zairving · zairving · Oct 24, 2025 · Oct 6, 2025 · Oct 6, 2025 · Oct 6, 2025
diff --git a/docs/README.md b/docs/README.md
@@ -1,6 +1,6 @@
 # Documentation
 
-To generate the Sphinx documentation for `opticam_new`, install the package with its documentation requirements:
+To generate the Sphinx documentation for `opticam`, install the package with its documentation requirements:
 
 ```
 pip install -e .[docs]

diff --git a/docs/tutorials/applying_corrections.ipynb b/docs/tutorials/applying_corrections.ipynb
diff --git a/docs/tutorials/backgrounds.ipynb b/docs/tutorials/backgrounds.ipynb
diff --git a/docs/tutorials/finders.ipynb b/docs/tutorials/finders.ipynb
diff --git a/docs/tutorials/local_backgrounds.ipynb b/docs/tutorials/local_backgrounds.ipynb
diff --git a/docs/tutorials/reduction.ipynb b/docs/tutorials/reduction.ipynb
diff --git a/docs/tutorials/timing_methods.ipynb b/docs/tutorials/timing_methods.ipynb
diff --git a/opticam/__init__.py b/opticam/__init__.py
@@ -4,7 +4,7 @@
 from opticam.finders import DefaultFinder
 from opticam.reducer import Reducer
 from opticam.analysis.differential_photometer import DifferentialPhotometer
-from opticam.photometers import SimplePhotometer, OptimalPhotometer
+from opticam.photometers import AperturePhotometer, OptimalPhotometer
 from opticam.correctors.flat_field_corrector import FlatFieldCorrector
 from opticam.analysis.analyzer import Analyzer
 from opticam.utils.generate import generate_flats, generate_observations, generate_gappy_observations

diff --git a/opticam/align.py b/opticam/align.py
@@ -106,7 +106,6 @@ def align_batch(
         data = np.asarray(
             get_data(
                 file,
-                gains[file],
                 flat_corrector=flat_corrector,
                 rebin_factor=rebin_factor,
                 return_error=False,
@@ -125,8 +124,8 @@ def align_batch(
             logger.info(f'[OPTICAM] No sources detected in {file}: {e}.')
             continue
 
-        if len(coords) < len(reference_coords):
-            logger.info(f'[OPTICAM] n_alignment_sources={len(reference_coords)} but only {len(coords)} sources detected in {file}. Skipping.')
+        if len(coords) < n_alignment_sources and transform_type == 'translation':
+            logger.info(f'[OPTICAM] {len(coords)} sources detected in {file} but n_alignment_sources={n_alignment_sources} and transform_type="translation". Skipping. To attempt to align images in which fewer than n_alignment_sources are detected, try transform_type="affine".')
             continue
 
         if transform_type == 'translation':

diff --git a/opticam/analysis/analyzer.py b/opticam/analysis/analyzer.py
@@ -140,15 +140,15 @@ def rebin_light_curves(
 
     def plot_light_curves(
         self,
-        title: str | None = None,
+        show_gtis: bool = False,
         ) -> Figure:
         """
         Plot the light curves.
 
         Parameters
         ----------
-        title : str | None, optional
-            The figure title, by default `None`.
+        show_gtis : bool, optional
+            Whether to highlight the Good Time Intervals on the light curve plot, by default `False`.
 
         Returns
         -------
@@ -170,9 +170,7 @@ def plot_light_curves(
             axes = [axes]
 
         for i, (fltr, lc) in enumerate(self.light_curves.items()):
-
             for lc_segment in lc.split_by_gti(min_points=1):
-
                 t = (np.asarray(lc_segment.time) - self.t_ref) * 86400
 
                 axes[i].errorbar(
@@ -183,6 +181,7 @@ def plot_light_curves(
                     linestyle='none',
                     ecolor='grey',
                     elinewidth=1,
+                    alpha=.5,
                     )
                 axes[i].step(
                     t,
@@ -202,12 +201,24 @@ def plot_light_curves(
                 va='top',
                 ha='right',
             )
+
+            if show_gtis:
+                gti = 86400 * (np.asarray(lc.gti) - self.t_ref)
+                for j in range(gti.shape[0] - 1):
+                    stop = gti[j][1]
+                    start = gti[j + 1][0]
+
+                    axes[i].fill_betweenx(
+                        axes[i].set_ylim(),
+                        stop,
+                        start,
+                        color='grey',
+                        edgecolor='none',
+                        alpha=.5,
+                    )
 
         axes[-1].set_xlabel(f'Time from BMJD {self.t_ref:.4f} [s]', fontsize='large')
-        axes[len(self.light_curves) // 2].set_ylabel('Normalised flux', fontsize='large')
-
-        if title is not None:
-            axes[0].set_title(title)
+        axes[len(self.light_curves) // 2].set_ylabel('Normalized flux', fontsize='large')
 
         for ax in axes:
             ax.minorticks_on()
@@ -307,7 +318,9 @@ def phase_bin_light_curves(
         period: Quantity,
         t0: float | None = None,
         n_bins: int = 10,
-        plot=True,
+        plot: bool = True,
+        subplot : bool = True,
+        sharey: bool = False,
         ) -> Dict[str, Dict[str, NDArray]]:
         """
         Phase bin each light curve using the given period.
