Merge pull request #128 from CosmoStat/rename-PSFSimulator

Rename SimPSFToolkit.py module

docs/source/wf_psf.sims.SimPSFToolkit.rst

@@ -1,7 +1,7 @@
-wf\_psf.sims.SimPSFToolkit module
+wf\_psf.sims.psf_simulator module
 =================================
 
-.. automodule:: wf_psf.sims.SimPSFToolkit
+.. automodule:: wf_psf.sims.psf_simulator
    :members:
    :undoc-members:
    :show-inheritance:

docs/source/wf_psf.sims.rst

@@ -12,4 +12,4 @@ Submodules
 .. toctree::
    :maxdepth: 4
 
-   wf_psf.sims.SimPSFToolkit
+   wf_psf.sims.psf_simulator

src/wf_psf/data/training_preprocessing.py

@@ -10,7 +10,6 @@
 import wf_psf.utils.utils as utils
 import tensorflow as tf
 import tensorflow_addons as tfa
-import wf_psf.sims.SimPSFToolkit as SimPSFToolkit
 import os
 
 
@@ -24,7 +23,7 @@ class TrainingDataHandler:
     training_data_params: Recursive Namespace object
         Recursive Namespace object containing training data parameters
     simPSF: object
-        SimPSFToolkit instance
+        PSFSimulator instance
     n_bins_lambda: int
         Number of bins in wavelength
 
@@ -66,7 +65,7 @@ class TestDataHandler:
     test_data_params: Recursive Namespace object
         Recursive Namespace object containing test data parameters
     simPSF: object
-        SimPSFToolkit instance
+        PSFSimulator instance
     n_bins_lambda: int
         Number of bins in wavelength
 

src/wf_psf/metrics/metrics.py

@@ -5,7 +5,7 @@
 import wf_psf.utils.utils as utils
 from wf_psf.psf_models.tf_psf_field import build_PSF_model
 from wf_psf.psf_models import tf_psf_field as psf_field
-from wf_psf.sims import SimPSFToolkit as SimPSFToolkit
+from wf_psf.sims import psf_simulator as psf_simulator
 import logging
 
 logger = logging.getLogger(__name__)
@@ -640,7 +640,7 @@ def gen_GT_wf_model(test_wf_file_path, pred_output_Q=1, pred_output_dim=64):
 
     ## Generate initializations
     # Prepare np input
-    simPSF_np = SimPSFToolkit(
+    simPSF_np = psf_simulator.PSFSimulator(
         zernikes,
         max_order=wf_test_params["max_order"],
         pupil_diameter=wf_test_params["pupil_diameter"],

src/wf_psf/metrics/metrics_interface.py

@@ -66,7 +66,7 @@ def evaluate_metrics_polychromatic_lowres(self, psf_model, simPSF, dataset):
         psf_model: object
             PSF model class instance of the psf model selected for metrics evaluation.
         simPSF: object
-            SimPSFToolkit instance
+            PSFSimulator instance
         test_dataset: dict
             Test dataset dictionary
 
@@ -111,7 +111,7 @@ def evaluate_metrics_mono_rmse(self, psf_model, simPSF, dataset):
         psf_model: object
             PSF model class instance of the psf model selected for metrics evaluation.
         simPSF: object
-            SimPSFToolkit instance
+            PSFSimulator instance
         test_dataset: dict
             Test dataset dictionary
 
@@ -157,7 +157,7 @@ def evaluate_metrics_opd(self, psf_model, simPSF, dataset):
         psf_model: object
             PSF model class instance of the psf model selected for metrics evaluation.
         simPSF: object
-            SimPSFToolkit instance
+            PSFSimulator instance
         test_dataset: dict
             Test dataset dictionary
 
@@ -201,7 +201,7 @@ def evaluate_metrics_shape(self, psf_model, simPSF, dataset):
         psf_model: object
             PSF model class instance of the psf model selected for metrics evaluation.
         simPSF: object
-            SimPSFToolkit instance
+            PSFSimulator instance
         dataset: dict
             Test dataset dictionary
 

src/wf_psf/psf_models/psf_model_parametric.py

@@ -170,7 +170,7 @@ def predict_mono_psfs(self, input_positions, lambda_obs, phase_N):
 
         phase_N: int
             Required wavefront dimension. Should be calculated with as:
-            ``simPSF_np = wf.SimPSFToolkit(...)``
+            ``simPSF_np = wf_psf.sims.psf_simulator.PSFSimulator(...)``
             ``phase_N = simPSF_np.feasible_N(lambda_obs)``
         """
 

src/wf_psf/psf_models/psf_model_semiparametric.py

@@ -223,7 +223,7 @@ def predict_mono_psfs(self, input_positions, lambda_obs, phase_N):
 
         phase_N: int
             Required wavefront dimension. Should be calculated with as:
-            ``simPSF_np = wf.SimPSFToolkit(...)``
+            ``simPSF_np = wf_psf.sims.psf_simulator.PSFSimulator(...)``
             ``phase_N = simPSF_np.feasible_N(lambda_obs)``
 
         """

src/wf_psf/psf_models/psf_models.py

@@ -11,7 +11,7 @@
 import tensorflow as tf
 from tensorflow.python.keras.engine import data_adapter
 from wf_psf.utils.utils import PI_zernikes, zernike_generator
-from wf_psf.sims.SimPSFToolkit import SimPSFToolkit
+from wf_psf.sims.psf_simulator import PSFSimulator
 import glob
 from sys import exit
 import logging
@@ -186,7 +186,7 @@ def tf_obscurations(pupil_diam, N_filter=2):
         TensorFlow EagerTensor type
 
