Revert "filter provided opd table by month"

This reverts commit 2eb1fe3.
BradleySappington · Feb 13, 2024 · 96468bf · 96468bf
1 parent 461df7e
commit 96468bf
Showing 1 changed file with 37 additions and 79 deletions.
diff --git a/webbpsf/trending.py b/webbpsf/trending.py
@@ -339,12 +339,9 @@ def wfe_histogram_plot(
     pre_or_post = []
     for row in opdtable1:
         if download_opds:
-            full_file_path = os.path.join(
-                webbpsf.utils.get_webbpsf_data_path(),
-                "MAST_JWST_WSS_OPDs",
-                row["fileName"],
-            )
-        if "rms_wfe" not in opdtable1.colnames:
+            full_file_path = os.path.join(webbpsf.utils.get_webbpsf_data_path(), 'MAST_JWST_WSS_OPDs', row['fileName'])
+        if 'rms_wfe' not in opdtable1.colnames:
+
             if ote_only == False:
                 rmses.append(fits.getheader(full_file_path, ext=1)["RMS_WFE"])
             elif ote_only == True:
@@ -367,10 +364,10 @@ def wfe_histogram_plot(
         mjds = opdtable1["date_obs_mjd"]
         pre_or_post.append(webbpsf.mast_wss.infer_pre_or_post_correction(row))
 
-    where_pre = ["pre" in a for a in pre_or_post]
-    where_post = ["post" in a for a in pre_or_post]
+    where_pre = ['pre' in a for a in pre_or_post]
+    where_post = ['post' in a for a in pre_or_post]
 
-    dates = astropy.time.Time(opdtable1["date"], format="isot")
+    dates = astropy.time.Time(opdtable1['date'], format='isot')
 
     # Interpolate those RMSes into an even grid over time
     interp_fn = scipy.interpolate.interp1d(mjds, rmses, kind="linear")
@@ -385,21 +382,14 @@ def wfe_histogram_plot(
         figsize=(16, 10), nrows=nrows, gridspec_kw={"hspace": hspace}
     )
 
-    ms = 14  # markersize
+    ms = 14 #markersize
 
-    axes[0].plot_date(
-        dates.plot_date,
-        np.asarray(rmses) * 1e3,
-        ".",
-        ms=ms,
-        ls="-",
-        label="Sensing visit",
-    )
+    axes[0].plot_date(dates.plot_date, np.asarray(rmses)*1e3, '.', ms=ms, ls='-', label='Sensing visit')
     axes[0].xaxis.set_major_locator(matplotlib.dates.DayLocator(bymonthday=[1]))
     axes[0].xaxis.set_minor_locator(matplotlib.dates.DayLocator(interval=1))
-    axes[0].tick_params("x", length=10, rotation=30)
+    axes[0].tick_params('x', length=10, rotation=30)
 
-    if mark_corrections == "lines":
+    if mark_corrections=='lines':
         # Add vertical lines for corrections
         icorr = 0
         for i, idate in enumerate(where_post):
@@ -414,18 +404,12 @@ def wfe_histogram_plot(
                 if icorr == 0:
                     plot.set_label("Corrections")
                     icorr += 1
-    elif mark_corrections == "triangles":
-        yval = (np.asarray(rmses) * 1e3).max() * 1.01
-        axes[0].scatter(
-            dates[where_post].plot_date,
-            np.ones(np.sum(where_post)) * yval,
-            marker="v",
-            s=100,
-            color="limegreen",
-            label="Corrections",
-        )
-    elif mark_corrections == "arrows":
-        rms_nm = np.asarray(rmses) * 1e3
+    elif mark_corrections=='triangles':
+        yval = (np.asarray(rmses)*1e3).max() *1.01
+        axes[0].scatter(dates[where_post].plot_date, np.ones(np.sum(where_post))*yval,
+                        marker='v', s=100, color='limegreen', label='Corrections')
+    elif mark_corrections=='arrows':
+        rms_nm =  np.asarray(rmses)*1e3
 
         sub_height = fig.get_figheight() / (nrows + hspace)
         plot_size_points = np.asarray([fig.get_figwidth(), sub_height]) * fig.dpi
@@ -434,16 +418,9 @@ def wfe_histogram_plot(
             np.diff(axes[0].get_ylim())[0],
         ]
 
