fixed broken imports

src/aspired/__init__.py

@@ -27,4 +27,6 @@
     "spectral_reduction",
     "standard_list",
     "util",
+    "flux_calibration",
+    "wavelength_calibration",
 ]

src/aspired/flux_calibration.py

@@ -498,7 +498,7 @@ def load_standard(
     def inspect_standard(
         self,
         display: bool = True,
-        rendererLstr="default",
+        renderer: str = "default",
         width: int = 1280,
         height: int = 720,
         return_jsonstring: bool = False,
@@ -1047,7 +1047,7 @@ def get_sensitivity(
         sens_deg: int = 7,
         use_continuum: bool = False,
         recompute_continuum: bool = False,
-        *args,
+        *args: str,
     ):
         """
         The sensitivity curve is computed by dividing the true values by the

src/aspired/image_reduction.py

@@ -20,7 +20,7 @@
 
 from .util import bfixpix, create_bad_pixel_mask, create_cutoff_mask
 
-__all__ = ["ImageReduction", "Reducer"]
+__all__ = ["ImageReduction", "ImageReducer"]
 
 
 class ImageReducer:
@@ -2960,7 +2960,7 @@ def list_files(self):
             print(i)
 
 
-class ImageReducer(Reducer):
+class ImageReduction(ImageReducer):
     """
     Wrapper class of ImageReduction that will be deprecated in the next
     release.

src/aspired/spectrum_oneD.py

@@ -4,9 +4,10 @@
 import os
 from typing import Callable, Union
 
+import astropy
 import numpy as np
 from astropy.io import fits
-from rascal import Calibrator
+from rascal.calibrator import Calibrator
 from scipy import interpolate as itp
 
 __all__ = ["SpectrumOneD"]
@@ -94,10 +95,8 @@ def __init__(
             self.handler = logging.StreamHandler()
         else:
             if log_file_name == "default":
-                log_file_name = "{}_{}.log".format(
-                    logger_name,
-                    datetime.datetime.now().strftime("%Y_%m_%d_%H_%M_%S"),
-                )
+                t_str = datetime.datetime.now().strftime("%Y_%m_%d_%H_%M_%S")
+                log_file_name = "{logger_name}_{t_str}.log"
             # Save log to file
             if log_file_folder == "default":
                 log_file_folder = ""
@@ -114,7 +113,7 @@ def __init__(
         # spectrum ID
         if spec_id is None:
             self.spec_id = 0
-        elif type(spec_id) == int:
+        elif isinstance(spec_id, int):
             self.spec_id = spec_id
         else:
             error_msg = (
@@ -481,7 +480,7 @@ def __init__(
         for d1, d2 in zip(self.hdu_name.values(), number_of_hdus.values()):
             self.n_hdu[d1] = d2
 
-    def merge(self, spectrum_oned: SpectrumOneD, overwrite: bool = False):
+    def merge(self, spectrum_oned, overwrite: bool = False):
         """
         This function copies all the info from the supplied spectrum_oned to
         this one, including the spec_id.
@@ -525,10 +524,10 @@ def add_spectrum_header(
         """
 
         if header is not None:
-            if type(header) == fits.Header:
+            if isinstance(header, fits.Header):
                 self.spectrum_header = header
                 self.logger.info("spectrum_header is stored.")
-            elif type(header[0]) == fits.Header:
+            elif isinstance(header[0], fits.Header):
                 self.spectrum_header = header[0]
                 self.logger.info("spectrum_header is stored.")
             else:
@@ -564,10 +563,10 @@ def add_standard_header(
         """
 
         if header is not None:
-            if type(header) == fits.Header:
+            if isinstance(header, fits.Header):
                 self.standard_header = header
                 self.logger.info("standard_header is stored.")
-            elif type(header[0]) == fits.Header:
+            elif isinstance(header[0], fits.Header):
                 self.standard_header = header[0]
                 self.logger.info("standard_header is stored.")
             else:
@@ -857,14 +856,14 @@ def remove_variances(self):
         self.var = None
 
     def add_line_spread_profile_upsampled(
-        self, line_spread_profile_upsampled: astropy.model
+        self, line_spread_profile_upsampled: astropy.modeling.Fittable1DModel
     ):
         """
         Add the empirical line spread profile as measured from the upsampled image.
 
         Parameters
         ----------
-        profile_func: a fitted astropy.model
+        profile_func: a fitted astropy.modeling.Fittable1DModel
             The fitted trace profile.
         """
 
@@ -877,13 +876,15 @@ def remove_line_spread_profile_upsampled(self):
 
         self.line_spread_profile_upsampled = None
 
-    def add_line_spread_profile(self, line_spread_profile: astropy.model):
+    def add_line_spread_profile(
+        self, line_spread_profile: astropy.modeling.Fittable1DModel
+    ):
         """
         Add the empirical line spread profile as measured.
 
