diff --git a/docs/source/installation.rst b/docs/source/installation.rst
index 9de0176..1c8cacd 100644
--- a/docs/source/installation.rst
+++ b/docs/source/installation.rst
@@ -5,3 +5,12 @@ Installation
 At the command line::
 
     $ pip install lightcurve-fitting
+
+To install the stable version directly from GitHub::
+
+    $ pip install git+https://github.com/griffin-h/lightcurve_fitting.git
+
+If you want the bleeding-edge "development" version (not recommended)::
+
+    $ pip install git+https://github.com/griffin-h/lightcurve_fitting.git@dev
+
diff --git a/docs/source/release-history.rst b/docs/source/release-history.rst
index c86c98f..69a37df 100644
--- a/docs/source/release-history.rst
+++ b/docs/source/release-history.rst
@@ -2,6 +2,21 @@
 Release History
 ===============
 
+v0.4.0 (2022-02-08)
+-------------------
+* Fix bug in min/max validity times when using intrinsic scatter parameter
+* Change prior on blackbody temperature from log-uniform to uniform
+* Don't italicize some filter names
+* Return axes objects in light curve corner plot
+* Give option to plot magnitudes in light curve corner plot
+* Fix plotting of wavelength when units are supplied
+* Add option to calculate phase in rest-frame hours
+* Issue warning when filters do not receive extinction correction
+* Switch from to generic filter curves from the SVO Filter Profile Service where possible
+* Add progress bars for MCMC fitting
+* Add option to save chain plots. Burn-in and sampling plots are combined into the same figure.
+* Add option to save chain in bolometric light curve fitting
+
 v0.3.0 (2021-09-22)
 -------------------
 * Switch the default table format from ``'ascii.fixed_width'`` to just ``'ascii'``
diff --git a/docs/source/usage.rst b/docs/source/usage.rst
index bb63de5..b5df739 100644
--- a/docs/source/usage.rst
+++ b/docs/source/usage.rst
@@ -169,7 +169,7 @@ If you used the Rabinak & Waxman option, the model fails even earlier, but you w
 .. code-block:: python
 
     p_mean = sampler.flatchain.mean(axis=0)
-    t_max = ShockCooling2.t_max(*p_mean)
+    t_max = ShockCooling2.t_max(p_mean)
     print(t_max)
     if lc_early['MJD'].max() > t_max:
         print('Warning: your model is not valid for all your observations')
diff --git a/lightcurve_fitting.ipynb b/lightcurve_fitting.ipynb
index 2c62c5c..19ab0c2 100644
--- a/lightcurve_fitting.ipynb
+++ b/lightcurve_fitting.ipynb
@@ -134,7 +134,7 @@
    "outputs": [],
    "source": [
     "p_mean = sampler.flatchain.mean(axis=0)\n",
-    "t_max = model.t_max(*p_mean)\n",
+    "t_max = model.t_max(p_mean)\n",
     "print(t_max)\n",
     "if lc_early['MJD'].max() > t_max:\n",
     "    print('Warning: your model is not valid for all your observations')"
diff --git a/lightcurve_fitting/bolometric.py b/lightcurve_fitting/bolometric.py
index b8753fc..35dce53 100644
--- a/lightcurve_fitting/bolometric.py
+++ b/lightcurve_fitting/bolometric.py
@@ -53,7 +53,7 @@ def pseudo(temp, radius, z, filter0=filtdict['I'], filter1=filtdict['U'], cutoff
 
 
 def blackbody_mcmc(epoch1, z, p0=None, show=False, outpath='.', nwalkers=10, burnin_steps=200, steps=100,
-                   T_range=(1., 100.), R_range=(0.01, 1000.), cutoff_freq=np.inf, prev_temp=None):
+                   T_range=(1., 100.), R_range=(0.01, 1000.), cutoff_freq=np.inf, prev_temp=None, save_chains=False):
     """
     Fit a blackbody spectrum to a spectral energy distribution using a Markov-chain Monte Carlo routine
 
@@ -83,6 +83,8 @@ def blackbody_mcmc(epoch1, z, p0=None, show=False, outpath='.', nwalkers=10, bur
         Cutoff frequency (in terahertz) for a modified blackbody spectrum (see https://doi.org/10.3847/1538-4357/aa9334)
     prev_temp : scipy.stats.gaussian_kde, optional
         Temperature distribution from fitting the previous epoch's SED. If given, this is used as the prior.
+    save_chains : bool, optional
+        If True, save the MCMC chain histories to the directory ``outpath``. Default: only save the corner plot
 
     Returns
     -------
@@ -104,7 +106,7 @@ def log_prior(p):  # p = [T, R]
         elif prev_temp is not None:
             return prev_temp.logpdf(p[0]) - np.log(p[1])
         else:
-            return -np.sum(np.log(p))
+            return -np.log(p[1])
 
     def log_likelihood(p, filtobj, y, dy):
         y_fit = blackbody_to_filters(filtobj, p[0], p[1], z, cutoff_freq)
@@ -155,6 +157,9 @@ def log_posterior(p, filtobj, y, dy):
     filename = os.path.join(outpath, f'{mjdavg:.1f}.png')
     print(filename)
     f4.savefig(filename)
+    if save_chains:
+        chain_filename = os.path.join(outpath, f'{mjdavg:.1f}.npy')
+        np.save(chain_filename, sampler.flatchain)
     if show:
         plt.show()
     else:
@@ -458,7 +463,7 @@ def plot_color_curves(t, colors=None, fmt='o', limit_length=0.1, xcol='MJD'):
 
 def calculate_bolometric(lc, z, outpath='.', res=1., nwalkers=10, burnin_steps=200, steps=100,
                          T_range=(1., 100.), R_range=(0.01, 1000.), save_table_as=None, min_nfilt=3,
-                         cutoff_freq=np.inf, show=False, colors=None, do_mcmc=True):
+                         cutoff_freq=np.inf, show=False, colors=None, do_mcmc=True, save_chains=False):
     """
     Calculate the full bolometric light curve from a table of broadband photometry
 
@@ -469,7 +474,7 @@ def calculate_bolometric(lc, z, outpath='.', res=1., nwalkers=10, burnin_steps=2
     z : float
         Redshift between the blackbody (rest frame) and the filters (observed frame)
     outpath : str, optional
-        Directory to which to save the corner plots. Default: current directory
+        Directory to which to save the corner plots and MCMC chains. Default: current directory
     res : float, optional
         Approximate resolution for grouping, in days. Default: 1 day.
     nwalkers : int, optional
@@ -495,6 +500,8 @@ def calculate_bolometric(lc, z, outpath='.', res=1., nwalkers=10, burnin_steps=2
     do_mcmc : bool, optional
         If True (default), also fit the spectral energy distribution with an MCMC routine. This is slower but gives
         more realistic uncertainties.
+    save_chains : bool, optional
+        If True, save the MCMC chain histories to the directory ``outpath``. Default: only save the corner plot
 
     Returns
     -------
@@ -567,7 +574,7 @@ def calculate_bolometric(lc, z, outpath='.', res=1., nwalkers=10, burnin_steps=2
                 raise ValueError
             sampler = blackbody_mcmc(epoch1, z, p0, outpath=outpath, nwalkers=nwalkers, burnin_steps=burnin_steps,
                                      steps=steps, T_range=T_range, R_range=R_range, cutoff_freq=cutoff_freq, show=show,
-                                     prev_temp=prev_temp)
+                                     prev_temp=prev_temp, save_chains=save_chains)
             L_mcmc_opt = pseudo(sampler.flatchain[:, 0], sampler.flatchain[:, 1], z, cutoff_freq=cutoff_freq)
             (T_mcmc, R_mcmc), (dT0_mcmc, dR0_mcmc), (dT1_mcmc, dR1_mcmc) = median_and_unc(sampler.flatchain)
             L_mcmc, dL_mcmc0, dL_mcmc1 = median_and_unc(L_mcmc_opt)
diff --git a/lightcurve_fitting/filters.py b/lightcurve_fitting/filters.py
index 685dd71..892213f 100644
--- a/lightcurve_fitting/filters.py
+++ b/lightcurve_fitting/filters.py
@@ -38,6 +38,8 @@ class Filter:
         The line color used when plotting photometry in this filter. Default: same as ``color``.
     textcolor : str, tuple, optional
         The color used when printing the name of this filter. Default: same as ``linecolor``.
+    italics : bool, optional
+        Italicize the filter name when used with LaTeX. Default: True.
 
