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eb94785a89
...
7662ff176c
34
Cargo.toml
34
Cargo.toml
@ -1,6 +1,6 @@
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[package]
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name = "lasprs"
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version = "0.6.1"
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version = "0.6.0"
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edition = "2021"
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authors = ["J.A. de Jong <j.a.dejong@ascee.nl>"]
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description = "Library for Acoustic Signal Processing (Rust edition, with optional Python bindings via pyo3)"
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@ -12,7 +12,7 @@ categories = ["multimedia::audio", "science", "mathematics"]
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[lib]
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name = "lasprs"
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crate-type = ["cdylib", "rlib"]
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crate-type = ["cdylib", "rlib",]
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[dependencies]
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# Error handling
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@ -29,12 +29,8 @@ num = "0.4.3"
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rayon = "1.10.0"
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# Python bindings
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pyo3 = { version = "0.21.2", optional = true, features = [
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"extension-module",
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"anyhow",
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] }
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# Python bindings for Numpy arrays
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numpy = { version = "0.21.0", optional = true }
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pyo3 = { version = "0.22.2", optional = true, features = ["extension-module", "anyhow"]}
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numpy = { git = "https://github.com/JRRudy1/rust-numpy", branch = "pyo3-0.22.0" , optional = true}
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# White noise etc
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rand = "0.8.5"
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@ -83,12 +79,7 @@ chrono = { version = "0.4.38", optional = true }
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uuid = { version = "1.10.0", features = ["v4"] , optional = true}
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# Command line argument parser, for CLI apps
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clap = { version = "4.5.13", features = [
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"derive",
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"color",
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"help",
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"suggestions",
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] }
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clap = { version = "4.5.13", features = ["derive", "color", "help", "suggestions"] }
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# FFT's
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realfft = "3.3.0"
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@ -113,20 +104,7 @@ default = ["f64", "cpal-api", "record"]
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# Use this to test if everything works well in f32
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# default = ["f32", "cpal-api", "record"]
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# When building Python bindings of Lasprs, you should enable the feature flag
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# "python-bindings". When debugging these, to safe the flag specification you
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# could just uncomment the line below here and comment the one above. If only
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# testing the implementations, or building the extension module, you should
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# call:
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# $ maturin develop -F python-bindings
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# Or:
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# $ maturin develop --release -F python-bindings
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# For faster code
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# Use this for debugging extensions
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# default = ["f64", "python-bindings", "record", "cpal-api"]
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pulse-api = []
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@ -12,12 +12,11 @@ and processing of (multi) sensor data in real time on a PC and output results.
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Documentation is provided at [doc.rs](https://docs.rs/lasprs/latest/lasprs).
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## Python bindings and examples
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## Python bindings
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The library has Python bindings (via [pyo3](https://pyo3.rs), which can be installed via:
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```
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$ pip install git+https://code.ascee.nl/ascee/lasprs --install-option "python-bindings"
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$ pip install git+https://code.ascee.nl/ascee/lasprs --install-option "--all-features"
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```
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@ -32,10 +32,7 @@ pub trait Stream {
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}
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/// Stream API descriptor: type and corresponding text
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// Do the following when Pyo3 0.22 can finally be used combined with rust-numpy:
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//#[cfg_attr(feature = "python-bindings", pyclass(eq, eq_int))]
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// For now:
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#[cfg_attr(feature = "python-bindings", pyclass)]
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#[cfg_attr(feature = "python-bindings", pyclass(eq, eq_int))]
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#[derive(strum_macros::EnumMessage, Debug, Clone, PartialEq, Serialize, Deserialize, strum_macros::Display)]
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#[allow(dead_code)]
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pub enum StreamApiDescr {
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@ -7,11 +7,8 @@ use crate::config::*;
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/// Data type description for samples coming from a stream
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#[derive(strum_macros::EnumMessage, PartialEq, Copy, Debug, Clone, Serialize, Deserialize)]
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// Do the following when Pyo3 0.22 can finally be used combined with rust-numpy:
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//#[cfg_attr(feature = "python-bindings", pyclass(eq, eq_int))]
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// For now:
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#[cfg_attr(feature = "python-bindings", pyclass)]
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#[allow(dead_code)]
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#[cfg_attr(feature = "python-bindings", pyclass(eq, eq_int))]
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pub enum DataType {
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/// 32-bit floats
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#[strum(message = "F32", detailed_message = "32-bits floating points")]
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@ -50,10 +50,7 @@ use api::*;
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use crate::config::*;
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/// Stream types that can be started
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///
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// Do the following when Pyo3 0.22 can finally be used combined with rust-numpy:
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// #[cfg_attr(feature = "python-bindings", pyclass(eq, eq_int))]
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// For now:
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#[cfg_attr(feature = "python-bindings", pyclass)]
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#[cfg_attr(feature = "python-bindings", pyclass(eq, eq_int))]
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#[derive(PartialEq, Clone, Copy)]
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pub enum StreamType {
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/// Input-only stream
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@ -7,10 +7,8 @@ use strum_macros;
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use serde::{Serialize, Deserialize};
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/// Physical quantities that are I/O of a Daq device.
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// Do the following when Pyo3 0.22 can finally be used combined with rust-numpy:
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// #[cfg_attr(feature = "python-bindings", pyclass(eq, eq_int))]
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#[cfg_attr(feature = "python-bindings", pyclass)]
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#[derive(PartialEq, Serialize, Deserialize, strum_macros::EnumMessage, Debug, Clone, Copy)]
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#[cfg_attr(feature = "python-bindings", pyclass(eq, eq_int))]
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#[allow(dead_code)]
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pub enum Qty {
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/// Number
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@ -3,12 +3,7 @@ use crate::config::*;
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/// Errors that happen in a stream
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#[derive(strum_macros::EnumMessage, PartialEq, Debug, Clone, Display, Copy)]
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// Do the following when Pyo3 0.22 can finally be used combined with rust-numpy:
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//#[cfg_attr(feature = "python-bindings", pyclass(eq, eq_int))]
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// For now:
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#[cfg_attr(feature = "python-bindings", pyclass)]
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#[cfg_attr(feature = "python-bindings", pyclass(eq, eq_int))]
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pub enum StreamError {
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/// Input overrun
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#[strum(
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@ -478,7 +478,6 @@ impl BandDescriptor for ThirdOctaveBandDescriptor {
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}
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}
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#[cfg(feature = "python-bindings")]
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#[cfg_attr(feature = "python-bindings", pymethods)]
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impl StandardFilterDescriptor {
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#[pyo3(name = "genFilter")]
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@ -34,14 +34,12 @@ impl FFT {
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nfftF: nfft as Flt,
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}
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}
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pub fn process<'a, T, U>(&mut self, time: T, freq: U)
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pub fn process<'a, T>(&mut self, time: &[Flt], freq: T)
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where
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T: Into<ArrayView<'a, Flt, Ix1>>,
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U: Into<ArrayViewMut<'a, Cflt, Ix1>>,
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T: Into<ArrayViewMut<'a, Cflt, Ix1>>,
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{
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let mut freq = freq.into();
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let time = time.into();
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self.timescratch.copy_from_slice(time.as_slice().unwrap());
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self.timescratch.copy_from_slice(time);
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let _ = self
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.fft
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.process(&mut self.timescratch, freq.as_slice_mut().unwrap());
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@ -1,11 +1,7 @@
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use crate::config::*;
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use strum_macros::{Display, EnumMessage};
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/// Sound level frequency weighting type (A, C, Z)
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// Do the following when Pyo3 0.22 can finally be used combined with rust-numpy:
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// #[cfg_attr(feature = "python-bindings", pyclass(eq, eq_int))]
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// For now:
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#[cfg_attr(feature = "python-bindings", pyclass)]
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#[cfg_attr(feature = "python-bindings", pyclass(eq, eq_int))]
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#[derive(Display, Debug, EnumMessage, Default, Clone, PartialEq)]
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pub enum FreqWeighting {
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/// A-weighting
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41
src/ps/ps.rs
41
src/ps/ps.rs
@ -7,8 +7,8 @@ use std::usize;
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use crate::Dcol;
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use super::fft::FFT;
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use super::window::*;
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use super::fft::FFT;
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use std::mem::MaybeUninit;
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use realfft::{RealFftPlanner, RealToComplex};
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@ -46,6 +46,7 @@ pub trait CrossPowerSpecra {
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fn tf(&self, chi: usize, chj: usize, chRef: Option<usize>) -> Array1<Cflt>;
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}
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impl CrossPowerSpecra for CPSResult {
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fn ap(&self, ch: usize) -> Array1<Flt> {
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// Slice out one value for all frequencies, map to only real part, and
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@ -86,10 +87,10 @@ impl CrossPowerSpecra for CPSResult {
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/// estimation.
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///
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pub struct PowerSpectra {
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/// Window used in estimator. The actual Window in here is normalized with
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/// the square root of the Window power. This safes one division when
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/// processing time data.
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pub window_normalized: Window,
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/// Window used in estimator
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pub window: Window,
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/// The window power, is corrected for in power spectra estimants
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pub sqrt_win_pwr: Flt,
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ffts: Vec<FFT>,
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@ -102,7 +103,7 @@ pub struct PowerSpectra {
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impl PowerSpectra {
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/// Returns the FFT length used in power spectra computations
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pub fn nfft(&self) -> usize {
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self.window_normalized.win.len()
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self.window.win.len()
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}
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/// Create new power spectra estimator. Uses FFT size from window length
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///
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@ -115,12 +116,9 @@ impl PowerSpectra {
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///
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/// - `window` - A `Window` struct, from which NFFT is also used.
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///
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pub fn newFromWindow(mut window: Window) -> PowerSpectra {
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pub fn newFromWindow(window: Window) -> PowerSpectra {
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let nfft = window.win.len();
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let win_pwr = window.win.mapv(|w| w.powi(2)).sum() / (nfft as Flt);
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let sqrt_win_pwr = Flt::sqrt(win_pwr);
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window.win.mapv_inplace(|v| v / sqrt_win_pwr);
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assert!(nfft > 0);
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assert!(nfft % 2 == 0);
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@ -130,7 +128,8 @@ impl PowerSpectra {
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let Fft = FFT::new(fft);
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PowerSpectra {
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window_normalized: window,
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window,
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sqrt_win_pwr: Flt::sqrt(win_pwr),
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ffts: vec![Fft],
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timedata: Array2::zeros((nfft, 1)),
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freqdata: Array2::zeros((nfft / 2 + 1, 1)),
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@ -139,7 +138,7 @@ impl PowerSpectra {
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/// Compute FFTs of input channel data. Stores the scaled FFT data in
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/// self.freqdata.
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fn compute_ffts(&mut self, timedata: ArrayView2<Flt>) -> ArrayView2<Cflt> {
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fn compute_ffts(&mut self, timedata: ArrayView2<Flt>) -> &Array2<Cflt> {
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let (n, nch) = timedata.dim();
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let nfft = self.nfft();
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assert!(n == nfft);
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@ -154,27 +153,25 @@ impl PowerSpectra {
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}
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assert!(n == self.nfft());
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assert!(n == self.window_normalized.win.len());
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assert!(n == self.window.win.len());
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let sqrt_win_pwr = self.sqrt_win_pwr;
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// Multiply signals with window function, and compute fft's for each channel
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Zip::from(timedata.axis_iter(Axis(1)))
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.and(self.timedata.axis_iter_mut(Axis(1)))
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.and(&mut self.ffts)
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.and(self.freqdata.axis_iter_mut(Axis(1)))
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.par_for_each(|time_in, mut time_tmp_storage, fft, mut freq| {
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let DC = time_in.mean().unwrap();
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.par_for_each(|time_in,mut time, fft, mut freq| {
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azip!((t in &mut time_tmp_storage, &tin in time_in, &win in &self.window_normalized.win) {
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// Substract DC value from time data, as this leaks into
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// positive frequencies due to windowing.
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// Multiply with window and copy over to local time data buffer
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*t=(tin-DC)*win});
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azip!((t in &mut time, &tin in time_in, &win in &self.window.win) *t=tin*win/sqrt_win_pwr);
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fft.process(&time_tmp_storage, &mut freq);
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freq[0] = DC + 0. * I;
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let tslice = time.as_slice().unwrap();
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let fslice = freq.as_slice_mut().unwrap();
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fft.process(tslice, fslice);
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});
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self.freqdata.view()
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&self.freqdata
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}
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/// Compute cross power spectra from input time data. First axis is
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@ -24,7 +24,7 @@
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//! let settings = SLMSettingsBuilder::default()
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//! .fs(48e3)
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//! .freqWeighting(FreqWeighting::A)
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//! .timeWeighting(TimeWeighting::Fast{})
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//! .timeWeighting(TimeWeighting::Fast)
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//! .filterDescriptors(&[desc]).build().unwrap();
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//!
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//! let mut slm = SLM::new(settings);
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@ -33,7 +33,7 @@
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//! data[0] = 1.;
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//!
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//! // Now apply some data. This is a kind of the SLM-s impulse response
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//! let res = slm.run(data.as_slice().unwrap(), true).unwrap();
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//! let res = slm.run(&data.as_slice().unwrap()).unwrap();
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//!
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//! // Only one channel of result data
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//! assert_eq!(res.len(), 1);
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@ -28,7 +28,6 @@ pub struct SLMSettings {
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pub filterDescriptors: Vec<StandardFilterDescriptor>,
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}
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#[cfg(feature="python-bindings")]
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#[cfg_attr(feature = "python-bindings", pymethods)]
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impl SLMSettings {
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#[new]
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@ -205,7 +205,6 @@ impl SLM {
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}
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}
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#[cfg(feature="python-bindings")]
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#[cfg_attr(feature = "python-bindings", pymethods)]
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impl SLM {
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#[new]
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@ -1,10 +1,6 @@
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use crate::config::*;
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/// Time weighting to use in level detection of Sound Level Meter.
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///
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// Do the following when Pyo3 0.22 can finally be used combined with rust-numpy:
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// #[cfg_attr(feature = "python-bindings", pyclass(eq))]
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// For now:
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#[cfg_attr(feature = "python-bindings", pyclass)]
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#[cfg_attr(feature = "python-bindings", pyclass(eq))]
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#[derive(Clone, Copy, PartialEq)]
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pub enum TimeWeighting {
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// I know that the curly braces here are not required and add some
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