update to next caskade version

.readthedocs.yaml

@@ -37,7 +37,6 @@ build:
 
 python:
   install:
-    - requirements: requirements.txt # Path to your requirements.txt file
     - requirements: docs/requirements.txt # Path to your requirements.txt file
     - method: pip
-      path: . # Install the package itself
+      path: .[dev] # Install the package itself

astrophot/__init__.py

@@ -1,6 +1,3 @@
-import argparse
-import requests
-import torch
 from . import config, models, plots, utils, fit, image, errors
 from .param import forward, Param, Module
 
@@ -38,110 +35,6 @@
 __author__ = "Connor Stone"
 __email__ = "connorstone628@gmail.com"
 
-
-def run_from_terminal() -> None:
-    """
-    Running from terminal no longer supported. This is only used for convenience to download the tutorials.
-
-    """
-    config.logger.debug("running from the terminal, not sure if it will catch me.")
-    parser = argparse.ArgumentParser(
-        prog="astrophot",
-        description="Fast and flexible astronomical image photometry package. For the documentation go to: https://astrophot.readthedocs.io",
-        epilog="Please see the documentation or contact connor stone (connorstone628@gmail.com) for further assistance.",
-    )
-    parser.add_argument(
-        "filename",
-        nargs="?",
-        metavar="configfile",
-        help="the path to the configuration file. Or just 'tutorial' to download tutorials.",
-    )
-    # parser.add_argument(
-    #     "--config",
-    #     type=str,
-    #     default="astrophot",
-    #     choices=["astrophot", "galfit"],
-    #     metavar="format",
-    #     help="The type of configuration file being being provided. One of: astrophot, galfit.",
-    # )
-    parser.add_argument(
-        "-v",
-        "--version",
-        action="version",
-        version=f"%(prog)s {__version__}",
-        help="print the current AstroPhot version to screen",
-    )
-    # parser.add_argument(
-    #     "--log",
-    #     type=str,
-    #     metavar="logfile.log",
-    #     help="set the log file name for AstroPhot. use 'none' to suppress the log file.",
-    # )
-    # parser.add_argument(
-    #     "-q",
-    #     action="store_true",
-    #     help="quiet flag to stop command line output, only print to log file",
-    # )
-    # parser.add_argument(
-    #     "--dtype",
-    #     type=str,
-    #     choices=["float64", "float32"],
-    #     metavar="datatype",
-    #     help="set the float point precision. Must be one of: float64, float32",
-    # )
-    # parser.add_argument(
-    #     "--device",
-    #     type=str,
-    #     choices=["cpu", "gpu"],
-    #     metavar="device",
-    #     help="set the device for AstroPhot to use for computations. Must be one of: cpu, gpu",
-    # )
-
-    args = parser.parse_args()
-
-    if args.log is not None:
-        config.set_logging_output(
-            stdout=not args.q, filename=None if args.log == "none" else args.log
-        )
-    elif args.q:
-        config.set_logging_output(stdout=not args.q, filename="AstroPhot.log")
-
-    if args.dtype is not None:
-        config.DTYPE = torch.float64 if args.dtype == "float64" else torch.float32
-    if args.device is not None:
-        config.DEVICE = "cpu" if args.device == "cpu" else "cuda:0"
-
-    if args.filename is None:
-        raise RuntimeError(
-            "Please pass a config file to astrophot. See 'astrophot --help' for more information, or go to https://astrophot.readthedocs.io"
-        )
-    if args.filename in ["tutorial", "tutorials"]:
-        tutorials = [
-            "https://raw.github.com/Autostronomy/AstroPhot/main/docs/source/tutorials/GettingStarted.ipynb",
-            "https://raw.github.com/Autostronomy/AstroPhot/main/docs/source/tutorials/GroupModels.ipynb",
-            "https://raw.github.com/Autostronomy/AstroPhot/main/docs/source/tutorials/ModelZoo.ipynb",
-            "https://raw.github.com/Autostronomy/AstroPhot/main/docs/source/tutorials/JointModels.ipynb",
-            "https://raw.github.com/Autostronomy/AstroPhot/main/docs/source/tutorials/FittingMethods.ipynb",
-            "https://raw.github.com/Autostronomy/AstroPhot/main/docs/source/tutorials/CustomModels.ipynb",
-            "https://raw.github.com/Autostronomy/AstroPhot/main/docs/source/tutorials/BasicPSFModels.ipynb",
-            "https://raw.github.com/Autostronomy/AstroPhot/main/docs/source/tutorials/AdvancedPSFModels.ipynb",
-            "https://raw.github.com/Autostronomy/AstroPhot/main/docs/source/tutorials/ConstrainedModels.ipynb",
-        ]
-        for url in tutorials:
-            try:
-                R = requests.get(url)
-                with open(url[url.rfind("/") + 1 :], "w") as f:
-                    f.write(R.text)
-            except:
-                print(
-                    f"WARNING: couldn't find tutorial: {url[url.rfind('/')+1:]} check internet connection"
-                )
-
-        config.logger.info("collected the tutorials")
-    else:
-        raise ValueError(f"Unrecognized request")
-
-
 __all__ = (
     "models",
     "image",
@@ -170,7 +63,7 @@ def run_from_terminal() -> None:
     "Module",
     "config",
     "backend",
-    "run_from_terminal",
+    "ArrayLike",
     "__version__",
     "__author__",
     "__email__",

astrophot/fit/hmc.py

@@ -52,7 +52,8 @@ def new_configure(self, mass_matrix_shape, adapt_mass_matrix=True, options={}):
         self.inverse_mass_matrix = inverse_mass_matrix
 
 
-BlockMassMatrix.configure = new_configure
+if pyro is not None:
+    BlockMassMatrix.configure = new_configure
 ############################################
 
 

astrophot/models/base.py

@@ -63,7 +63,6 @@ def __init__(self, *, name=None, target=None, window=None, mask=None, filename=N
             setattr(self, key, param)
 
         self.saveattrs.update(self.options)
-        self.saveattrs.add("window.extent")
 
         kwargs.pop("model_type", None)  # model_type is set by __new__
         if len(kwargs) > 0:

astrophot/models/mixins/ferrer.py

@@ -85,10 +85,10 @@ class iFerrerMixin:
 
     _model_type = "ferrer"
     _parameter_specs = {
-        "rout": {"units": "arcsec", "valid": (0.0, None), "shape": (), "dynamic": True},
-        "alpha": {"units": "unitless", "valid": (0, 10), "shape": (), "dynamic": True},
-        "beta": {"units": "unitless", "valid": (0, 2), "shape": (), "dynamic": True},
-        "I0": {"units": "flux/arcsec^2", "valid": (0.0, None), "shape": (), "dynamic": True},
+        "rout": {"units": "arcsec", "valid": (0.0, None), "dynamic": True},
+        "alpha": {"units": "unitless", "valid": (0, 10), "dynamic": True},
+        "beta": {"units": "unitless", "valid": (0, 2), "dynamic": True},
+        "I0": {"units": "flux/arcsec^2", "valid": (0.0, None), "dynamic": True},
     }
 
     @torch.no_grad()

astrophot/models/model_object.py

@@ -46,6 +46,7 @@ def __init__(self, *args, psf=None, psf_convolve: bool = False, **kwargs):
         super().__init__(*args, **kwargs)
         self.psf = psf
         self.psf_convolve = psf_convolve
+        self.saveattrs.add("window.extent")
 
     @property
     def psf(self):

docs/source/tutorials/AdvancedPSFModels.ipynb

@@ -71,7 +71,7 @@
    "source": [
     "# Now we initialize on the image\n",
     "psf_model = ap.Model(\n",
-    "    name=\"init psf\",\n",
+    "    name=\"init_psf\",\n",
     "    model_type=\"moffat psf model\",\n",
     "    target=psf_target,\n",
     ")\n",
@@ -134,7 +134,7 @@
     "    target=psf_target,\n",
     ")\n",
     "psf_group_model = ap.Model(\n",
-    "    name=\"psf group\",\n",
+    "    name=\"psf_group\",\n",
     "    model_type=\"psf group model\",\n",
     "    target=psf_target,\n",
     "    models=[psf_model1, psf_model2],\n",
@@ -175,7 +175,7 @@
     ")\n",
     "\n",
     "true_psf_model = ap.Model(\n",
-    "    name=\"true psf\",\n",
+    "    name=\"true_psf\",\n",
     "    model_type=\"moffat psf model\",\n",
     "    target=psf_target,\n",
     "    n=2,\n",
@@ -190,7 +190,7 @@
     ")\n",
     "\n",
     "true_model = ap.Model(\n",
-    "    name=\"true model\",\n",
+    "    name=\"true_model\",\n",
     "    model_type=\"sersic galaxy model\",\n",
     "    target=target,\n",
     "    center=[50.0, 50.0],\n",
@@ -227,7 +227,7 @@
     "\n",
     "# Here we set up a sersic model for the galaxy\n",
     "plain_galaxy_model = ap.Model(\n",
-    "    name=\"galaxy model\",\n",
+    "    name=\"galaxy_model\",\n",
     "    model_type=\"sersic galaxy model\",\n",
     "    target=target,\n",
     ")\n",
@@ -283,7 +283,7 @@
     "\n",
     "# Here we set up a sersic model for the galaxy\n",
     "live_galaxy_model = ap.Model(\n",
-    "    name=\"galaxy model\",\n",
+    "    name=\"galaxy_model\",\n",
     "    model_type=\"sersic galaxy model\",\n",
     "    target=target,\n",
     "    psf_convolve=True,\n",