     Attributes
     ----------
@@ -53,6 +55,8 @@ class Filter:
         The line color used when plotting photometry in this filter
     textcolor : str, tuple
         The color used when printing the name of this filter
+    italics : bool
+        Italicize the filter name when used with LaTeX
     mec : str, tuple
         The marker edge color used when plotting photometry in this filter
     plotstyle : dict
@@ -86,7 +90,7 @@ class Filter:
     """The names of recognized filters listed in (approximate) decreasing order of effective frequency"""
 
     def __init__(self, names, color='k', offset=0, system=None, fnu=3.631e-23, filename='', angstrom=False,
-                 linecolor=None, textcolor=None):
+                 linecolor=None, textcolor=None, italics=True):
         if type(names) == list:
             self.name = names[0]
             self.names = names
@@ -110,6 +114,7 @@ def __init__(self, names, color='k', offset=0, system=None, fnu=3.631e-23, filen
             self.textcolor = textcolor
         else:
             self.textcolor = self.linecolor
+        self.italics = italics
         self.system = system
         if self.system == 'Johnson':
             self.mec = 'k'
@@ -191,6 +196,9 @@ def read_curve(self, show=False, force=False):
                 ax2.set_xlabel('Frequency (THz)')
                 ax2.set_ylabel('Transmission')
 
