adding in ACS HRC filters and enhancing the filter plotting routine

beast/plotting/plot_filters.py

@@ -16,7 +16,7 @@ def plot_filters(
  filter_names,
  filterLib=None,
  save_name="beast_filters",
- xlim=[1.4e3, 2e4],
+ xlim=[3e3, 1e3],
  ylim=[1e-4, 2],
  show_plot=True,
 ):
@@ -50,8 +50,11 @@ def plot_filters(
  )
 
  color_indices = np.log10(np.array(np.sort([f.norm for f in flist])))
- color_indices -= color_indices.min()
- color_indices /= color_indices.max()
+ if len(color_indices) > 1:
+ color_indices -= color_indices.min()
+ color_indices /= color_indices.max()
+ else:
+ color_indices = [0.0]
 
  cmap = mpl.cm.plasma
  # ax.set_prop_cycle(color=[cmap(i) for i in color_indices])
@@ -61,19 +64,25 @@ def plot_filters(
  c = next(color)
  ax.plot(f.wavelength, f.transmit, color=c, lw=2)
  ax.fill_between(f.wavelength, f.transmit, alpha=0.2, color=c)
+ yval_text = max(f.transmit * 0.1)
  ax.text(
- np.nanmean(f.wavelength[f.transmit > 100.0 * ylim[0]]),
- 1.3 * np.nanmax(f.transmit[f.transmit > ylim[0]]),
+ np.nanmean(f.wavelength[f.transmit > yval_text]),
+ 1.3 * np.nanmax(f.transmit[f.transmit > yval_text]),
  f.name.split("_")[-1],
  ha="center",
  color=c,
  )
+ gvals = (f.transmit > ylim[0]) & (f.transmit < ylim[1])
+ if min(f.wavelength[gvals]) < xlim[0]:
+ xlim[0] = min(f.wavelength[gvals])
+ if max(f.wavelength[gvals]) > xlim[1]:
+ xlim[1] = max(f.wavelength[gvals])
 
  ax.set_xscale("log")
  ax.set_yscale("log")
  ax.set_xlim(xlim)
  ax.set_ylim(ylim)
- ax.set_xlabel(r"$\lambda$ [$\mu m$]")
+ ax.set_xlabel(r"$\lambda$ [$\AA$]")
  ax.set_ylabel(r"$B_i(\lambda)$")
 
  # ax.set_xticks([0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 2.0])
@@ -95,9 +104,7 @@ def plot_filters(
  default="filters.appendVegaFilter",
  help="Save figure to file",
  )
- args = parser.parse_args()
-
- filter_names = [
+ def_filter_names = [
  "HST_WFC3_F225W",
  "HST_WFC3_F275W",
  "HST_WFC3_F336W",
@@ -107,8 +114,13 @@ def plot_filters(
  "HST_WFC3_F110W",
  "HST_WFC3_F160W",
  ]
+ parser.add_argument("filter_names",
+ help="names of filters",
+ nargs='+',
+ default=def_filter_names)
+ args = parser.parse_args()
 
- fig = plot_filters(filter_names, show_plot=False)
+ fig = plot_filters(args.filter_names, show_plot=False)
 
  if args.tex:
  plt.rc({"usetex": True})

beast/tools/make_libfile.py

@@ -84,6 +84,16 @@ def make_libfile():
  "f775w",
  "f814w",
  ]
+
+ acs_hrc = [
+ "f115lp",
+ "f125lp",
+ "f140lp",
+ "f150lp",
+ "f165lp",
+ "f122m",
+ ]
+
  # galex
  galex = ["fuv", "nuv"]
 
@@ -228,7 +238,7 @@ def make_libfile():
  pwaves.append(newfilt.lpivot.value)
  comments.append("avg of 1, 2, 3, 4")
 
- # Loop through ACS filters
+ # Loop through ACS WFC filters
  for filt in acs_wfc:
 
  # define wfc1, wfc2 modes
@@ -270,6 +280,44 @@ def make_libfile():
  pwaves.append(newfilt.lpivot.value)
  comments.append("avg of wfc1 and wfc2")
 
+ # Loop through ACS HRC filters
+ for filt in acs_hrc:
+
+ # define ir mode
+ mode = "acs, sbc, " + filt
+
+ # pull bandpasses from stsynphot for the two uvis modes
+ bp = stsyn.band(mode)
+
+ # extract the wavelength array
+ wave = bp.waveset
+
+ # define the filter name
+ filter_name = "HST_ACS_SBC_" + filt.upper()
+
+ # build array of wavelength and throughput
+ arr = np.array(
+ list(zip(wave.value.astype(np.float64), bp(wave).astype(np.float64))),
+ dtype=[("WAVELENGTH", "float64"), ("THROUGHPUT", "float64")],
+ )
+
+ # append dataset to the hdf5 filters group
+ f.create_dataset(filter_name, data=arr)
+
+ # generate filter instance to compute relevant info
+ newfilt = phot.Filter(wave, bp(wave), name=filt.upper())
+
+ # populate contents lists with relevant information
+ tablenames.append(filter_name)
+ observatories.append("HST")
+ instruments.append("ACS")
+ names.append(newfilt.name)
+ norms.append(newfilt.norm.value)
+ cwaves.append(newfilt.cl.value)
+ pwaves.append(newfilt.lpivot.value)
+ comments.append("")
+
+
  # Loop through GALEX filters:
  for filt in galex:
  # define ir mode