Apply pyupgrade to update code style

deepcell/__init__.py

@@ -25,9 +25,6 @@
 # ==============================================================================
 """Package for single cell image segmentation with convolutional neural networks"""
 
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
 
 from deepcell._version import __version__
 
@@ -53,7 +50,3 @@
 from deepcell.training import train_model_sample
 from deepcell.training import train_model_siamese_daughter
 from deepcell.utils import *
-
-del absolute_import
-del division
-del print_function

deepcell/_version.py

@@ -28,7 +28,7 @@
 __description__ = 'Deep learning for single cell image segmentation'
 __url__ = 'https://github.com/vanvalenlab/deepcell-tf'
 __version__ = '0.12.5'
-__download_url__ = '{}/tarball/{}'.format(__url__, __version__)
+__download_url__ = f'{__url__}/tarball/{__version__}'
 __author__ = 'The Van Valen Lab'
 __author_email__ = 'vanvalen@caltech.edu'
 __license__ = 'LICENSE'

deepcell/applications/__init__.py

@@ -25,9 +25,6 @@
 # ==============================================================================
 """Deepcell Applications - Pre-trained models for specific functions"""
 
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
 
 from deepcell.applications.application import Application
 from deepcell.applications.cytoplasm_segmentation import CytoplasmSegmentation
@@ -37,7 +34,3 @@
 from deepcell.applications.cell_tracking import CellTracking
 from deepcell.applications.label_detection import LabelDetection
 from deepcell.applications.scale_detection import ScaleDetection
-
-del absolute_import
-del division
-del print_function

deepcell/applications/application.py

@@ -25,9 +25,6 @@
 # ==============================================================================
 """Base class for applications"""
 
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
 
 import logging
 import timeit
@@ -37,7 +34,7 @@
 from deepcell_toolbox.utils import resize, tile_image, untile_image
 
 
-class Application(object):
+class Application:
     """Application object that takes a model with weights
     and manages predictions
 

deepcell/applications/application_test.py

@@ -25,9 +25,6 @@
 # ==============================================================================
 """Tests for Application"""
 
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
 
 from itertools import product
 from unittest.mock import Mock

deepcell/applications/cell_tracking.py

@@ -25,9 +25,6 @@
 # ==============================================================================
 """A model that can detect whether 2 cells are same, different, or related."""
 
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
 
 import os
 
@@ -140,7 +137,7 @@ def __init__(self,
             model_path = os.path.splitext(archive_path)[0]
             model = tf.keras.models.load_model(model_path)
 
-        super(CellTracking, self).__init__(
+        super().__init__(
             model,
             model_mpp=MODEL_MPP,
             preprocessing_fn=None,

deepcell/applications/cell_tracking_test.py

@@ -25,9 +25,6 @@
 # ==============================================================================
 """Tests for CellTracking Application"""
 
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
 
 from tensorflow.python.platform import test
 import numpy as np

deepcell/applications/cytoplasm_segmentation.py

@@ -25,9 +25,6 @@
 # ==============================================================================
 """Cytoplasmic segmentation application"""
 
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
 
 import os
 
@@ -106,7 +103,7 @@ def __init__(self, model=None,
             model_path = os.path.splitext(archive_path)[0]
             model = tf.keras.models.load_model(model_path)
 
-        super(CytoplasmSegmentation, self).__init__(
+        super().__init__(
             model,
             model_image_shape=model.input_shape[1:],
             model_mpp=0.65,

deepcell/applications/cytoplasm_segmentation_test.py

@@ -25,9 +25,6 @@
 # ==============================================================================
 """Tests for CytoplasmSegmentationModel"""
 
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
 
 from tensorflow.python.platform import test
 import numpy as np

deepcell/applications/label_detection.py

@@ -25,9 +25,6 @@
 # ==============================================================================
 """Classify the type of an input image to send the data to the correct model"""
 
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
 
 import os
 
@@ -139,7 +136,7 @@ def __init__(self, model=None):
             model_path = os.path.splitext(archive_path)[0]
             model = tf.keras.models.load_model(model_path)
 
-        super(LabelDetection, self).__init__(
+        super().__init__(
             model,
             model_image_shape=model.input_shape[1:],
             model_mpp=0.65,

deepcell/applications/label_detection_test.py

@@ -25,9 +25,6 @@
 # ==============================================================================
 """Tests for LabelDetectionModel"""
 
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
 
 import numpy as np
 import tensorflow as tf

deepcell/applications/mesmer.py

@@ -25,9 +25,6 @@
 # ==============================================================================
 """Mesmer application"""
 
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
 
 import os
 
@@ -58,7 +55,7 @@ def mesmer_preprocess(image, **kwargs):
     """
 
     if len(image.shape) != 4:
-        raise ValueError("Image data must be 4D, got image of shape {}".format(image.shape))
+        raise ValueError(f"Image data must be 4D, got image of shape {image.shape}")
 
     output = np.copy(image)
     threshold = kwargs.get('threshold', True)
@@ -221,7 +218,7 @@ def __init__(self, model=None):
             model_path = os.path.splitext(archive_path)[0]
             model = tf.keras.models.load_model(model_path)
 
-        super(Mesmer, self).__init__(
+        super().__init__(
             model,
             model_image_shape=model.input_shape[1:],
             model_mpp=0.5,

deepcell/applications/mesmer_test.py

@@ -25,9 +25,6 @@
 # ==============================================================================
 """Tests for Mesmer Application"""
 
