experiment_list = [("environmental_datasets.cfg", "CRU10",
"../data/species/occ_data.csv", "peromyscus maniculatus")]
# ( "environmental_datasets.cfg", "CRU10",
# "../data/species/occ_data.csv", "ursus americanus" ) ]
mod = om.OpenModeller()
algmd = mod.availableAlgorithms()
num = mod.numAvailableAlgorithms()
omtest_list = []
# run every experiment for every algorithm available
for i in range(0, num):
alg_id = algmd[i].id
for exp in experiment_list:
# append a list with function to be executed, test name
# and parameters to be passed to function
omtest_list.append(
(algorithm_serialization, "%s: %s" % (alg_id, exp[3].capitalize()),
[exp[0], exp[1], alg_id, exp[2], exp[3]]))
if __name__ == '__main__':
omtest.setup_run('algorithm_serialization')
omtest.run_tests(omtest_list, omtest.parseOptions())
omtest.summarize()
return ('fail', None)
def sample_dummy_blowup(args, options):
(a, b) = 0
return ('fail', None)
def sample_dummy_skip(args, options):
# you can test the command line arguments like that:
if not omtest.checkArguments(options, "algorithm", "bioclim"):
return ('success', None)
else:
return ('skip', None)
###############################################################################
omtest_list = [
sample_dummy_success, sample_dummy_failure, sample_dummy_blowup,
sample_dummy_skip
]
if __name__ == '__main__':
omtest.setup_run('dummy_test')
omtest.run_tests(omtest_list, omtest.parseOptions())
omtest.summarize()
return ('skip', None)
mod = om.OpenModeller()
try:
algMetadata = mod.algorithmMetadata(alg_id)
return ('success', None)
except:
return ('fail', None)
###############################################################################
omtest_list = [(check_algorithm, "Bioclim", "Bioclim"),
(check_algorithm, "BioclimDistance", "BioclimDistance"),
(check_algorithm, "DistanceToAverage", "DistanceToAverage"),
(check_algorithm, "MinimumDistance", "MinimumDistance"),
(check_algorithm, "CSMBS", "CSMBS"),
(check_algorithm, "GARP", "GARP"),
(check_algorithm, "DG_GARP", "DG_GARP"),
(check_algorithm, "GARP_BS", "GARP_BS"),
(check_algorithm, "DG_GARP_BS", "DG_GARP_BS")]
if __name__ == '__main__':
omtest.setup_run('algorithm_presence_test')
omtest.run_tests(omtest_list, omtest.parseOptions())
omtest.summarize()
# Copyright (c) 2003, Frank Warmerdam <*****@*****.**> # # This library is free software; you can redistribute it and/or # modify it under the terms of the GNU Library General Public # License as published by the Free Software Foundation; either # version 2 of the License, or (at your option) any later version. # # This library is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU # Library General Public License for more details. # # You should have received a copy of the GNU Library General Public # License along with this library; if not, write to the # Free Software Foundation, Inc., 59 Temple Place - Suite 330, # Boston, MA 02111-1307, USA. ############################################################################### # import sys sys.path.append( 'pymod' ) import omtest test_list = [ 'algs' ] omtest.setup_run( 'om_user_test_all' ) omtest.run_all( test_list, omtest.parseOptions() ) omtest.summarize()
"../data/species/abs_data.csv", "strix varia")]
mod = om.OpenModeller()
algmd = mod.availableAlgorithms()
num = mod.numAvailableAlgorithms()
omtest_list = []
# run every experiment for every algorithm available
for i in range(0, num):
alg_id = algmd[i].id
# find out whether algorithm accepts absence data
usesAbsences = algmd[i].absence
for exp in experiment_list:
# append a list with function to be executed, test name
# and parameters to be passed to function
omtest_list.append(
(algorithm_absences, "%s: %s" % (alg_id, exp[3].capitalize()),
[exp[0], exp[1], alg_id, usesAbsences, exp[2], exp[3]]))
if __name__ == '__main__':
omtest.setup_run('algorithm_absences_test')
omtest.run_tests(omtest_list, omtest.parseOptions())
omtest.summarize()
###############################################################################
experiment_list = [("environmental_datasets.cfg", "CRU10",
"../data/species/abs_data.csv", "strix varia")]
mod = om.OpenModeller()
algmd = mod.availableAlgorithms()
num = mod.numAvailableAlgorithms()
omtest_list = []
# run every experiment for every algorithm available
for i in range(0, num):
alg_id = algmd[i].id
for exp in experiment_list:
# append a list with function to be executed, test name
# and parameters to be passed to function
omtest_list.append(
(matrix_input, "%s: %s" % (alg_id, exp[3].capitalize()),
[exp[0], exp[1], alg_id, exp[2], exp[3]]))
if __name__ == '__main__':
omtest.setup_run('matrix_input_test')
omtest.run_tests(omtest_list, omtest.parseOptions())
omtest.summarize()
("environmental_datasets.cfg", "CRU10",
"../data/species/occ_data.csv", "strix varia"),
("environmental_datasets.cfg", "CRU10",
"../data/species/occ_data.csv", "mephitis mephitis"),
("environmental_datasets.cfg", "CRU10",
"../data/species/occ_data.csv", "ursus americanus")]
mod = om.OpenModeller()
algmd = mod.availableAlgorithms()
num = mod.numAvailableAlgorithms()
omtest_list = []
# run every experiment for every algorithm available
for i in range(0, num):
alg_id = algmd[i].id
for exp in experiment_list:
# append a list with function to be executed, test name
# and parameters to be passed to function
omtest_list.append(
(algorithm_run, "%s: %s" % (alg_id, exp[3].capitalize()),
[exp[0], exp[1], alg_id, exp[2], exp[3]]))
if __name__ == '__main__':
omtest.setup_run('algorithm_run_test')
omtest.run_tests(omtest_list, omtest.parseOptions())
omtest.summarize()