, unknowns, targets, exogenous = krusell_smith_dag
household, firm = ks_model['hh'], ks_model['firm']
T = 10
# Automatically calculate the general equilibrium Jacobian
G2 = ks_model.... | 3,585 | 40.697674 | 95 | py |
sequence-jacobian | sequence-jacobian-master/tests/base/test_transitional_dynamics.py | """Test all models' non-linear transitional dynamics computations"""
import numpy as np
from sequence_jacobian import combine
from sequence_jacobian.examples import two_asset
from sequence_jacobian.hetblocks import hh_twoasset as hh
# TODO: Figure out a more robust way to check similarity of the linear and non-line... | 5,401 | 42.216 | 118 | py |
sequence-jacobian | sequence-jacobian-master/tests/base/test_displacement_handlers.py | """Test displacement handler classes: Ignore, IgnoreVector, Displace, Perturb, Reporter"""
import numpy as np
from sequence_jacobian.blocks.support.simple_displacement import (
IgnoreInt, IgnoreFloat, IgnoreVector, Displace, AccumulatedDerivative, numeric_primitive
)
# Define useful helper functions for testing
... | 14,019 | 55.99187 | 130 | py |
sequence-jacobian | sequence-jacobian-master/tests/base/test_multiexog.py | import numpy as np
import sequence_jacobian as sj
from sequence_jacobian import het, simple, combine
def household_init(a_grid, y, r, sigma):
c = np.maximum(1e-8, y[..., np.newaxis] + np.maximum(r, 0.04) * a_grid)
Va = (1 + r) * (c ** (-sigma))
return Va
def search_frictions(f, s):
Pi_e = np.vstack(... | 3,779 | 35 | 109 | py |
sequence-jacobian | sequence-jacobian-master/tests/base/test_workflow.py | import numpy as np
from sequence_jacobian import simple, solved, create_model, markov_rouwenhorst, agrid
from sequence_jacobian.classes.impulse_dict import ImpulseDict
from sequence_jacobian.hetblocks.hh_sim import hh
'''Part 1: Household block'''
def make_grids(rho_e, sd_e, nE, amin, amax, nA):
e_grid, e_dist,... | 5,800 | 33.945783 | 123 | py |
sequence-jacobian | sequence-jacobian-master/tests/base/__init__.py | """Tests for base-level functionality of the package""" | 55 | 55 | 55 | py |
sequence-jacobian | sequence-jacobian-master/tests/base/test_options.py | import numpy as np
import pytest
from sequence_jacobian.examples import krusell_smith
def test_jacobian_h(krusell_smith_dag):
_, ss, dag, *_ = krusell_smith_dag
hh = dag['hh']
lowacc = hh.jacobian(ss, inputs=['r'], outputs=['C'], T=10, h=0.05)
midacc = hh.jacobian(ss, inputs=['r'], outputs=['C'], T=10... | 2,593 | 42.966102 | 110 | py |
sequence-jacobian | sequence-jacobian-master/tests/base/test_jacobian_dict_block.py | """Test JacobianDictBlock functionality"""
import numpy as np
from sequence_jacobian import combine
from sequence_jacobian.examples import rbc
from sequence_jacobian.blocks.auxiliary_blocks.jacobiandict_block import JacobianDictBlock
from sequence_jacobian import SteadyStateDict
def test_jacobian_dict_block_impulse... | 1,204 | 29.125 | 90 | py |
sequence-jacobian | sequence-jacobian-master/tests/base/test_solved_block.py | import numpy as np
from sequence_jacobian import simple, solved
from sequence_jacobian.classes.steady_state_dict import SteadyStateDict
from sequence_jacobian.classes.jacobian_dict import FactoredJacobianDict
@simple
def myblock(u, i):
res = 0.5 * i(1) - u**2 - u(1)
return res
@solved(unknowns={'u': (-10.0... | 1,148 | 34.90625 | 118 | py |
sequence-jacobian | sequence-jacobian-master/tests/base/test_stage_block.py | import numpy as np
from sequence_jacobian.blocks.stage_block import StageBlock
from sequence_jacobian.hetblocks.hh_sim import hh, hh_init
from sequence_jacobian.blocks.support.stages import Continuous1D, ExogenousMaker
from sequence_jacobian import interpolate, grids, misc, combine
from sequence_jacobian.classes impor... | 5,577 | 39.715328 | 114 | py |
sequence-jacobian | sequence-jacobian-master/tests/base/test_public_classes.py | """Test public-facing classes"""
import numpy as np
import pytest
from sequence_jacobian import het
from sequence_jacobian.classes.steady_state_dict import SteadyStateDict
from sequence_jacobian.classes.impulse_dict import ImpulseDict
from sequence_jacobian.utilities.bijection import Bijection
def test_impulsedict(k... | 1,734 | 31.735849 | 130 | py |
sequence-jacobian | sequence-jacobian-master/tests/base/test_het_support.py | import numpy as np
from sequence_jacobian.blocks.support.het_support import (Transition,
PolicyLottery1D, PolicyLottery2D, Markov, CombinedTransition,
lottery_1d, lottery_2d)
from sequence_jacobian.utilities.multidim import batch_multiply_ith_dimension
def test_combined_markov():
shape = (5, 6, 7)
np.... | 6,429 | 34.136612 | 120 | py |
sequence-jacobian | sequence-jacobian-master/tests/base/test_combined_block.py | import numpy as np
import sequence_jacobian as sj
def test_jacobian_accumulation():