@@ -323,6 +336,11 @@ def phase_bin_light_curves(
             The number of phase bins, by default 10.
         plot : bool, optional
             Whether to plot the phase binned light curves, by default True.
+        subplot : bool, optional
+            Whether to plot filters in separate subplots, by default True.
+        sharey : bool, optional
+            Whether to render the plot with a common y-axis (useful for directly comparing amplitudes), by default
+            False. Only used if `plot=True` and `subplot=True`.
 
         Returns
         -------
@@ -367,46 +385,77 @@ def phase_bin_light_curves(
             }
 
         if plot:
-            fig, axes = plt.subplots(
-                tight_layout=True,
-                nrows=len(self.light_curves),
-                sharex=True,
-                figsize=(6.4, (0.5 * len(self.light_curves) * 4.8)),
-                gridspec_kw={'hspace': 0.},
-                )
-
-            for i, (fltr, lc) in enumerate(self.light_curves.items()):
-                axes[i].errorbar(
-                    np.append(results[fltr]['phase'], results[fltr]['phase'] + 1),
-                    np.append(results[fltr]['flux'], results[fltr]['flux']),
-                    np.append(results[fltr]['flux error'], results[fltr]['flux error']),
-                    marker='none',
-                    linestyle='none',
-                    color=colors[fltr],
-                    ecolor='grey',
-                    elinewidth=1,
+            if subplot:
+                fig, axes = plt.subplots(
+                    tight_layout=True,
+                    nrows=len(self.light_curves),
+                    sharex=True,
+                    sharey=sharey,
+                    figsize=(6.4, (0.5 * len(self.light_curves) * 4.8)),
+                    gridspec_kw={'hspace': 0.},
                     )
-                axes[i].step(
-                    np.append(results[fltr]['phase'], results[fltr]['phase'] + 1),
-                    np.append(results[fltr]['flux'], results[fltr]['flux']),
-                    where='mid',
-                    color=colors[fltr],
-                    lw=1,
-                )
-                axes[i].text(
-                    .95,
-                    .9,
-                    fltr,
-                    fontsize='large',
-                    va='top',
-                    ha='right',
-                    transform=axes[i].transAxes,
-                )
-
-            axes[-1].set_xlabel('Phase')
-            axes[len(self.light_curves) // 2].set_ylabel('Normalized flux')
-
-            for ax in axes.flatten():
+
+                for i, (fltr, lc) in enumerate(self.light_curves.items()):
+                    axes[i].errorbar(
+                        np.append(results[fltr]['phase'], results[fltr]['phase'] + 1),
+                        np.append(results[fltr]['flux'], results[fltr]['flux']),
+                        np.append(results[fltr]['flux error'], results[fltr]['flux error']),
+                        marker='none',
+                        linestyle='none',
+                        color=colors[fltr],
+                        ecolor='grey',
+                        elinewidth=1,
+                        )
+                    axes[i].step(
+                        np.append(results[fltr]['phase'], results[fltr]['phase'] + 1),
+                        np.append(results[fltr]['flux'], results[fltr]['flux']),
+                        where='mid',
+                        color=colors[fltr],
+                        lw=1,
+                    )
+                    axes[i].text(
+                        .95,
+                        .9,
+                        fltr,
+                        fontsize='large',
+                        va='top',
+                        ha='right',
+                        transform=axes[i].transAxes,
+                    )
+
+                axes[-1].set_xlabel('Phase', fontsize='large')
+                axes[len(self.light_curves) // 2].set_ylabel('Normalized flux', fontsize='large')
+
+                for ax in axes.flatten():
+                    ax.minorticks_on()
+                    ax.tick_params(which='both', direction='in', top=True, right=True)
+            else:
+                fig, ax = plt.subplots(
+                    tight_layout=True,
+                    )
+
+                for i, (fltr, lc) in enumerate(self.light_curves.items()):
+                    ax.errorbar(
+                        np.append(results[fltr]['phase'], results[fltr]['phase'] + 1),
+                        np.append(results[fltr]['flux'], results[fltr]['flux']),
+                        np.append(results[fltr]['flux error'], results[fltr]['flux error']),
+                        marker='none',
+                        linestyle='none',
+                        color=colors[fltr],
+                        ecolor='grey',
+                        elinewidth=1,
+                        )
+                    ax.step(
+                        np.append(results[fltr]['phase'], results[fltr]['phase'] + 1),
+                        np.append(results[fltr]['flux'], results[fltr]['flux']),
+                        where='mid',
+                        color=colors[fltr],
+                        label=fltr,
+                    )
+
+                ax.set_xlabel('Phase', fontsize='large')
+                ax.set_ylabel('Normalized flux', fontsize='large')
+                ax.legend(fontsize='large')
                 ax.minorticks_on()
                 ax.tick_params(which='both', direction='in', top=True, right=True)
 
@@ -679,14 +728,13 @@ def validate_light_curves(
             counts /= mean_flux
             counts_err /= mean_flux
 
-            # convert DataFrame to Lightcurve
             validated_light_curves[fltr] = Lightcurve(
                 time,
                 counts,
                 err=counts_err,
                 gti=gtis,
                 err_dist='gauss',
-                )
+                ).sort()
 
     return sort_filters(validated_light_curves)