Complete migration of SPATZ to this repository

spatz/__init__.py

@@ -1,8 +1,8 @@
 import spatz.connections as connections
-from connections import *
+from spatz.connections import *
 
 import spatz.utils as utils
-from utils import *
+from spatz.utils import *
 
 import spatz.transforms as transforms
 from spatz.transforms import *

spatz/dataset.py

@@ -8,7 +8,7 @@ from typing import List
 from numpy.typing import ArrayLike
 from scipy.spatial.transform import Rotation
 
-from logger import Advanceable
+from spatz.logger import Advanceable
 
 
 class Phase(Enum):

spatz/sensors/__init__.py

@@ -1,6 +1,4 @@
-from sensor import Sensor
-from compound import CompoundSensor
-
-from imu import Accelerometer
-from imu import Gyroscope
-from imu import IMU
+from spatz.sensors.sensor import Sensor
+from spatz.sensors.imu import Accelerometer, Gyroscope, IMU
+from spatz.sensors.pressure import PressureSensor
+from spatz.sensors.compound import CompoundSensor

spatz/sensors/compound.py

@@ -3,7 +3,7 @@ import numpy as np
 from typing import List
 from numpy.typing import ArrayLike
 
-from sensor import Sensor
+from spatz.sensors import Sensor
 from spatz.dataset import Dataset, List
 from spatz.logger import Logger
 from spatz.transforms import Transform

spatz/sensors/imu/__init__.py

@@ -1,2 +1,3 @@
-from accelerometer import Accelerometer
-from gyroscope import Gyroscope
+from spatz.sensors.imu.accelerometer import Accelerometer
+from spatz.sensors.imu.gyroscope import Gyroscope
+from spatz.sensors.imu.imu import IMU

spatz/sensors/imu/imu.py

@@ -1,7 +1,8 @@
 from typing import List
 from spatz.dataset import Dataset, List
 from spatz.logger import Logger
-from spatz.sensors import CompoundSensor, Accelerometer, Gyroscope
+from spatz.sensors.compound import CompoundSensor
+from spatz.sensors.imu import Accelerometer, Gyroscope
 from spatz.sensors.sensor import Sensor
 from spatz.transforms import Transform
 

spatz/sensors/pressure/__init__.py

@@ -1,2 +1 @@
-from pressure import PressureSensor
-from ms5611_01ba03 import MS5611_01BA03
+from spatz.sensors.pressure.pressure import PressureSensor

spatz/sensors/pressure/ms5611_01ba03.py

@@ -1,8 +1,7 @@
 from typing import List, AnyStr
 from numpy.typing import ArrayLike
 
-from pressure import PressureSensor
-
+from spatz.sensors import PressureSensor
 from spatz.dataset import Dataset, Phase
 from spatz.logger import Logger
 from spatz.transforms import GaussianNoise, Transform

spatz/sensors/sensor.py

@@ -51,14 +51,4 @@ class Sensor:
             for i in range(len(out)):
                 self._log(f'out_{i}', out[i])
 
-        return out
-    
-
-class CompoundSensor(Sensor):
-    def __init__(self, sensors: List[Sensor]):
-        super(CompoundSensor, self).__init__(None)
-
-        self.__sensors = sensors
-
-    def _get_data(self) -> ArrayLike:
-        return np.stack([sensor() for sensor in self.__sensors])
+        return out

spatz/simulation.py

@@ -5,9 +5,9 @@ from tqdm import tqdm
 from spatz.dataset import Dataset
 from spatz.logger import Logger
 from spatz.sensors import Sensor
-from dataset import Dataset
-from logger import Logger
-from sensor import Sensor
+from spatz.dataset import Dataset
+from spatz.logger import Logger
+from spatz.sensors import Sensor
 
 
 class UniformTimeSteps:

spatz/transforms/__init__.py

@@ -1,3 +1,3 @@
-from failures import *
-from noise import *
-from transform import *
+from spatz.transforms.transform import Transform
+from spatz.transforms.noise import GaussianNoise
+from spatz.transforms.failures import Downtime

spatz/utils/__init__.py

@@ -0,0 +1 @@
+from spatz.utils.preprocess import preprocess_file

spatz/utils/preprocess.py

@@ -0,0 +1,189 @@
+import os
+import math
+import pathlib
+import pandas as pd
+
+from numpy import log10
+
+
+__all__ = [
+    'preprocess_file'
+]
+
+
+def filter_zero_steps(df: pd.DataFrame) -> pd.DataFrame:
+    """Filter all rows with time steps of length 0.
+
+    Args:
+        df (pd.DataFrame): The dataframe to preprocess.
+
+    Returns:
+        pd.DataFrame: The preprocessed dataframe.
+    """
+    dts = df['Time'].diff().fillna(1)
+    df['dts'] = dts
+
+    return df[dts != 0]
+
+
+def preprocess_velocity(df: pd.DataFrame) -> pd.DataFrame:
+    """Transforms the velocities from km/s to m/s.
+
+    Args:
+        df (pd.DataFrame): The DataFrame to preprocess.
+
+    Returns:
+        pd.DataFrame: The modified DataFrame.
+    """
+    for axis in ['x', 'y', 'z']:
+        df['v{}_FL'.format(axis)] *= 1e3
+
+    return df
+
+
+def preprocess_position(df: pd.DataFrame) -> pd.DataFrame:
+    for axis in ['x', 'y', 'z']:
+        df['{}_FL'.format(axis)] *= 1e3
+
+    return df
+
+
+def compute_acceleration(df: pd.DataFrame) -> pd.DataFrame:
+    """
+
+    Args:
+        df (pd.DataFrame): _description_
+
+    Returns:
+        pd.DataFrame: _description_
+    """
+    # Time deltas.
+    dts = df['Time'].diff().fillna(0)
+
+    for axis in ['x', 'y', 'z']:
+        # Raw differences between velocity across time steps.
+        das = df['v{}_FL'.format(axis)].diff().fillna(0)
+
+        # Velocity differences divided by time deltas.
+        df['a{}_FL'.format(axis)] = das.divide(dts).fillna(0)
+
+    return df
+
+
+def preprocess_rotations(df: pd.DataFrame) -> pd.DataFrame:
+    df['pitch_l'] *= math.pi / 180
+    df['yaw_l'] *= math.pi / 180
+    df['roll_l'] *= math.pi / 180
+    df['declination'] *= math.pi / 180
+    df['longitude'] *= math.pi / 180
+    df['latitude'] *= math.pi / 180
+
+    return df
+
+
+def compute_omegas(df: pd.DataFrame) -> pd.DataFrame:
+    dts = df['Time'].diff().fillna(0)
+
+    for axis in ['X', 'Y', 'Z']:
+        # Raw differences between omegas across time steps.
+        dos = df['OMEGA_{}'.format(axis)].diff().fillna(0)
+
+        # Omega differences divided by time deltas.
+        df['omega_{}'.format(axis)] = dos.divide(dts).fillna(0)
+
+    return df
+
+
+def preprocess_file(path):
+    """_summary_
+
+    Args:
+        path (_type_): _description_
+
+    Returns:
+        _type_: _description_
+    """
+    df = pd.read_csv(path, delimiter="\t" , encoding='latin')
+    df = df.drop(0, axis=0)
+    df = df.astype(float)
+
+    df['Phase'] = df['Phase'].replace({
+        1: 'onpad',         # rocket waiting on pad
+        2: 'loi',           # rocket liftoff
+        3: 'rci',           # rail clearance
+        4: 'eci',           # engine cutoff
+        5: 'adi'            # apogee and drogue
+    })
+
+    # Select all the relevant columns
+    df = df[[
+        'Time',
+        'Phase',
+        'declination',
+        'longitude',
+        'latitude',
+        'altitude',
+        'mach',
+        'sonic_velocity',
+        'x_FL',
+        'y_FL',
+        'z_FL',
+        'vx_FL',
+        'vy_FL',
+        'vz_FL',
+        'OMEGA_X', 
+        'OMEGA_Y', 
+        'OMEGA_Z',
+        'pitch_l',
+        'yaw_l',
+        'roll_l',
+        'flightpath_speed',
+        'acc_total',
+        'atmos_pressure',
+        'atmos_temperature',
+        'drag',
+        'mass_total'
+    ]]
+
+    df = filter_zero_steps(df)
+    df = preprocess_position(df)
+    df = preprocess_velocity(df)
+    df = compute_acceleration(df)
+    df = compute_omegas(df)
+    df = preprocess_rotations(df)
+
+    renaming = {
+        'sonic_velocity':       'speedofsound',
+        'Time':                 'time',
+        'Phase':                'phase',
+        'flightpath_speed':     'velocity',
+        'acc_total':            'acceleration',
+        'atmos_pressure':       'pressure',
+        'atmos_temperature':    'temperature',
+        'x_FL':                 'x',
+        'y_FL':                 'y',
+        'z_FL':                 'z',
+        'vx_FL':                'vx',
+        'vy_FL':                'vy',
+        'vz_FL':                'vz',
+        'ax_FL':                'ax',
+        'ay_FL':                'ay',
+        'az_FL':                'az'
+    }
+
+    df = df.rename(renaming, axis=1)
+
+    return df
+
+
+def to_traj_file(path, name, df: pd.DataFrame):
+    with open(path, 'w') as f:
+        f.write(f"#epsg 0\n#name { name }\n#fields t,px,py,pz,ex,ey,ez,vx,vy,vz\n")
+        
+    df.to_csv(path, columns=['time', 'x', 'y', 'z', 'pitch', 'yaw', 'roll', 'vx_global', 'vy_global', 'vz_global'], header=False, index=False, mode='a')
+
+
+if __name__ == '__main__':
+    for file in os.listdir('data/simulations/'):
+        df = preprocess_file('data/simulations/' + file)
+