+            self.wl_eff = wl_eff
+            self.dwl = dwl
+            self.wl_range = (wl_eff.value - wl0, wl1 - wl_eff.value)
             self.freq_eff = freq_eff
             self.dfreq = -dfreq
             self.freq_range = (freq_eff.value - freq0, freq1 - freq_eff.value)
@@ -252,39 +260,42 @@ def _resample_filter_curve(filename, outfile):
     Filter(['UVW2', 'uvw2', 'W2', '2', 'uw2'], '#FF007F', 8, 'Swift', 7.379e-24, 'Swift_UVOT.UVW2.dat', angstrom=True),
     Filter(['UVM2', 'uvm2', 'M2', 'M', 'um2'], 'm', 8, 'Swift', 7.656e-24, 'Swift_UVOT.UVM2.dat', angstrom=True),
     Filter(['UVW1', 'uvw1', 'W1', '1', 'uw1'], '#7F00FF', 4, 'Swift', 9.036e-24, 'Swift_UVOT.UVW1.dat', angstrom=True),
-    Filter(['u', "u'", 'up'], '#4700CC', 3, 'Gunn', filename='sdss-up-183.asci'),  # brightened from '#080017'
+    Filter(['u', "u'", 'up'], '#4700CC', 3, 'Gunn', filename='SLOAN_SDSS.u.dat', angstrom=True),  # brightened from '#080017'
     Filter(['U_S', 's', 'us'], '#230047', 3, 'Swift', 1.419e-23, filename='Swift_UVOT.U.dat', angstrom=True),
-    Filter('U', '#3C0072', 3, 'Johnson', 1.790e-23, filename='jnsn-uv-183.asci'),
-    Filter('B', '#0057FF', 2, 'Johnson', 4.063e-23, filename='jnsn-bu-183.asci'),
+    Filter('U', '#3C0072', 3, 'Johnson', 1.790e-23, filename='Generic_Johnson.U.dat', angstrom=True),
+    Filter('B', '#0057FF', 2, 'Johnson', 4.063e-23, filename='Generic_Johnson.B.dat', angstrom=True),
     Filter(['B_S', 'b', 'bs'], '#4B00FF', 2, 'Swift', 4.093e-23, filename='Swift_UVOT.B.dat', angstrom=True),
-    Filter(['g', "g'", 'gp', 'F475W'], '#00CCFF', 1, 'Gunn', filename='sdss-gp-183.asci'),
+    Filter(['g', "g'", 'gp', 'F475W'], '#00CCFF', 1, 'Gunn', filename='SLOAN_SDSS.g.dat', angstrom=True),
     Filter('g-DECam', '#00CCFF', 1, 'DECam', filename='CTIO_DECam.g.dat', angstrom=True),
     Filter(['c', 'cyan'], 'c', 1, 'ATLAS', filename='ATLAS_cyan.txt'),
-    Filter('V', '#79FF00', 1, 'Johnson', 3.636e-23, filename='jnsn-vx-183.asci', textcolor='#46CC00'),
+    Filter('V', '#79FF00', 1, 'Johnson', 3.636e-23, filename='Generic_Johnson.V.dat', angstrom=True, textcolor='#46CC00'),
     Filter(['V_S', 'v', 'vs'], '#00FF30', 1, 'Swift', 3.664e-23, filename='Swift_UVOT.V.dat', angstrom=True),
-    Filter(['unfilt.', '0', 'Clear', 'C', 'clear'], 'w', 0, 'Itagaki', filename='KAF-1001E.asci', linecolor='k'),
-    Filter('white', 'w', 0, 'MOSFiT', filename='white.txt', linecolor='k'),
-    Filter(['pseudobolometric', 'griz'], 'w', 0, 'MOSFiT', filename='pseudobolometric.txt', linecolor='k'),
+    Filter('Itagaki', 'w', 0, 'Itagaki', filename='KAF-1001E.asci', linecolor='k', italics=False),
+    Filter('white', 'w', 0, 'MOSFiT', filename='white.txt', linecolor='k', italics=False),
+    Filter(['unfilt.', '0', 'Clear', 'C', 'clear', 'pseudobolometric', 'griz'], 'w', 0, 'MOSFiT',
+           filename='pseudobolometric.txt', linecolor='k', italics=False),
     Filter('G', 'w', 0, 'Gaia', filename='GAIA_GAIA0.G.dat', angstrom=True, linecolor='k'),
-    Filter('Kepler', 'r', 0, 'Kepler', filename='Kepler_Kepler.K.dat', angstrom=True),
-    Filter('TESS', 'r', 0, 'TESS', filename='TESS_TESS.Red.dat', angstrom=True),
-    Filter('w', 'w', 0, 'Gunn', filename='pstr-wx-183.asci', linecolor='k'),
+    Filter('Kepler', 'r', 0, 'Kepler', filename='Kepler_Kepler.K.dat', angstrom=True, italics=False),
+    Filter('TESS', 'r', 0, 'TESS', filename='TESS_TESS.Red.dat', angstrom=True, italics=False),
+    Filter('DLT40', 'w', 0, 'DLT40', filename='QE_E2V_MBBBUV_Broadband.csv', linecolor='k', italics=False),
+    Filter('w', 'w', 0, 'Gunn', filename='PAN-STARRS_PS1.w.dat', angstrom=True, linecolor='k'),
     Filter(['o', 'orange'], 'orange', 0, 'ATLAS', filename='ATLAS_orange.txt'),
-    Filter(['r', "r'", 'rp', 'F625W'], '#FF7D00', 0, 'Gunn', filename='sdss-rp-183.asci'),
+    Filter(['r', "r'", 'rp', 'F625W'], '#FF7D00', 0, 'Gunn', filename='SLOAN_SDSS.r.dat', angstrom=True),
     Filter('r-DECam', '#FF7D00', 0, 'DECam', filename='CTIO_DECam.r.dat', angstrom=True),
-    Filter(['R', 'Rc', 'R_s'], '#FF7000', 0, 'Johnson', 3.064e-23, filename='cous-rs-183.asci'),  # '#CC5900'
-    Filter(['i', "i'", 'ip', 'F775W'], '#90002C', -1, 'Gunn', filename='sdss-ip-183.asci'),
+    Filter(['R', 'Rc', 'R_s'], '#FF7000', 0, 'Johnson', 3.064e-23, filename='Generic_Cousins.R.dat', angstrom=True),  # '#CC5900'
+    Filter(['i', "i'", 'ip', 'F775W'], '#90002C', -1, 'Gunn', filename='SLOAN_SDSS.i.dat', angstrom=True),
     Filter('i-DECam', '#90002C', -1, 'DECam', filename='CTIO_DECam.i.dat', angstrom=True),
-    Filter(['I', 'Ic'], '#66000B', -1, 'Johnson', 2.416e-23, filename='cous-ic-183.asci'),  # brightened from '#1C0003'
-    Filter(['z', "z'", 'Z', 'zs'], '#000000', -2, 'Gunn', filename='pstr-zs-183.asci'),
+    Filter(['I', 'Ic'], '#66000B', -1, 'Johnson', 2.416e-23, filename='Generic_Cousins.I.dat', angstrom=True),  # brightened from '#1C0003'
+    Filter('zs', '#000000', -2, 'Gunn', filename='PAN-STARRS_PS1.z.dat', angstrom=True),
+    Filter(['z', "z'", 'zp'], '#000000', -2, 'Gunn', filename='SLOAN_SDSS.z.dat', angstrom=True),
     Filter('z-DECam', '#000000', -2, 'DECam', filename='CTIO_DECam.z.dat', angstrom=True),
-    Filter('y', 'y', -3, 'Gunn', filename='pstr-yx-183.asci'),
+    Filter('y', 'y', -3, 'Gunn', filename='PAN-STARRS_PS1.y.dat', angstrom=True),
     Filter('y-DECam', 'y', -3, 'DECam', filename='CTIO_DECam.Y.dat', angstrom=True),
     Filter('J', '#444444', -2, 'UKIRT', 1.589e-23, filename='Gemini_Flamingos2.J.dat', angstrom=True),
     Filter('H', '#888888', -3, 'UKIRT', 1.021e-23, filename='Gemini_Flamingos2.H.dat', angstrom=True),
     Filter(['K', 'Ks'], '#CCCCCC', -4, 'UKIRT', 0.640e-23, filename='Gemini_Flamingos2.Ks.dat', angstrom=True),
     Filter('L', 'r', -4, 'UKIRT', 0.285e-23),
-    Filter(['unknown', '?'], 'w', 0, 'unknown', linecolor='k')]
+    Filter(['unknown', '?'], 'w', 0, 'unknown', linecolor='k', italics=False)]
 Filter.order = [f.name for f in all_filters]
 filtdict = {}
 for filt in all_filters:
diff --git a/lightcurve_fitting/filters/Generic_Bessell.B.dat b/lightcurve_fitting/filters/Generic_Bessell.B.dat
deleted file mode 100644
index 9d2eb16..0000000
--- a/lightcurve_fitting/filters/Generic_Bessell.B.dat
+++ /dev/null
@@ -1,21 +0,0 @@
-3600.0 0.0000000000
-3700.0 0.0300000000
-3800.0 0.1340000000
-3900.0 0.5670000000
-4000.0 0.9200000000
-4100.0 0.9780000000
-4200.0 1.0000000000
-4300.0 0.9780000000
-4400.0 0.9350000000
-4500.0 0.8530000000
-4600.0 0.7400000000
-4700.0 0.6400000000
-4800.0 0.5360000000
-4900.0 0.4240000000
-5000.0 0.3250000000
-5100.0 0.2350000000
-5200.0 0.1500000000
-5300.0 0.0950000000
-5400.0 0.0430000000
-5500.0 0.0090000000
-5600.0 0.0000000000
diff --git a/lightcurve_fitting/filters/Generic_Bessell.V.dat b/lightcurve_fitting/filters/Generic_Bessell.V.dat
deleted file mode 100644
index 241fc92..0000000
--- a/lightcurve_fitting/filters/Generic_Bessell.V.dat
+++ /dev/null
@@ -1,24 +0,0 @@
-4700.0 0.0000000000
-4800.0 0.0300000000
-4900.0 0.1630000000
-5000.0 0.4580000000
-5100.0 0.7800000000
-5200.0 0.9670000000
-5300.0 1.0000000000
-5400.0 0.9730000000
-5500.0 0.8980000000
-5600.0 0.7920000000
-5700.0 0.6840000000
-5800.0 0.5740000000
-5900.0 0.4610000000
-6000.0 0.3590000000
-6100.0 0.2700000000
-6200.0 0.1970000000
-6300.0 0.1350000000
-6400.0 0.0810000000
-6500.0 0.0450000000
-6600.0 0.0250000000
-6700.0 0.0170000000
-6800.0 0.0130000000
-6900.0 0.0090000000
-7000.0 0.0000000000
diff --git a/lightcurve_fitting/filters/Generic_Cousins.I.dat b/lightcurve_fitting/filters/Generic_Cousins.I.dat
new file mode 100644
index 0000000..462e6ed
--- /dev/null
+++ b/lightcurve_fitting/filters/Generic_Cousins.I.dat
@@ -0,0 +1,43 @@
+7000 0.000
+7050 0.005
+7100 0.020
+7150 0.050
+7200 0.100
+7250 0.170
+7300 0.330
+7350 0.700
+7400 0.820
+7450 0.900
+7500 0.950
+7550 0.980
+7600 0.990
+7650 0.994
+7700 0.980
+7750 0.950
+7800 0.913
+7850 0.870
+7900 0.830
+7950 0.790
+8000 0.750
+8050 0.710
+8100 0.673
+8150 0.650
+8200 0.630
+8250 0.610
+8300 0.580
+8350 0.550
+8400 0.510
+8450 0.470
+8500 0.405
+8550 0.330
+8600 0.250
+8650 0.180
+8700 0.140
+8750 0.110
+8800 0.080
+8850 0.060
+8900 0.035
+8950 0.020
+9000 0.010
+9050 0.005
+9100 0.000
diff --git a/lightcurve_fitting/filters/Generic_Cousins.R.dat b/lightcurve_fitting/filters/Generic_Cousins.R.dat
new file mode 100644
index 0000000..b31f243
--- /dev/null
+++ b/lightcurve_fitting/filters/Generic_Cousins.R.dat
@@ -0,0 +1,53 @@
+5400 0.000
+5450 0.002
+5500 0.010
+5550 0.030
+5600 0.070
+5650 0.180
+5700 0.400
+5750 0.770
+5800 0.890
+5850 0.960
+5900 0.990
+5950 0.999
+6000 1.000
+6050 0.997
+6100 0.990
+6150 0.976
+6200 0.960
+6250 0.946
+6300 0.930
+6350 0.912
+6400 0.895
+6450 0.880
+6500 0.860
+6550 0.845
+6600 0.825
+6650 0.806
+6700 0.788
+6750 0.765
+6800 0.742
+6850 0.720
+6900 0.700
+6950 0.676
+7000 0.650
+7050 0.626
+7100 0.600
+7150 0.568
+7200 0.530
+7250 0.480
+7300 0.395
+7350 0.300
+7400 0.215
+7450 0.155
+7500 0.120
+7550 0.100
+7600 0.085
+7650 0.075
+7700 0.060
+7750 0.050
+7800 0.040
+7850 0.029
+7900 0.020
+7950 0.010
+8000 0.000
diff --git a/lightcurve_fitting/filters/Generic_Johnson.U.dat b/lightcurve_fitting/filters/Generic_Johnson.U.dat
new file mode 100644
index 0000000..9982846
--- /dev/null
+++ b/lightcurve_fitting/filters/Generic_Johnson.U.dat
@@ -0,0 +1,13 @@
+3000.0 0.0000000000
+3100.0 0.1000000000
+3200.0 0.6100000000
+3300.0 0.8400000000
+3400.0 0.9300000000
+3500.0 0.9700000000
+3600.0 1.0000000000
+3700.0 0.9700000000
+3800.0 0.7300000000
+3900.0 0.3600000000
+4000.0 0.0500000000
+4100.0 0.0100000000
+4200.0 0.0000000000
diff --git a/lightcurve_fitting/filters/PAN-STARRS_PS1.w.dat b/lightcurve_fitting/filters/PAN-STARRS_PS1.w.dat
new file mode 100644
index 0000000..ae9aa6a
--- /dev/null
+++ b/lightcurve_fitting/filters/PAN-STARRS_PS1.w.dat
@@ -0,0 +1,465 @@
+3880 0.001
+3890 0.006
+3900 0.006
+3910 0.005
+3920 0.005
+3930 0.005
+3940 0.006
+3950 0.006
+3960 0.008
+3970 0.01
+3980 0.014
+3990 0.021
+4000 0.032
+4010 0.049
+4020 0.071
+4030 0.096
+4040 0.123
+4050 0.148
+4060 0.169
+4070 0.186
+4080 0.198
+4090 0.208
+4100 0.216
+4110 0.223
+4120 0.231
+4130 0.24
+4140 0.248
+4150 0.257
+4160 0.265
+4170 0.272
+4180 0.278
+4190 0.284
+4200 0.288
+4210 0.293
+4220 0.297
+4230 0.303
+4240 0.308
+4250 0.315
+4260 0.322
+4270 0.328
+4280 0.335
+4290 0.342
+4300 0.35
+4310 0.358
+4320 0.367
+4330 0.375
+4340 0.382
+4350 0.389
+4360 0.396
+4370 0.402
+4380 0.408
+4390 0.411
+4400 0.416
+4410 0.421
+4420 0.426
+4430 0.43
+4440 0.433
+4450 0.437
+4460 0.442
+4470 0.446
+4480 0.449
+4490 0.453
+4500 0.458
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diff --git a/lightcurve_fitting/filters/PAN-STARRS_PS1.y.dat b/lightcurve_fitting/filters/PAN-STARRS_PS1.y.dat
new file mode 100644
index 0000000..cf4cdb3
--- /dev/null
+++ b/lightcurve_fitting/filters/PAN-STARRS_PS1.y.dat
@@ -0,0 +1,201 @@
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diff --git a/lightcurve_fitting/filters/PAN-STARRS_PS1.z.dat b/lightcurve_fitting/filters/PAN-STARRS_PS1.z.dat
new file mode 100644
index 0000000..7e2be47
--- /dev/null
+++ b/lightcurve_fitting/filters/PAN-STARRS_PS1.z.dat
@@ -0,0 +1,153 @@
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diff --git a/lightcurve_fitting/filters/QE_E2V_MBBBUV_Broadband.csv b/lightcurve_fitting/filters/QE_E2V_MBBBUV_Broadband.csv
new file mode 100644
index 0000000..250a0df
--- /dev/null
+++ b/lightcurve_fitting/filters/QE_E2V_MBBBUV_Broadband.csv
@@ -0,0 +1,160 @@
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diff --git a/lightcurve_fitting/filters/SLOAN_SDSS.g.dat b/lightcurve_fitting/filters/SLOAN_SDSS.g.dat
new file mode 100644
index 0000000..ef08bea
--- /dev/null
+++ b/lightcurve_fitting/filters/SLOAN_SDSS.g.dat
@@ -0,0 +1,89 @@
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diff --git a/lightcurve_fitting/filters/SLOAN_SDSS.i.dat b/lightcurve_fitting/filters/SLOAN_SDSS.i.dat
new file mode 100644
index 0000000..aac944e
--- /dev/null
+++ b/lightcurve_fitting/filters/SLOAN_SDSS.i.dat
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diff --git a/lightcurve_fitting/filters/SLOAN_SDSS.r.dat b/lightcurve_fitting/filters/SLOAN_SDSS.r.dat
new file mode 100644
index 0000000..813c48e
--- /dev/null
+++ b/lightcurve_fitting/filters/SLOAN_SDSS.r.dat
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diff --git a/lightcurve_fitting/filters/SLOAN_SDSS.u.dat b/lightcurve_fitting/filters/SLOAN_SDSS.u.dat
new file mode 100644
index 0000000..6290169
--- /dev/null
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diff --git a/lightcurve_fitting/filters/SLOAN_SDSS.z.dat b/lightcurve_fitting/filters/SLOAN_SDSS.z.dat
new file mode 100644
index 0000000..c20bd3e
--- /dev/null
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diff --git a/lightcurve_fitting/filters/Swift_UVOT.white.dat b/lightcurve_fitting/filters/Swift_UVOT.white.dat
deleted file mode 100644
index 144d09e..0000000
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diff --git a/lightcurve_fitting/filters/astrodon.uv.txt b/lightcurve_fitting/filters/astrodon.uv.txt
deleted file mode 100644
index a3be7d3..0000000
--- a/lightcurve_fitting/filters/astrodon.uv.txt
+++ /dev/null
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diff --git a/lightcurve_fitting/filters/bssl-bx-004.txt b/lightcurve_fitting/filters/bssl-bx-004.txt
deleted file mode 100644
index aa49362..0000000
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diff --git a/lightcurve_fitting/filters/bssl-ix-023.txt b/lightcurve_fitting/filters/bssl-ix-023.txt
deleted file mode 100644
index f620da0..0000000
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diff --git a/lightcurve_fitting/filters/bssl-rx-007.txt b/lightcurve_fitting/filters/bssl-rx-007.txt
deleted file mode 100644
index ad821e3..0000000
--- a/lightcurve_fitting/filters/bssl-rx-007.txt
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diff --git a/lightcurve_fitting/filters/bssl-ux-022.txt b/lightcurve_fitting/filters/bssl-ux-022.txt
deleted file mode 100644
index ec9d4fa..0000000
--- a/lightcurve_fitting/filters/bssl-ux-022.txt
+++ /dev/null
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diff --git a/lightcurve_fitting/filters/bssl-vx-022.txt b/lightcurve_fitting/filters/bssl-vx-022.txt
deleted file mode 100644
index 7829c90..0000000
--- a/lightcurve_fitting/filters/bssl-vx-022.txt
+++ /dev/null
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diff --git a/lightcurve_fitting/filters/cous-ic-183.asci b/lightcurve_fitting/filters/cous-ic-183.asci
deleted file mode 100644
index 5ffd57f..0000000
--- a/lightcurve_fitting/filters/cous-ic-183.asci
+++ /dev/null
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diff --git a/lightcurve_fitting/filters/cous-rs-183.asci b/lightcurve_fitting/filters/cous-rs-183.asci
deleted file mode 100644
index 3068af7..0000000
--- a/lightcurve_fitting/filters/cous-rs-183.asci
+++ /dev/null
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diff --git a/lightcurve_fitting/filters/jnsn-bu-183.asci b/lightcurve_fitting/filters/jnsn-bu-183.asci
deleted file mode 100644
index eb4e70a..0000000
--- a/lightcurve_fitting/filters/jnsn-bu-183.asci
+++ /dev/null
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diff --git a/lightcurve_fitting/filters/jnsn-uv-183.asci b/lightcurve_fitting/filters/jnsn-uv-183.asci
deleted file mode 100644
index f585998..0000000
--- a/lightcurve_fitting/filters/jnsn-uv-183.asci
+++ /dev/null
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diff --git a/lightcurve_fitting/filters/jnsn-vx-183.asci b/lightcurve_fitting/filters/jnsn-vx-183.asci
deleted file mode 100644
index 66b7411..0000000
--- a/lightcurve_fitting/filters/jnsn-vx-183.asci
+++ /dev/null
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diff --git a/lightcurve_fitting/filters/nbnd-o3-008.txt b/lightcurve_fitting/filters/nbnd-o3-008.txt
deleted file mode 100644
index e9f968c..0000000
--- a/lightcurve_fitting/filters/nbnd-o3-008.txt
+++ /dev/null
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diff --git a/lightcurve_fitting/filters/pstr-wx-183.asci b/lightcurve_fitting/filters/pstr-wx-183.asci
deleted file mode 100644
index 3bf10ee..0000000
--- a/lightcurve_fitting/filters/pstr-wx-183.asci
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diff --git a/lightcurve_fitting/filters/pstr-yx-008.txt b/lightcurve_fitting/filters/pstr-yx-008.txt
deleted file mode 100644
index 920becc..0000000
--- a/lightcurve_fitting/filters/pstr-yx-008.txt
+++ /dev/null
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diff --git a/lightcurve_fitting/filters/pstr-yx-183.asci b/lightcurve_fitting/filters/pstr-yx-183.asci
deleted file mode 100644
index f0b09ea..0000000
--- a/lightcurve_fitting/filters/pstr-yx-183.asci
+++ /dev/null
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diff --git a/lightcurve_fitting/filters/pstr-zs-008.txt b/lightcurve_fitting/filters/pstr-zs-008.txt
deleted file mode 100644
index 7cdc7ac..0000000
--- a/lightcurve_fitting/filters/pstr-zs-008.txt
+++ /dev/null
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diff --git a/lightcurve_fitting/filters/pstr-zs-183.asci b/lightcurve_fitting/filters/pstr-zs-183.asci
deleted file mode 100644
index 05e0cd5..0000000
--- a/lightcurve_fitting/filters/pstr-zs-183.asci
+++ /dev/null
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diff --git a/lightcurve_fitting/filters/sdss-gp-183.asci b/lightcurve_fitting/filters/sdss-gp-183.asci
deleted file mode 100644
index 7b34cea..0000000
--- a/lightcurve_fitting/filters/sdss-gp-183.asci
+++ /dev/null
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diff --git a/lightcurve_fitting/filters/sdss-ip-183.asci b/lightcurve_fitting/filters/sdss-ip-183.asci
deleted file mode 100644
index 5b47915..0000000
--- a/lightcurve_fitting/filters/sdss-ip-183.asci
+++ /dev/null
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diff --git a/lightcurve_fitting/filters/sdss-rp-183.asci b/lightcurve_fitting/filters/sdss-rp-183.asci
deleted file mode 100644
index d4a4e88..0000000
--- a/lightcurve_fitting/filters/sdss-rp-183.asci
+++ /dev/null
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diff --git a/lightcurve_fitting/filters/sdss-up-183.asci b/lightcurve_fitting/filters/sdss-up-183.asci
deleted file mode 100644
index 8dca980..0000000
--- a/lightcurve_fitting/filters/sdss-up-183.asci
+++ /dev/null
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-            278	          1e-10
-            277	          1e-10
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diff --git a/lightcurve_fitting/filters/sdss.gp.txt b/lightcurve_fitting/filters/sdss.gp.txt
deleted file mode 100644
index a3d02b6..0000000
--- a/lightcurve_fitting/filters/sdss.gp.txt
+++ /dev/null
@@ -1,4667 +0,0 @@
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diff --git a/lightcurve_fitting/filters/sdss.ip.txt b/lightcurve_fitting/filters/sdss.ip.txt
deleted file mode 100644
index ff25e72..0000000
--- a/lightcurve_fitting/filters/sdss.ip.txt
+++ /dev/null
@@ -1,4667 +0,0 @@
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diff --git a/lightcurve_fitting/filters/sdss.rp.txt b/lightcurve_fitting/filters/sdss.rp.txt
deleted file mode 100644
index 68582ed..0000000
--- a/lightcurve_fitting/filters/sdss.rp.txt
+++ /dev/null
@@ -1,4667 +0,0 @@
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diff --git a/lightcurve_fitting/filters/sdss.up.txt b/lightcurve_fitting/filters/sdss.up.txt
deleted file mode 100644
index 33b38a5..0000000
--- a/lightcurve_fitting/filters/sdss.up.txt
+++ /dev/null
@@ -1,4667 +0,0 @@
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diff --git a/lightcurve_fitting/filters/skmp-vs-008.txt b/lightcurve_fitting/filters/skmp-vs-008.txt
deleted file mode 100644
index 195885d..0000000
--- a/lightcurve_fitting/filters/skmp-vs-008.txt
+++ /dev/null
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diff --git a/lightcurve_fitting/filters/solr-vr-008.txt b/lightcurve_fitting/filters/solr-vr-008.txt
deleted file mode 100644
index b088a3e..0000000
--- a/lightcurve_fitting/filters/solr-vr-008.txt
+++ /dev/null
@@ -1,5501 +0,0 @@
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diff --git a/lightcurve_fitting/fitting.py b/lightcurve_fitting/fitting.py
index 77cf5dd..e88cabb 100644
--- a/lightcurve_fitting/fitting.py
+++ b/lightcurve_fitting/fitting.py
@@ -9,7 +9,7 @@
 
 def lightcurve_mcmc(lc, model, priors=None, p_min=None, p_max=None, p_lo=None, p_up=None,
                     nwalkers=100, nsteps=1000, nsteps_burnin=1000, model_kwargs=None,
-                    show=False, save_sampler_as='', use_sigma=False):
+                    show=False, save_plot_as='', save_sampler_as='', use_sigma=False):
     """
     Fit an analytical model to observed photometry using a Markov-chain Monte Carlo routine
 
@@ -41,6 +41,8 @@ def lightcurve_mcmc(lc, model, priors=None, p_min=None, p_max=None, p_lo=None, p
         Keyword arguments to be passed to the model
     show : bool, optional
         If True, plot and display the chain histories
+    save_plot_as : str, optional
+        Save a plot of the chain histories to this filename
     save_sampler_as : str, optional
         Save the aggregated chain histories to this filename
     use_sigma : bool, optional
@@ -119,9 +121,11 @@ def log_posterior(p):
     sampler = emcee.EnsembleSampler(nwalkers, ndim, log_posterior)
 
     starting_guesses = np.random.rand(nwalkers, ndim) * (p_up - p_lo) + p_lo
-    pos, _, _ = sampler.run_mcmc(starting_guesses, nsteps_burnin)
-    if show:
-        f1, ax1 = plt.subplots(ndim, figsize=(6, 2 * ndim))
+    pos, _, _ = sampler.run_mcmc(starting_guesses, nsteps_burnin, progress=True, progress_kwargs={'desc': ' Burn-in'})
+
+    if show or save_plot_as:
+        fig, ax = plt.subplots(ndim, 2, figsize=(12., 2. * ndim))
+        ax1 = ax[:, 0]
         for i in range(ndim):
             ax1[i].plot(sampler.chain[:, :, i].T, 'k', alpha=0.2)
             ax1[i].set_ylabel(model.axis_labels[i])
@@ -129,26 +133,35 @@ def log_posterior(p):
         ax1[-1].set_xlabel('Step Number')
 
     sampler.reset()
-    sampler.run_mcmc(pos, nsteps)
+    sampler.run_mcmc(pos, nsteps, progress=True, progress_kwargs={'desc': 'Sampling'})
     if save_sampler_as:
         np.save(save_sampler_as, sampler.flatchain)
         print('saving sampler.flatchain as ' + save_sampler_as)
 
-    if show:
-        f2, ax2 = plt.subplots(ndim, figsize=(6, 2 * ndim))
+    if show or save_plot_as:
+        ax2 = ax[:, 1]
         for i in range(ndim):
             ax2[i].plot(sampler.chain[:, :, i].T, 'k', alpha=0.2)
             ax2[i].set_ylabel(model.axis_labels[i])
+            ax2[i].yaxis.set_label_position('right')
+            ax2[i].yaxis.tick_right()
         ax2[0].set_title('After Burn In')
         ax2[-1].set_xlabel('Step Number')
-        plt.show()
+        fig.tight_layout()
+
+        if save_plot_as:
+            print('saving chain plot as ' + save_plot_as)
+            fig.savefig(save_plot_as)
+
+        if show:
+            plt.show()
 
     return sampler
 
 
 def lightcurve_corner(lc, model, sampler_flatchain, model_kwargs=None,
                       num_models_to_plot=100, lcaxis_posn=(0.7, 0.55, 0.2, 0.4),
-                      filter_spacing=0.5, tmin=None, tmax=None, t0_offset=None, save_plot_as=''):
+                      filter_spacing=0.5, tmin=None, tmax=None, t0_offset=None, save_plot_as='', ycol='lum'):
     """
     Plot the posterior distributions in a corner (pair) plot, with an inset showing the observed and model light curves.
 
