def test2():
print "test 2: train from file, codes init. from data"
print "----------------------------------------------"
data = csom.open_entries(in_data_file)
if (data == "NULL"):
print "\ndata file " + in_data_file + " could not be opened"
return 1
codes = csom.randinit_codes(data, csom.TOPOL_HEXA, csom.NEIGH_BUBBLE, 12,
8)
params = csom.construct_teach_params(codes, csom.LINEAR, csom.LINEAR)
csom.init_training_session(params, alpha, radius, rlen, ewin)
csom.timing_start(params)
csom.train_fromdataset(params, data, csom.CYCLIC)
csom.timing_stop(params)
time = csom.get_training_time(params)
print "training session completed in", time, "seconds"
error = csom.write_entries(codes, out_code_file2)
if (error):
print "\nfile " + out_code_file2 + " could not be written"
return 1
print "output written to " + out_code_file2
# cleanup
csom.close_entries(data)
csom.close_entries(codes)
csom.free_teach_params(params) # WKV 2003-07-28
print "test 2 succesfully completed"
return 0
def test2(): print "test 2: train from file, codes init. from data" print "----------------------------------------------" data = csom.open_entries(in_data_file) if (data == "NULL"): print "\ndata file " + in_data_file + " could not be opened" return 1 codes = csom.randinit_codes(data,csom.TOPOL_HEXA,csom.NEIGH_BUBBLE,12,8) params = csom.construct_teach_params(codes, csom.LINEAR, csom.LINEAR) csom.init_training_session(params, alpha, radius, rlen, ewin) csom.timing_start(params) csom.train_fromdataset(params, data, csom.CYCLIC) csom.timing_stop(params) time = csom.get_training_time(params) print "training session completed in", time, "seconds" error = csom.write_entries(codes, out_code_file2) if (error): print "\nfile " + out_code_file2 + " could not be written" return 1 print "output written to " + out_code_file2 # cleanup csom.close_entries(data) csom.close_entries(codes) csom.free_teach_params(params) # WKV 2003-07-28 print "test 2 succesfully completed" return 0
def test1():
# test 1:
# SOM's model vectors are read in from ex.cod. SOM is then trained using
# a dataset created from ex.dat. After training, model vectors are saved to
# test1.cod.
print "test 1: codes from file, train from file"
print "----------------------------------------"
data = csom.open_entries(in_data_file)
if (data == "NULL"):
print "\ndata file " + in_data_file + " could not be opened"
return 1
codes = csom.open_entries(in_code_file)
if (codes == "NULL"):
print "\ncode file " + in_code_file + " could not be opened"
return 1
params = csom.construct_teach_params(codes, csom.LINEAR, csom.LINEAR)
csom.init_training_session(params, alpha, radius, rlen, ewin)
csom.timing_start(params)
csom.train_fromdataset(params, data, csom.CYCLIC)
csom.timing_stop(params)
time = csom.get_training_time(params)
print "training session completed in", time, "seconds"
error = csom.write_entries(codes, out_code_file1)
if (error):
print "\nfile " + out_code_file1 + " could not be written"
return 1
print "output written to " + out_code_file1
print "for verification, see test_devrobs.c output"
# cleanup
csom.close_entries(data)
csom.close_entries(codes)
csom.free_teach_params(params) # WKV 2003-07-28
print "test 1 succesfully completed"
return 0
