def test_sphere_mcplot_command_invmiaevm_opt(self):
model = "invmiaevonmises"
# Generate input data
argv_str = "{0} {1} -m {2} -M optimizing -ff -nmix 2".format(
self.__input_e, self.__input_ds, model)
argv = argv_str.split()
args = sphere_estimate.argument_parse(argv)
sphere_estimate.main(args, SphereMcplotTest.logger)
# Visualize plot
argv_str = "{0} {1} {2} 0 -m {3} -M optimizing".format(
self.__output, self.__input_ds, self.__input_e, model)
argv = argv_str.split()
args = sphere_mcplot.argument_parse(argv)
sphere_mcplot.main(args, SphereMcplotTest.logger)
def test_sphere_mcplot_command_wc(self):
model = "wrappedcauchy"
# Generate input data
argv_str = "{0} {1} -m {2} -si 50 -sw 10 -sc 1".format(
self.__input_e, self.__input_d, model)
argv = argv_str.split()
args = sphere_estimate.argument_parse(argv)
sphere_estimate.main(args, SphereMcplotTest.logger)
# Visualize plot
argv_str = "{0} {1} {2} 0 -m {3}".format(self.__output, self.__input_d,
self.__input_e, model)
argv = argv_str.split()
args = sphere_mcplot.argument_parse(argv)
sphere_mcplot.main(args, SphereMcplotTest.logger)
def test_sphere_mcplot_argument_parse(self):
argv_str = "{0} {1} {2} 0".format(self.__output, self.__input_d,
self.__input_e)
argv = argv_str.split()
args = sphere_mcplot.argument_parse(argv)
args_answer = {
"depth_file_path": self.__input_d,
"estimated_tsv": self.__input_e,
"output_dest": self.__output,
"index": 0,
"pn": 50,
"model_type": "vonmises",
"fs": 18,
"M": "sampling"
}
self.assertDictEqual(args, args_answer)