# Define two blocks. Notice: Second one does not use output from the first!
@sj.solved(unknowns={'p': (-10, 1000)}, targets=['valuation'] , solver="brentq")
def equity(r1, p, Y):
valuation = Y + p(+1) / (1 + r1) -... | 1,583 | 36.714286 | 85 | py |
sequence-jacobian | sequence-jacobian-master/tests/performance/__init__.py | """Tests to check the performance of the code""" | 48 | 48 | 48 | py |
sequence-jacobian | sequence-jacobian-master/tests/utils/test_function.py | from sequence_jacobian.utilities.ordered_set import OrderedSet
from sequence_jacobian.utilities.function import (DifferentiableExtendedFunction, ExtendedFunction,
CombinedExtendedFunction, metadata)
import numpy as np
def f1(a, b, c):
k = a + 1
l = b - c
return k, l
def f2(b):
... | 2,154 | 25.9375 | 100 | py |
sequence-jacobian | sequence-jacobian-master/tests/utils/test_ordered_set.py | from sequence_jacobian.utilities.ordered_set import OrderedSet
def test_ordered_set():
# order matters
assert OrderedSet([1,2,3]) != OrderedSet([3,2,1])
# first insertion determines order
assert OrderedSet([5,1,6,5]) == OrderedSet([5,1,6])
# union preserves first and second order
assert (Ord... | 1,965 | 33.491228 | 95 | py |
sequence-jacobian | sequence-jacobian-master/tests/utils/test_multidim.py | from sequence_jacobian.utilities.multidim import outer
import numpy as np
def test_2d():
a = np.random.rand(10)
b = np.random.rand(12)
assert np.allclose(np.outer(a,b), outer([a,b]))
def test_3d():
a = np.array([1., 2])
b = np.array([1., 7])
small = np.outer(a, b)
c = np.array([2., 4])
... | 462 | 22.15 | 54 | py |
sequence-jacobian | sequence-jacobian-master/tests/utils/test_DAG.py | from sequence_jacobian.utilities.graph import DAG
from sequence_jacobian.utilities.ordered_set import OrderedSet
from sequence_jacobian import simple, combine
import pytest
class Block:
def __init__(self, inputs, outputs):
self.inputs = OrderedSet(inputs)
self.outputs = OrderedSet(outputs)
test_d... | 1,893 | 26.449275 | 100 | py |
APIHarvest | APIHarvest-main/backend.py | import elasticsearch
import json
import requests
import csv
from flask import Flask, request, jsonify
from flask_cors import CORS
import traceback
app = Flask(__name__)
CORS(app)
es = elasticsearch.Elasticsearch(["http://localhost:9200"])
def es_create_index_if_not_exists(es, index):
"""Create the given ElasticS... | 2,337 | 21.266667 | 84 | py |
APIHarvest | APIHarvest-main/scripts/import_arseek_so.py | import elasticsearch
import json
import requests
def es_create_index_if_not_exists(es, index):
"""Create the given ElasticSearch index and ignore error if it already exists"""
try:
es.indices.create(index=index)
except elasticsearch.exceptions.RequestError as ex:
if ex.error == 'resource_al... | 1,245 | 32.675676 | 84 | py |
APIHarvest | APIHarvest-main/scripts/import_haryono_cve.py | import elasticsearch
import json
import requests
import os
def es_create_index_if_not_exists(es, index):
"""Create the given ElasticSearch index and ignore error if it already exists"""
try:
es.indices.create(index=index)
except elasticsearch.exceptions.RequestError as ex:
if ex.error == 'r... | 994 | 32.166667 | 84 | py |
APIHarvest | APIHarvest-main/scripts/import_ausearch_code.py | import elasticsearch
import json
import requests
def es_create_index_if_not_exists(es, index):
"""Create the given ElasticSearch index and ignore error if it already exists"""
try:
es.indices.create(index=index)
except elasticsearch.exceptions.RequestError as ex:
if ex.error == 'resource_al... | 980 | 29.65625 | 84 | py |
APIHarvest | APIHarvest-main/scripts/import_zhang_tweet.py | import elasticsearch
import json
import requests
import os
def es_create_index_if_not_exists(es, index):
"""Create the given ElasticSearch index and ignore error if it already exists"""
try:
es.indices.create(index=index)
except elasticsearch.exceptions.RequestError as ex:
if ex.error == 'r... | 1,090 | 28.486486 | 84 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/setup.py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import os
