Cleanup docs and examples

pyphastft/example.py

@@ -1,7 +1,8 @@
 import matplotlib.pyplot as plt
 import numpy as np
+from numpy.fft import fft
 
-from pyphastft import fft
+# from pyphastft import fft
 
 
 def main():
@@ -16,7 +17,7 @@ def main():
     )  # Adjusted time vector
 
     # Generate the signal
-    s_re = 2 * np.sin(2 * np.pi * t) + np.sin(2 * np.pi * 10 * t)
+    s_re = 2 * np.sin(2 * np.pi * t + 1) + np.sin(2 * np.pi * 10 * t + 1)
     s_im = np.ascontiguousarray([0.0] * len(s_re), dtype=np.float64)
 
     # Plot the original signal
@@ -30,7 +31,7 @@ def main():
     plt.legend()
 
     # Perform FFT
-    fft(s_re, s_im, direction="f")
+    s_re = fft(s_re)
 
     # Plot the magnitude spectrum of the FFT result
     plt.subplot(2, 1, 2)

pyphastft/src/lib.rs

@@ -1,5 +1,5 @@
 use numpy::PyReadwriteArray1;
-use phastft::{fft as fft_rs, planner::Direction};
+use phastft::{fft_64 as fft_64_rs, planner::Direction};
 use pyo3::prelude::*;
 
 #[pyfunction]
@@ -11,7 +11,7 @@ fn fft(mut reals: PyReadwriteArray1<f64>, mut imags: PyReadwriteArray1<f64>, dir
         Direction::Reverse
     };
 
-    fft_rs(
+    fft_64_rs(
         reals.as_slice_mut().unwrap(),
         imags.as_slice_mut().unwrap(),
         dir,

pyphastft/vis_qt.py

@@ -1,9 +1,10 @@
-from pyphastft import fft
+import sys
+
 import numpy as np
 import pyaudio
 import pyqtgraph as pg
+from pyphastft import fft
 from pyqtgraph.Qt import QtWidgets, QtCore
-import sys
 
 
 class RealTimeAudioSpectrum(QtWidgets.QWidget):
@@ -28,7 +29,7 @@ def init_ui(self):
         self.plot_widget.setBackground("k")
         self.plot_item = self.plot_widget.getPlotItem()
         self.plot_item.setTitle(
-            "Real-Time Audio Spectrum Visualizer\npowered by PhastFT",
+            "Real-Time Audio Spectrum Visualizer powered by PhastFT",
             color="w",
             size="16pt",
         )
@@ -79,10 +80,10 @@ def init_audio_stream(self):
     def audio_callback(self, in_data, frame_count, time_info, status):
         audio_data = np.frombuffer(in_data, dtype=np.float32)
         reals = np.zeros(self.n_fft_bins)
-        imaginaries = np.zeros(self.n_fft_bins)
+        imags = np.zeros(self.n_fft_bins)
         reals[: len(audio_data)] = audio_data  # Fill the reals array with audio data
-        fft(reals, imaginaries, direction="f")
-        fft_magnitude = np.sqrt(reals**2 + imaginaries**2)[: self.n_fft_bins // 2]
+        fft(reals, imags, direction="f")
+        fft_magnitude = np.sqrt(reals**2 + imags**2)[: self.n_fft_bins // 2]
 
         # Aggregate or interpolate FFT data to fit into display bins
         new_fft_data = np.interp(
@@ -93,13 +94,12 @@ def audio_callback(self, in_data, frame_count, time_info, status):
 
         # Apply exponential moving average filter
         self.ema_fft_data = self.ema_fft_data * self.smoothing_factor + new_fft_data * (
-            1 - self.smoothing_factor
+            1.0 - self.smoothing_factor
         )
-        return (in_data, pyaudio.paContinue)
+        return in_data, pyaudio.paContinue
 
     def update(self):
-        if hasattr(self, "ema_fft_data"):
-            self.bar_graph.setOpts(height=self.ema_fft_data, width=self.bar_width)
+        self.bar_graph.setOpts(height=self.ema_fft_data, width=self.bar_width)
 
     def closeEvent(self, event):
         self.stream.stop_stream()

src/lib.rs

@@ -30,8 +30,7 @@ macro_rules! impl_fft_for {
         ///
         /// # Panics
         ///
-        /// Panics if `reals.len() != imags.len()` or if `reals.len()` and `imags.len()` are not a power of
-        /// 2
+        /// Panics if `reals.len() != imags.len()`, or if the input length is _not_ a power of 2.
         ///
         /// ## References
         /// <https://inst.eecs.berkeley.edu/~ee123/sp15/Notes/Lecture08_FFT_and_SpectAnalysis.key.pdf>
@@ -77,8 +76,7 @@ macro_rules! impl_fft_with_opts_and_plan_for {
         ///
         /// # Panics
         ///
-        /// Panics if `reals.len() != imags.len()` or if `reals.len()` and `imags.len()` are not a power of
-        /// 2
+        /// Panics if `reals.len() != imags.len()`, or if the input length is _not_ a power of 2.
         pub fn $func_name(
             reals: &mut [$precision],
             imags: &mut [$precision],