     """
-    obscurations = SimPSFToolkit.generate_pupil_obscurations(
+    obscurations = PSFSimulator.generate_pupil_obscurations(
         N_pix=pupil_diam, N_filter=N_filter
     )
     return tf.convert_to_tensor(obscurations, dtype=tf.complex64)
@@ -208,7 +208,7 @@ def simPSF(model_params):
 
     """
 
-    simPSF_np = SimPSFToolkit(
+    simPSF_np = PSFSimulator(
         max_order=model_params.param_hparams.n_zernikes,
         pupil_diameter=model_params.pupil_diameter,
         output_dim=model_params.output_dim,

src/wf_psf/psf_models/tf_layers.py

@@ -126,7 +126,7 @@ class TF_batch_poly_PSF(tf.keras.layers.Layer):
     """Calculate a polychromatic PSF from an OPD and stored SED values.
 
     The calculation of the packed values with the respective SED is done
-    with the SimPSFToolkit class but outside the TF class.
+    with the PSFSimulator class but outside the TF class.
 
     Parameters
     ----------
@@ -238,7 +238,7 @@ class TF_batch_mono_PSF(tf.keras.layers.Layer):
     """Calculate a monochromatic PSF from a batch of OPDs.
 
     The calculation of the ``phase_N`` variable is done
-    with the SimPSFToolkit class but outside the TF class.
+    with the PSFSimulator class but outside the TF class.
 
     Parameters
     ----------
@@ -945,7 +945,7 @@ class OLD_TF_batch_poly_PSF(tf.keras.layers.Layer):
     """Calculate a polychromatic PSF from an OPD and stored SED values.
 
     The calculation of the packed values with the respective SED is done
-    with the SimPSFToolkit class but outside the TF class.
+    with the PSFSimulator class but outside the TF class.
 
 
 

src/wf_psf/psf_models/tf_modules.py

@@ -231,7 +231,7 @@ def __call__(self, opd):
 #     """Calculate a polychromatic PSF from an OPD and stored SED values.
 
 #     The calculation of the packed values with the respective SED is done
-#     with the SimPSFToolkit class but outside the TF class.
+#     with the PSFSimulator class but outside the TF class.
 
 #     packed_elems: Tuple of tensors
 #         Contains three 1D tensors with the parameters needed for

src/wf_psf/psf_models/tf_psf_field.py

@@ -155,7 +155,7 @@ def predict_mono_psfs(self, input_positions, lambda_obs, phase_N):
 
         phase_N: int
             Required wavefront dimension. Should be calculated with as:
-            ``simPSF_np = wf.SimPSFToolkit(...)``
+            ``simPSF_np = wf_psf.sims.psf_simulator.PSFSimulator(...)``
             ``phase_N = simPSF_np.feasible_N(lambda_obs)``
         """
 
@@ -391,7 +391,7 @@ def predict_mono_psfs(self, input_positions, lambda_obs, phase_N):
 
         phase_N: int
             Required wavefront dimension. Should be calculated with as:
-            ``simPSF_np = wf.SimPSFToolkit(...)``
+            ``simPSF_np =wf_psf.sims.psf_simulator.PSFSimulator(...)``
             ``phase_N = simPSF_np.feasible_N(lambda_obs)``
         """
 
@@ -821,7 +821,7 @@ def predict_mono_psfs(self, input_positions, lambda_obs, phase_N):
             Observed wavelength in um.
         phase_N: int
             Required wavefront dimension. Should be calculated with as:
-            ``simPSF_np = wf.SimPSFToolkit(...)``
+            ``simPSF_np = wf_psf.sims.psf_simulator.PSFSimulator(...)``
             ``phase_N = simPSF_np.feasible_N(lambda_obs)``
 
         """
@@ -1103,7 +1103,7 @@ def predict_mono_psfs(self, input_positions, lambda_obs, phase_N):
             Observed wavelength in um.
         phase_N: int
             Required wavefront dimension. Should be calculated with as:
-            ``simPSF_np = wf.SimPSFToolkit(...)``
+            ``simPSF_np = wf_psf.sims.psf_simulator.PSFSimulator(...)``
             ``phase_N = simPSF_np.feasible_N(lambda_obs)``
 
         """

src/wf_psf/sims/SimPSFToolkit.py → src/wf_psf/sims/psf_simulator.py

@@ -21,7 +21,7 @@
         print("Problem importing skimage..")
 
 
-class SimPSFToolkit(object):
+class PSFSimulator(object):
     """Simulate PSFs.
 
     In the future the zernike maps could be created with galsim or some other

src/wf_psf/utils/utils.py

@@ -40,7 +40,7 @@ def generate_SED_elems(SED, sim_psf_toolkit, n_bins=20):
     ----------
     SED:
     sim_psf_toolkit:
-        An instance of the SimPSFToolkit class with the correct
+        An instance of the PSFSimulator class with the correct
     initialization values.
     n_bins: int
         Number of wavelength bins
@@ -64,7 +64,7 @@ def generate_SED_elems_in_tensorflow(
     ----------
     SED:
     sim_psf_toolkit:
-        An instance of the SimPSFToolkit class with the correct
+        An instance of the PSFSimulator class with the correct
     initialization values.
     n_bins: int
         Number of wavelength bins