nyx_space/io/tracking_data.rs
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/*
Nyx, blazing fast astrodynamics
Copyright (C) 2018-onwards Christopher Rabotin <christopher.rabotin@gmail.com>
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU Affero General Public License as published
by the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU Affero General Public License for more details.
You should have received a copy of the GNU Affero General Public License
along with this program. If not, see <https://www.gnu.org/licenses/>.
*/
use crate::{
io::{MissingDataSnafu, ParquetSnafu},
linalg::{allocator::Allocator, DefaultAllocator, OVector},
od::{msr::TrackingArc, Measurement},
};
#[cfg(feature = "python")]
use crate::NyxError;
use arrow::{
array::{Float64Array, StringArray},
record_batch::RecordBatchReader,
};
use hifitime::Epoch;
use parquet::arrow::arrow_reader::ParquetRecordBatchReaderBuilder;
use snafu::prelude::*;
use std::fs::File;
use std::{collections::HashMap, error::Error, fmt::Display, path::Path};
#[cfg(feature = "python")]
use pyo3::prelude::*;
use super::{InputOutputError, StdIOSnafu};
/// A dynamic tracking arc allows loading a set of measurements from a parquet file and converting them
/// to the concrete measurement type when desired.
#[cfg_attr(feature = "python", pyclass)]
pub struct DynamicTrackingArc {
pub device_cfg: String,
pub path: String,
metadata: HashMap<String, String>,
}
impl DynamicTrackingArc {
pub fn from_parquet<P: AsRef<Path>>(path: P) -> Result<Self, Box<dyn Error>> {
let file = File::open(&path)?;
let builder = ParquetRecordBatchReaderBuilder::try_new(file).unwrap();
let mut metadata = HashMap::new();
let mut device_cfg = String::new();
// Build the custom metadata
if let Some(file_metadata) = builder.metadata().file_metadata().key_value_metadata() {
for key_value in file_metadata {
if !key_value.key.starts_with("ARROW:") {
metadata.insert(
key_value.key.clone(),
key_value.value.clone().unwrap_or("[unset]".to_string()),
);
if key_value.key == "devices" {
device_cfg = key_value.value.clone().unwrap_or("[unset]".to_string());
}
}
}
}
let me = Self {
path: path.as_ref().to_string_lossy().to_string(),
metadata,
device_cfg,
};
for item in me.repr() {
info!("{item}");
}
Ok(me)
}
/// Reads through the loaded parquet file and attempts to convert to the provided tracking arc.
pub fn to_tracking_arc<Msr>(&self) -> Result<TrackingArc<Msr>, InputOutputError>
where
Msr: Measurement,
DefaultAllocator: Allocator<Msr::MeasurementSize>,
{
// Read the file since we closed it earlier
let file = File::open(&self.path).context(StdIOSnafu {
action: "opening file for tracking arc",
})?;
let builder = ParquetRecordBatchReaderBuilder::try_new(file).unwrap();
let reader = builder.build().context(ParquetSnafu {
action: "reading tracking arc",
})?;
// Check the schema
let mut has_epoch = false;
let mut has_tracking_dev = false;
let mut range_avail = false;
let mut rate_avail = false;
for field in &reader.schema().fields {
match field.name().as_str() {
"Epoch (UTC)" => has_epoch = true,
"Tracking device" => has_tracking_dev = true,
"Range (km)" => range_avail = true,
"Doppler (km/s)" => rate_avail = true,
_ => {}
}
}
ensure!(
has_epoch,
MissingDataSnafu {
which: "Epoch (UTC)"
}
);
ensure!(
has_tracking_dev,
MissingDataSnafu {
which: "Tracking device"
}
);
ensure!(
range_avail || rate_avail,
MissingDataSnafu {
which: "`Range (km)` or `Doppler (km/s)`"
}
);
let expected_type = std::any::type_name::<Msr>().split("::").last().unwrap();
// Only check that the file contains the data we need
match expected_type {
"RangeDoppler" => {
if !range_avail || !rate_avail {
return Err(InputOutputError::MissingData {
which: "`Range (km)` and `Doppler (km/s)`".to_string(),
});
}
}
"RangeMsr" => {
if !range_avail {
return Err(InputOutputError::MissingData {
which: "`Range (km)`".to_string(),
});
}
}
"RangeRate" => {
return Err(InputOutputError::MissingData {
which: "`Doppler (km/s)`".to_string(),
});
}
_ => {
return Err(InputOutputError::UnsupportedData {
which: expected_type.to_string(),
});
}
}
// At this stage, we know that the measurement is valid and the conversion is supported.
let mut arc = TrackingArc {
device_cfg: self.device_cfg.clone(),
measurements: Vec::new(),
};
// Now convert each batch on the fly
for maybe_batch in reader {
let batch = maybe_batch.unwrap();
let tracking_device = batch
.column_by_name("Tracking device")
.unwrap()
.as_any()
.downcast_ref::<StringArray>()
.unwrap();
let epochs = batch
.column_by_name("Epoch (UTC)")
.unwrap()
.as_any()
.downcast_ref::<StringArray>()
.unwrap();
// Now read the data depending on what we're deserializing as
match expected_type {
"RangeDoppler" => {
let range_data = batch
.column_by_name("Range (km)")
.unwrap()
.as_any()
.downcast_ref::<Float64Array>()
.unwrap();
let rate_data = batch
.column_by_name("Doppler (km/s)")
.unwrap()
.as_any()
.downcast_ref::<Float64Array>()
.unwrap();
// Set the measurements in the tracking arc
for i in 0..batch.num_rows() {
arc.measurements.push((
tracking_device.value(i).to_string(),
Msr::from_observation(
Epoch::from_gregorian_str(epochs.value(i)).map_err(|e| {
InputOutputError::Inconsistency {
msg: format!("{e} when parsing epoch"),
}
})?,
OVector::<f64, Msr::MeasurementSize>::from_iterator([
range_data.value(i),
rate_data.value(i),
]),
),
));
}
}
"RangeMsr" => {
let range_data = batch
.column_by_name("Range (km)")
.unwrap()
.as_any()
.downcast_ref::<Float64Array>()
.unwrap();
// Set the measurements in the tracking arc
for i in 0..batch.num_rows() {
arc.measurements.push((
tracking_device.value(i).to_string(),
Msr::from_observation(
Epoch::from_gregorian_str(epochs.value(i)).map_err(|e| {
InputOutputError::Inconsistency {
msg: format!("{e} when parsing epoch"),
}
})?,
OVector::<f64, Msr::MeasurementSize>::from_iterator([
range_data.value(i)
]),
),
));
}
}
"RangeRate" => {
let rate_data = batch
.column_by_name("Doppler (km/s)")
.unwrap()
.as_any()
.downcast_ref::<Float64Array>()
.unwrap();
// Set the measurements in the tracking arc
for i in 0..batch.num_rows() {
arc.measurements.push((
tracking_device.value(i).to_string(),
Msr::from_observation(
Epoch::from_gregorian_str(epochs.value(i)).map_err(|e| {
InputOutputError::Inconsistency {
msg: format!("{e} when parsing epoch"),
}
})?,
OVector::<f64, Msr::MeasurementSize>::from_iterator([
rate_data.value(i)
]),
),
));
}
}
_ => unreachable!("should have errored earlier"),
}
}
Ok(arc)
}
fn repr(&self) -> Vec<String> {
let mut r = Vec::new();
r.push(format!("File: {}", self.path));
for (k, v) in &self.metadata {
if k != "devices" {
r.push(format!("{k}: {v}"));
}
}
r
}
}
impl Display for DynamicTrackingArc {
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
for item in self.repr() {
writeln!(f, "{item}")?;
}
Ok(())
}
}
#[cfg(feature = "python")]
#[pymethods]
impl DynamicTrackingArc {
/// Initializes a new dynamic tracking arc from the provided parquet file
#[new]
fn new(path: String) -> Result<Self, NyxError> {
Self::from_parquet(path).map_err(|e| NyxError::CustomError { msg: e.to_string() })
}
fn __repr__(&self) -> String {
format!("{self}")
}
}