Merge branch 'release/v1.5.0a2'

CITATION.cff

@@ -0,0 +1,32 @@
+cff-version: 1.2.0
+message: "If you use this software in your work, please cite the SMC 2020 paper as below."
+authors:
+- family-names: "Tiraboschi"
+  given-names: "Marco"
+  orcid: "https://orcid.org/0000-0001-5761-4837"
+title: "SAMPLE"
+version: 1.5.0a2
+date-released: 2021-02-26
+url: "https://github.com/limunimi/sample"
+repository-code: "https://github.com/limunimi/sample"
+license: MIT
+type: software
+preferred-citation:
+  type: proceedings
+  title: "Spectral Analysis for Modal Parameters Linear Estimate"
+  authors:
+    - family-names: "Tiraboschi"
+      given-names: "Marco"
+      orcid: "https://orcid.org/0000-0001-5761-4837"
+    - family-names: "Avanzini"
+      given-names: "Federico"
+      orcid: "https://orcid.org/0000-0002-1257-5878"
+    - family-names: "Ntalampiras"
+      given-names: "Stavros"
+      orcid: "https://orcid.org/0000-0003-3482-9215"
+  doi: "10.5281/zenodo.3898795"
+  journal: "Proceedings of the 17th Sound and Music Computing Conference"
+  month: 6
+  year: 2020
+  start: 276
+  end: 283

README.md

@@ -52,7 +52,7 @@ You can install the GUI from the command line with Python via pip.
 It is recommended run these commands in a virtual environment in  
 order to to keep your system clean
 
-```pip install lim-sample[gui]==1.5.0a0```
+```pip install lim-sample[gui]==1.5.0a2```
 
 To run the GUI from the command line, run
 
@@ -87,23 +87,3 @@ https://github.com/limunimi/sample
 ### Notebooks
 For learning to use the package, you can refer to the interactive
 notebooks in the [notebooks](https://github.com/limunimi/sample/tree/master/notebooks) folder
-
-## Paper
-Your can find the paper in the SMC 2020 proceedings [here](https://smc2020torino.it/adminupload/file/SMCCIM_2020_paper_167.pdf).
-
-### Abstract
-*Modal synthesis is used to generate the sounds associated with the vibration of rigid bodies, according to the characteristics of the force applied onto the object. Towards obtaining sounds of high quality, a great quantity of modes is necessary, the development of which is a long and tedious task for sound designers as they have to manually write the modal parameters.
-This paper presents a new approach for practical modal parameter estimation based on the spectral analysis of a single audio example. The method is based on modelling the spectrum of the sound with a time-varying sinusoidal model and fitting the modal parameters with linear and semi-linear techniques.
-We also detail the physical and mathematical principles that motivate the algorithm design choices.
-A Python implementation of the proposed approach has been developed and tested on a dataset of impact sounds considering objects of different shapes and materials. We assess the performance of the algorithm by evaluating the quality of the resynthesised sounds. Resynthesis is carried out via the Sound Design Toolkit (SDT) modal engine and compared to the sounds resynthesised from parameters extracted by SDT's own estimator. The proposed method was thoroughly evaluated both objectively using perceptually relevant features and subjectively following the MUSHRA protocol.*
-
-### Cite
-```
-@inproceedings{tiraboschi2020spectral,
-	title={Spectral Analysis for Modal Parameters Linear Estimate},
-	author={Tiraboschi, M and Avanzini, F and Ntalampiras, S},
-	booktitle={Sound \& Music Computing Conference},
-	year={2020},
-	organization={SMC},
-}
-```

changelog/v1_5_0.md

@@ -1,4 +1,4 @@
-## v1.5.0a0
+## v1.5.0a2
 This version is still in its alpha phase
 
 ### GUI

requirements.txt

@@ -21,6 +21,7 @@ requests
 ttkthemes
 Pillow
 pygame
+throttle
 
 # Pylint
 pylint

sample/__init__.py

@@ -25,7 +25,7 @@
 from sample.sample import SAMPLE
 
 
-__version__ = "1.5.0a0"
+__version__ = "1.5.0a2"
 
 
 @cli.main(__name__)

sample/gui.py

@@ -1,24 +1,29 @@
 """SAMPLE GUI launcher"""
 from chromatictools import cli
-from sample.widgets import main, logging
-import sample
 import multiprocessing
-import logging as _logging
 import argparse
 import sys
 
