+++ /dev/null
-# -*- coding: utf-8 -*-
-#
-# Copyright (c) 2007-2010 Guillaume Pellerin <yomguy@parisson.com>
-# Copyright (c) 2010 Olivier Guilyardi <olivier@samalyse.com>
-
-# This file is part of TimeSide.
-
-# TimeSide is free software: you can redistribute it and/or modify
-# it under the terms of the GNU General Public License as published by
-# the Free Software Foundation, either version 2 of the License, or
-# (at your option) any later version.
-
-# TimeSide 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 General Public License for more details.
-
-# You should have received a copy of the GNU General Public License
-# along with TimeSide. If not, see <http://www.gnu.org/licenses/>.
-
-
-from timeside.core import Processor, implements, interfacedoc, FixedSizeInputAdapter
-from timeside.api import IGrapher
-from timeside.grapher.core import *
-
-class WaveformImageJoyContour(WaveformImage):
-
- def __init__(self, image_width, image_height, nframes, samplerate, fft_size, bg_color, color_scheme, ndiv=1, symetry=None):
- WaveformImage.__init__(self, image_width, image_height, nframes, samplerate, fft_size, bg_color, color_scheme)
- self.contour = numpy.zeros(self.image_width)
- self.centroids = numpy.zeros(self.image_width)
- self.ndiv = ndiv
- self.x = numpy.r_[0:self.image_width-1:1]
- self.dx1 = self.x[1]-self.x[0]
- self.symetry = symetry
-
- def get_peaks_contour(self, x, peaks, spectral_centroid=None):
- self.contour[x] = numpy.max(peaks)
- self.centroids[x] = spectral_centroid
-
- def mean(self, samples):
- return numpy.mean(samples)
-
- def normalize(self, contour):
- contour = contour-min(contour)
- return contour/max(contour)
-
- def draw_peaks_contour(self):
- contour = self.contour.copy()
-
- # Smoothing
- contour = smooth(contour, window_len=16)
-
- # Normalize
- contour = self.normalize(contour)
-
- # Scaling
- #ratio = numpy.mean(contour)/numpy.sqrt(2)
- ratio = 1
- contour = self.normalize(numpy.expm1(contour/ratio))*(1-10**-6)
-
- # Spline
- #contour = cspline1d(contour)
- #contour = cspline1d_eval(contour, self.x, dx=self.dx1, x0=self.x[0])
-
- if self.symetry:
- height = int(self.image_height/2)
- else:
- height = self.image_height
-
- # Multicurve rotating
- for i in range(0,self.ndiv):
- self.previous_x, self.previous_y = None, None
-
- #bright_color = 255
- bright_color = int(255*(1-float(i)/(self.ndiv*2)))
-# bright_color = 255-bright_color+150
-# line_color = self.color_lookup[int(self.centroids[j]*255.0)]
- line_color = (bright_color,bright_color,bright_color)
-
- # Linear
- #contour = contour*(1.0-float(i)/self.ndiv)
- #contour = contour*(1-float(i)/self.ndiv)
-
- # Cosine
- contour = contour*numpy.arccos(float(i)/self.ndiv)*2/numpy.pi
- #contour = self.contour*(1-float(i)*numpy.arccos(float(i)/self.ndiv)*2/numpy.pi/self.ndiv)
-
- # Negative Sine
- #contour = contour + ((1-contour)*2/numpy.pi*numpy.arcsin(float(i)/self.ndiv))
-
- curve = (height-1)*contour
-# curve = contour*(height-2)/2+height/2
-
- for x in self.x:
- x = int(x)
- y = curve[x]
- if not x == 0:
- if not self.symetry:
- self.draw.line([self.previous_x, self.previous_y, x, y], line_color)
- self.draw_anti_aliased_pixels(x, y, y, line_color)
- else:
- self.draw.line([self.previous_x, self.previous_y+height, x, y+height], line_color)
- self.draw_anti_aliased_pixels(x, y+height, y+height, line_color)
- self.draw.line([self.previous_x, -self.previous_y+height, x, -y+height], line_color)
- self.draw_anti_aliased_pixels(x, -y+height, -y+height, line_color)
- else:
- if not self.symetry:
- self.draw.point((x, y), line_color)
- else:
- self.draw.point((x, y+height), line_color)
- self.previous_x, self.previous_y = x, y
-
- def process(self, frames, eod):
- if len(frames) != 1:
- buffer = frames[:,0].copy()
- buffer.shape = (len(buffer),1)
- for samples, end in self.pixels_adapter.process(buffer, eod):
- if self.pixel_cursor < self.image_width:
- #(spectral_centroid, db_spectrum) = self.spectrum.process(buffer, True)
- peaks = self.peaks(samples)
- self.get_peaks_contour(self.pixel_cursor, peaks)
- self.pixel_cursor += 1
- if eod:
- self.draw_peaks_contour()
-
- def save(self, filename):
- """ Apply last 2D transforms and write all pixels to the file. """
- # middle line (0 for none)
- a = 1
- for x in range(self.image_width):
- self.pixel[x, self.image_height/2] = tuple(map(lambda p: p+a, self.pixel[x, self.image_height/2]))
- self.image = self.image.transpose(Image.FLIP_TOP_BOTTOM)
- self.image.save(filename)
-
-
-class WaveformJoyDiv(Processor):
- implements(IGrapher)
-
- FFT_SIZE = 0x400
-
- @interfacedoc
- def __init__(self, width=1024, height=256, bg_color=(136,136,136), color_scheme='default'):
- self.width = width
- self.height = height
- self.bg_color = bg_color
- self.color_scheme = color_scheme
- self.graph = None
- self.ndiv = 4
- self.symetry = False
-
- @staticmethod
- @interfacedoc
- def id():
- return "waveform_joydiv"
-
- @staticmethod
- @interfacedoc
- def name():
- return "Waveform JoyDiv"
-
- @interfacedoc
- def set_colors(self, background, scheme):
- self.bg_color = background
- self.color_scheme = scheme
-
- @interfacedoc
- def setup(self, channels=None, samplerate=None, nframes=None):
- super(WaveformJoyDiv, self).setup(channels, samplerate, nframes)
- if self.graph:
- self.graph = None
- self.graph = WaveformImageJoyContour(self.width, self.height, self.nframes(), self.samplerate(), self.FFT_SIZE,
- bg_color=self.bg_color, color_scheme=self.color_scheme, ndiv=self.ndiv, symetry=self.symetry)
-
- @interfacedoc
- def process(self, frames, eod=False):
- self.graph.process(frames, eod)
- return frames, eod
-
- @interfacedoc
- def render(self, output):
- if output:
- self.graph.save(output)
- return self.graph.image
projects / timeside.git / commitdiff