Skip to content
Projects
Groups
Snippets
Help
Loading...
Sign in
Toggle navigation
D
dlib
Project
Project
Details
Activity
Cycle Analytics
Repository
Repository
Files
Commits
Branches
Tags
Contributors
Graph
Compare
Charts
Issues
0
Issues
0
List
Board
Labels
Milestones
Merge Requests
0
Merge Requests
0
CI / CD
CI / CD
Pipelines
Jobs
Schedules
Charts
Wiki
Wiki
Snippets
Snippets
Members
Members
Collapse sidebar
Close sidebar
Activity
Graph
Charts
Create a new issue
Jobs
Commits
Issue Boards
Open sidebar
钟尚武
dlib
Commits
ed9beffa
Commit
ed9beffa
authored
7 years ago
by
Davis King
Browse files
Options
Browse Files
Download
Email Patches
Plain Diff
Added python example for find_max_global()
parent
c3f2c1df
Hide whitespace changes
Inline
Side-by-side
Showing
1 changed file
with
47 additions
and
0 deletions
+47
-0
global_optimization.py
python_examples/global_optimization.py
+47
-0
No files found.
python_examples/global_optimization.py
0 → 100755
View file @
ed9beffa
#!/usr/bin/python
# The contents of this file are in the public domain. See LICENSE_FOR_EXAMPLE_PROGRAMS.txt
#
#
# This is an example illustrating the use of the global optimization routine,
# find_max_global(), from the dlib C++ Library. This is a tool for finding the
# inputs to a function that result in the function giving its maximal output.
# This is a very useful tool for hyper parameter search when applying machine
# learning methods. There are also many other applications for this kind of
# general derivative free optimization. However, in this example program, we
# simply show how to call the method. For that, we use a common global
# optimization test function, as you can see below.
#
#
# COMPILING/INSTALLING THE DLIB PYTHON INTERFACE
# You can install dlib using the command:
# pip install dlib
#
# Alternatively, if you want to compile dlib yourself then go into the dlib
# root folder and run:
# python setup.py install
#
# Compiling dlib should work on any operating system so long as you have
# CMake and boost-python installed. On Ubuntu, this can be done easily by
# running the command:
# sudo apt-get install libboost-python-dev cmake
#
import
dlib
from
math
import
sin
,
cos
,
pi
,
exp
,
sqrt
# This is a standard test function for these kinds of optimization problems.
# It has a bunch of local maxima, with the global maximum resulting in
# holder_table()==19.2085025679.
def
holder_table
(
x0
,
x1
):
return
abs
(
sin
(
x0
)
*
cos
(
x1
)
*
exp
(
abs
(
1
-
sqrt
(
x0
*
x0
+
x1
*
x1
)
/
pi
)))
# Find the optimal inputs to holder_table(). The print statements that follow
# show that find_max_global() finds the optimal settings to high precision.
x
,
y
=
dlib
.
find_max_global
(
holder_table
,
[
-
10
,
-
10
],
# Lower bound constraints on x0 and x1 respectively
[
10
,
10
],
# Upper bound constraints on x0 and x1 respectively
80
)
# The number of times find_max_global() will call holder_table()
print
(
"optimal inputs: {}"
.
format
(
x
));
print
(
"optimal output: {}"
.
format
(
y
));
This diff is collapsed.
Click to expand it.
Write
Preview
Markdown
is supported
0%
Try again
or
attach a new file
Attach a file
Cancel
You are about to add
0
people
to the discussion. Proceed with caution.
Finish editing this message first!
Cancel
Please
register
or
sign in
to comment