from setuptools import setup, Extension
import numpy
# Version number
version = '0.0.1'
def read(fname):
return open(os.path.join(os.path.dirname(__file__), fname)).read()
# cos_module_np = Extension('cos_module_np',
# sources=['PcgCom... | 1,546 | 36.731707 | 87 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/experiment_powerplant.py | import sys
import numpy as np
import random as ran
import PcgComp
import random as ran
import time
def standardizeData(array):
arr = array.copy()
rows, cols = arr.shape
for col in xrange(cols):
std = np.std(arr[:,col])
mean = np.mean(arr[:,col])
arr[:,col] = (arr[:,col] - mean) / std
return arr
def normaliz... | 2,263 | 24.727273 | 122 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/experiment_concrete.py | import sys
import numpy as np
import random as ran
import PcgComp
import random as ran
import time
def standardizeData(array):
arr = array.copy()
rows, cols = arr.shape
for col in xrange(cols):
std = np.std(arr[:,col])
mean = np.mean(arr[:,col])
arr[:,col] = (arr[:,col] - mean) / std
return arr
def normaliz... | 2,261 | 24.704545 | 122 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/experiment_protein.py | import sys
import numpy as np
import random as ran
import PcgComp
import random as ran
import time
def standardizeData(array):
arr = array.copy()
rows, cols = arr.shape
for col in xrange(cols):
std = np.std(arr[:,col])
mean = np.mean(arr[:,col])
arr[:,col] = (arr[:,col] - mean) / std
return arr
def normaliz... | 2,260 | 24.693182 | 122 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/PcgComp/__init__.py | import warnings
warnings.filterwarnings("ignore", category=DeprecationWarning)
import methods
import preconditioners
import kernels
def load(file_path):
"""
Load a previously pickled model, using `m.pickle('path/to/file.pickle)'
:param file_name: path/to/file.pickle
"""
import cPickle as pickle
... | 530 | 21.125 | 75 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/PcgComp/methods/cg.py | import numpy as np
"""
Solve linear system using conjugate gradient
Params:
K - Covariance Matrix
Y - Target labels
init - Initial solution
thershold - Termintion criteria
"""
class Cg(object):
def __init__(self, K, Y, init=None, threshold=1e-9):
N = np.shape(K)[0]
if init is None:
init = np.zeros((N,1))... | 772 | 17.853659 | 63 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/PcgComp/methods/laplaceCg.py | import numpy as np
from scipy.stats import norm
from cg import Cg
import random
"""
Laplace approximation using conjugate gradient
Params:
K - Covariance Matrix
Y - Target labels
init - Initial solution
threshold - Termintion criteria for algorithm
"""
class LaplaceCg(object):
def __init__(self, K, ... | 1,118 | 20.519231 | 68 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/PcgComp/methods/regularPcg.py | import numpy as np
"""
Solve linear system using regular preconditioned conjugate gradient
Params:
K - Covariance Matrix
Y - Target labels
P - Preconditioner Matrix (can be set to none)
init - Initial solution
threshold - Termintion criteria for outer loop
preconInv - Inversion of preconditione... | 1,109 | 20.764706 | 72 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/PcgComp/methods/flexPcg.py | import numpy as np
from cg import Cg
"""
Solve linear system using flexible conjugate gradient (without truncation)
Params:
K - Covariance Matrix
Y - Target labels
P - Preconditioner Matrix (can be set to none)
init - Initial solution
threshold - Termintion criteria for outer loop
innerThreshol... | 1,709 | 27.983051 | 95 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/PcgComp/methods/kronCgDirect.py | import numpy as np
from ..util.kronHelper import KronHelper
from scipy import sparse
import time
"""
Solve linear system using conjugate gradient (intended for SKI inference)
Params:
K - Covariance Matrix
Ws - Sparse representation of weight matrix W
WTs - Sparse representation of transposed wieght matrix ... | 1,384 | 29.108696 | 140 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/PcgComp/methods/kronTruncFlexPcg.py | import numpy as np
from cg import Cg
from scipy import sparse
from kronCgDirect import KronCgDirect
"""
Solve linear system using truncated flexible conjugate gradient (intended for SKI inference)
Params:
K - Covariance Matrix
Y - Target labels
P - Preconditioning matrix
W - Weight matrix W
Ku - A... | 2,176 | 28.418919 | 98 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/PcgComp/methods/truncFlexPcg.py | import numpy as np
from cg import Cg
"""
Solve linear system using flexible conjugate gradient (with truncation)
Params:
K - Covariance Matrix
Y - Target labels
P - Preconditioner Matrix (can be set to none)
init - Initial solution
thershold - Termintion criteria for outer loop
innerThreshold -... | 1,869 | 27.333333 | 95 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/PcgComp/methods/__init__.py | from cg import Cg
from regularPcg import RegularPcg
from flexPcg import FlexiblePcg
from truncFlexPcg import TruncatedFlexiblePcg
from kronCgDirect import KronCgDirect
from kronTruncFlexPcg import KronTruncatedFlexiblePcg
from laplaceCg import LaplaceCg
from laplacePcg import LaplacePcg | 287 | 35 | 53 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/PcgComp/methods/laplacePcg.py | import numpy as np
from scipy.stats import norm
from regularPcg import RegularPcg
import random
"""
Laplace approximation using preconditioned conjugate gradient
Params:
K - Covariance Matrix
Y - Target labels
P - Preconditioner Matrix (can be set to none)
init - Initial solution
threshold - Termin... | 1,278 | 23.132075 | 105 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/PcgComp/util/inducingPointsHelper.py | #This implementation is based on the article:
# @inproceedings{snelson2005sparse,
# title={Sparse Gaussian processes using pseudo-inputs},
# author={Snelson, Edward and Ghahramani, Zoubin},
# booktitle={Advances in neural information processing systems},
# pages={1257--1264},
# year={2005}
# }
from __future... | 5,072 | 30.70625 | 190 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/PcgComp/util/kronHelper.py | #This implementation is based on the article:
#
# @article{gilboa2015scaling,
# title={Scaling multidimensional inference for structured Gaussian processes},
# author={Gilboa, Elad and Saat{\c{c}}i, Yunus and Cunningham, John P},
# journal={Pattern Analysis and Machine Intelligence, IEEE Transactions on},
# vol... | 1,634 | 24.546875 | 81 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/PcgComp/util/__init__.py | from kronHelper import KronHelper
from inducingPointsHelper import InducingPointsHelper
from ssgp import SsgpHelper | 115 | 37.666667 | 53 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/PcgComp/util/ssgp.py | #This implementation of spectral GP approximation is based on the article:
#
# @article{lazaro2010sparse,
# title={Sparse spectrum Gaussian process regression},
# author={L{\'a}zaro-Gredilla, Miguel and Qui{\~n}onero-Candela, Joaquin and Rasmussen, Carl Edward and Figueiras-Vidal, An{\'\i}bal R},
# journal={The J... | 1,999 | 30.25 | 168 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/PcgComp/preconditioners/svd.py | import numpy as np
import time
from sklearn.utils.extmath import randomized_svd
from preconditioner import Preconditioner
"""
Randomized Singular Value Decomposition (SVD) Preconditioner
"""
class SVD(Preconditioner):
"""
Construct preconditioning matrix
X - Training data
kern - Class of kernel function
M - ... | 2,924 | 27.676471 | 101 | py |
preconditioned_GPs | preconditioned_GPs-master/code/pcgComparison/PcgComp/PcgComp/preconditioners/kiss.py | #This implementation of Structured Kernel Interpolation is based on the article:
#
# @inproceedings{DBLP:conf/icml/WilsonN15,
# author = {Andrew Gordon Wilson and
# Hannes Nickisch},
# title = {Kernel Interpolation for Scalable Structured Gaussian Processes {(KISS-GP)}},
# booktitle = {Proce... | 4,131 | 30.784615 | 113 | py |
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