refactoring codebase

DGAC · May 8, 2024 · 00a692c · 00a692c
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diff --git a/.gitignore b/.gitignore
@@ -1,3 +1,5 @@
+tmp/
+
 .DS_Store
 
 # Byte-compiled / optimized / DLL files

diff --git a/acropole/__init__.py b/acropole/__init__.py
@@ -0,0 +1 @@
+from .estimator import FuelEstimator
diff --git a/acropole/columns.py b/acropole/columns.py
diff --git a/acropole/data/__init__.py b/acropole/data/__init__.py
diff --git a/acropole/data/acft_params.csv b/acropole/data/acft_params.csv
diff --git a/acropole/data/aircraft_params.csv b/acropole/data/aircraft_params.csv
@@ -0,0 +1,30 @@
+ACFT_ICAO_TYPE,ENGINE_ICAO,PERCENTAGE,FUEL_FLOW_TO,TYPE,WTC,SURFACE,MAX_OPE_ALTI,MAX_OPE_MACH_NUM,MAX_TO_WEIGHT,OPE_EMPTY_WEIGHT,ACFT_SPAN,ACFT_LENGTH,ENGINE_NUM,TRAIN_ON,MAX_OPE_SPEED,CONF_IND,ENGINE_TYPE
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diff --git a/acropole/estimator.py b/acropole/estimator.py
@@ -0,0 +1,141 @@
+import warnings
+
+import numpy as np
+import pandas as pd
+import pkg_resources
+import tensorflow as tf
+
+
+class FuelEstimator:
+    """
+    Class that contains data pipelines for trajectory enhancement
+    """
+
+    DEFAULT_MASS = -1.0
+    MAXIMUMS = np.array([1, 5000, 50, 50, 600, 50000, 800, 50000, 800, 800, 5000, 1])
+    MINIMUMS = np.array([0, -5000, -50, -50, 0, 0, 200, 0, 200, 200, -5000, 0])
+
+    def __init__(self, aircraft_params_path: str = None, model_path: str = None):
+        """
+        Initializes the Trajectory class.
+
+        Args:
+            aircraft_table_path (str): The path to the aircraft table. Default is None (use package data).
+            model_path (str): The path to the prediction model. Default is None (use package data).
+
+        """
+
+        if aircraft_params_path is None:
+            aircraft_params_path = pkg_resources.resource_filename(
+                "acropole", "data/aircraft_params.csv"
+            )
+
+        self.aircraft_params = pd.read_csv(aircraft_params_path)
+
+        if model_path is None:
+            model_path = pkg_resources.resource_filename(
+                "acropole", "models/acropole.keras"
+            )
+
+        self.model = tf.keras.models.load_model(model_path)
+
+    def estimate(self, flight: pd.DataFrame, **kwargs) -> pd.DataFrame:
+        """
+        Estimates fuel flow and consumption based on the flight trajectory.
+
+        Args:
+            flight (pd.DataFrame): The flight data as a pandas DataFrame.
+            **kwargs: Additional keyword arguments for customization.
+
+        Keyword Args:
+            typecode (str): The column name for the aircraft type code. Default is "typecode".
+            timestamp (str): The column name for the timestamp. Default is "timestamp".
+            groundspeed (str): The column name for the groundspeed. Default is "groundspeed".
+            altitude (str): The column name for the altitude. Default is "altitude".
+            vertical_rate (str): The column name for the vertical rate. Default is "vertical_rate".
+            airspeed (str): The column name for the airspeed. Default is "airspeed".
+            mass (str): The column name for the mass. Default is "mass".
+
+        Returns:
+            pd.DataFrame: The flight data with additional estimated fuel parameters.
+
+        Raises:
+            AssertionError: If the 'timestamp' column is not of type float.
+
+        Warnings:
+            If the aircraft type code is not supported.
+
+        """
+
+        col_typecode = kwargs.get("typecode", "typecode")
+        col_timestamp = kwargs.get("timestamp", "timestamp")
+        col_groundspeed = kwargs.get("groundspeed", "groundspeed")
