Logging and BibTeX

.zenodo.json

@@ -1,8 +1,8 @@
 {
     "description": "smooth inference for reinterpretation studies",
     "license": "MIT",
-    "title": "SpeysideHEP/spey: v0.1.5",
-    "version": "v0.1.5",
+    "title": "SpeysideHEP/spey: v0.1.6",
+    "version": "v0.1.6",
     "upload_type": "software",
     "creators": [
         {
@@ -29,7 +29,7 @@
         },
         {
             "scheme": "url",
-            "identifier": "https://github.com/SpeysideHEP/spey/tree/v0.1.5",
+            "identifier": "https://github.com/SpeysideHEP/spey/tree/v0.1.6",
             "relation": "isSupplementTo"
         },
         {

docs/api.rst

@@ -16,15 +16,19 @@ Top-Level
 
     version
     about
+    check_updates
     ExpectationType
     AvailableBackends
     get_backend
     get_backend_metadata
+    get_backend_bibtex
+    cite
     reset_backend_entries
     statistical_model_wrapper
     helper_functions.correlation_to_covariance
     helper_functions.covariance_to_correlation
     optimizer.core.fit
+    set_log_level
 
 Main Classes
 ------------

docs/releases/changelog-v0.1.md

@@ -28,6 +28,15 @@
 * Update clarification on text based keyword arguments.
   ([#30](https://github.com/SpeysideHEP/spey/pull/30))
 
+* Adding logging across the software and implement tools to scilence them.
+  ([#32](https://github.com/SpeysideHEP/spey/pull/32))
+
+* Spey will automatically look for updates during initiation.
+  ([#32](https://github.com/SpeysideHEP/spey/pull/32))
+
+* Utilities to retreive bibtex information for third-party plug-ins.
+  ([#32](https://github.com/SpeysideHEP/spey/pull/32))
+
 ## Bug Fixes
 
 * In accordance to the latest updates ```UnCorrStatisticsCombiner``` has been updated with

setup.py

@@ -12,6 +12,7 @@
     "autograd==1.5",
     "semantic_version~=2.10",
     "tqdm>=4.64.0",
+    "requests>=2.31.0",
 ]
 
 backend_plugins = [

src/spey/__init__.py

@@ -1,4 +1,9 @@
-from typing import Any, Callable, Dict, List, Optional, Text, Tuple, Union
+import logging
+import os
+import re
+import sys
+import textwrap
+from typing import Any, Callable, Dict, List, Optional, Text, Tuple, Union, Literal
 
 import numpy as np
 import pkg_resources
@@ -7,7 +12,9 @@
 from spey.base import BackendBase, ConverterBase
 from spey.combiner import UnCorrStatisticsCombiner
 from spey.interface.statistical_model import StatisticalModel, statistical_model_wrapper
+from spey.system import logger
 from spey.system.exceptions import PluginError
+from spey.system.webutils import get_bibtex, check_updates
 
 from ._version import __version__
 from .about import about
@@ -25,13 +32,43 @@
     "BackendBase",
     "ConverterBase",
     "about",
+    "check_updates",
+    "get_backend_bibtex",
+    "cite",
+    "set_log_level",
 ]
 
 
 def __dir__():
     return __all__
 
 
+logger.init(LoggerStream=sys.stdout)
+log = logging.getLogger("Spey")
+log.setLevel(logging.INFO)
+
+
+def set_log_level(level: Literal[0, 1, 2, 3]) -> None:
+    """
+    Set log level for spey
+
+    Args:
+        level (``int``): log level
+
+            * 0: error
+            * 1: warning
+            * 2: info
+            * 3: debug
+    """
+    log_dict = {
+        0: logging.ERROR,
+        1: logging.WARNING,
+        2: logging.INFO,
+        3: logging.DEBUG,
+    }
+    log.setLevel(log_dict[level])
+
+
 def version() -> Text:
     """
     Version of ``spey`` package
@@ -59,7 +96,7 @@ def reset_backend_entries() -> None:
     _backend_entries = _get_backend_entrypoints()
 
