Merge pull request #10 from sede-open/apply_thinning

Apply thinning

.gitignore

@@ -109,6 +109,9 @@ target/
 profile_default/
 ipython_config.py
 
+# vscode local settings
+.vscode
+
 # pyenv
 #   For a library or package, you might want to ignore these files since the code is
 #   intended to run in multiple environments; otherwise, check them in:

.vscode/settings.json

@@ -0,0 +1,7 @@
+{
+    "python.testing.pytestArgs": [
+        "tests"
+    ],
+    "python.testing.unittestEnabled": false,
+    "python.testing.pytestEnabled": true
+}

pyproject.toml

@@ -8,7 +8,7 @@ build-backend = "poetry.core.masonry.api"
 
 [tool.poetry]
 name = "pyelq-sdk"
-version = "1.0.6"
+version = "1.0.7"
 description = "Package for detection, localization and quantification code."
 authors = ["Bas van de Kerkhof", "Matthew Jones", "David Randell"]
 homepage = "https://sede-open.github.io/pyELQ/"

src/pyelq/model.py

@@ -5,8 +5,8 @@
 # -*- coding: utf-8 -*-
 """ELQModel module.
 
-This module provides a class definition main functionalities of the codebase, providing the interface with the openMCMC
-repo and defining some plotting wrappers.
+This module provides a class definition for the main functionalities of the codebase, providing the interface with the
+openMCMC repo and defining some plotting wrappers.
 
 """
 import warnings
@@ -42,6 +42,7 @@ class ELQModel:
         mcmc (MCMC): MCMC object containing model and sampler specification for the problem. Constructed from the
             other components in self.to_mcmc().
         n_iter (int): number of MCMC iterations to be run.
+        n_thin (int): number of iterations to thin by.
         fitted_values (np.ndarray): samples of fitted values (i.e. model predictions for the data) generated during the
             MCMC sampler. Attached in self.from_mcmc().
 
@@ -52,6 +53,7 @@ class ELQModel:
     model: Model = field(init=False)
     mcmc: MCMC = field(init=False)
     n_iter: int = 1000
+    n_thin: int = 1
     fitted_values: np.ndarray = field(init=False)
 
     def __init__(
@@ -151,7 +153,7 @@ def to_mcmc(self):
         for component in self.components.values():
             sampler_list = component.make_sampler(self.model, sampler_list)
 
-        self.mcmc = MCMC(initial_state, sampler_list, self.model, n_burn=0, n_iter=self.n_iter)
+        self.mcmc = MCMC(initial_state, sampler_list, self.model, n_burn=0, n_iter=self.n_iter, n_thin=self.n_thin)
 
     def run_mcmc(self):
         """Run the mcmc function."""

src/pyelq/preprocessing.py

@@ -156,9 +156,9 @@ def filter_on_met(self, filter_variable: list, lower_limit: list = None, upper_l
 
         """
         if lower_limit is None:
-            lower_limit = [-np.infty] * len(filter_variable)
+            lower_limit = [-np.inf] * len(filter_variable)
         if upper_limit is None:
-            upper_limit = [np.infty] * len(filter_variable)
+            upper_limit = [np.inf] * len(filter_variable)
 
         for vrb, low, high in zip(filter_variable, lower_limit, upper_limit):
             for sns_key, met_key in zip(self.sensor_object, self.met_object):