Use new Stats class in precise-test

feature/cyclic
Matthew D. Scholefield 2019-03-20 22:29:01 -05:00
parent 3373dc81bb
commit 63e5553129
1 changed files with 9 additions and 50 deletions

View File

@ -12,12 +12,11 @@
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from collections import namedtuple
from prettyparse import create_parser
from precise.network_runner import Listener
from precise.params import inject_params
from precise.stats import Stats
from precise.train_data import TrainData
usage = '''
@ -35,60 +34,20 @@ usage = '''
...
'''
Stats = namedtuple('Stats', 'false_pos false_neg true_pos true_neg')
def stats_to_dict(stats: Stats) -> dict:
return {
'true_pos': len(stats.true_pos),
'true_neg': len(stats.true_neg),
'false_pos': len(stats.false_pos),
'false_neg': len(stats.false_neg),
}
def show_stats(stats: Stats, show_filenames):
false_pos, false_neg, true_pos, true_neg = stats
num_correct = len(true_pos) + len(true_neg)
total = num_correct + len(false_pos) + len(false_neg)
def prc(a: int, b: int): # Rounded percent
return round(100.0 * (b and a / b), 2)
def show_stats(stats: Stats, show_filenames: bool):
if show_filenames:
fp_files = stats.calc_filenames(False, True)
fn_files = stats.calc_filenames(False, False)
print('=== False Positives ===')
for i in false_pos:
print(i)
print('\n'.join(fp_files))
print()
print('=== False Negatives ===')
for i in false_neg:
print(i)
print('\n'.join(fn_files))
print()
print('=== Counts ===')
print('False Positives:', len(false_pos))
print('True Negatives:', len(true_neg))
print('False Negatives:', len(false_neg))
print('True Positives:', len(true_pos))
print(stats.counts_str())
print()
print('=== Summary ===')
print(num_correct, "out of", total)
print(prc(num_correct, total), "%")
print()
print(prc(len(false_pos), len(false_pos) + len(true_neg)), "% false positives")
print(prc(len(false_neg), len(false_neg) + len(true_pos)), "% false negatives")
def calc_stats(filenames, targets, predictions) -> Stats:
stats = Stats([], [], [], [])
for name, target, prediction in zip(filenames, targets, predictions):
{
(True, False): stats.false_pos,
(True, True): stats.true_pos,
(False, True): stats.false_neg,
(False, False): stats.true_neg
}[prediction[0] > 0.5, target[0] > 0.5].append(name)
return stats
print(stats.summary_str())
def main():
@ -102,7 +61,7 @@ def main():
filenames = sum(data.train_files if args.use_train else data.test_files, [])
predictions = Listener.find_runner(args.model)(args.model).predict(inputs)
stats = calc_stats(filenames, targets, predictions)
stats = Stats(predictions, targets, filenames)
print('Data:', data)
show_stats(stats, not args.no_filenames)