 
-def AvailableBackends() -> List[Text]:
+def AvailableBackends() -> List[Text]:  # pylint: disable=C0103
     """
     Returns a list of available backends. The default backends are automatically installed
     with ``spey`` package. To enable other backends, please see the relevant section
@@ -209,10 +246,72 @@ def get_backend_metadata(name: Text) -> Dict[Text, Any]:
             "spey_requires": statistical_model.spey_requires,
             "doi": list(getattr(statistical_model, "doi", [])),
             "arXiv": list(getattr(statistical_model, "arXiv", [])),
+            "zenodo": list(getattr(statistical_model, "zenodo", [])),
         }
 
     raise PluginError(
         f"The backend {name} is unavailable. Available backends are "
         + ", ".join(AvailableBackends())
         + "."
     )
+
+
+def get_backend_bibtex(name: Text) -> List[Text]:
+    """
+    Retreive BibTex entry for backend plug-in if available.
+
+    The bibtext entries are retreived both from Inspire HEP, doi.org and zenodo.
+    If the arXiv number matches the DOI the output will include two versions
+    of the same reference. If backend does not include an arXiv or DOI number
+    it will return an empty list.
+
+    Args:
+        name (``Text``): backend identifier. This backend refers to different packages
+          that prescribes likelihood function.
+
+    Returns:
+        ``List[Text]``:
+        BibTex entries for the backend.
+    """
+    # pylint: disable=import-outside-toplevel, W1203
+    txt = []
+    meta = get_backend_metadata(name)
+
+    for arxiv_id in meta.get("arXiv", []):
+        tmp = get_bibtex("inspire/arxiv", arxiv_id)
+        if tmp != "":
+            txt.append(textwrap.indent(tmp, " " * 4))
+        else:
+            log.debug(f"Can not find {arxiv_id} in Inspire")
+    for doi in meta.get("doi", []):
+        tmp = get_bibtex("inspire/doi", doi)
+        if tmp == "":
+            log.debug(f"Can not find {doi} in Inspire, looking at doi.org")
+            tmp = get_bibtex("doi", doi)
+            if tmp != "":
+                txt.append(tmp)
+            else:
+                log.debug(f"Can not find {doi} in doi.org")
+        else:
+            txt.append(textwrap.indent(tmp, " " * 4))
+    for zenodo_id in meta.get("zenodo", []):
+        tmp = get_bibtex("zenodo", zenodo_id)
+        if tmp != "":
+            txt.append(textwrap.indent(tmp, " " * 4))
+        else:
+            log.debug(f"{zenodo_id} is not a valid zenodo identifier")
+
+    return txt
+
+
+def cite() -> List[Text]:
+    """Retreive BibTex information for Spey"""
+    arxiv = textwrap.indent(get_bibtex("inspire/arxiv", "2307.06996"), " " * 4)
+    zenodo = get_bibtex("zenodo", "10156353")
+    linker = re.search("@software{(.+?),\n", zenodo).group(1)
+    zenodo = textwrap.indent(zenodo.replace(linker, "spey_zenodo"), " " * 4)
+    return arxiv + "\n\n" + zenodo
+
+
+if os.environ.get("SPEY_CHECKUPDATE", "ON").upper() != "OFF":
+    check_updates()

src/spey/_version.py

@@ -1,3 +1,3 @@
 """Version number (major.minor.patch[-label])"""
 
-__version__ = "0.1.5"
+__version__ = "0.1.6"

src/spey/about.py

@@ -8,7 +8,7 @@
 import scipy
 import semantic_version
 import tqdm
-from pkg_resources import iter_entry_points
+from pkg_resources import get_distribution, iter_entry_points
 
 
 def about() -> None:
@@ -21,13 +21,7 @@ def about() -> None:
     )
     print(f"Numpy version:            {numpy.__version__}")
     print(f"Scipy version:            {scipy.__version__}")
-    print(
-        "Autograd version:         %s"
-        % check_output([sys.executable, "-m", "pip", "show", "autograd"])
-        .decode()
-        .split("\n")[1]
-        .split(":")[1][1:]
-    )
+    print(f"Autograd version:         {get_distribution('autograd').version}")
     print(f"tqdm version:             {tqdm.__version__}")
     print(f"semantic_version version: {semantic_version.__version__}")
 

src/spey/backends/default_pdf/__init__.py

@@ -1,5 +1,6 @@
 """Interface for default PDF sets"""
 
+import logging
 from typing import Any, Callable, Dict, List, Optional, Text, Tuple, Union
 
 from autograd import grad, hessian, jacobian
@@ -17,6 +18,9 @@
 from .uncertainty_synthesizer import signal_uncertainty_synthesizer
 