         Parameters
         ----------
-        profile_func: a fitted astropy.model
+        profile_func: a fitted astropy.modeling.Fittable1DModel
             The fitted trace profile.
         """
 
@@ -902,7 +903,7 @@ def add_profile_func(self, profile_func: Callable):
 
         Parameters
         ----------
-        profile_func: a fitted astropy.model
+        profile_func: a fitted astropy.modeling.Fittable1DModel
             The fitted trace profile.
         """
 

src/aspired/twodspec.py

@@ -32,7 +32,7 @@
     optimal_extraction_marsh89,
     tophat_extraction,
 )
-from .image_reduction import ImageReduction, Reducer
+from .image_reduction import ImageReducer, ImageReduction
 from .line_spread_function import (
     build_line_spread_profile,
     get_line_spread_function,
@@ -56,7 +56,7 @@ def __init__(
             fits.hdu.hdulist.HDUList,
             fits.hdu.hdulist.PrimaryHDU,
             fits.hdu.hdulist.ImageHDU,
-            Reducer,
+            ImageReducer,
             ImageReduction,
         ] = None,
         header: fits.Header = None,
@@ -233,7 +233,7 @@ def __init__(
             "SEEDIMM",
             "DSEEING",
         ]
-        # AEPOSURE is the average exposure time computed in Reducer
+        # AEPOSURE is the average exposure time computed in ImageReducer
         # it is the effective exposure time suitable for computing
         # the sensitivity curve.
         self.exptime_keyword = [
@@ -262,14 +262,14 @@ def add_data(
             fits.hdu.hdulist.PrimaryHDU,
             fits.hdu.hdulist.ImageHDU,
             CCDData,
-            Reducer,
+            ImageReducer,
             ImageReduction,
         ],
         header: fits.Header = None,
     ):
         """
         Adding the 2D image data to be processed. The data can be a 2D numpy
-        array, an AstroPy ImageHDU/Primary HDU object or an Reducer
+        array, an AstroPy ImageHDU/Primary HDU object or an ImageReducer
         object.
 
         parameters
@@ -324,10 +324,10 @@ def add_data(
             self.bad_mask = create_bad_pixel_mask(self.img)[0]
             self.logger.info("A CCDData is loaded as data.")
 
-        # If it is an Reducer object
-        elif isinstance(data, (Reducer, ImageReduction)):
+        # If it is an ImageReducer object
+        elif isinstance(data, (ImageReducer, ImageReduction)):
             # If the data is not reduced, reduce it here. Error handling is
-            # done by the Reducer class
+            # done by the ImageReducer class
             if data.image_fits is None:
                 data.create_image_fits()
 
@@ -343,7 +343,7 @@ def add_data(
 
             else:
                 self.logger.warning(
-                    "Arc frame is not in the Reducer "
+                    "Arc frame is not in the ImageReducer "
                     "object, please supplied manually if you wish to perform "
                     "wavelength calibration."
                 )
@@ -380,7 +380,7 @@ def add_data(
             error_msg = (
                 "Please provide a numpy array, an "
                 + "astropy.io.fits.hdu.image.PrimaryHDU object "
-                + "or an Reducer object."
+                + "or an ImageReducer object."
             )
             self.logger.critical(error_msg)
             raise TypeError(error_msg)
@@ -1142,7 +1142,7 @@ def add_bad_mask(
 
         Parameters
         ----------
-        bad_mask: numpy.ndarray, PrimaryHDU/ImageHDU, Reducer, str
+        bad_mask: numpy.ndarray, PrimaryHDU/ImageHDU, ImageReducer, str
             The bad pixel mask of the image, make sure it is of the same size
             as the image and the right orientation.
 
@@ -1245,7 +1245,7 @@ def add_arc(
 
         Parameters
         ----------
-        arc: numpy.ndarray, PrimaryHDU/ImageHDU, Reducer, str
+        arc: numpy.ndarray, PrimaryHDU/ImageHDU, ImageReducer, str
             The image of the arc image.
         header: FITS header (deafult: None)
             An astropy.io.fits.Header object. This is not used if arc is
@@ -1345,7 +1345,7 @@ def add_arc(
                 "astropy.io.fits.hdu.image.PrimaryHDU object, an "
                 "astropy.io.fits.hdu.image.ImageHDU object, an "
                 "astropy.io.fits.HDUList object, or an "
-                "aspired.Reducer object."
+                "aspired.ImageReducer object."
             )
             self.logger.critical(error_msg)
             raise TypeError(error_msg)

src/aspired/wavelength_calibration.py

@@ -2,6 +2,7 @@
 import datetime
 import logging
 import os
+from typing import Union
 
 import numpy as np
 from plotly import graph_objects as go
@@ -95,10 +96,8 @@ def __init__(
             self.handler = logging.StreamHandler()
         else:
             if log_file_name == "default":
-                log_file_name = "{}_{}.log".format(
-                    logger_name,
-                    datetime.datetime.now().strftime("%Y_%m_%d_%H_%M_%S"),
-                )
+                t_str = datetime.datetime.now().strftime("%Y_%m_%d_%H_%M_%S")
+                log_file_name = f"{logger_name}_{t_str}.log"
             # Save log to file
             if log_file_folder == "default":
                 log_file_folder = ""