Merge pull request #9 from jmbhughes/make-ruff-pass

Make ruff pass

.github/workflows/CI.yml

@@ -33,11 +33,9 @@ jobs:
     - name: Test with pytest
       run: |
         pip install .
-        python setup.py pytest --addopts "--cov ."
-#    - name: Upload coverage to Codecov
-#      uses: codecov/codecov-action@v4
-#      env:
-#        CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}
-#      with:
-#        fail_ci_if_error: true
-#        verbose: true
+        coverage run --branch -m pytest tests
+    - name: Upload coverage reports to Codecov
+      uses: codecov/[email protected]
+      with:
+        token: ${{ secrets.CODECOV_TOKEN }}
+        slug: jmbhughes/overlappogram

README.md

@@ -7,6 +7,8 @@
 Overlappogram is a Python package for inverting overlappogram observations of the Sun, for examples MaGIXS observations
 or ECCCO observations.
 
+This code was originally written by Dyana Beabout.
+
 ## How to Use
 
 `python run_multiion_inversion.py ./path/to/image.fits ./path/to/config.toml`

configs/old/img_norm.toml

@@ -30,7 +30,7 @@ rhos = [1.0]
 # Inversion Time = 75.56018900871277  # my no shared memory thread pool executor with 11 max workers
 # Inversion Time = 77.73930597305298  # my process pool executor with copy on write for global with 11 max workers
 # Inversion Time = 88.20389604568481  # same as above with numpy having 2 threads
-# Inversion Time = 42.56954908370972  # same as above wtih numpy having 1 thread and selection='cyclic'
+# Inversion Time = 42.56954908370972  # same as above with numpy having 1 thread and selection='cyclic'
 
 # changing alpha can dramatically slow things
 # set alpha = 0.1 then Inversion Time = 1208.5097889900208

docs/conf.py

@@ -6,23 +6,22 @@
 # -- Project information -----------------------------------------------------
 # https://www.sphinx-doc.org/en/master/usage/configuration.html#project-information
 
-project = 'overlappogram'
-copyright = '2024, Dyana Beabout, J. Marcus Hughes'
-author = 'Dyana Beabout, J. Marcus Hughes'
-release = '0.0.1'
+project = "overlappogram"
+copyright = "2024, Dyana Beabout, J. Marcus Hughes"
+author = "Dyana Beabout, J. Marcus Hughes"
+release = "0.0.1"
 
 # -- General configuration ---------------------------------------------------
 # https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration
 
 extensions = []
 
-templates_path = ['_templates']
-exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store']
-
+templates_path = ["_templates"]
+exclude_patterns = ["_build", "Thumbs.db", ".DS_Store"]
 
 
 # -- Options for HTML output -------------------------------------------------
 # https://www.sphinx-doc.org/en/master/usage/configuration.html#options-for-html-output
 
-html_theme = 'alabaster'
-html_static_path = ['_static']
+html_theme = "alabaster"
+html_static_path = ["_static"]

experiment_scripts/ECCCO_multiion_inversion.py

@@ -10,14 +10,14 @@
 
 import numpy as np
 from astropy.io import fits
-#from overlappogram.inversion_field_angles_logts_ions import Inversion
+# from overlappogram.inversion_field_angles_logts_ions import Inversion
 from sklearn.linear_model import ElasticNet as enet
 
 from magixs_data_products import MaGIXSDataProducts
 from overlappogram.elasticnet_model import ElasticNetModel as model
 from overlappogram.inversion_field_angles import Inversion
 
-'''def calculate_weights(data, weights, sig_read, exp_time):
+"""def calculate_weights(data, weights, sig_read, exp_time):
     # Read image
     image_hdul = fits.open(data)
     image = image_hdul[0].data
@@ -31,90 +31,107 @@
     hdu = fits.PrimaryHDU(data = sample_weights)
     hdulist = fits.HDUList([hdu])
     hdulist.writeto(sample_weight_file, overwrite=True)
-    return sample_weight_file'''
-
-if __name__ == '__main__':
-
-    channel = 'all'
-    abund='feldman'
-    fwhm='0'
-    #psfs=[2,3,4,5]
-    #psfs=[1,2,3,4,5]
-    #psfs=[3,5]
-    psfs=[4]
+    return sample_weight_file"""
+
+if __name__ == "__main__":
+    channel = "all"
+    abund = "feldman"
+    fwhm = "0"
+    # psfs=[2,3,4,5]
+    # psfs=[1,2,3,4,5]
+    # psfs=[3,5]
+    psfs = [4]
     for psf in psfs:
+        mdp = MaGIXSDataProducts()
+        # PSA for magixs1
 
