updated README

README.rst

@@ -10,7 +10,7 @@ The package contains several primary classes for loading, simulating, and manipu
 Installation
 ------------
 
-The latest stable version (`1.2.7 <https://github.com/achael/eht-imaging/releases/tag/v1.2.7>`_) is available on `PyPi <https://pypi.org/project/ehtim/>`_. Simply install pip and run
+The latest stable version (`1.2.8 <https://github.com/achael/eht-imaging/releases/tag/v1.2.7>`_) is available on `PyPi <https://pypi.org/project/ehtim/>`_. Simply install pip and run
 
 .. code-block:: bash
 
@@ -86,16 +86,8 @@ Let us know if you use ehtim in your publication and we'll list it here!
 
 - First M87 Event Horizon Telescope Results IV: Imaging the Central Supermassive Black Hole, `EHTC et al. 2019 <https://arxiv.org/abs/1906.11241>`_
 
-- VLBI Imaging of black holes via second moment regularization, `Issaoun et al. 2019b <https://arxiv.org/pdf/1908.01296.pdf>`_
-
-- Using evolutionary algorithms to model relativistic jets: Application to NGC 1052, `Fromm et al. 2019 <https://arxiv.org/pdf/1904.00106.pdf>`_
-
 - EHT-HOPS Pipeline for Millimeter VLBI Data Reduction, `Blackburn et al. 2019 <https://arxiv.org/pdf/1903.08832>`_
 
-- Multi-wavelength torus-jet model for Sagittarius A*, `Vincent et al. 2019 <https://arxiv.org/pdf/1902.01175>`_
-
-- How to tell an accreting boson star from a black hole, `Olivares et al. 2020 <https://arxiv.org/abs/1809.08682>`_
-
 - Discriminating Accretion States via Rotational Symmetry in Simulated Polarimetric Images of M87, `Palumbo et al. 2020 <https://arxiv.org/pdf/2004.01751.pdf>`_
 
 - SYMBA: An end-to-end VLBI synthetic data generation pipeline, `Roelofs et al. 2020 <https://arxiv.org/pdf/2004.01161.pdf>`_
@@ -114,8 +106,6 @@ Let us know if you use ehtim in your publication and we'll list it here!
 
 - A D-term Modeling Code (DMC) for Simultaneous Calibration and Full-Stokes Imaging of VLBI Data, `Pesce et al. 2021 <https://iopscience.iop.org/article/10.3847/1538-3881/abe3f8/pdf>`_
 
-- Polarization Images of Accretion Flows around Supermassive BLack Holes: Imprints of Toroidal Field Structure, `Tsunetoe et al. 2021 <https://watermark.silverchair.com/psab054.pdf?token=AQECAHi208BE49Ooan9kkhW_Ercy7Dm3ZL_9Cf3qfKAc485ysgAAAsUwggLBBgkqhkiG9w0BBwagggKyMIICrgIBADCCAqcGCSqGSIb3DQEHATAeBglghkgBZQMEAS4wEQQMdrsOAaUsDGsDHa2cAgEQgIICeMLAC3MR9Ld7lYRP4iEip8FSTz3TTR4K_yaxhw9kPthLhZLq4Zxs8_b7EyY8BywyYn6jUVlNM1czBskta4icw9YOQf2WX-2SkBGlQo7EdpZmHStribHPOF3ZtF4YA1dWNfzrXMFSR-ZZZW9iAfUFhKhgsyc0AY1O0rJLIAvlYPBE8SEAFUpV4Ck2nV-j-u_lyqe3CZcNO_tNB4fdE1x1HwhVWb_rxyC6n13hJhCJI7U3UJ5Q2u6dNH2BS4SUzet3JZ9RvIr9GkkSRRfdp0EDwNw6aG9TpAf8B-Fu7oW_NI7w_Jvh8kZBGzhnHisZ8acBRoMwbdHMv3cHqEUY5SKcYXVYART-z0QY_MJgxCoa4KDPG6rHl52Vf-eXJaYCmL4Y7xVas_hyPeUNk9TbhPqz4c8kOceb_BTo5oC5AFnwIIKw8kWmvwL7ofkcYmsrTlo0zWtgJ1I6lU7S1wxgD2JzRDg4gtVFdIcapB8q6ZhWWcBEvmwZ9Ad39UbH-hi4VZC8-IvzbvHNqfaifGsw1yvI86uNSu-iMY5ce0vAcZijbkVpAsbkvKGD6wP_T6OczWzayk13gegLvV2wZImleSWNFKO6cOpQSTKy2TbChWuYITc_tW3wUK-QOhjsdoB4V7SvXk_9d-bvjvBflRqDEUN5P8Yj4hpDpJYty4nxGJ4K6IWkyDRt_EZ2k9SOuwgXRZXxWA4tfJvKzvab8sRFqh98EcFNqDyAs_RZt1IVDch9GVl8X1VEbdD7MSzmw04kB-5U0l8HfmgBZyXs_i2hHUKesh1oUShTLUGcx86HApZXjtA4tSJct5CD8fvk_Vim2i5xx1_xGnBt3k7Z>`_
-
 - Using space-VLBI to probe gravity around Sgr A*, `Fromm et al. 2021 <https://www.aanda.org/articles/aa/pdf/2021/05/aa37335-19.pdf>`_
 
 - Persistent Non-Gaussian Structure in the Image of Sagittarius A* at 86 GHz, `Issaoun et al. 2021 <https://iopscience.iop.org/article/10.3847/1538-4357/ac00b0/pdf>`_
@@ -128,6 +118,20 @@ Let us know if you use ehtim in your publication and we'll list it here!
 
 - Unravelling the Innermost Jet Structure of OJ 287 with the First GMVA+ALMA Observations, `Zhao et al. 2022 <https://arxiv.org/pdf/2205.00554.pdf>`_
 
+- First Sagittarius A* Event Horizon Telescope Results. III: Imaging of the Galactic Center Supermassive Black Hole, `EHTC et al. 2022 <https://arxiv.org/pdf/2311.09479.pdf>`_
+
+- Resolving the Inner Parsec of the Blazar J1924-2914 with the Event Horizon Telescope, `Issaoun et al. 2022 <https://arxiv.org/pdf/2208.01662.pdf>`_
+
+- The Event Horizon Telescope Image of the Quasar NRAO 530, `Jorstad et al. 2023 <https://arxiv.org/pdf/2302.04622.pdf>`_
+
+- First M87 Event Horizon Telescope Results. IX. Detection of Near-horizon Circular Polarization, `EHTC et al. 2023 <https://arxiv.org/pdf/2311.10976.pdf>`_
+
+- Filamentary structures as the origin of blazar jet radio variability, `Fuentes et al. 2023 <https://arxiv.org/pdf/2311.01861.pdf>`_
+
+- The persistent shadow of the supermassive black hole of M 87. I. Observations, calibration, imaging, and analysis, `EHTC et al. 2023 <https://ui.adsabs.harvard.edu/abs/2024A%26A...681A..79E/abstract>`_
+
+- Parsec-scale evolution of the gigahertz-peaked spectrum quasar PKS 0858-279, `Kosogorov et al. 2024 <https://arxiv.org/pdf/2401.03603.pdf>`_
+
 oifits Documentation
 --------------------
 

ehtim/features/rex.py

@@ -75,7 +75,8 @@
 
 class Profiles(object):
 