def test1(): # test 1: # SOM's model vectors are read in from ex.cod. SOM is then trained using # a dataset created from ex.dat. After training, model vectors are saved to # test1.cod. print "test 1: codes from file, train from file" print "----------------------------------------" data = csom.open_entries(in_data_file) if (data == "NULL"): print "\ndata file " + in_data_file + " could not be opened" return 1 codes = csom.open_entries(in_code_file) if (codes == "NULL"): print "\ncode file " + in_code_file + " could not be opened" return 1 params = csom.construct_teach_params(codes, csom.LINEAR, csom.LINEAR) csom.init_training_session(params, alpha, radius, rlen, ewin) csom.timing_start(params) csom.train_fromdataset(params, data, csom.CYCLIC) csom.timing_stop(params) time = csom.get_training_time(params) print "training session completed in", time, "seconds" error = csom.write_entries(codes, out_code_file1) if (error): print "\nfile " + out_code_file1 + " could not be written" return 1 print "output written to " + out_code_file1 print "for verification, see test_devrobs.c output" # cleanup csom.close_entries(data) csom.close_entries(codes) csom.free_teach_params(params) # WKV 2003-07-28 print "test 1 succesfully completed" return 0
def test3():
print "test 3: codes from file, data/train dynamically, view SRN levels"
print "----------------------------------------------------------------"
# Moved from above WKV 2003-07-28
p0 = build_float_array([13.57, 12.61, -1.38, -1.99, 399.77])
p1 = build_float_array([19.58, 13.08, -1.17, -0.84, 400.03])
p2 = build_float_array([29.36, 38.69, -1.10, -0.87, 405.21])
p3 = build_float_array([19.82, 27.08, -2.35, -3.70, 404.86])
mask = build_short_array([0, 0, 1, 0, 1])
codes = csom.open_entries(in_code_file)
if (codes == "NULL"):
print "\ncode file " + in_code_file + " could not be opened"
return 1
params = csom.construct_teach_params(codes, csom.LINEAR, csom.LINEAR)
csom.init_training_session(params, alpha, radius, rlen, ewin)
data = csom.init_dataset(5)
csom.addto_dataset(data, csom.make_data_entry(p0))
csom.addto_dataset(data, csom.make_data_entry(p1))
csom.addto_dataset(
data,
#csom.make_data_entry_weighted_masked(p2, 3, mask, 5))
csom.make_data_entry_weighted_masked(p2, 3, mask, 5,
[])) # WKV 2003-07-28
csom.addto_dataset(data, csom.make_data_entry(p3))
print "data set:"
csom.print_dataset(data)
p = csom.get_eptr()
input = csom.rewind_entries(data, p)
last_coords = build_int_array([-1, -1]) # WKV 2003-07-28
while (input != None):
print "input:", input
#coords = csom.train_one(params, input)
coords = csom.train_one(params, input, last_coords,
1) # WKV 2003-07-28
csom.delete_intarray(last_coords) # WKV 2003-07-28
last_coords = coords # WKV 2003-07-28
#points = csom._csom.data_entry_points_get(input)
points = csom.data_entry_points_get(input)
mylist = build_list(points, 5)
output = csom.get_model_vector(codes, coords)
print "input: [",
for pt in mylist:
print "%.2f" % (pt),
print "]"
if (output == "NULL"):
print "output null"
#points = csom._csom.data_entry_points_get(output)
points = csom.data_entry_points_get(output)
mylist = build_list(points, 5)
print "maps to model: [",
for pt in mylist:
print "%.2f" % (pt),
print "] coords: (", ptrvalue(coords, 0), ptrvalue(coords, 1), ")"
sample = input
input = csom.next_entry(p)
print "last mapping produces the following gaussian SRN activations:"
levels = csom.get_activation_levels(
params,
coords,
radius2, # use last_coords?