 # pylint: disable=E1101,E1120
+log = logging.getLogger("Spey")
+
+# pylint: disable=W1203
 
 
 class DefaultPDFBase(BackendBase):
@@ -92,7 +96,7 @@ def __init__(
             self.signal_uncertainty_configuration = signal_uncertainty_synthesizer(
                 signal_yields=self.signal_yields,
                 **signal_uncertainty_configuration,
-                domain=slice(len(background_yields) + 1, None)
+                domain=slice(len(background_yields) + 1, None),
             )
 
         minimum_poi = -np.inf
@@ -101,6 +105,7 @@ def __init__(
                 self.background_yields[self.signal_yields > 0.0]
                 / self.signal_yields[self.signal_yields > 0.0]
             )
+        log.debug(f"Min POI set to : {minimum_poi}")
 
         self._main_model = None
         self._constraint_model = None
@@ -243,6 +248,7 @@ def get_objective_function(
             self.background_yields if expected == ExpectationType.apriori else self.data
         )
         data = current_data if data is None else data
+        log.debug(f"Data: {data}")
 
         def negative_loglikelihood(pars: np.ndarray) -> np.ndarray:
             """Compute twice negative log-likelihood"""
@@ -291,6 +297,7 @@ def get_logpdf_func(
             self.background_yields if expected == ExpectationType.apriori else self.data
         )
         data = current_data if data is None else data
+        log.debug(f"Data: {data}")
 
         return lambda pars: self.main_model.log_prob(
             pars, data[: len(self.data)]
@@ -329,6 +336,7 @@ def get_hessian_logpdf_func(
             self.background_yields if expected == ExpectationType.apriori else self.data
         )
         data = current_data if data is None else data
+        log.debug(f"Data: {data}")
 
         def log_prob(pars: np.ndarray) -> np.ndarray:
             """Compute log-probability"""

src/spey/backends/default_pdf/third_moment.py

@@ -1,12 +1,13 @@
 """Tools for computing third moment expansion"""
 import warnings
 from typing import Optional, Tuple, Union
-
+import logging
 import autograd.numpy as np
 from scipy import integrate
 from scipy.stats import norm
 
-# pylint: disable=E1101,E1120
+# pylint: disable=E1101,E1120,W1203
+log = logging.getLogger("Spey")
 
 
 def third_moment_expansion(
@@ -37,11 +38,11 @@ def third_moment_expansion(
     """
     cov_diag = np.diag(covariance_matrix)
 
-    # ! Assertion error is removed, instead nan values will be converted to zero.
-    # assert np.all(8.0 * cov_diag**3 >= third_moment**2), (
-    #     "Given covariance matrix and diagonal terms of the third moment does not "
-    #     + "satisfy the condition: 8 * diag(cov)**3 >= third_moment**2."
-    # )
+    if not np.all(8.0 * cov_diag**3 >= third_moment**2):
+        log.warning(
+            r"Third moments does not satisfy the following condition: $8\Sigma_{ii}^3 \geq (m^{(3)}_i)^2$"
+        )
+        log.warning("The values that do not satisfy this condition will be set to zero.")
 
     # arXiv:1809.05548 eq. 2.9
     with warnings.catch_warnings(record=True) as w:
@@ -61,12 +62,15 @@ def third_moment_expansion(
             category=RuntimeWarning,
         )
         C = np.where(np.isnan(C), 0.0, C)
+    log.debug(f"C: {C}")
 
     # arXiv:1809.05548 eq. 2.10
     B = np.sqrt(cov_diag - 2 * C**2)
+    log.debug(f"B: {B}")
 
     # arXiv:1809.05548 eq. 2.11
     A = expectation_value - C
+    log.debug(f"A: {A}")
 
     # arXiv:1809.05548 eq. 2.12
     eps = 1e-5
@@ -88,6 +92,7 @@ def third_moment_expansion(
                 if i != j:
                     corr[j, i] = corr[i, j]
 
+        log.debug(f"rho: {corr}")
         return A, B, C, corr
 
     return A, B, C
@@ -154,5 +159,6 @@ def compute_x3BifurgatedGaussian(x: float, upper: float, lower: float) -> float:
 
     if return_integration_error:
         return np.array(third_moment), np.array(error)
+    log.debug(f"Error: {error}")
 
     return np.array(third_moment)