Merge branch 'dev' into feature/CMAPSS

Author: teubert

examples/dataset.py

@@ -63,7 +63,6 @@ def run_example():
     plt.ylabel('Voltage (V)')
     plt.show()
 
-
 # This allows the module to be executed directly 
 if __name__=='__main__':
     run_example()

sphinx_config/datasets.rst

@@ -0,0 +1,17 @@
+Datasets
+================================================================
+
+The `prog_models` dataset subpackage is used to download labeled prognostics data for use in model building, analysis, or validation. Every dataset comes equipped with a  `load_data` function which loads the specified data. Some datasets require a dataset number or id. This indicates the specific data to load from the larger dataset. The format of the data is specific to the dataset downloaded. Details of the specific datasets are summarized below:
+
+..  contents:: 
+    :backlinks: top
+
+Variable Load Battery Data (nasa_battery)
+----------------------------------------------------
+.. autofunction:: prog_models.datasets.nasa_battery.load_data
+
+
+CMAPSS Jet Engine Data (nasa_cmapss)
+----------------------------------------------------
+.. autofunction:: prog_models.datasets.nasa_cmapss.load_data
+ 

sphinx_config/index.rst

@@ -17,6 +17,7 @@ If you are new to this package, see `<getting_started.html>`__.
    models
    prognostics_model
    simresult
+   datasets
    exceptions
    ProgAlgs <https://nasa.github.io/prog_algs>
    dev_guide

src/prog_models/datasets/nasa_battery.py

@@ -101,3 +101,7 @@ def load_data(batt_id):
     ]
 
     return desc, result
+
+def clear_cache():
+    """Clears the cache of downloaded data"""
+    cache.clear()

src/prog_models/prognostics_model.py

@@ -6,6 +6,7 @@
 from numbers import Number
 import numpy as np
 from copy import deepcopy
+import itertools
 from warnings import warn
 from collections import abc, namedtuple
 from .sim_result import SimResult, LazySimResult
@@ -419,7 +420,7 @@ def __next_state(self, x, u, dt) -> dict:
         """
 
         # Calculate next state and add process noise
-        next_state = self.apply_process_noise(self.next_state(x, u, dt))
+        next_state = self.apply_process_noise(self.next_state(x, u, dt), dt)
 
         # Apply Limits
         return self.apply_limits(next_state)
@@ -744,9 +745,10 @@ def simulate_to_threshold(self, future_loading_eqn, first_output = None, thresho
             raise ProgModelInputException("'dt' must be a number or function, was a {}".format(type(config['dt'])))
         if isinstance(config['dt'], Number) and config['dt'] < 0:
             raise ProgModelInputException("'dt' must be positive, was {}".format(config['dt']))
-        if not isinstance(config['save_freq'], Number):
+        if not isinstance(config['save_freq'], Number) and not isinstance(config['save_freq'], tuple):
             raise ProgModelInputException("'save_freq' must be a number, was a {}".format(type(config['save_freq'])))
-        if config['save_freq'] <= 0:
+        if (isinstance(config['save_freq'], Number) and config['save_freq'] <= 0) or \
+            (isinstance(config['save_freq'], tuple) and config['save_freq'][1] <= 0):
             raise ProgModelInputException("'save_freq' must be positive, was {}".format(config['save_freq']))
         if not isinstance(config['save_pts'], abc.Iterable):
             raise ProgModelInputException("'save_pts' must be list or array, was a {}".format(type(config['save_pts'])))
@@ -795,9 +797,20 @@ def check_thresholds(thresholds_met):
         saved_states = []  
         saved_outputs = []
         saved_event_states = []
-        save_freq = config['save_freq']
         horizon = t+config['horizon']
-        next_save = t+save_freq
+        if isinstance(config['save_freq'], tuple):
+            # Tuple used to specify start and frequency
+            t_step = config['save_freq'][1]
+            # Use starting time or the next multiple
+            t_start = config['save_freq'][0]
+            start = max(t_start, t - (t-t_start)%t_step)
+            iterator = itertools.count(start, t_step)
+        else:
+            # Otherwise - start is t0
+            t_step = config['save_freq']
+            iterator = itertools.count(t, t_step)
+        next(iterator) # Skip current time
+        next_save = next(iterator)
         save_pt_index = 0
         save_pts = config['save_pts']
         save_pts.append(1e99)  # Add last endpoint
@@ -839,13 +852,15 @@ def next_time(t, x):
 
         while t < horizon:
             dt = next_time(t, x)
-            t = t + dt
+            t = t + dt/2
+            # Use state at midpoint of step to best represent the load during the duration of the step
             u = future_loading_eqn(t, x)
+            t = t + dt/2
             x = next_state(x, u, dt)
 
