Noise library and examples for basic FFT and frequency binning
authorPhil Howard <phil@gadgetoid.com>
Tue, 17 Sep 2019 10:45:48 +0000 (11:45 +0100)
committerPhil Howard <phil@gadgetoid.com>
Tue, 17 Sep 2019 10:45:48 +0000 (11:45 +0100)
examples/noise-amps-at-freqs.py [new file with mode: 0644]
examples/noise-profile.py [new file with mode: 0644]
library/enviroplus/noise.py

diff --git a/examples/noise-amps-at-freqs.py b/examples/noise-amps-at-freqs.py
new file mode 100644 (file)
index 0000000..0a8040b
--- /dev/null
@@ -0,0 +1,41 @@
+import ST7735
+from PIL import Image, ImageDraw
+from enviroplus.noise import Noise
+
+SAMPLERATE = 16000
+
+FREQ_LOW = 100.0
+FREQ_HIGH = 2000.0
+WIDTH = 100
+
+noise = Noise()
+
+disp = ST7735.ST7735(
+        port=0,
+        cs=ST7735.BG_SPI_CS_FRONT,
+        dc=9,
+        backlight=12,
+        rotation=90)
+
+disp.begin()
+
+img = Image.new('RGB', (disp.width, disp.height), color=(0, 0, 0))
+draw = ImageDraw.Draw(img)
+
+
+while True:
+    amps = noise.get_amplitudes_at_frequency_ranges([
+        (100,200),
+        (500,600),
+        (1000,1200)
+    ])
+    amps = [n * 32 for n in amps]
+    img2 = img.copy()
+    draw.rectangle((0, 0, disp.width, disp.height), (0, 0, 0))
+    img.paste(img2, (1, 0))
+    draw.line((0, 0, 0, amps[0]), fill=(0, 0, 255))
+    draw.line((0, 0, 0, amps[1]), fill=(0, 255, 0))
+    draw.line((0, 0, 0, amps[2]), fill=(255, 0, 0))
+
+    disp.display(img)
+
diff --git a/examples/noise-profile.py b/examples/noise-profile.py
new file mode 100644 (file)
index 0000000..70aa6ab
--- /dev/null
@@ -0,0 +1,39 @@
+import ST7735
+from PIL import Image, ImageDraw
+from enviroplus.noise import Noise
+
+SAMPLERATE = 16000
+
+FREQ_LOW = 100.0
+FREQ_HIGH = 2000.0
+WIDTH = 100
+
+noise = Noise()
+
+disp = ST7735.ST7735(
+        port=0,
+        cs=ST7735.BG_SPI_CS_FRONT,
+        dc=9,
+        backlight=12,
+        rotation=90)
+
+disp.begin()
+
+img = Image.new('RGB', (disp.width, disp.height), color=(0, 0, 0))
+draw = ImageDraw.Draw(img)
+
+
+while True:
+    low, mid, high, amp = noise.measure()
+    low *= 128
+    mid *= 128
+    high *= 128
+    amp *= 64
+
+    img2 = img.copy()
+    draw.rectangle((0, 0, disp.width, disp.height), (0, 0, 0))
+    img.paste(img2, (1, 0))
+    draw.line((0, 0, 0, amp), fill=(int(low), int(mid), int(high)))
+
+    disp.display(img)
+
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..57e869d89ef91b66315bbc55d0d6d9b56e82f8c5 100644 (file)
@@ -0,0 +1,66 @@
+import sounddevice
+import numpy
+import math
+
+class Noise():
+    def __init__(
+        self,
+        sample_rate=16000,
+        duration=0.5):
+
+        self.duration = duration
+        self.sample_rate = sample_rate
+
+    def get_amplitudes_at_frequency_ranges(self, ranges):
+        recording = self._record()
+        magnitude = numpy.abs(numpy.fft.rfft(recording[:, 0], n=self.sample_rate))
+        result = []
+        for r in ranges:
+            start, end = r
+            result.append(numpy.mean(magnitude[start:end]))
+        return result
+
+    def get_amplitude_at_frequency_range(self, start, end):
+        n = self.sample_rate // 2
+        if start > n or end > n:
+            raise ValueError("Maxmimum frequency is {}".format(n))
+
+        recording = self._record()
+        magnitude = numpy.abs(numpy.fft.rfft(recording[:, 0], n=self.sample_rate))
+        return numpy.mean(magnitude[start:end])
+
+    def get_noise_profile(
+        self,
+        noise_floor=100,
+        low=0.12,
+        mid=0.36,
+        high=None):
+
+        if high is None:
+            high = 1.0 - low - mid
+
+        recording = self._record()
+        magnitude = numpy.abs(numpy.fft.rfft(recording[:, 0], n=self.sample_rate))
+
+        sample_count = (self.sample_rate // 2) - noise_floor
+
+        mid_start = noise_floor + int(sample_count * low)
+        high_start = mid_start + int(sample_count * mid)
+        noise_ceiling = high_start + int(sample_count * high)
+
+        amp_low = numpy.mean(magnitude[self.noise_floor:mid_start])
+        amp_mid = numpy.mean(magnitude[mid_start:high_start])
+        amp_high = numpy.mean(magnitude[high_start:noise_ceiling])
+        amp_total = (low + mid + high) / 3.0
+
+        return amp_low, amp_mid, amp_high, amp_total
+
+    def _record(self):
+        return sounddevice.rec(
+            int(self.duration * self.sample_rate),
+            samplerate=self.sample_rate,
+            blocking=True,
+            channels=1,
+            dtype='float64'
+        )
+