implement #1018

sysquant/optimisation/generic_optimiser.py

@@ -55,12 +55,31 @@ def weights(self) -> pd.DataFrame:
         ## apply cost weight
         return weights
 
+    @property
+    def fit_dates(self) -> list:
+        return self.optimiser.fit_dates
+
+    @property
+    def correlation_estimator(self):
+        return self.optimiser.correlation_estimator
+
+    @property
+    def mean_estimator(self):
+        return self.optimiser.mean_estimator
+
+    @property
+    def stdev_estimator(self):
+        return self.optimiser.stdev_estimator
+
     def raw_weights(self) -> pd.DataFrame:
+        return self.optimiser.weights()
+
+    @property
+    def optimiser(self) -> optimiseWeightsOverTime:
         optimiser = optimiseWeightsOverTime(
             self.net_returns, log=self.log, **self.weighting_params
         )
-
-        return optimiser.weights()
+        return optimiser
 
     def weights_post_processing(self, weights: pd.DataFrame) -> pd.DataFrame:
         # apply cost weights

sysquant/optimisation/optimise_over_time.py

@@ -36,6 +36,18 @@ def __init__(
     def fit_dates(self) -> listOfFittingDates:
         return self._fit_dates
 
+    @property
+    def correlation_estimator(self):
+        return self.optimiser.correlation_estimator()
+
+    @property
+    def mean_estimator(self):
+        return self.optimiser.mean_estimator()
+
+    @property
+    def stdev_estimator(self):
+        return self.optimiser.stdev_estimator()
+
     @property
     def optimiser(self) -> portfolioOptimiser:
         return self._optimiser

sysquant/optimisation/portfolio_optimiser.py

@@ -138,28 +138,38 @@ def data_length_for_period(self, fit_period: fitDates) -> int:
     def calculate_correlation_matrix_for_period(
         self, fit_period: fitDates
     ) -> correlationEstimate:
-        return self.calculate_estimate_for_period(
-            fit_period, param_entry="correlation_estimate"
-        )
+        estimator = self.correlation_estimator()
+        estimate = estimator.calculate_estimate_for_period(fit_period)
+
+        return estimate
 
     def calculate_stdev_for_period(self, fit_period: fitDates) -> stdevEstimates:
-        return self.calculate_estimate_for_period(
-            fit_period, param_entry="vol_estimate"
-        )
+        estimator = self.stdev_estimator()
+        estimate = estimator.calculate_estimate_for_period(fit_period)
 
-    def calculate_mean_for_period(self, fit_period: fitDates) -> meanEstimates:
-        return self.calculate_estimate_for_period(
-            fit_period, param_entry="mean_estimate"
-        )
+        return estimate
 
-    def calculate_estimate_for_period(
-        self, fit_period: fitDates, param_entry: str = "mean_estimate"
-    ):
-        estimator = self._generic_estimator(param_entry)
+    def calculate_mean_for_period(self, fit_period: fitDates) -> meanEstimates:
+        estimator = self.mean_estimator()
         estimate = estimator.calculate_estimate_for_period(fit_period)
 
         return estimate
 
+    def correlation_estimator(self):
+        estimator = self._generic_estimator("correlation_estimate")
+
+        return estimator
+
+    def mean_estimator(self):
+        estimator = self._generic_estimator("mean_estimate")
+
+        return estimator
+
+    def stdev_estimator(self):
+        estimator = self._generic_estimator("vol_estimate")
+
+        return estimator
+
     def _generic_estimator(
         self, param_entry: str = "mean_estimate"
     ) -> genericEstimator:

systems/portfolio.py

@@ -651,6 +651,23 @@ def get_raw_estimated_instrument_weights(self) -> pd.DataFrame:
 
         return instrument_weights
 
+    def fit_periods(self):
+        # FIXME, NO GUARANTEE THIS OBJECT HAS AN ESTIMATOR UNLESS IT INHERITS FROM
+        # SOME KIND OF BASECLASS
+
+        weight_calculator = self.calculation_of_raw_instrument_weights()
+
+        return weight_calculator.fit_dates
+
+    @diagnostic()
+    def correlation_estimator_for_subsystem_returns(self):
+        # FIXME, NO GUARANTEE THIS OBJECT HAS AN ESTIMATOR UNLESS IT INHERITS FROM
+        # SOME KIND OF BASECLASS
+
+        weight_calculator = self.calculation_of_raw_instrument_weights()
+
+        return weight_calculator.correlation_estimator
+
     @diagnostic(protected=True, not_pickable=True)
     def calculation_of_raw_instrument_weights(self):