docs/source/tutorials/ConstrainedModels.ipynb

@@ -195,7 +195,7 @@
     "            psf.Rd = allstars[0].psf.Rd\n",
     "        allstars.append(\n",
     "            ap.Model(\n",
-    "                name=f\"star {x} {y}\",\n",
+    "                name=f\"star_{x}_{y}\".replace(\"-\", \"n\"),\n",
     "                model_type=\"point model\",\n",
     "                center=[x, y],\n",
     "                flux=1,\n",
@@ -211,7 +211,7 @@
     "# A group model holds all the stars together\n",
     "sky = ap.Model(name=\"sky\", model_type=\"flat sky model\", I=1e-5, target=target)\n",
     "MODEL = ap.Model(\n",
-    "    name=\"spatial PSF\",\n",
+    "    name=\"spatial_PSF\",\n",
     "    model_type=\"group model\",\n",
     "    models=[sky] + allstars,\n",
     "    target=target,\n",

docs/source/tutorials/CustomModels.ipynb

@@ -131,7 +131,7 @@
    "outputs": [],
    "source": [
     "my_model = My_Sersic(  # notice we are now using the custom class\n",
-    "    name=\"wow I made a model\",\n",
+    "    name=\"wow_I_made_a_model\",\n",
     "    target=target,  # now the model knows what its trying to match\n",
     "    # note we have to give initial values for our new parameters. AstroPhot doesn't know how to auto-initialize them because they are custom\n",
     "    my_n=1.0,\n",
@@ -249,7 +249,7 @@
    "outputs": [],
    "source": [
     "my_super_model = ap.Model(\n",
-    "    name=\"goodness I made another one\",\n",
+    "    name=\"goodness_I_made_another_one\",\n",
     "    model_type=\"super mysersic galaxy model\",  # this is the type we defined above\n",
     "    target=target,\n",
     ")\n",

docs/source/tutorials/FittingMethods.ipynb

@@ -108,7 +108,7 @@
     "    for i, params in enumerate(sersic_params):\n",
     "        model_list.append(\n",
     "            ap.Model(\n",
-    "                name=f\"sersic {i}\",\n",
+    "                name=f\"sersic_{i}\",\n",
     "                model_type=\"sersic galaxy model\",\n",
     "                target=target,\n",
     "                center=[params[0], params[1]],\n",

docs/source/tutorials/GettingStarted.ipynb

@@ -123,7 +123,7 @@
    "source": [
     "# This model now has a target that it will attempt to match\n",
     "model2 = ap.Model(\n",
-    "    name=\"model with target\",\n",
+    "    name=\"model_with_target\",\n",
     "    model_type=\"sersic galaxy model\",\n",
     "    target=target,\n",
     ")\n",
@@ -330,7 +330,7 @@
     "# here we make a sersic model that can only have q and n in a narrow range\n",
     "# Also, we give PA and initial value and lock that so it does not change during fitting\n",
     "constrained_param_model = ap.Model(\n",
-    "    name=\"constrained parameters\",\n",
+    "    name=\"constrained_parameters\",\n",
     "    model_type=\"sersic galaxy model\",\n",
     "    q={\"valid\": (0.4, 0.6)},\n",
     "    n={\"valid\": (2, 3)},\n",

docs/source/tutorials/GettingStartedJAX.ipynb

@@ -144,7 +144,7 @@
    "source": [
     "# This model now has a target that it will attempt to match\n",
     "model2 = ap.Model(\n",
-    "    name=\"model with target\",\n",
+    "    name=\"model_with_target\",\n",
     "    model_type=\"sersic galaxy model\",\n",
     "    target=target,\n",
     ")\n",
@@ -351,7 +351,7 @@
     "# here we make a sersic model that can only have q and n in a narrow range\n",
     "# Also, we give PA and initial value and lock that so it does not change during fitting\n",
     "constrained_param_model = ap.Model(\n",
-    "    name=\"constrained parameters\",\n",
+    "    name=\"constrained_parameters\",\n",
     "    model_type=\"sersic galaxy model\",\n",
     "    q={\"valid\": (0.4, 0.6)},\n",
     "    n={\"valid\": (2, 3)},\n",

