Merge pull request #24 from LSSTDESC/user/aimalz/renaming

naming consistency/clarity within src/rail/estimation

src/rail/estimation/algos/naiveStack.py → src/rail/estimation/algos/naive_stack.py

@@ -9,11 +9,11 @@
 import qp
 
 
-class NaiveStack(PZSummarizer):
+class NaiveStackSummarizer(PZSummarizer):
     """Summarizer which simply histograms a point estimate
     """
 
-    name = 'NaiveStack'
+    name = 'NaiveStackSummarizer'
     config_options = PZSummarizer.config_options.copy()
     config_options.update(zmin=Param(float, 0.0, msg="The minimum redshift of the z grid"),
                           zmax=Param(float, 3.0, msg="The maximum redshift of the z grid"),

src/rail/estimation/algos/pointEstimateHist.py → src/rail/estimation/algos/point_est_hist.py

@@ -9,11 +9,11 @@
 import qp
 
 
-class PointEstimateHist(PZSummarizer):
+class PointEstHistSummarizer(PZSummarizer):
     """Summarizer which simply histograms a point estimate
     """
 
-    name = 'PointEstimateHist'
+    name = 'PointEstHistSummarizer'
     config_options = PZSummarizer.config_options.copy()
     config_options.update(zmin=Param(float, 0.0, msg="The minimum redshift of the z grid"),
                           zmax=Param(float, 3.0, msg="The maximum redshift of the z grid"),

src/rail/estimation/algos/randomPZ.py → src/rail/estimation/algos/random_gauss.py

@@ -12,11 +12,11 @@
 import qp
 
 
-class RandomPZ(CatEstimator):
+class RandomGaussEstimator(CatEstimator):
     """Random CatEstimator
     """
 
-    name = 'RandomPZ'
+    name = 'RandomGaussEstimator'
     inputs = [('input', TableHandle)]
     config_options = CatEstimator.config_options.copy()
     config_options.update(rand_width=Param(float, 0.025, "ad hock width of PDF"),

src/rail/estimation/algos/trainZ.py → src/rail/estimation/algos/train_z.py

@@ -23,11 +23,11 @@ def __init__(self, zgrid, pdf, zmode):
         self.zmode = zmode
 
 
-class Inform_trainZ(CatInformer):
+class TrainZInformer(CatInformer):
     """Train an Estimator which returns a global PDF for all galaxies
     """
 
-    name = 'Inform_trainZ'
+    name = 'TrainZInformer'
     config_options = CatInformer.config_options.copy()
     config_options.update(zmin=SHARED_PARAMS,
                           zmax=SHARED_PARAMS,
@@ -56,11 +56,11 @@ def run(self):
         self.add_data('model', self.model)
 
 
-class TrainZ(CatEstimator):
+class TrainZEstimator(CatEstimator):
     """CatEstimator which returns a global PDF for all galaxies
     """
 
-    name = 'TrainZ'
+    name = 'TrainZEstimator'
     config_options = CatEstimator.config_options.copy()
     config_options.update(zmin=SHARED_PARAMS,
                           zmax=SHARED_PARAMS,

src/rail/estimation/algos/varInference.py → src/rail/estimation/algos/var_inf.py

@@ -13,7 +13,7 @@
 TEENY = 1.e-15
 
 
-class VarInferenceStack(PZSummarizer):
+class VarInfStackSummarizer(PZSummarizer):
     """Variational inference summarizer based on notebook created by Markus Rau
     The summzarizer is appropriate for the likelihoods returned by
     template-based codes, for which the NaiveSummarizer are not appropriate.
@@ -32,7 +32,7 @@ class VarInferenceStack(PZSummarizer):
       number of samples used in dirichlet to determind error bar
     """
 
-    name = 'VarInferenceStack'
+    name = 'VarInfStackSummarizer'
     config_options = PZSummarizer.config_options.copy()
     config_options.update(zmin=Param(float, 0.0, msg="The minimum redshift of the z grid"),
                           zmax=Param(float, 3.0, msg="The maximum redshift of the z grid"),

src/rail/estimation/summarizer.py

@@ -106,7 +106,7 @@ def summarize(self, input_data):
 
 class SZPZSummarizer(RailStage):  #pragma: no cover
     """The base class for classes that use two sets of data: a photometry sample with
-    spec-z values, and a photometry sample with unknown redshifts, e.g. simpleSOM and
+    spec-z values, and a photometry sample with unknown redshifts, e.g. minisom_som and
     outputs a QP Ensemble with bootstrap realization of the N(z) distribution
     """
     name = 'SZPZtoNZSummarizer'

src/rail/examples_data/goldenspike_data/goldenspike.yml

@@ -42,21 +42,21 @@ stages:
 - classname: QuantityCut
   name: quantity_cut
   nprocess: 1
-- classname: Inform_trainZ
+- classname: TrainZInformer
   name: inform_trainZ
   nprocess: 1
 - classname: Estimator
   name: estimate_bpz
   nprocess: 1
-- classname: TrainZ
+- classname: TrainZEstimator
   name: estimate_trainZ
   nprocess: 1
-- classname: RandomPZ
+- classname: RandomGaussEstimator
   name: estimate_randomZ
   nprocess: 1
-- classname: PointEstimateHist
+- classname: PointEstHistSummarizer
   name: point_estimate_test
   nprocess: 1
-- classname: NaiveStack
+- classname: NaiveStackSummarizer
   name: naive_stack_test
   nprocess: 1

src/rail/stages/__init__.py

@@ -4,11 +4,11 @@
 
 from rail.estimation.estimator import *
 from rail.estimation.summarizer import *
-from rail.estimation.algos.naiveStack import *
-from rail.estimation.algos.randomPZ import *
-from rail.estimation.algos.pointEstimateHist import *
-from rail.estimation.algos.trainZ import *
-from rail.estimation.algos.varInference import *
+from rail.estimation.algos.naive_stack import *
+from rail.estimation.algos.random_gauss import *
+from rail.estimation.algos.point_est_hist import *
+from rail.estimation.algos.train_z import *
+from rail.estimation.algos.var_inf import *
 
 from rail.creation.degrader import *
 #from rail.creation.degradation.spectroscopic_degraders import *

tests/estimation/test_algos.py

@@ -4,7 +4,7 @@
 
 from rail.core.algo_utils import one_algo
 from rail.core.stage import RailStage
-from rail.estimation.algos import randomPZ, trainZ
+from rail.estimation.algos import random_gauss, train_z
 
 sci_ver_str = scipy.__version__.split(".")
 
@@ -25,7 +25,7 @@ def test_random_pz():
     }
     # zb_expected = np.array([1.359, 0.013, 0.944, 1.831, 2.982, 1.565, 0.308, 0.157, 0.986, 1.679])
     train_algo = None
-    pz_algo = randomPZ.RandomPZ
+    pz_algo = random_gauss.RandomGaussEstimator
     results, rerun_results, rerun3_results = one_algo(
         "RandomPZ", train_algo, pz_algo, train_config_dict, estim_config_dict
     )
@@ -44,8 +44,8 @@ def test_train_pz():
     zb_expected = np.repeat(0.1445183, 10)
     pdf_expected = np.zeros(shape=(301,))
     pdf_expected[10:16] = [7, 23, 8, 23, 26, 13]
-    train_algo = trainZ.Inform_trainZ
-    pz_algo = trainZ.TrainZ
+    train_algo = train_z.TrainZInformer
+    pz_algo = train_z.TrainZEstimator
     results, rerun_results, rerun3_results = one_algo(
         "TrainZ", train_algo, pz_algo, train_config_dict, estim_config_dict
     )

tests/estimation/test_summarizers.py

@@ -7,7 +7,7 @@
 from rail.core.data import QPHandle
 from rail.core.stage import RailStage
 from rail.core.utils import RAILDIR
-from rail.estimation.algos import naiveStack, pointEstimateHist, varInference
+from rail.estimation.algos import naive_stack, point_est_hist, var_inf
 
 testdata = os.path.join(RAILDIR, "rail/examples_data/testdata/output_BPZ_lite.fits")
 DS = RailStage.data_store
@@ -29,17 +29,17 @@ def one_algo(key, summarizer_class, summary_kwargs):
 
 def test_naive_stack():
     summary_config_dict = {}
-    summarizer_class = naiveStack.NaiveStack
+    summarizer_class = naive_stack.NaiveStackSummarizer
     results = one_algo("NaiveStack", summarizer_class, summary_config_dict)
 
 
 def test_point_estimate_hist():
     summary_config_dict = {}
-    summarizer_class = pointEstimateHist.PointEstimateHist
+    summarizer_class = point_est_hist.PointEstHistSummarizer
     results = one_algo("PointEstimateHist", summarizer_class, summary_config_dict)
 
 
 def test_var_inference_stack():
     summary_config_dict = {}
-    summarizer_class = varInference.VarInferenceStack
+    summarizer_class = var_inf.VarInfStackSummarizer
     results = one_algo("VariationalInference", summarizer_class, summary_config_dict)