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
 
 import pytest
 

deepcell/applications/multiplex_segmentation.py

@@ -28,8 +28,5 @@
 Deprecated in favor of ``deepcell.applications.Mesmer`` instead.
 """
 
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
 
 from deepcell.applications.mesmer import Mesmer as MultiplexSegmentation

deepcell/applications/nuclear_segmentation.py

@@ -25,9 +25,6 @@
 # ==============================================================================
 """Nuclear segmentation application"""
 
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
 
 import os
 
@@ -119,7 +116,7 @@ def __init__(self, model=None,
             model_path = os.path.splitext(archive_path)[0]
             model = tf.keras.models.load_model(model_path)
 
-        super(NuclearSegmentation, self).__init__(
+        super().__init__(
             model,
             model_image_shape=model.input_shape[1:],
             model_mpp=MODEL_MPP,

deepcell/applications/nuclear_segmentation_test.py

@@ -25,9 +25,6 @@
 # ==============================================================================
 """Tests for NuclearSegmentationApplication"""
 
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
 
 from tensorflow.python.platform import test
 import numpy as np

deepcell/applications/scale_detection.py

@@ -25,9 +25,6 @@
 # ==============================================================================
 """Detect the scale of input data for rescaling for other models"""
 
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
 
 import os
 
@@ -137,7 +134,7 @@ def __init__(self, model=None):
             model_path = os.path.splitext(archive_path)[0]
             model = tf.keras.models.load_model(model_path)
 
-        super(ScaleDetection, self).__init__(
+        super().__init__(
             model,
             model_image_shape=model.input_shape[1:],
             model_mpp=0.65,

deepcell/applications/scale_detection_test.py

@@ -25,9 +25,6 @@
 # ==============================================================================
 """Tests for ScaleDetectionModel"""
 
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
 
 import numpy as np
 import tensorflow as tf

deepcell/callbacks.py

@@ -25,9 +25,6 @@
 # ==============================================================================
 """Custom Callbacks for DeepCell"""
 
-from __future__ import absolute_import
-from __future__ import print_function
-from __future__ import division
 
 import timeit
 
@@ -40,7 +37,7 @@ class InferenceTimer(tf.keras.callbacks.Callback):
     """Callback to log inference speed per epoch."""
 
     def __init__(self, samples=100):
-        super(InferenceTimer, self).__init__()
+        super().__init__()
         self._samples = int(samples)
         self._batch_times = []
         self._samples_seen = []
@@ -70,8 +67,8 @@ def on_predict_end(self, logs=None):
         avg = np.mean(per_sample)
         std = np.std(per_sample)
 
-        print('Average inference speed per sample for %s total samples: '
-              '%0.5fs ± %0.5fs.' % (total_samples, avg, std))
+        print('Average inference speed per sample for {} total samples: '
+              '{:0.5f}s ± {:0.5f}s.'.format(total_samples, avg, std))
 
     def on_epoch_end(self, epoch, logs=None):
         shape = tuple([self._samples] + list(self.model.input_shape[1:]))

deepcell/callbacks_test.py

@@ -25,9 +25,6 @@
 # ==============================================================================
 """Custom Callbacks for DeepCell"""
 
-from __future__ import absolute_import
-from __future__ import print_function
-from __future__ import division
 
 import sys
 

deepcell/data/__init__.py

@@ -25,9 +25,6 @@
 # ==============================================================================
 """Data utilities using ``tf.data``."""
 
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
 
 
 def split_dataset(dataset, val_size, test_size=0):
@@ -77,8 +74,3 @@ def split_dataset(dataset, val_size, test_size=0):
 
 
 from deepcell.data import tracking
-
-
-del absolute_import
-del division
-del print_function

deepcell/data/tracking.py

@@ -25,9 +25,6 @@
 # ==============================================================================
 """Dataset Builders"""
 
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
 
 import math
 import functools
@@ -50,7 +47,7 @@
 from deepcell.data import split_dataset
 
 
-class Track(object):  # pylint: disable=useless-object-inheritance
+class Track:  # pylint: disable=useless-object-inheritance
 
     def __init__(self, path=None, tracked_data=None,
                  appearance_dim=32, distance_threshold=64,
@@ -289,9 +286,9 @@ def concat_adj_matrices(tracks, matrix_name):
 
     # TODO: these keys must match the Track attributes.
     data_dict = {
-        'appearances': get_array_of_max_shape((t.appearances for t in tracks)),
-        'centroids': get_array_of_max_shape((t.centroids for t in tracks)),
-        'morphologies': get_array_of_max_shape((t.morphologies for t in tracks)),
+        'appearances': get_array_of_max_shape(t.appearances for t in tracks),
+        'centroids': get_array_of_max_shape(t.centroids for t in tracks),
+        'morphologies': get_array_of_max_shape(t.morphologies for t in tracks),
     }
 
     for track in tracks:

deepcell/data/tracking_test.py

@@ -25,9 +25,6 @@
 # ==============================================================================
 """Tests for tracking functions"""
 
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
 
 from absl.testing import parameterized
 
@@ -75,7 +72,7 @@ def get_dummy_data(num_labels=3, batches=2):
     return data
 
 
-class TestTrack(object):
+class TestTrack:
 
     def test_init(self, mocker):
         num_labels = 3