-        yoffset = (1.2 * ms) * plot_size_data[1] / plot_size_points[1]
-        axes[0].scatter(
-            dates[where_post].plot_date,
-            rms_nm[where_post] + yoffset,
-            marker="v",
-            s=100,
-            color="limegreen",
-            label="Corrections",
-            zorder=99,
-        )
+        yoffset =  (1.2*ms) * plot_size_data[1] / plot_size_points[1]
+        axes[0].scatter(dates[where_post].plot_date, rms_nm[where_post] + yoffset,
+                        marker='v', s=100, color='limegreen', label='Corrections', zorder=99)
 
         yoffsets = [
             0.6 * ms * plot_size_data[0] / plot_size_points[0],
@@ -480,14 +457,11 @@ def wfe_histogram_plot(
 
     nbins = 100
     binwidth = 1
-    minbin = np.round(np.min(interp_rmses * 1e3) - binwidth)
-    maxbin = np.round(np.max(interp_rmses * 1e3) + binwidth)
+    minbin = np.round( np.min(interp_rmses*1e3) - binwidth)
+    maxbin = np.round( np.max(interp_rmses*1e3) + binwidth)
 
-    axes[1].set_title(
-        f"{fig_title} WFE Histogram from {start_date.isot[0:10]} to {end_date.isot[0:10]}",
-        fontsize=14,
-        fontweight="bold",
-    )
+    axes[1].set_title(f"{fig_title} WFE Histogram from {start_date.isot[0:10]} to {end_date.isot[0:10]}",
+                     fontsize=14, fontweight='bold')
 
     hist_values = axes[1].hist(
         interp_rmses * 1e3,
@@ -530,16 +504,12 @@ def wfe_histogram_plot(
     if thresh:
         for i in [1]:
             if thresh <= xmax:
-                axes[i].axvline(thresh, color="C2", linestyle="dashed")
-            fractime = (interp_rmses * 1e3 < thresh).sum() / len(interp_rmses)
-            axes[i].text(
-                xmin + 0.68 * (xmax - xmin),
-                0.65 * ymax,
-                f"{fractime*100:.1f}% of the time has \nmeasured {ylabel} WFE < {thresh}",
-                color="C2",
-                fontweight="bold",
-                fontsize=14,
-            )
+                axes[i].axvline(thresh, color='C2', linestyle='dashed')
+            fractime = (interp_rmses*1e3 < thresh).sum()/len(interp_rmses)
+            axes[i].text(xmin+0.68*(xmax-xmin), 0.65*ymax,
+                     f"{fractime*100:.1f}% of the time has \nmeasured {ylabel} WFE < {thresh}", color='C2',
+                    fontweight='bold', fontsize=14)
+
 
     # Add vertical lines for dates of PID observations
     if pid:
@@ -1357,6 +1327,7 @@ def filter_opdtable_for_month(year, mon, opdtable):
     to the first one
     """
     start_date, end_date = get_month_start_end(year, mon)
+
     # Start a little early, such that we are going to have at least 1 WFS before the start date
     pre_start_date = astropy.time.Time(start_date) - astropy.time.TimeDelta(4 * u.day)
     opdtable = webbpsf.mast_wss.filter_opd_table(
@@ -1447,16 +1418,9 @@ def get_dates_for_pid(pid, project="jwst"):
         return
 
 
-def monthly_trending_plot(
-    year,
-    month,
-    verbose=True,
-    instrument="NIRCam",
-    filter="F200W",
-    vmax=200,
-    pid=None,
-    opdtable=None,
-):
+
+
+def monthly_trending_plot(year, month, verbose=True, instrument='NIRCam', filter='F200W', vmax=200, pid=None, opdtable=None):
     """Make monthly trending plot showing OPDs, mirror moves, RMS WFE, and the resulting PSF EEs
 
     year, month : integers
@@ -1626,16 +1590,10 @@ def basic_show_image(image, ax, vmax=0.3, nanmask=1):
 
     #### Plot 1: Wavefront Error
 
-    axes[0].plot_date(
-        dates_array.plot_date,
-        rms_obs * 1e9,
-        color="C1",
-        ls="-",
-        label="Observatory WFE at NIRCam NRCA3",
-    )
-    axes[0].plot_date(
-        dates_array.plot_date, rms_ote * 1e9, color="C0", ls="-", label="Telescope WFE"
-    )
+    axes[0].plot_date(dates_array.plot_date, rms_obs * 1e9,
+                      color='C1', ls='-', label='Observatory WFE at NIRCam NRCA3')
+    axes[0].plot_date(dates_array.plot_date, rms_ote * 1e9,
+                      color='C0', ls='-', label='Telescope WFE')
 
     for ax in axes:
         for corr_date in correction_times: