Merge pull request #139 from BBQuercus/release_0.1.3

Release 0.1.3

.bumpversion.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.1.2
+current_version = 0.1.3
 commit = False
 tag = True
 

conda/meta.yaml

@@ -1,6 +1,6 @@
 package:
     name: "deepblink"
-    version: 0.1.2
+    version: 0.1.3
 source:
     path: ..
 
@@ -13,11 +13,11 @@ build:
 
 requirements:
     build:
-      - python>=3.6,<3.8
+      - python>=3.6,<3.9
       - pip
       - setuptools
     run:
-      - python>=3.6,<3.8
+      - python>=3.6,<3.9
       - matplotlib>=3.0.0
       - requests>=2.0.0
       - numpy>=1.17.0

deepblink/__init__.py

@@ -16,7 +16,7 @@
 - util: Basic utility functions not fitting into a category.
 """
 
-__version__ = "0.1.2"
+__version__ = "0.1.3"
 
 from . import augment
 from . import cli

deepblink/cli/_argparse.py

@@ -426,6 +426,7 @@ def _parse_args_visualize(
     )
     group2 = parser.add_argument_group(f"{Color.optional}Optional{Color.end}")
     group2.add_argument(
+        "-ds",
         "--dataset",
         type=FileType(["npz"]),
         default=None,
@@ -436,6 +437,7 @@ def _parse_args_visualize(
         ),
     )
     group2.add_argument(
+        "-s",
         "--subset",
         type=str,
         default="train",
@@ -446,6 +448,7 @@ def _parse_args_visualize(
         ),
     )
     group2.add_argument(
+        "-idx",
         "--index",
         type=int,
         default=None,
@@ -455,6 +458,7 @@ def _parse_args_visualize(
         ),
     )
     group2.add_argument(
+        "-i",
         "--image",
         type=FileType(EXTENSIONS),
         default=None,
@@ -465,12 +469,14 @@ def _parse_args_visualize(
         ),
     )
     group2.add_argument(
+        "-p",
         "--prediction",
         type=FileType(["csv"]),
         default=None,
         help=(
             "Prediction csv file (output from deepBlink predict) to visualize. "
-            "[default: None]"
+            "Will try to find the image's corresponding csv file if not given. "
+            "[default: image.csv]"
         ),
     )
     _add_utils(parser)

deepblink/cli/_parseutil.py

@@ -158,7 +158,6 @@ class Color:
     end = "\033[0m" if ispos else ""
 
 
-# TODO find a simpler and safer solution
 def _add_utils(parser: argparse.ArgumentParser):
     """A very hacky way of trying to move this group to the bottom of help text."""
     group = parser.add_argument_group(f"{Color.general}General utilities{Color.end}")
@@ -173,7 +172,7 @@ def _add_utils(parser: argparse.ArgumentParser):
         "-V",
         "--version",
         action="version",
-        version="%(prog)s 0.1.2",
+        version="%(prog)s 0.1.3",
         help="Show %(prog)s's version number.",
     )
     group.add_argument(

deepblink/cli/_predict.py

@@ -113,8 +113,6 @@ def path_output(self) -> str:
             outpath = self.path_input
         return outpath
 
-    # TODO solve double definition of replace_chars here and in ShapeType
-    # TODO solve mypy return type bug
     @property
     def shape(self) -> List[str]:
         """Resolve input shape."""

deepblink/cli/_util.py

@@ -17,14 +17,13 @@ def get_pixel_size(
         return (pixel_size, pixel_size)
 
     # Try to predict pixel size
+    size = (1.0, 1.0)
     try:
         size = predict_pixel_size(image)
         logger.debug(f"using predicted pixel size {size}")
-        return size
     except (ValueError, KeyError, IndexError) as e:
         logger.warning(
             f"\U000026A0 {e} encountered. Pixel size for image {image} could not be predicted."
         )
-
-    logger.debug(f"defaulting pixel size to {size}")
-    return (1.0, 1.0)
+        logger.debug(f"defaulting pixel size to {size}")
+    return size

deepblink/cli/_visualize.py

@@ -1,6 +1,7 @@
 """CLI submodule for visualization."""
 
 import logging
+import os
 import random
 
 import matplotlib.pyplot as plt
@@ -42,7 +43,7 @@ def __call__(self):
         if self.dataset is not None:
             self.logger.info("\U0001F5BC Visualizing dataset provided.")
             self.visualize_dataset()
-        elif self.image is not None and self.prediction is not None:
+        elif self.image is not None:
             self.logger.info("\U0001F5BC visualizing image provided.")
             self.visualize_image()
         else:
@@ -91,6 +92,10 @@ def visualize_image(self):
         image = load_image(self.image)
         if image.ndim != 2:
             self.logger.error("invalid image dimension")
+
+        if self.prediction is None:
+            self.prediction = f"{os.path.splitext(self.image)[0]}.csv"
+            self.logger.debug("using same name prediction file")
         df = load_prediction(self.prediction)
         coords = df[["x [px]", "y [px]"]].values
 

deepblink/io.py

@@ -110,6 +110,8 @@ def load_model(fname: Union[str, "os.PathLike[str]"]) -> tf.keras.models.Model:
 
 def load_prediction(fname: Union[str, "os.PathLike[str]"]) -> pd.DataFrame:
     """Import a prediction file (output from deepBlink predict) as pandas dataframe."""
+    if not os.path.isfile(fname):
+        raise ValueError(f"File must exist - '{fname}' does not.")
     df = pd.read_csv(fname)
     if any([c in df.columns for c in ["x [µm]", "y [µm]"]]):
         raise ValueError(

deepblink/util.py

@@ -132,6 +132,7 @@ def predict_shape(shape: tuple) -> str:
     return order
 
 
+# TODO account for resolution unit (µm / cm)
 def predict_pixel_size(fname: Union[str, "os.PathLike[str]"]) -> Tuple[float, float]:
     """Predict the pixel size based on tifffile metadata."""
     if not os.path.splitext(fname)[1] == ".tif":

docs/conf.py

@@ -37,7 +37,7 @@
 year = "2020"
 author = "Bastian Eichenberger"
 copyright = f"{year}, {author}"
-version = release = "0.1.2"
+version = release = "0.1.3"
 
 pygments_style = "trac"
 templates_path = ["."]

setup.py

@@ -11,7 +11,7 @@
 setup(
     # Description
     name="deepblink",
-    version="0.1.2",
+    version="0.1.3",
     license="MIT",
     description="Threshold independent detection and localization of diffraction-limited spots.",
     long_description_content_type="text/plain",