Force bool to float32, add explicit error message

eye_patch/logging.py

@@ -0,0 +1,45 @@
+from __future__ import annotations
+
+import logging
+
+# Create logger
+logging.captureWarnings(True)
+logger = logging.getLogger("eye-patch")
+logger.setLevel(logging.INFO)
+
+# Create console handler and set level to debug
+ch = logging.StreamHandler()
+ch.setLevel(logging.INFO)
+
+
+class CustomFormatter(logging.Formatter):
+    """A custom logger formatter"""
+
+    grey = "\x1b[38;20m"
+    blue = "\x1b[34;20m"
+    green = "\x1b[32;20m"
+    yellow = "\x1b[33;20m"
+    red = "\x1b[31;20m"
+    bold_red = "\x1b[31;1m"
+    reset = "\x1b[0m"
+    format_str = "%(asctime)s.%(msecs)03d %(module)s - %(funcName)s: %(message)s"
+
+    FORMATS = {  # noqa: RUF012
+        logging.DEBUG: f"{blue}%(levelname)s{reset} {format_str}",
+        logging.INFO: f"{green}%(levelname)s{reset} {format_str}",
+        logging.WARNING: f"{yellow}%(levelname)s{reset} {format_str}",
+        logging.ERROR: f"{red}%(levelname)s{reset} {format_str}",
+        logging.CRITICAL: f"{bold_red}%(levelname)s{reset} {format_str}",
+    }
+
+    def format(self, record: logging.LogRecord) -> str:
+        log_fmt = self.FORMATS.get(record.levelno)
+        formatter = logging.Formatter(log_fmt, "%Y-%m-%d %H:%M:%S")
+        return formatter.format(record)
+
+
+# Add formatter to ch
+ch.setFormatter(CustomFormatter())
+
+# Add ch to logger
+logger.addHandler(ch)

eye_patch/masking.py

@@ -4,7 +4,6 @@
 
 from __future__ import annotations
 
-import logging
 from argparse import ArgumentParser
 from pathlib import Path
 from typing import NamedTuple, TypeAlias
@@ -26,6 +25,7 @@
 from scipy.ndimage import binary_fill_holes, label, maximum_filter, minimum_filter
 from scipy.signal import fftconvolve
 
+from eye_patch.logging import logger
 from eye_patch.naming import FITSMaskNames, create_fits_mask_names
 
 # Add explicit export so mypy on tests is ok
@@ -37,8 +37,6 @@
 # during fits file creation.
 MaskLike: TypeAlias = NDArray[np.floating]
 
-logger = logging.getLogger("__name__")
-
 
 class MaskingOptions(BaseOptions):
     """Contains options for the creation of clean masks from some subject
@@ -918,7 +916,7 @@ def create_snr_mask_from_fits(
     logger.info(f"Writing {mask_names.mask_fits}")
     fits.writeto(
         filename=mask_names.mask_fits,
-        data=mask_data,
+        data=mask_data.astype(np.float32),
         header=fits_header,
         overwrite=overwrite,
     )
@@ -967,6 +965,12 @@ def convolve_image_by_scale(
     logger.info(f"Generating gaussian kernel for {scale=} {fwhm=:.3f} {sigma=:.3f}")
 
     pix_sigma = int(sigma * 5)
+    if pix_sigma < 1:
+        # linspace can only take integer inputs, and if sigma is too small then this array comes
+        # out as length zero.
+        msg = f"{scale=} is too small and an appropriately sized kernel can not be formed. Consider removing it. "
+        raise ValueError(msg)
+
     x = np.linspace(0, pix_sigma, pix_sigma)
     y = np.linspace(0, pix_sigma, pix_sigma)