@@ -177,11 +190,17 @@ def lightcurve_corner(lc, model, sampler_flatchain, model_kwargs=None,
         the model light curve.
     save_plot_as : str, optional
         Filename to which to save the resulting plot
+    ycol : str, optional
+        Quantity to plot on the light curve inset. Choices: "lum" (default) or "absmag".
 
     Returns
     -------
     fig : matplotlib.pyplot.Figure
         Figure object containing the plot
+    corner_ax : array-like
+        Array of matplotlib.pyplot.Axes objects corresponding to the corner plot
+    ax : matplotlib.pyplot.Axes
+        Axes object for the light curve inset
     """
     if model_kwargs is None:
         model_kwargs = {}
@@ -219,23 +238,31 @@ def lightcurve_corner(lc, model, sampler_flatchain, model_kwargs=None,
     y_fit = model(xfit, ufilts, *ps, **model_kwargs)
 
     mjd_offset = np.floor(tmin)
-    if y_fit.max() > 0.:
+    if ycol == 'lum':
+        dycol = 'dlum'
         yscale = 10. ** np.round(np.log10(y_fit.max()))
-    else:
+        ylabel = 'Luminosity $L_\\nu$ (10$^{{{:.0f}}}$ erg s$^{{-1}}$ Hz$^{{-1}}$) + Offset'.format(
+            np.log10(yscale) + 7)  # W --> erg / s
+    elif ycol == 'absmag':
+        dycol = 'dmag'
         yscale = 1.
+        ylabel = 'Absolute Magnitude + Offset'
+        y_fit = [[[filt.M0]] for filt in ufilts] - 2.5 * np.log10(y_fit)
+        ax.invert_yaxis()
+    else:
+        raise ValueError(f'ycol="{ycol}" is not recognized. Use "lum" or "absmag".')
     offset = -len(ufilts) // 2 * filter_spacing
     for filt, yfit in zip(ufilts, y_fit):
         offset += filter_spacing
         lc_filt = lc.where(filter=filt)
-        ax.errorbar(lc_filt['MJD'] - mjd_offset, lc_filt['lum'] / yscale + offset, lc_filt['dlum'] / yscale,
+        ax.errorbar(lc_filt['MJD'] - mjd_offset, lc_filt[ycol] / yscale + offset, lc_filt[dycol] / yscale,
                     ls='none', marker='o', **filt.plotstyle)
         ax.plot(xfit - mjd_offset, yfit / yscale + offset, color=filt.linecolor, alpha=0.05)
-        txt = '${}{:+.1f}$'.format(filt.name, offset) if offset else filt.name
+        txt = f'${filt.name}{offset:+.1f}$' if filt.italics else rf'$\mathrm{{{filt.name}}}{offset:+.1f}$'
         ax.text(1.03, yfit[-1, 0] / yscale + offset, txt, color=filt.textcolor,
                 ha='left', va='center', transform=ax.get_yaxis_transform())
     ax.set_xlabel('MJD $-$ {:.0f}'.format(mjd_offset))
-    ax.set_ylabel('Luminosity $L_\\nu$ (10$^{{{:.0f}}}$ erg s$^{{-1}}$ Hz$^{{-1}}$) + Offset'
-                  .format(np.log10(yscale) + 7))  # W --> erg / s
+    ax.set_ylabel(ylabel)
 
     paramtexts = format_credible_interval(sampler_flatchain, varnames=model.input_names, units=model.units)
     fig.text(0.45, 0.95, '\n'.join(paramtexts), va='top', ha='center', fontdict={'size': 'large'})
@@ -243,7 +270,7 @@ def lightcurve_corner(lc, model, sampler_flatchain, model_kwargs=None,
         fig.savefig(save_plot_as)
         print('saving figure as ' + save_plot_as)
 
-    return fig
+    return fig, corner_axes, ax
 
 
 def format_credible_interval(x, sigfigs=1, percentiles=(15.87, 50., 84.14), axis=0, varnames=None, units=None):
diff --git a/lightcurve_fitting/lightcurve.py b/lightcurve_fitting/lightcurve.py
index cbaecea..3974f43 100644
--- a/lightcurve_fitting/lightcurve.py
+++ b/lightcurve_fitting/lightcurve.py
@@ -31,6 +31,7 @@ def __init__(self, hx, hy):
 othermarkers = ('o', *MarkerStyle.filled_markers[2:])
 itermarkers = itertools.cycle(othermarkers)
 usedmarkers = []
+itercolors = itertools.cycle(plt.rcParams['axes.prop_cycle'].by_key()['color'])
 
 # if you edit this list, also add the new names to usage.rst
 column_names = {
@@ -297,10 +298,19 @@ def calcAbsMag(self, dm=None, extinction=None, hostext=None):
             self.meta['hostext'] = {}
 
         self['absmag'] = self['mag'].data - self.meta['dm']
-        for filt, A in self.meta['extinction'].items():
-            self['absmag'][self['filter'] == filtdict[filt]] -= A
-        for filt, A in self.meta['hostext'].items():
-            self['absmag'][self['filter'] == filtdict[filt]] -= A
+        for filtobj in set(self['filter']):
+            for filt in filtobj.names:
+                if filt in self.meta['extinction']:
+                    self['absmag'][self['filter'] == filtobj] -= self.meta['extinction'][filt]
+                    break
+            else:
+                print('MW extinction not applied to filter', filtobj)
+            for filt in filtobj.names:
+                if filt in self.meta['hostext']:
+                    self['absmag'][self['filter'] == filtobj] -= self.meta['hostext'][filt]
+                    break
+            else:
+                print('host extinction not applied to filter', filtobj)
 
     def calcLum(self, nondetSigmas=None):
         """
@@ -326,26 +336,17 @@ def findPeak(self, **criteria):
             Use only a subset of the light curve matching some criteria when calculating the peak date (stored in
             ``self.sn.peakcriteria``
         """
-        useforpeak = np.ones_like(self, bool)
         if 'nondet' in self.colnames:
-            useforpeak &= ~self['nondet']
-        for key, value in criteria.items():
-            if isinstance(value, list):
-                subuseforpeak = np.tile(False, len(self))
-                for val in value:
-                    subuseforpeak |= self[key] == val
-            else:
-                subuseforpeak = self[key] == value
-            useforpeak &= subuseforpeak
-        if np.any(useforpeak):
-            peaktable = self[useforpeak]
+            criteria['nondet'] = False
+        peaktable = self.where(**criteria)
+        if len(peaktable):
             imin = np.argmin(peaktable['mag'])
             self.sn.peakdate = peaktable['MJD'][imin]
         else:
             self.sn.peakdate = np.nan
         self.sn.peakcriteria = criteria
 
-    def calcPhase(self, rdsp=False):
+    def calcPhase(self, rdsp=False, hours=False):
         """
         Calculate the rest-frame ``'phase'`` column from the ``'MJD'`` column and ``self.sn.refmjd`` and ``self.sn.z``
 
@@ -374,6 +375,12 @@ def calcPhase(self, rdsp=False):
             self['dphase0'] = self['dMJD0'] / (1. + self.meta['redshift'])
         if 'dMJD1' in self.colnames:
             self['dphase1'] = self['dMJD1'] / (1. + self.meta['redshift'])
+        if hours:
+            self['phase'] *= 24.
+            if 'dphase0' in self.colnames:
+                self['dphase0'] *= 24.
+            if 'dphase1' in self.colnames:
+                self['dphase1'] *= 24.
 