-    def __init__(self, im, x0, y0, profs, thetas, rmin=RMIN, rmax=RMAX, flux_norm=NORMFLUX,
+    def __init__(self, im, x0, y0, profs, thetas, rmin=RMIN, rmax=RMAX, 
+                 interptype='cubic',flux_norm=NORMFLUX,
                  profsQ=[], profsU=[]):
 
         self.x0 = x0
@@ -103,7 +104,7 @@ def __init__(self, im, x0, y0, profs, thetas, rmin=RMIN, rmax=RMAX, flux_norm=NO
 
         self.xs = np.arange(im.xdim)*im.psize/ehc.RADPERUAS
         self.ys = np.arange(im.ydim)*im.psize/ehc.RADPERUAS
-        self.interp = scipy.interpolate.interp2d(self.ys, self.xs, self.imarr, kind='cubic')
+        self.interp = scipy.interpolate.interp2d(self.ys, self.xs, self.imarr, kind=interptype)
 
         self.profiles = np.array(profs)
         self.profilesQ = np.array(profsQ)
@@ -709,7 +710,8 @@ def quad_interp_radius(r_max, dr, val_list):
 
 def compute_ring_profile(im, x0, y0, title="",
                          nrays=NRAYS, nrs=NRS, rmin=RMIN, rmax=RMAX,
-                         flux_norm=NORMFLUX, pol_profs=False):
+                         flux_norm=NORMFLUX, pol_profs=False,
+                         interptype='cubic'):
     """compute a ring profile  given a center location
     """
 
@@ -722,7 +724,7 @@ def compute_ring_profile(im, x0, y0, title="",
     ys = np.arange(im.ydim)*im.psize/ehc.RADPERUAS
 
     # TODO: test fiducial images with linear?
-    interp = scipy.interpolate.interp2d(ys, xs, imarr, kind='cubic')
+    interp = scipy.interpolate.interp2d(ys, xs, imarr, kind=interptype)
 
     def ringVals(theta):
         xxs = x0 - rs*np.sin(theta)
@@ -742,8 +744,8 @@ def ringVals(theta):
     if len(im.qvec) > 0 and len(im.uvec > 0) and pol_profs:
         qarr = im.qvec.reshape(im.ydim, im.xdim)[::-1] * factor  # in brightness temperature K
         uarr = im.uvec.reshape(im.ydim, im.xdim)[::-1] * factor  # in brightness temperature K
-        interpQ = scipy.interpolate.interp2d(ys, xs, qarr, kind='cubic')
-        interpU = scipy.interpolate.interp2d(ys, xs, uarr, kind='cubic')
+        interpQ = scipy.interpolate.interp2d(ys, xs, qarr, kind=interptype)
+        interpU = scipy.interpolate.interp2d(ys, xs, uarr, kind=interptype)
 
         def ringValsQ(theta):
             xxs = x0 - rs*np.sin(theta)
@@ -765,8 +767,9 @@ def ringValsU(theta):
             valsU = ringValsU(thetas[j])
             profsU.append(valsU)
 
-    profiles = Profiles(im, x0, y0, profs, thetas, rmin=rmin, rmax=rmax, flux_norm=flux_norm,
-                        profsQ=profsQ, profsU=profsU)
+
+    profiles = Profiles(im, x0, y0, profs, thetas, rmin=rmin, rmax=rmax, interptype=interptype,
+                        flux_norm=flux_norm,profsQ=profsQ, profsU=profsU)
 
     return profiles
 

ehtim/image.py

@@ -2563,7 +2563,8 @@ def observe(self, array, tint, tadv, tstart, tstop, bw,
                stabilize_scan_phase (bool): if True, random phase errors are constant over scans
                stabilize_scan_amp (bool): if True, random amplitude errors are constant over scans
                neggains (bool): if True, force the applied gains to be <1
-
+               
+               tau (float): the base opacity at all sites, or a dict giving one opacity per site
                taup (float): the fractional std. dev. of the random error on the opacities
                gainp (float): the fractional std. dev. of the random error on the gains
                               or a dict giving one std. dev. per site

setup.py

@@ -7,7 +7,7 @@ def read(fname):
 if __name__ == "__main__":
     setup(name="ehtim",
 
-          version = "1.2.7",
+          version = "1.2.8",
 
           author = "Andrew Chael",
           author_email = "[email protected]",