docs/source/tutorials/GroupModels.ipynb

@@ -121,7 +121,7 @@
     "for win in windows:\n",
     "    seg_models.append(\n",
     "        ap.Model(\n",
-    "            name=f\"object {win:02d}\",\n",
+    "            name=f\"object_{win:02d}\",\n",
     "            window=windows[win],\n",
     "            model_type=\"sersic galaxy model\",\n",
     "            target=target,\n",
@@ -131,7 +131,7 @@
     "        )\n",
     "    )\n",
     "sky = ap.Model(\n",
-    "    name=f\"sky level\",\n",
+    "    name=f\"sky_level\",\n",
     "    model_type=\"flat sky model\",\n",
     "    target=target,\n",
     "    I={\"valid\": (0, None)},\n",

docs/source/tutorials/ImageAlignment.ipynb

@@ -75,17 +75,17 @@
     "# fmt: off\n",
     "# r-band model\n",
     "psfr = ap.Model(name=\"psfr\", model_type=\"moffat psf model\", n=2, Rd=1.0, target=target_r.psf_image(data=np.zeros((51, 51))))\n",
-    "star1r = ap.Model(name=\"star1-r\", model_type=\"point model\", window=[0, 60, 80, 135], center=[12, 9], psf=psfr, target=target_r)\n",
-    "star2r = ap.Model(name=\"star2-r\", model_type=\"point model\", window=[40, 90, 20, 70], center=[3, -7], psf=psfr, target=target_r)\n",
-    "star3r = ap.Model(name=\"star3-r\", model_type=\"point model\", window=[109, 150, 40, 90], center=[-15, -3], psf=psfr, target=target_r)\n",
-    "modelr = ap.Model(name=\"model-r\", model_type=\"group model\", models=[star1r, star2r, star3r], target=target_r)\n",
+    "star1r = ap.Model(name=\"star1_r\", model_type=\"point model\", window=[0, 60, 80, 135], center=[12, 9], psf=psfr, target=target_r)\n",
+    "star2r = ap.Model(name=\"star2_r\", model_type=\"point model\", window=[40, 90, 20, 70], center=[3, -7], psf=psfr, target=target_r)\n",
+    "star3r = ap.Model(name=\"star3_r\", model_type=\"point model\", window=[109, 150, 40, 90], center=[-15, -3], psf=psfr, target=target_r)\n",
+    "modelr = ap.Model(name=\"model_r\", model_type=\"group model\", models=[star1r, star2r, star3r], target=target_r)\n",
     "\n",
     "# g-band model\n",
     "psfg = ap.Model(name=\"psfg\", model_type=\"moffat psf model\", n=2, Rd=1.0, target=target_g.psf_image(data=np.zeros((51, 51))))\n",
-    "star1g = ap.Model(name=\"star1-g\", model_type=\"point model\", window=[0, 60, 80, 135], center=star1r.center, psf=psfg, target=target_g)\n",
-    "star2g = ap.Model(name=\"star2-g\", model_type=\"point model\", window=[40, 90, 20, 70], center=star2r.center, psf=psfg, target=target_g)\n",
-    "star3g = ap.Model(name=\"star3-g\", model_type=\"point model\", window=[109, 150, 40, 90], center=star3r.center, psf=psfg, target=target_g)\n",
-    "modelg = ap.Model(name=\"model-g\", model_type=\"group model\", models=[star1g, star2g, star3g], target=target_g)\n",
+    "star1g = ap.Model(name=\"star1_g\", model_type=\"point model\", window=[0, 60, 80, 135], center=star1r.center, psf=psfg, target=target_g)\n",
+    "star2g = ap.Model(name=\"star2_g\", model_type=\"point model\", window=[40, 90, 20, 70], center=star2r.center, psf=psfg, target=target_g)\n",
+    "star3g = ap.Model(name=\"star3_g\", model_type=\"point model\", window=[109, 150, 40, 90], center=star3r.center, psf=psfg, target=target_g)\n",
+    "modelg = ap.Model(name=\"model_g\", model_type=\"group model\", models=[star1g, star2g, star3g], target=target_g)\n",
     "\n",
     "# total model\n",
     "target_full = ap.TargetImageList([target_r, target_g])\n",