     def plot(self, xcol='phase', ycol='absmag', offset_factor=1., color='filter', marker=None, use_lines=False,
              normalize=False, fillmark=True, **kwargs):
@@ -423,29 +430,19 @@ def plot(self, xcol='phase', ycol='absmag', offset_factor=1., color='filter', ma
                 marker = 'telescope'
             else:
                 marker = 'o'
-        plotthese = np.tile(True, len(self))
         criteria = {key: val for key, val in kwargs.items() if key in self.colnames}
         plot_kwargs = {key: val for key, val in kwargs.items() if key not in self.colnames}
-        for key, value in criteria.items():
-            if isinstance(value, list):
-                subplotthese = np.tile(False, len(self))
-                for val in value:
-                    subplotthese |= self[key] == val
-            else:
-                subplotthese = self[key] == value
-            plotthese &= subplotthese
-        if np.any(plotthese):
-            plottable = self[plotthese]
-        else:
+        plottable = self.where(**criteria)
+        if len(plottable) == 0:
             return
-        groupby = []
+        groupby = set()
         if color in plottable.keys():
-            groupby.append(color)
+            groupby.add(color)
         if marker in plottable.keys():
-            groupby.append(marker)
+            groupby.add(marker)
         if groupby:
-            plottable = plottable.group_by(groupby)
-        for g in plottable.groups:
+            plottable = plottable.group_by(list(groupby))
+        for g, k in zip(plottable.groups, plottable.groups.keys):
             filt = g['filter'][0]
             if color == 'filter':
                 col = filt.color
@@ -454,8 +451,7 @@ def plot(self, xcol='phase', ycol='absmag', offset_factor=1., color='filter', ma
                 col = self.sn.plotcolor
                 mec = col if col not in ['w', '#FFFFFF'] else 'k'
             else:
-                col = 'k'
-                mec = 'k'
+                col = mec = next(itercolors)
             mfc = col if fillmark else 'none'
             if marker == 'name':
                 mark = self.sn.marker
@@ -466,14 +462,12 @@ def plot(self, xcol='phase', ycol='absmag', offset_factor=1., color='filter', ma
                             self.markers[g[marker][0]] = nextmarker
                             break
                     else:
-                        for nextmarker in itermarkers:
-                            self.markers[g[marker][0]] = nextmarker
-                            break
+                        self.markers[g[marker][0]] = next(itermarkers)
                 mark = self.markers[g[marker][0]]
             elif marker in MarkerStyle.markers:
                 mark = marker
             else:
-                mark = MarkerStyle.markers[0]
+                mark = next(itermarkers)
             usedmarkers.append(mark)
             if use_lines:
                 g.sort(xcol)
@@ -489,12 +483,14 @@ def plot(self, xcol='phase', ycol='absmag', offset_factor=1., color='filter', ma
                 y -= self.sn.peakabsmag
             if 'mag' in ycol and 'nondet' in g.keys() and marker:  # don't plot if no markers used
                 plt.plot(x[g['nondet']], y[g['nondet']], marker=arrow, linestyle='none', ms=25, mec=mec, **plot_kwargs)
-            if len(filt.name) >= 4 and not filt.offset:
-                label = filt.name
-            elif offset_factor:
-                label = '${}{:+.0f}$'.format(filt.name, -filt.offset * offset_factor)
-            else:
-                label = '${}$'.format(filt.name)
+            if 'filter' in k.colnames:
+                if len(filt.name) >= 4 and not filt.offset:
+                    k['filter'] = filt.name
+                elif offset_factor:
+                    k['filter'] = '${}{:+.0f}$'.format(filt.name, -filt.offset * offset_factor)
+                else:
+                    k['filter'] = '${}$'.format(filt.name)
+            label = ' '.join([str(kv) for kv in k.values()])
             if self.sn is None:
                 linestyle = None
                 linewidth = None
diff --git a/lightcurve_fitting/models.py b/lightcurve_fitting/models.py
index d53d420..2787e81 100644
--- a/lightcurve_fitting/models.py
+++ b/lightcurve_fitting/models.py
@@ -158,22 +158,28 @@ def shock_cooling(t_in, f, v_s, M_env, f_rho_M, R, t_exp=0., kappa=1., n=1.5, RW
     return y_fit
 
 
-def t_min(v_s, M_env, f_rho_M, R, t_exp=0., kappa=1.):
+def t_min(p, kappa=1.):
     """
     The minimum validity time for the :func:`shock_cooling` model
 
     :math:`t_\\mathrm{min} = (0.2\\,\\mathrm{d}) \\frac{R}{v_s}
     \\max\\left[0.5, \\frac{R^{0.4}}{(f_ρ M κ)^{0.2} v_s^{-0.7}}\\right] + t_\\mathrm{exp}` (Eq. 17)
     """
+    v_s = p[0]
+    f_rho_M = p[2]
+    R = p[3]
+    t_exp = p[4] if len(p) > 4 else 0.
     return 0.2 * R / v_s * np.maximum(0.5, R ** 0.4 * (f_rho_M * kappa) ** -0.2 * v_s ** -0.7) + t_exp
 
 
-def t_max(v_s, M_env, f_rho_M, R, t_exp=0., kappa=1.):
+def t_max(p, kappa=1.):
     """
     The maximum validity time for the :func:`shock_cooling` model
 
     :math:`t_\\mathrm{max} = (7.4\,\\mathrm{d}) \\left(\\frac{R}{κ}\\right)^{0.55} + t_\\mathrm{exp}` (Eq. 24)
     """
+    R = p[3]
+    t_exp = p[4] if len(p) > 4 else 0.
     return 7.4 * (R / kappa) ** 0.55 + t_exp
 
 
@@ -273,12 +279,15 @@ def t_min2(*args):
     raise NotImplementedError('t_min cannot be translated to these parameters')
 
 
-def t_max2(T_1, L_1=0., t_tr=0., t_exp=0., n=1.5):
+def t_max2(p, n=1.5):
     """
     The maximum validity time for the :func:`shock_cooling2` model
 
     :math:`t_\\mathrm{max} = \\left(\\frac{8.12\\,\\mathrm{kK}}{T_1}\\right)^{1/(2 ε_1 - 0.5)} + t_\\mathrm{exp}`
     """
+    T_1 = p[0]
+    t_exp = p[3] if len(p) > 3 else 0.
+
     if n == 1.5:
         epsilon_1 = 0.027
     elif n == 3.:
diff --git a/lightcurve_fitting/speccal.py b/lightcurve_fitting/speccal.py
index d6eb1f6..93dab23 100755
--- a/lightcurve_fitting/speccal.py
+++ b/lightcurve_fitting/speccal.py
@@ -2,6 +2,7 @@
 
 import numpy as np
 from .lightcurve import LC
+from .filters import filtdict
 from astropy import constants as const, units as u
 from astropy.io import fits
 from astropy.wcs import WCS
@@ -12,6 +13,7 @@
 import os
 import warnings
 import json
+import re
 
 
 def removebadcards(hdr):
@@ -85,7 +87,10 @@ def readfitsspec(filename, header=False, ext=None):
     with warnings.catch_warnings():
         warnings.simplefilter('ignore')
         wcs = WCS(removebadcards(hdr), naxis=1, relax=False, fix=False)
-    wl = wcs.wcs_pix2world(np.arange(len(flux)), 0)[0]
+    if 'CUNIT1' in hdr:
+        wl = wcs.pixel_to_world(np.arange(len(flux))).to(hdr['CUNIT1']).value
+    else:
+        wl = wcs.wcs_pix2world(np.arange(len(flux)), 0)[0]
     if header:
         return wl, flux, hdr
     else:
@@ -123,7 +128,7 @@ def convert_spectrum_units(wl, flux, hdr, default_bunit='erg / (Angstrom cm2 s)'
         bunit = bunit.replace('Ang', 'Angstrom')
     if 'Angstrom' not in bunit:
         bunit = bunit.replace('A', 'Angstrom')
-    cunit = hdr.get('CUNIT1', default_cunit)
+    cunit = hdr.get('CUNIT1', hdr.get('XUNITS', default_cunit))
     if cunit.lower() == 'angstroms':
         cunit = cunit.rstrip('s')
     wl = u.Quantity(wl, cunit).to(default_cunit)
@@ -213,22 +218,23 @@ def readspec(f, verbose=False):
         x, y, hdr = readfitsspec(f, header=True)
     elif ext == '.json':
         x, y, hdr = readOSCspec(f)
-    elif ext in ['.ascii', '.asci', '.flm', '.txt', '.dat']:
+    elif ext in ['.ascii', '.asci', '.flm', '.txt', '.dat', '.csv']:
         t = Table.read(f, format='ascii')
         # assume it's the first two columns, regardless of if column names are given
         x = t.columns[0]
         y = t.columns[1]
-        if 'comments' in t.meta:
-            hdr = {kwd.strip(' #'): val.strip(' "\'') for kwd, val in
-                   [(line.split('=')[0], '='.join(line.split(' / ')[0].split('=')[1:])) for line in t.meta['comments']
-                    if '=' in line]}
-            # (anything before first '=', anything between first '=' and ' / ')
-        else:
-            hdr = {}
+        hdr = {}
+        comments = t.meta.get('comments', [])
+        for line in comments:
+            match = re.search('([^ ]*) *[=:] *([^/]*)', line)
+            if match is None:
+                continue
+            kwd, val = match.groups()  # (anything before first '='/':', anything between first '='/':' and '/')
+            hdr[kwd.strip(' #')] = val.strip(' "\'')
     else:
         raise Exception('ext not recognized:', f)
-
-    for kwd in ['MJD-OBS', 'MJD_OBS', 'MJD', 'JD', 'DATE-AVG', 'UTMIDDLE', 'DATE-OBS', 'DATE_BEG', 'UTSHUT']:
+    for kwd in ['MJD-OBS', 'MJD_OBS', 'MJD', 'JD', 'DATE-AVG', 'UTMIDDLE', 'DATE-OBS', 'DATE_BEG', 'UTSHUT', 'OBS_DATE',
+                'AVE_MJD']:
         if kwd in hdr and hdr[kwd]:
             if 'MJD' in kwd:
                 date = Time(float(hdr[kwd]), format='mjd')
@@ -238,6 +244,8 @@ def readspec(f, verbose=False):
                 date = Time(float(hdr[kwd]) + 2400000, format='jd')
             elif 'T' in hdr[kwd]:
                 date = Time(hdr[kwd])
+            elif kwd == 'OBS_DATE':
+                date = Time(hdr[kwd].split('+')[0])
             elif '-' in hdr[kwd]:
                 for kwd2 in ['UTMIDDLE', 'EXPSTART', 'UT']:
                     if kwd2 in hdr and type(hdr[kwd2]) == str and ':' in hdr[kwd2]:
@@ -255,7 +263,6 @@ def readspec(f, verbose=False):
                 continue
             break
     else:  # hope it's in the filename
-        import re
         m1 = re.search('24[0-9][0-9][0-9][0-9][0-9]\.[0-9]+', f)  # JD w/1 or more decimals
         m2 = re.search('([12][90][0-9][0-9])-?(0[0-9]|1[0-2])-?(0[1-9]|[12][0-9]|3[01])', f)  # YYYYMMDD
         m_tns = re.search(
@@ -279,10 +286,20 @@ def readspec(f, verbose=False):
 
     if 'TELESCOP' in hdr:
         telescope = hdr['TELESCOP'].strip()
+    elif 'TELESCOPE' in hdr:
+        telescope = hdr['TELESCOPE'].strip()
+    elif 'OBSERVAT' in hdr:
+        telescope = hdr['OBSERVAT'].strip()
     else:
         telescope = ''
     if 'INSTRUME' in hdr:
         instrument = hdr['INSTRUME'].strip()
+    elif 'INSTRUMENT' in hdr:
+        instrument = hdr['INSTRUMENT'].strip()
+    elif 'INSTR' in hdr:
+        instrument = hdr['INSTR'].strip()
+    elif 'INSTRUMENT_ID' in hdr:
+        instrument = hdr['INSTRUMENT_ID']
     else:
         instrument = ''
 
@@ -315,7 +332,7 @@ def calibrate_spectra(spectra, lc, filters=None, order=0, subtract_percentile=No
         Plot the observed light curve and the uncalibrated and calibrated spectra, and ask whether to save the results
     """
     if filters is not None:
-        lc = lc.where(filt=filters)
+        lc = lc.where(filter=[filtdict[f] for f in filters])
     lc.calcFlux()
     lc.sort('MJD')
     filts = set(lc['filter'])
@@ -324,11 +341,14 @@ def calibrate_spectra(spectra, lc, filters=None, order=0, subtract_percentile=No
         filt.read_curve()
         filt.trans.sort('freq')
 
+    plt.ion()
+    fig = plt.figure(figsize=(8., 6.))
+
     for spec in spectra:
         wl, flux, time, _, _ = readspec(spec)
         mjd = time.mjd
         if show:
-            fig = plt.figure(figsize=(8., 6.))
+            fig.clf()
             ax1 = plt.subplot(211)
             lc.plot(xcol='MJD', ycol='flux', offset_factor=0)
             ax1.axvline(mjd)
@@ -336,10 +356,10 @@ def calibrate_spectra(spectra, lc, filters=None, order=0, subtract_percentile=No
             ax1.set_ylabel('$F_\\nu$ (W Hz$^{-1}$)')
             ax2 = plt.subplot(212)
         good = ~np.isnan(flux)
-        wl = wl[good] * u.angstrom
+        lam = wl[good] * u.angstrom
         Flam = flux[good] * u.erg / u.s / u.angstrom / u.cm**2
-        nu = const.c / wl
-        Fnu = (Flam * wl / nu).to(u.W / u.Hz / u.m**2).value[::-1]
+        nu = const.c / lam
+        Fnu = (Flam * lam / nu).to(u.W / u.Hz / u.m**2).value[::-1]
         nu = nu.to(u.THz).value[::-1]
         if subtract_percentile is not None:
             Fnu -= np.nanpercentile(Fnu, subtract_percentile)
@@ -361,12 +381,13 @@ def calibrate_spectra(spectra, lc, filters=None, order=0, subtract_percentile=No
             ratio = flux_lc / flux_spec
             if show:
                 ax2.axvspan(freq0, freq1, color=filt.color, alpha=0.2)
-                ax2.plot(filt.freq_eff, flux_lc, marker='o', color=filt.color, zorder=5)
+                ax2.plot(filt.freq_eff, flux_lc, marker='o', zorder=5, **filt.plotstyle)
             ratios.append(ratio)
             freqs.append(filt.freq_eff.value)
         if not ratios:
             print('no filters for', spec)
-            plt.close(fig)
+            if show:
+                plt.close(fig)
             continue
         scale = np.mean(ratios)
         if order:
@@ -383,7 +404,7 @@ def calibrate_spectra(spectra, lc, filters=None, order=0, subtract_percentile=No
             if order:
                 ax2.plot(nu, Fnu * corr, color='C2', label='rescaled & warped')
                 plt.legend(loc='best')
-            plt.show()
+            plt.pause(0.1)
             ans = input('accept this scale? [Y/n] ')
         if not show or ans.lower() != 'n':
             data_out = np.array([wl[good], flux[good] * corr]).T
diff --git a/requirements.txt b/requirements.txt
index 379b4ce..5d3e987 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,7 +1,7 @@
 # List required packages in this file, one per line.
 numpy
 matplotlib
-emcee
+emcee >= 3.1.1
 corner
 astropy
 scipy
\ No newline at end of file