 
-if sys.platform == "linux":
-  default_theme = "radiance"
-else:
-  default_theme = "arc"
-
-
 def launch(args):
   """Launch the GUI main loop
 
   Args:
     args (Namespace): Command-line arguments namespace"""
+  from sample.widgets import main, logging  # pylint: disable=C0415
+  import logging as _logging  # pylint: disable=C0415
+  import sample  # pylint: disable=C0415
+
+  _logging.basicConfig(
+    level=_logging.WARNING,
+    format="%(asctime)s %(name)-12s %(levelname)-8s: %(message)s",
+    datefmt="%Y-%m-%d %H:%M:%S",
+  )
+  _logging.captureWarnings(True)
+  logging.setLevel(args.log_level)
+  logging.info("SAMPLE: version %s", sample.__version__)
+  logging.info("Args: %s", args)
+
   root = main.main(
     splash_time=args.splash_time,
     gui_kwargs=dict(
@@ -31,12 +36,10 @@ def launch(args):
 @cli.main(__name__, *sys.argv[1:])
 def run(*argv):
   """Launch the SAMPLE GUI"""
-  _logging.basicConfig(
-    level=_logging.WARNING,
-    format="%(asctime)s %(name)-12s %(levelname)-8s: %(message)s",
-    datefmt="%Y-%m-%d %H:%M:%S",
-  )
-  _logging.captureWarnings(True)
+  if sys.platform == "linux":
+    default_theme = "radiance"
+  else:
+    default_theme = "arc"
 
   parser = argparse.ArgumentParser(description=__doc__)
   parser.add_argument(
@@ -57,10 +60,6 @@ def run(*argv):
   )
   args, _ = parser.parse_known_args(argv)
 
-  logging.setLevel(args.log_level)
-  logging.info("SAMPLE: version %s", sample.__version__)
-  logging.info("Args: %s", args)
-
   root = multiprocessing.Process(target=launch, args=(args,))
   root.start()
   root.join()

sample/plots.py

@@ -22,8 +22,19 @@ def sine_tracking_2d(m: sm.SinusoidalModel, ax=None):
     The axes list"""
   if ax is None:
     _, ax = plt.subplots(1, 2, sharex=True)
+  tmax = 0
+  if m.reverse:
+    if m.save_intermediate:
+      tmax = len(m.intermediate_["stft"]) * m.h / m.fs
+    else:
+      tmax = max(
+        (track["start_frame"] + track["freq"].size) * m.h / m.fs
+        for track in m.sine_tracker_.all_tracks_
+      )
   for track in m.sine_tracker_.all_tracks_:
     t_x = (track["start_frame"] + np.arange(track["freq"].size)) * m.h / m.fs
+    if m.reverse:
+      t_x = tmax - t_x
     ax[0].plot(t_x, track["freq"])
     ax[1].plot(t_x, track["mag"])
 

sample/widgets/analysis.py

@@ -70,8 +70,11 @@ def __init__(
       ax.set_yticks(())
     # ------------------------------------------------------------------------
 
+    self.progressbar = tk.Progressbar(self, maximum=1, value=0)
+    self.progressbar.grid(row=1)
+
     self.bottom_row = tk.Frame(self)
-    self.bottom_row.grid(row=1)
+    self.bottom_row.grid(row=2)
     self.bottom_row.responsive(1, 4)
 
     # Analysis button
@@ -99,11 +102,9 @@ def update_plot(self):
       ax.clear()
     m = self.sample_object.sinusoidal_model
     stft = np.array([mx for mx, _ in m.intermediate_["stft"]]).T
-    tmax = max((
-        track["start_frame"] + track["freq"].size
-        for track in m.sine_tracker_.all_tracks_
-      ), default=0,
-    ) * m.h / m.fs
+    if m.reverse:
+      stft = np.fliplr(stft)
+    tmax = len(m.intermediate_["stft"]) * m.h / m.fs
 
     plots.sine_tracking_2d(m, ax=self.ax)
 
@@ -175,13 +176,13 @@ def analysis_cbk(self, *args, **kwargs):  # pylint: disable=W0613
       self.sample_object.fit(
         x, sinusoidal_model__fs=self.audio_sr,
         sinusoidal_model__save_intermediate=True,
+        sinusoidal_model__progressbar=self.progressbar,
       )
     except Exception as e:  # pylint: disable=W0703
       messagebox.showerror(
         type(e).__name__, str(e)
       )
       return
-    messagebox.showinfo("Success", "Analysis done!")
     self.audio_resynth_x = None
     self.update_plot()
 

sample/widgets/sample.py

@@ -0,0 +1,107 @@
+"""SAMPLE class for use in GUI"""
+from sample import sample
+from sample.sms import mm
+import tkinter as tk
+import numpy as np
+import throttle
+from typing import Optional, Tuple
+
+
+class SAMPLE(sample.SAMPLE):
+  """SAMPLE model for use in the GUI. For a full list of arguments see
+  :class:`sample.sample.SAMPLE`"""
+  class SinusoidalModel(mm.ModalModel):
+    """Sinusoidal tracker for use in the GUI. For a full list of
+    arguments see :class:`sample.sms.mm.ModalModel`
+
+    Args:
+      progressbar (optional): Progressbar widget for visualizing
+        the peak tracking progress"""
+    def __init__(
+      self,
+      progressbar: Optional[tk.Widget] = None,
+      fs: int = 44100,
+      w: Optional[np.ndarray] = None,
+      n: int = 2048,
+      h: int = 500,
+      t: float = -90,
+      max_n_sines: int = 100,
+      min_sine_dur: float = 0.04,
+      freq_dev_offset: float = 20,
+      freq_dev_slope: float = 0.01,
+      reverse: bool = False,
+      sine_tracker_cls: type = mm.ModalTracker,
+      save_intermediate: bool = False,
+      frequency_bounds: Tuple[Optional[float], Optional[float]] = (20, 16000),
+      peak_threshold: float = -90,
+      merge_strategy: str = "average",
+      strip_t: Optional[float] = None,
+    ):
+      self.progressbar = progressbar
+      super().__init__(
+        fs=fs, w=w, n=n, h=h, t=t,
+        max_n_sines=max_n_sines,
+        min_sine_dur=min_sine_dur,
+        freq_dev_offset=freq_dev_offset,
+        freq_dev_slope=freq_dev_slope,
+        reverse=reverse,
+        sine_tracker_cls=sine_tracker_cls,
+        save_intermediate=save_intermediate,
+        frequency_bounds=frequency_bounds,
+        peak_threshold=peak_threshold,
+        merge_strategy=merge_strategy,
+        strip_t=strip_t,
+      )
+
+    def fit(self, x: np.ndarray, y=None, **kwargs):
+      """Analyze audio data
+
+      Args:
+        x (array): audio input
+        y (ignored): exists for compatibility
+        kwargs: Any parameter, overrides initialization
+
+      Returns:
+        SinusoidalModel: self"""
+      self.set_params(**kwargs)
+      self.w_ = self.normalized_window
+      if self.progressbar is not None:
+        self.progressbar["maximum"] = -1
+        self.progressbar.config(
+          value=0,
+          maximum=len(list(
+            self.time_frames(x)
+          ))
+        )
+      s = super().fit(x=x, y=y)
+      if self.progressbar is not None:
+        self.progressbar.config(value=1, maximum=1)
+      return s
+
+    @throttle.wrap(.0125, 1)
+    def progressbar_update(self, value: Optional[float] = None):
+      """Update the progress bar. This function is throttled"""
+      if value is not None:
+        self.progressbar.config(value=value)
+      self.progressbar.update()
+
+    def time_frames(self, x: np.ndarray):
+      """Generator of frames for a given input. Also,
+      updates the progressbar if one has been specified
+
+      Args:
+        x (array): Input
+
+      Returns:
+        generator: Generator of overlapping frames of the padded input"""
+      it = super().time_frames(x)
+      if self.progressbar is not None and self.progressbar["maximum"] > 0:
+        def func(t):
+          self.progressbar_update(value=t[0])
+          return t[-1]
+        it = map(func, enumerate(it))
+      for f in it:
+        yield f
+
+  def __init__(self, sinusoidal_model=SinusoidalModel(), **kwargs):
+    super().__init__(sinusoidal_model=sinusoidal_model, **kwargs)

sample/widgets/settings.py

@@ -1,6 +1,5 @@
 """Settings tab"""
-import sample
-from sample.widgets import responsive as tk, utils, logging
+from sample.widgets import responsive as tk, utils, logging, sample
 from matplotlib.backends import _backend_tk
 from scipy import signal
 import functools

setup.py

@@ -36,6 +36,7 @@
       "pygame",
       "matplotlib",
       "Pillow",
+      "throttle",
     ],
     "plots": [
       "matplotlib",