+        col_altitude = kwargs.get("altitude", "altitude")
+        col_vertical_rate = kwargs.get("vertical_rate", "vertical_rate")
+        col_airspeed = kwargs.get("airspeed", "airspeed")
+        col_mass = kwargs.get("mass", "mass")
+
+        assert (
+            flight[col_timestamp].dtype == float
+        ), "'timestamp' must be a series of float"
+
+        flight_typecode = flight[col_typecode].iloc[0]
+        if flight_typecode not in self.aircraft_params.ACFT_ICAO_TYPE.unique():
+            warnings.warn(
+                f"Aircraft type {flight_typecode} flight_typecode not supported"
+            )
+
+        flight = flight.merge(
+            self.aircraft_params,
+            how="left",
+            left_on=col_typecode,
+            right_on="ACFT_ICAO_TYPE",
+        )
+
+        if col_airspeed not in flight.columns:
+            flight = flight.assign(airspeed=lambda d: d[col_groundspeed])
+
+        if col_mass not in flight.columns:
+            flight = flight.assign(mass_norm=self.DEFAULT_MASS)
+        else:
+            flight = flight.assign(
+                mass_norm=lambda d: (d[col_mass] - d.OPE_EMPTY_WEIGHT)
+                / (d.MAX_TO_WEIGHT - d.OPE_EMPTY_WEIGHT)
+            )
+
+        # compute devrivatives of altitude and speeds
+        flight = flight.assign(dt=lambda d: d[col_timestamp].diff().bfill()).assign(
+            d_altitude=lambda d: (d[col_altitude].diff().bfill() / d.dt),
+            d_groundspeed=lambda d: (d[col_groundspeed].diff().bfill() / d.dt),
+            d_airspeed=lambda d: (d[col_airspeed].diff().bfill() / d.dt),
+        )
+
+        inputs = flight[
+            [
+                "ENGINE_TYPE",
+                "d_altitude",
+                "d_groundspeed",
+                "d_airspeed",
+                "SURFACE",
+                "MAX_OPE_ALTI",
+                "MAX_OPE_SPEED",
+                col_altitude,
+                col_groundspeed,
+                col_airspeed,
+                col_vertical_rate,
+                "mass_norm",
+            ]
+        ]
+
+        inputs_normalized = (inputs - self.MINIMUMS) / (self.MAXIMUMS - self.MINIMUMS)
+        data = tf.convert_to_tensor(inputs_normalized)
+
+        single_engine_fuelflow = self.model.predict(data).squeeze()
+
+        flight = flight.assign(
+            fuel_flow=lambda d: single_engine_fuelflow * d.ENGINE_NUM,
+            fuel_flow_kgh=lambda d: d.fuel_flow * d.FUEL_FLOW_TO * 3600,
+            fuel_cumsum=lambda d: (d.fuel_flow * d.dt).cumsum(),
+        )
+
+        return flight
diff --git a/acropole/models/Dense_Acropole_FuelFlow_Scaling/__init__.py b/acropole/models/Dense_Acropole_FuelFlow_Scaling/__init__.py
diff --git a/acropole/models/Dense_Acropole_FuelFlow_Scaling/assets/__init__.py b/acropole/models/Dense_Acropole_FuelFlow_Scaling/assets/__init__.py
diff --git a/acropole/models/Dense_Acropole_FuelFlow_Scaling/saved_model.pb b/acropole/models/Dense_Acropole_FuelFlow_Scaling/saved_model.pb
diff --git a/acropole/models/Dense_Acropole_FuelFlow_Scaling/variables/__init__.py b/acropole/models/Dense_Acropole_FuelFlow_Scaling/variables/__init__.py
diff --git a/acropole/models/Dense_Acropole_FuelFlow_Scaling/variables/variables.data-00000-of-00001 b/acropole/models/Dense_Acropole_FuelFlow_Scaling/variables/variables.data-00000-of-00001
diff --git a/acropole/models/Dense_Acropole_FuelFlow_Scaling/variables/variables.index b/acropole/models/Dense_Acropole_FuelFlow_Scaling/variables/variables.index
diff --git a/acropole/models/__init__.py b/acropole/models/__init__.py
diff --git a/acropole/models/acropole.keras b/acropole/models/acropole.keras