+        # Response function file path.
+        response_dir = "data/"
 
-        mdp=MaGIXSDataProducts()
-    #PSA for magixs1
-
-    # Response function file path.
-        response_dir ='data/'
-
-    # Response file.
-        #cube_file = response_dir + 'eccco_is_response_feldman_m_el_with_tables_lw_pm1230_'+str(psf)+'pix.fits'
+        # Response file.
+        # cube_file = response_dir + 'eccco_is_response_feldman_m_el_with_tables_lw_pm1230_'+str(psf)+'pix.fits'
         # cube_file = response_dir +'D16Feb2024_eccco_response_feldman_m_el_with_tables_s_i_slw_coopersun.fits'
-        cube_file = response_dir + 'D16Feb2024_eccco_response_feldman_m_el_with_tables_s_i_lw_coopersun.fits'
-        #cube_file = response_dir + "response_img_normalized.fits"
-        #cube_file = response_dir + 'D1Aug2023_eccco_response_feldman_m_el_with_tables_lw.fits'
-        #cube_file = response_dir + 'D14Feb2024_eccco_response_feldman_m_el_with_tables_lw.fits'
-
-        #weight_file = response_dir + 'oawave_eccco_is_lw.txt'
-
-    #Data directory and data file
-        data_dir ='data/'
-    #    summed_image  = data_dir + 'eccco_lw_forwardmodel_thermal_response_psf'+str(psf)+'pix_el_decon.fits'
-        summed_image  = data_dir+'eccco_is_lw_forwardmodel_thermal_response_psf'+str(psf)+'pix_el.fits'
-        #summed_img = data_dir+'forwardmodel_img_normalized.fits'
-        sample_weights_data = data_dir +'eccco_is_lw_forwardmodel_sample_weights_psf'+str(psf)+'pix_el.fits'
-        #sample_weights_data = data_dir + 'weights_img_normalized.fits'
-        #summed_image  = data_dir+'eccco_lw_forwardmodel_thermal_response_psf'+str(psf)+'pix_el.fits'
-        #sample_weights_data  = data_dir +'eccco_lw_forwardmodel_sample_weights_psf'+str(psf)+'pix_el.fits'
-
-    #The inversion directory is where the output will be written
-        inversion_dir = 'output/'
-
-    #Read in response,
+        cube_file = (
+            response_dir
+            + "D16Feb2024_eccco_response_feldman_m_el_with_tables_s_i_lw_coopersun.fits"
+        )
+        # cube_file = response_dir + "response_img_normalized.fits"
+        # cube_file = response_dir + 'D1Aug2023_eccco_response_feldman_m_el_with_tables_lw.fits'
+        # cube_file = response_dir + 'D14Feb2024_eccco_response_feldman_m_el_with_tables_lw.fits'
+
+        # weight_file = response_dir + 'oawave_eccco_is_lw.txt'
+
+        # Data directory and data file
+        data_dir = "data/"
+        #    summed_image  = data_dir + 'eccco_lw_forwardmodel_thermal_response_psf'+str(psf)+'pix_el_decon.fits'
+        summed_image = (
+            data_dir
+            + "eccco_is_lw_forwardmodel_thermal_response_psf"
+            + str(psf)
+            + "pix_el.fits"
+        )
+        # summed_img = data_dir+'forwardmodel_img_normalized.fits'
+        sample_weights_data = (
+            data_dir
+            + "eccco_is_lw_forwardmodel_sample_weights_psf"
+            + str(psf)
+            + "pix_el.fits"
+        )
+        # sample_weights_data = data_dir + 'weights_img_normalized.fits'
+        # summed_image  = data_dir+'eccco_lw_forwardmodel_thermal_response_psf'+str(psf)+'pix_el.fits'
+        # sample_weights_data  = data_dir +'eccco_lw_forwardmodel_sample_weights_psf'+str(psf)+'pix_el.fits'
+
+        # The inversion directory is where the output will be written
+        inversion_dir = "output/"
+
+        # Read in response,
 
         rsp_func_hdul = fits.open(cube_file)
 
         solution_fov_width = 2
         detector_row_range = [450, 455]
-        #detector_row_range = None
+        # detector_row_range = None
         field_angle_range = [-2160, 2160]
-        #field_angle_range = [-1260,1260]
+        # field_angle_range = [-1260,1260]
         # field_angle_range = None
 
-        rsp_dep_name = 'logt'
+        rsp_dep_name = "logt"
         rsp_dep_list = np.round((np.arange(57, 78, 1) / 10.0), decimals=1)
 
-    #smooth_over = 'spatial'
-        smooth_over = 'dependence'
-
-        inversion = Inversion(rsp_func_cube_file=cube_file,
-                          rsp_dep_name=rsp_dep_name, rsp_dep_list=rsp_dep_list,
-                          solution_fov_width=solution_fov_width,smooth_over=smooth_over,field_angle_range=field_angle_range)
-
-        #inversion.initialize_input_data(summed_image)#,image_mask_file)
-        #sample_weights_data = calculate_weights(summed_image, weight_file, 8., 1.)
-        #print(sample_weights_data)
-        #syntax (summed image, mask image, sample weights image)
+        # smooth_over = 'spatial'
+        smooth_over = "dependence"
+
+        inversion = Inversion(
+            rsp_func_cube_file=cube_file,
+            rsp_dep_name=rsp_dep_name,
+            rsp_dep_list=rsp_dep_list,
+            solution_fov_width=solution_fov_width,
+            smooth_over=smooth_over,
+            field_angle_range=field_angle_range,
+        )
+
+        # inversion.initialize_input_data(summed_image)#,image_mask_file)
+        # sample_weights_data = calculate_weights(summed_image, weight_file, 8., 1.)
+        # print(sample_weights_data)
+        # syntax (summed image, mask image, sample weights image)
         inversion.initialize_input_data(summed_image, None, sample_weights_data)
 
-        #new forweights
+        # new forweights
         # (photon convert file name:str, sigma read:float,exptime:float)
-        #error_parameters=(response_dir + 'oawave_eccco_is_lw.txt',8.,1.)
+        # error_parameters=(response_dir + 'oawave_eccco_is_lw.txt',8.,1.)
         alphas = [5]
-        rhos = [.1]
+        rhos = [0.1]
         for rho in rhos:
             for alpha in alphas:
-                enet_model = enet(alpha=alpha,
-                                  l1_ratio=rho,
-                                  max_iter=100000,
-                                  precompute=True,
-                                  positive=True,
-                                  fit_intercept=False,
-                                  selection='cyclic')
+                enet_model = enet(
+                    alpha=alpha,
+                    l1_ratio=rho,
+                    max_iter=100000,
+                    precompute=True,
+                    positive=True,
+                    fit_intercept=False,
+                    selection="cyclic",
+                )
                 inv_model = model(enet_model)
 
                 # regressor = SGDRegressor(penalty='elasticnet', alpha=alpha, l1_ratio=rho, fit_intercept=False)
@@ -126,10 +143,20 @@
                 basename = os.path.splitext(os.path.basename(summed_image))[0]
 
                 start = time.time()
-                inversion.multiprocessing_invert(inv_model, inversion_dir, output_file_prefix=basename,
-                #inversion.invert(inv_model, inversion_dir, output_file_prefix=basename,
-                            output_file_postfix='x'+str(solution_fov_width)+'_'+str(rho*10)+'_'+str(alpha)+'_wpsf' ,
-                                                 detector_row_range=detector_row_range,
-                                                 score=False)
+                inversion.multiprocessing_invert(
+                    inv_model,
+                    inversion_dir,
+                    output_file_prefix=basename,
+                    # inversion.invert(inv_model, inversion_dir, output_file_prefix=basename,
+                    output_file_postfix="x"
+                    + str(solution_fov_width)
+                    + "_"
+                    + str(rho * 10)
+                    + "_"
+                    + str(alpha)
+                    + "_wpsf",
+                    detector_row_range=detector_row_range,
+                    score=False,
+                )
                 end = time.time()
                 print("Inversion Time =", end - start)

experiment_scripts/compare_spectrally_pure.py

@@ -3,16 +3,19 @@
 import matplotlib.pyplot as plt
 import numpy as np
 from astropy.io import fits
-from scipy.signal import convolve2d
 from scipy.ndimage import gaussian_filter
 
