Merge pull request #61 from SpookyYomo/docs

Documentation fixes

sci-rs/src/signal/convolve.rs

@@ -171,6 +171,7 @@ mod tests {
     }
 
     #[test]
+    #[cfg(feature = "plot")]
     fn test_scipy_example() {
         use rand::distributions::{Distribution, Standard};
         use rand::thread_rng;

sci-rs/src/signal/filter/design/bilinear_zpk.rs

@@ -39,16 +39,16 @@ use super::{
 ///
 /// See Also
 /// --------
-/// lp2lp_zpk, lp2hp_zpk, lp2bp_zpk, lp2bs_zpk
-/// bilinear
+/// [lp2lp_zpk](super::lp2lp_zpk_dyn), [lp2hp_zpk](super::lp2hp_zpk_dyn),
+/// [lp2bp_zpk](super::lp2bp_zpk_dyn), [lp2bs_zpk](super::lp2bs_zpk_dyn), bilinear
 ///
 /// Notes
 /// -----
 /// .. versionadded:: 1.1.0
 ///
 /// Examples
 /// --------
-/// ```ignore
+/// ```custom,{class=language-python}
 /// >>> from scipy import signal
 /// >>> import matplotlib.pyplot as plt
 ///

sci-rs/src/signal/filter/design/cplx.rs

@@ -50,7 +50,6 @@ use super::{
 /// --------
 /// _cplxpair
 /// """
-
 #[cfg(feature = "alloc")]
 pub fn cplxreal_dyn<F>(z: Vec<Complex<F>>, tol: Option<F>) -> (Vec<Complex<F>>, Vec<Complex<F>>)
 where
@@ -84,7 +83,7 @@ where
     let mut zp: Vec<Complex<F>> = zc.iter().filter(|zi| zi.im > F::zero()).cloned().collect();
     let mut zn: Vec<Complex<F>> = zc.iter().filter(|zi| zi.im < F::zero()).cloned().collect();
     if zp.len() != zn.len() {
-        panic!("Array contains complex value with no matchin conjugate");
+        panic!("Array contains complex value with no matching conjugate");
     }
 
     // Find runs of (approximately) the same real part

sci-rs/src/signal/filter/design/iirfilter.rs

@@ -42,7 +42,6 @@ use alloc::vec::Vec;
 ///
 #[allow(clippy::too_many_arguments)]
 #[cfg(feature = "alloc")]
-#[allow(clippy::too_many_arguments)]
 pub fn iirfilter_dyn<F>(
     order: usize,
     wn: Vec<F>,

sci-rs/src/signal/filter/design/lp2bp_zpk.rs

@@ -59,7 +59,6 @@ use alloc::vec::Vec;
 /// .. versionadded:: 1.1.0
 ///
 /// """
-
 #[cfg(feature = "alloc")]
 pub fn lp2bp_zpk_dyn<F>(zpk: ZpkFormatFilter<F>, wo: Option<F>, bw: Option<F>) -> ZpkFormatFilter<F>
 where

sci-rs/src/signal/filter/design/lp2hp_zpk.rs

@@ -66,7 +66,7 @@ use alloc::vec::Vec;
 ///>>> plt.semilogx()
 ///>>> plt.grid(True)
 ///>>> plt.xlabel('Frequency [rad/s]')
-///>>> plt.ylabel('Magnitude [dB]')
+///>>> plt.ylabel('Magnitude \[dB\]')
 ///>>> plt.legend()
 pub fn lp2hp_zpk_dyn<F>(zpk: ZpkFormatFilter<F>, wo: Option<F>) -> ZpkFormatFilter<F>
 where

sci-rs/src/signal/filter/design/lp2lp_zpk.rs

@@ -15,35 +15,38 @@ use alloc::vec::Vec;
 /// Return an analog low-pass filter with cutoff frequency `wo`
 /// from an analog low-pass filter prototype with unity cutoff frequency,
 /// using zeros, poles, and gain ('zpk') representation.
+///
 /// Parameters
 /// ----------
-/// z : array_like
+/// * z : array_like  
 ///     Zeros of the analog filter transfer function.
-/// p : array_like
+/// * p : array_like  
 ///     Poles of the analog filter transfer function.
-/// k : float
+/// * k : float  
 ///     System gain of the analog filter transfer function.
-/// wo : float
+/// * wo : float  
 ///     Desired cutoff, as angular frequency (e.g., rad/s).
 ///     Defaults to no change.
+///
 /// Returns
 /// -------
-/// z : ndarray
+/// * z : ndarray  
 ///     Zeros of the transformed low-pass filter transfer function.
-/// p : ndarray
+/// * p : ndarray  
 ///     Poles of the transformed low-pass filter transfer function.
-/// k : float
+/// * k : float  
 ///     System gain of the transformed low-pass filter.
+///
 /// See Also
 /// --------
-/// lp2hp_zpk, lp2bp_zpk, lp2bs_zpk, bilinear
-/// lp2lp
+/// [lp2lp_zpk](super::lp2lp_zpk_dyn), [lp2hp_zpk](super::lp2hp_zpk_dyn),
+/// [lp2bp_zpk](super::lp2bp_zpk_dyn), [lp2bs_zpk](super::lp2bs_zpk_dyn), bilinear
+///
 /// Notes
 /// -----
-/// This is derived from the s-plane substitution
-/// .. math:: s \rightarrow \frac{s}{\omega_0}
+/// This is derived from the s-plane substitution  
+/// .. math:: s \rightarrow \frac{s}{\omega_0}  
 /// .. versionadded:: 1.1.0
-
 #[cfg(feature = "alloc")]
 pub fn lp2lp_zpk_dyn<F>(zpk: ZpkFormatFilter<F>, wo: Option<F>) -> ZpkFormatFilter<F>
 where

sci-rs/src/signal/filter/design/zpk2sos.rs

@@ -45,7 +45,6 @@ enum WhichNearestComplex {
 ///     specification.
 ///
 ///
-
 #[cfg(feature = "alloc")]
 pub fn zpk2sos_dyn<F>(
     order: usize,

sci-rs/src/signal/filter/sosfilt.rs

@@ -412,7 +412,7 @@ fn _sosfilt_isize_32<I: Copy + Into<isize>>(y: &[I], sos: &mut [Sos32], z: &mut
 ///
 /// A specialized cascaded Biquad filter for 32-bit floating point samples
 ///
-/// Including acceleratored
+/// Including accelerated
 ///  * Single-sided 4th and 8th order filters
 ///     * Example: 4th or 8th order lowpass Butterworth
 ///  * Double-sided 4th order filters are accelerated
@@ -422,12 +422,11 @@ pub fn sosfilt_fast32_st(y: &[f32], sos: &mut [Sos32], z: &mut [f32]) {
     _sosfilt32(y, sos, z);
 }
 
+/// A specialized cascaded Biquad filter for signed samples filtered as 32-bit floating point
+/// samples. Samples implement `Into<isize>` to convert to a signed integer for speed on native
+/// bitwidths.
 ///
-/// A specialized cascaded Biquad filter for signed samples
-/// filtered as 32-bit floating point samples. Samples implement
-/// Into<isize> to convert to a signed integer for speed on native bitwidths.
-///
-/// Including acceleratored
+/// Including accelerated
 ///  * Single-sided 4th and 8th order filters
 ///     * Example: 4th or 8th order lowpass Butterworth
 ///  * Double-sided 4th order filters are accelerated

sci-rs/src/signal/wave/mod.rs

@@ -6,7 +6,7 @@ use ndarray::{Array, ArrayBase, Data, Dimension, RawData};
 ///
 /// The square wave has a period ``2*pi``, has value +1 from 0 to
 /// ``2*pi*duty`` and -1 from ``2*pi*duty`` to ``2*pi``. `duty` must be in
-/// the interval [0,1].
+/// the interval \[0,1\].
 ///
 /// Note that this is not band-limited.  It produces an infinite number
 /// of harmonics, which are aliased back and forth across the frequency

sci-rs/src/stats.rs

@@ -428,8 +428,9 @@ where
     y.map(move |yi| ((*yi.borrow() - median) * F::from(0.6745).unwrap() / mad))
 }
 
-/// The median absolute deviation (MAD, [1]) computes the median over the absolute deviations from the median.
-/// It is a measure of dispersion similar to the standard deviation but more robust to outliers
+/// The median absolute deviation ([MAD](https://en.wikipedia.org/wiki/Median_absolute_deviation))
+/// computes the median over the absolute deviations from the median. It is a measure of dispersion
+/// similar to the standard deviation but more robust to outliers
 ///
 /// # Arguments
 ///