             # Save if at appropriate time
             if (t >= next_save):
-                next_save += save_freq
+                next_save = next(iterator)
                 update_all()
             if (t >= save_pts[save_pt_index]):
                 save_pt_index += 1

src/prog_models/utils/containers.py

@@ -18,12 +18,12 @@ class DictLikeMatrixWrapper():
         The contained data (e.g., input, state, output). If numpy array should be column vector in same order as keys
     """
     def __init__(self, keys, data):
-        self._keys = keys
+        self._keys = keys.copy()
         if isinstance(data, np.matrix):
             self.matrix = np.array(data)
         elif isinstance(data, np.ndarray):
             self.matrix = data
-        elif isinstance(data, dict):
+        elif isinstance(data, dict) or isinstance(data, DictLikeMatrixWrapper):
             self.matrix = np.array([[data[key]] for key in keys])
         else:
             raise ProgModelTypeError(f"Input must be a dictionary or numpy array, not {type(data)}")     
@@ -34,6 +34,13 @@ def __getitem__(self, key):
     def __setitem__(self, key, value):
         self.matrix[self._keys.index(key)] = np.atleast_1d(value)
 
+    def __delitem__(self, key):
+        self.matrix = np.delete(self.matrix, self._keys.index(key), axis=0)
+        self._keys.remove(key)
+
+    def __add__(self, other):
+        return DictLikeMatrixWrapper(self._keys, self.matrix + other.matrix)
+
     def __iter__(self):
         return iter(self._keys)
 

tests/test_centrifugal_pump.py

@@ -3,6 +3,7 @@
 import unittest
 from prog_models.models.centrifugal_pump import CentrifugalPump, CentrifugalPumpWithWear, CentrifugalPumpBase
 
+
 class TestCentrifugalPump(unittest.TestCase):
     def test_centrifugal_pump_base(self):
         pump = CentrifugalPumpBase(process_noise= 0)
@@ -73,7 +74,7 @@ def future_loading(t, x=None):
         pump.parameters['wA'] = 1e-2
         pump.parameters['wThrust'] = 1e-10
         (times, inputs, states, outputs, event_states) = pump.simulate_to_threshold(future_loading, pump.output(pump.initialize(future_loading(0),{})))
-        self.assertAlmostEqual(times[-1], 23891)
+        self.assertAlmostEqual(times[-1], 23892)
 
     def test_centrifugal_pump_with_wear(self):
         pump = CentrifugalPumpWithWear(process_noise= 0)
@@ -148,7 +149,7 @@ def future_loading(t, x=None):
         pump.parameters['x0']['wA'] = 1e-2
         pump.parameters['x0']['wThrust'] = 1e-10
         (times, inputs, states, outputs, event_states) = pump.simulate_to_threshold(future_loading, pump.output(pump.initialize(future_loading(0),{})))
-        self.assertAlmostEqual(times[-1], 23891)
+        self.assertAlmostEqual(times[-1], 23892)
 
         # Check warning when changing overwritten Parameters
         with self.assertWarns(UserWarning):

tests/test_dict_like_matrix_wrapper.py

@@ -54,6 +54,18 @@ def _checks(self, c1):
         self.assertEqual(c1['d'], 7)
         self.assertListEqual(c1.keys(), ['a', 'b', 'c', 'd'])
 
+        # deleting items
+        del c1['a']
+        self.assertTrue((c1.matrix == np.array([[2], [5], [7]])).all())
+        self.assertListEqual(c1.keys(), ['b', 'c', 'd'])
+        del c1['c']
+        self.assertTrue((c1.matrix == np.array([[2], [7]])).all())
+        self.assertListEqual(c1.keys(), ['b', 'd'])
+        del c1['d']
+        del c1['b']
+        self.assertTrue((c1.matrix == np.array([[]])).all())
+        self.assertListEqual(c1.keys(), [])
+
     def test_dict_init(self):
         c1 = DictLikeMatrixWrapper(['a', 'b'], {'a': 1, 'b': 2})
         self._checks(c1)
@@ -77,7 +89,7 @@ def run_tests():
 def main():
     l = unittest.TestLoader()
     runner = unittest.TextTestRunner()
-    print("\n\nTesting Base Models")
+    print("\n\nTesting Containers")
     result = runner.run(l.loadTestsFromTestCase(TestDictLikeMatrixWrapper)).wasSuccessful()
 
     if not result: