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Adds some gradient descent stuff

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This commit is contained in:
Deepak Mallubhotla 2021-08-02 08:57:07 -05:00
parent 472ff166cc
commit 026519697b
Signed by: deepak
GPG Key ID: 64BF53A3369104E7
7 changed files with 290 additions and 130 deletions
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3
.flake8
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@ -1,2 +1,3 @@
[flake8]
ignore = W191
ignore = W191, E501
max-line-length = 120

25
pathfinder/gradient_descent.py Normal file
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@ -0,0 +1,25 @@
import numpy
def find_sols(cost_array, jacobian, step_size=0.001, max_iterations=5, initial=(0, 0), desired_cost=1e-6, step_size_tries=10):
desired_cost_squared = desired_cost**2
current = numpy.array(initial)
iterations = 0
curr_cost = numpy.array(cost_array(current))
while iterations < max_iterations:
curr_cost = numpy.array(cost_array(current))
if curr_cost.dot(curr_cost) < desired_cost_squared:
return ("Finished early", current)
gradient = .5 * numpy.matmul(numpy.transpose(jacobian(current)), curr_cost)
next = current - step_size * gradient
next_cost = numpy.array(cost_array(next))
tries = step_size_tries
current_step = step_size
while tries > 0 and next_cost.dot(next_cost) > curr_cost.dot(curr_cost):
current_step = current_step / 10
next = current - current_step / 10 * gradient
next_cost = numpy.array(cost_array(next))
tries -= 1
current = next
iterations += 1
return ("Ran out of iterations", current)

9
pathfinder/pathfinder.py
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@ -0,0 +1,9 @@
import numpy # type: ignore
def circle_cost(x: float, y: float) -> float:
return 4 - x**2 - y**2
def circle_gradient(x: float, y: float) -> numpy.ndarray:
return numpy.array([-2 * x, -2 * y])

238
poetry.lock generated
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@ -1,107 +1,80 @@
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6
pyproject.toml
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@ -5,7 +5,8 @@ description = ""
authors = ["Deepak <dmallubhotla+github@gmail.com>"]
[tool.poetry.dependencies]
python = "^3.7"
python = "^3.8"
numpy = "^1.21.1"
[tool.poetry.dev-dependencies]
pytest = ">=6"
@ -16,3 +17,6 @@ mypy = "^0.790"
[build-system]
requires = ["poetry>=0.12"]
build-backend = "poetry.masonry.api"
[tool.pytest.ini_options]
testpaths = ["tests"]

29
scripts/patch.sh Normal file
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@ -0,0 +1,29 @@
#!/usr/bin/env bash
set -Eeuo pipefail
if [ -z "$(git status --porcelain)" ]; then
# Working directory clean
branch_name=$(git symbolic-ref -q HEAD)
branch_name=${branch_name##refs/heads/}
branch_name=${branch_name:-HEAD}
poetry version patch
version=`sed 's/version = "\([0-9]*.[0-9]*.[0-9]*\)"/\1/p' -n <pyproject.toml`
read -p "Create commit for version $version? " -n 1 -r
echo # (optional) move to a new line
if [[ $REPLY =~ ^[Yy]$ ]]
then
# do dangerous stuff
echo "Creating a new patch"
git add pyproject.toml
git commit -m "Created version $version"
git tag -a "$version" -m "patch.sh created version $version"
git push --tags
else
echo "Surrendering, clean up by reverting pyproject.toml..."
exit 2
fi
else
echo "Can't create patch version, working tree unclean..."
exit 1
fi

110
tests/test_gradient_descent.py Normal file
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@ -0,0 +1,110 @@
import numpy
import pathfinder.gradient_descent
def circ_cost(radius, center=(0, 0)):
def cf(pt):
pt2 = numpy.array(pt) - numpy.array(center)
return (radius**2 - pt2.dot(pt2))
return cf
def test_circ_cost():
cost = circ_cost(5)
actual = cost([3, 4])
expected = 0
assert actual == expected
cost = circ_cost(13, [12, 5])
actual = cost([0, 0])
expected = 0
assert actual == expected
def test_find_sols():
c1 = circ_cost(5)
c2 = circ_cost(13, [8, -8])
def costs(pt):
return numpy.array(
[c1(pt), c2(pt)]
)
def jac(pt):
x, y = pt
return numpy.array([[-2 * x, -2 * y], [-2 * (x - 8), -2 * (y + 8)]])
print(costs([3, 4]))
result = pathfinder.gradient_descent.find_sols(costs, jac, step_size=0.01, max_iterations=5000, initial=(2, 10), desired_cost=1e-6)
print(result)
def dipole_cost(vn, xn_raw):
xn = numpy.array(xn_raw)
def dc(pt):
p = pt[0:3]
s = pt[3:6]
diff = xn - s
return (vn * (numpy.linalg.norm(diff)**3)) - p.dot(diff)
return dc
def test_actual_dipole_finding():
def c0(pt):
p = pt[0:3]
return (p.dot(p) - 35)
v1 = -0.0554777
v2 = -0.0601857
v3 = -0.0636403
v4 = -0.0648838
v5 = -0.0629715
# the 0 here is a red herring for index purposes later
vns = [0, v1, v2, v3, v4, v5]
# the 0 here is a red herring
xns = [numpy.array([0, 0, n]) for n in range(0, 6)]
c1 = dipole_cost(v1, [0, 0, 1])
c2 = dipole_cost(v2, [0, 0, 2])
c3 = dipole_cost(v3, [0, 0, 3])
c4 = dipole_cost(v4, [0, 0, 4])
c5 = dipole_cost(v5, [0, 0, 5])
def costs(pt):
return numpy.array(
[c0(pt), c1(pt), c2(pt), c3(pt), c4(pt), c5(pt)]
)
def jac_row(n):
def jr(pt):
p = pt[0:3]
s = pt[3:6]
vn = vns[n]
xn = xns[n]
diff = xn - s
return [
-diff[0], -diff[1], -diff[2],
p[0] - vn * 3 * numpy.linalg.norm(diff) * (diff)[0],
p[1] - vn * 3 * numpy.linalg.norm(diff) * (diff)[1],
p[2] - vn * 3 * numpy.linalg.norm(diff) * (diff)[2]
]
return jr
def jac(pt):
return numpy.array([
[2 * pt[0], 2 * pt[1], 2 * pt[2], 0, 0, 0],
jac_row(1)(pt),
jac_row(2)(pt),
jac_row(3)(pt),
jac_row(4)(pt),
jac_row(5)(pt),
])
result = pathfinder.gradient_descent.find_sols(costs, jac, step_size=0.01, max_iterations=10000, initial=(1, 2, 3, 4, 5, 6), desired_cost=1e-6, step_size_tries=25)
print(result)