def test_problems(self):
folder = os.path.join(get_pymoo(), "pymoo", "usage", "problems")
files = [os.path.join(folder, fname) for fname in os.listdir(folder)]
files.append(
os.path.join(get_pymoo(), "pymoo", "usage", "usage_problem.py"))
test_usage(files)
def update_and_run_notebook(filename, replace=True, execute=False):
nb = load_notebook(filename)
if replace:
# Loop through all cells
for k in range(len(nb['cells'])):
# If cell is code and has usage metadata set, update the .ipynb json
if nb['cells'][k]['cell_type'] == 'code':
code = nb['cells'][k]['metadata'].get('code')
section = nb['cells'][k]['metadata'].get('section')
if code:
code = get_usage(code)
if section:
code = get_section(code, section)
nb['cells'][k]['source'] = code
# remove trailing empty cells
while len(nb["cells"]) > 0 and nb["cells"][-1]['cell_type'] == 'code' and len(nb["cells"][-1]['source']) == 0 \
and nb["cells"][-1]['execution_count'] is None:
nb["cells"] = nb["cells"][:-1]
if execute:
ep = ExecutePreprocessor(kernel_name='python3')
ep.preprocess(nb, {'metadata': {'path': get_pymoo()}})
with open(filename, 'wt') as f:
nbformat.write(nb, f)
def test(self):
PYMOO_DIR = get_pymoo()
DOC_DIR = os.path.join(PYMOO_DIR, "doc", "source")
ipynb = []
# collect all the jupyter ipynb in the documentation
for root, directories, filenames in os.walk(DOC_DIR):
for filename in filenames:
if filename.endswith(
".ipynb") and "checkpoint" not in filename:
ipynb.append(os.path.join(root, filename))
ep = ExecutePreprocessor(timeout=10000, kernel_name='python3')
for fname in ipynb:
print(fname.split("/")[-1])
import warnings
warnings.filterwarnings("ignore")
try:
nb = nbformat.read(fname, nbformat.NO_CONVERT)
ep.preprocess(nb, {'metadata': {'path': PYMOO_DIR}})
except CellExecutionError:
msg = 'Error executing the fname "%s".\n\n' % fname
print(msg)
raise
finally:
if OVERWRITE:
with open(fname, mode='wt') as f:
nbformat.write(nb, f)
def test_values_of_indicators(self):
l = [(GD, "gd"), (IGD, "igd")]
folder = os.path.join(get_pymoo(), "tests", "performance_indicator")
pf = np.loadtxt(os.path.join(folder, "performance_indicators.pf"))
for indicator, ext in l:
for i in range(1, 5):
F = np.loadtxt(
os.path.join(folder, "performance_indicators_%s.f" % i))
val = indicator(pf).calc(F)
correct = np.loadtxt(
os.path.join(folder,
"performance_indicators_%s.%s" % (i, ext)))
self.assertTrue(correct == val)
def test_usages(self):
folder = os.path.join(get_pymoo(), "pymoo", "usage")
test_usage([
os.path.join(folder, fname)
for fname in Path(folder).glob('**/*.py')
])
def get_pymoo_test():
return os.path.join(get_pymoo(), "tests")
def test_usages(self):
folder = os.path.join(get_pymoo(), "pymoo", "usage", "visualization")
test_usage([os.path.join(folder, fname) for fname in os.listdir(folder)])
def setUpClass(cls):
with open(
os.path.join(get_pymoo(), "tests", "resources",
"cnsga2_run_zdt4.dat"), 'rb') as f:
cls.data = pickle.load(f)
def test_termination_criterion(self):
folder = os.path.join(get_pymoo(), "pymoo", "usage", "termination")
test_usage(
[os.path.join(folder, fname) for fname in os.listdir(folder)])
import os
import numpy as np
from pymoo.configuration import get_pymoo
from pymoo.decision_making.high_tradeoff import HighTradeoffPoints
from pymoo.decision_making.high_tradeoff_inverted import HighTradeoffPointsInverted
from pymoo.visualization.scatter import Scatter
pf = np.loadtxt(
os.path.join(get_pymoo(), "pymoo", "usage", "decision_making",
"knee-2d.out"))
dm = HighTradeoffPoints()
I = dm.do(pf)
plot = Scatter(angle=(0, 0))
plot.add(pf, alpha=0.2)
plot.add(pf[I], color="red", s=100)
plot.show()
def test_decomposition(self):
folder = os.path.join(get_pymoo(), "pymoo", "usage", "decomposition")
test_usage(
[os.path.join(folder, fname) for fname in os.listdir(folder)])
def test_usages(self):
test_usage([
os.path.join(get_pymoo(), "pymoo", "usage",
"usage_performance_indicator.py")
])