 output_dir = "output/photons/plots/"
-ground_truth_path = "output/photons/ground_truth_spectrally_pure_data_cube_reshaped.fits"
+ground_truth_path = (
+    "output/photons/ground_truth_spectrally_pure_data_cube_reshaped.fits"
+)
 dep_ref = "data/ECCCO_speedtest_runs/eccco_sp_puremaps_psf4pix_inelectrons_cm3perspersr_with_tables.fits"
-output_paths = ["output/photons/combined_ECCCO_trim_sw_lw_s_i_scaled_spectrally_pure_data_cube_x2_1.0_0.1_wpsf.fits",
-                "output/photons/combined_ECCCO_trim_sw_lw_s_i_scaled_spectrally_pure_data_cube_x2_1.0_0.01_wpsf.fits",
-                "output/photons/combined_ECCCO_trim_sw_lw_s_i_scaled_spectrally_pure_data_cube_x2_1.0_0.2_wpsf.fits",
-                "output/photons/combined_ECCCO_trim_sw_lw_s_i_scaled_spectrally_pure_data_cube_x2_1.0_0.005_wpsf.fits"]
+output_paths = [
+    "output/photons/combined_ECCCO_trim_sw_lw_s_i_scaled_spectrally_pure_data_cube_x2_1.0_0.1_wpsf.fits",
+    "output/photons/combined_ECCCO_trim_sw_lw_s_i_scaled_spectrally_pure_data_cube_x2_1.0_0.01_wpsf.fits",
+    "output/photons/combined_ECCCO_trim_sw_lw_s_i_scaled_spectrally_pure_data_cube_x2_1.0_0.2_wpsf.fits",
+    "output/photons/combined_ECCCO_trim_sw_lw_s_i_scaled_spectrally_pure_data_cube_x2_1.0_0.005_wpsf.fits",
+]
 
 with fits.open(dep_ref) as hdul:
     dep_table = hdul[2].data
@@ -31,12 +34,17 @@
 
         # initial image comparison
         fig, axs = plt.subplots(ncols=3, figsize=(30, 10))
-        im1 = axs[0].imshow(gt, vmin=vmin, vmax=vmax, origin='lower')
+        im1 = axs[0].imshow(gt, vmin=vmin, vmax=vmax, origin="lower")
         axs[0].set_title("Ground truth")
-        axs[1].imshow(output_data[i], vmin=vmin, vmax=vmax, origin='lower')
+        axs[1].imshow(output_data[i], vmin=vmin, vmax=vmax, origin="lower")
         axs[1].set_title("Output")
-        im2 = axs[2].imshow(gt - output_data[i],
-                            origin='lower', cmap='seismic', vmin=-interval, vmax=interval)
+        im2 = axs[2].imshow(
+            gt - output_data[i],
+            origin="lower",
+            cmap="seismic",
+            vmin=-interval,
+            vmax=interval,
+        )
         axs[2].set_title("Ground truth - output")
         for ax in axs:
             ax.set_aspect(0.5)
@@ -48,8 +56,8 @@
 
         # scatter plots
         fig, ax = plt.subplots()
-        ax.plot(gt.flatten(), output_data[i].flatten(), '.', ms=1)
-        ax.plot([0, np.max(ground_truth[i])], [0, np.max(ground_truth[i])], 'r-')
+        ax.plot(gt.flatten(), output_data[i].flatten(), ".", ms=1)
+        ax.plot([0, np.max(ground_truth[i])], [0, np.max(ground_truth[i])], "r-")
         ax.set_title(dep_table[i][1])
         ax.set_xlabel("Ground truth")
         ax.set_ylabel("Unfolded recreation")
@@ -59,8 +67,8 @@
         # histogram
         Z, xedges, yedges = np.histogram2d(gt.flatten(), output_data[i].flatten(), 50)
         fig, ax = plt.subplots()
-        im = ax.pcolormesh(xedges, yedges, np.log10(Z.T + 1E-3))
-        ax.plot([0, np.max(ground_truth[i])], [0, np.max(ground_truth[i])], 'r-')
+        im = ax.pcolormesh(xedges, yedges, np.log10(Z.T + 1e-3))
+        ax.plot([0, np.max(ground_truth[i])], [0, np.max(ground_truth[i])], "r-")
         ax.set_title(dep_table[i][1])
         fig.colorbar(im, ax=ax)
         fig.savefig(output_dir + f"histogram_{dep_table[i][1]}_{short_path}.png")