csom.NEIGH_GAUSSIAN)
levels_list = build_list(levels, 96)
csom.delete_floatarray(levels) # WKV 2003-07-28
csom.delete_intarray(last_coords) # WKV 2003-07-28
i = 0
for level in levels_list:
if (i % 24 == 12):
print " ",
print "%.2f" % (level),
i = i + 1
if (i % 12 == 0):
print ""
print "last mapping produces the following dynamic error SRN activations:"
levels = csom.get_levels_by_error(params, sample, 0.0)
levels_list = build_list(levels, 96)
csom.delete_floatarray(levels) # WKV 2003-07-28
i = 0
for level in levels_list:
if (i % 24 == 12):
print " ",
print "%.2f" % (level),
i = i + 1
if (i % 12 == 0):
print ""
# cleanup (mostly written by WKV 2003-07-28)
for arr in (p0, p1, p2, p3):
csom.delete_floatarray(arr)
csom.free_eptr(p)
csom.delete_shortarray(mask)
csom.close_entries(codes)
#csom.close_entries(data)
csom.free_dataset(data)
csom.free_teach_params(params)
print "test 3 succesfully completed"
return 0
def test3():
print "test 3: codes from file, data/train dynamically, view SRN levels"
print "----------------------------------------------------------------"
# Moved from above WKV 2003-07-28
p0 = build_float_array([13.57, 12.61, -1.38, -1.99, 399.77])
p1 = build_float_array([19.58, 13.08, -1.17, -0.84, 400.03])
p2 = build_float_array([29.36, 38.69, -1.10, -0.87, 405.21])
p3 = build_float_array([19.82, 27.08, -2.35, -3.70, 404.86])
mask = build_short_array([0,0,1,0,1])
codes = csom.open_entries(in_code_file)
if (codes == "NULL"):
print "\ncode file " + in_code_file + " could not be opened"
return 1
params = csom.construct_teach_params(codes, csom.LINEAR, csom.LINEAR)
csom.init_training_session(params, alpha, radius, rlen, ewin)
data = csom.init_dataset(5)
csom.addto_dataset(data, csom.make_data_entry(p0))
csom.addto_dataset(data, csom.make_data_entry(p1))
csom.addto_dataset(data,
#csom.make_data_entry_weighted_masked(p2, 3, mask, 5))
csom.make_data_entry_weighted_masked(p2, 3, mask, 5,
[])) # WKV 2003-07-28
csom.addto_dataset(data, csom.make_data_entry(p3))
print "data set:"
csom.print_dataset(data)
p = csom.get_eptr()
input = csom.rewind_entries(data, p)
last_coords = build_int_array([-1,-1]) # WKV 2003-07-28
while(input != None):
print "input:", input
#coords = csom.train_one(params, input)
coords = csom.train_one(params, input, last_coords, 1) # WKV 2003-07-28
csom.delete_intarray(last_coords) # WKV 2003-07-28
last_coords = coords # WKV 2003-07-28
#points = csom._csom.data_entry_points_get(input)
points = csom.data_entry_points_get(input)
mylist = build_list(points,5)
output = csom.get_model_vector(codes, coords)
print "input: [",
for pt in mylist:
print "%.2f" % (pt),
print "]"
if(output == "NULL"):
print "output null"
#points = csom._csom.data_entry_points_get(output)
points = csom.data_entry_points_get(output)
mylist = build_list(points,5)
print "maps to model: [",
for pt in mylist:
print "%.2f" % (pt),
print "] coords: (", ptrvalue(coords,0), ptrvalue(coords,1), ")"
sample = input
input = csom.next_entry(p)
print "last mapping produces the following gaussian SRN activations:"
levels = csom.get_activation_levels(params, coords, radius2, # use last_coords?
csom.NEIGH_GAUSSIAN)
levels_list = build_list(levels,96)
csom.delete_floatarray(levels) # WKV 2003-07-28
csom.delete_intarray(last_coords) # WKV 2003-07-28
i = 0
for level in levels_list:
if(i%24 == 12):
print " ",
print "%.2f" % (level),
i = i + 1
if(i%12 == 0):
print ""
print "last mapping produces the following dynamic error SRN activations:"
levels = csom.get_levels_by_error(params, sample, 0.0)
levels_list = build_list(levels,96)
csom.delete_floatarray(levels) # WKV 2003-07-28
i = 0
for level in levels_list:
if(i%24 == 12):
print " ",
print "%.2f" % (level),
i = i + 1
if(i%12 == 0):
print ""
# cleanup (mostly written by WKV 2003-07-28)
for arr in (p0, p1, p2, p3):
csom.delete_floatarray(arr)
csom.free_eptr(p)
csom.delete_shortarray(mask)
csom.close_entries(codes)
#csom.close_entries(data)
csom.free_dataset(data)
csom.free_teach_params(params)
print "test 3 succesfully completed"
return 0