Add sound reactive ear code

Sound_Reactive_Ears/code.py

@@ -0,0 +1,111 @@
+"""
+Circuit Playground Express sounds activated ears.
+
+Adafruit invests time and resources providing this open source code.
+Please support Adafruit and open source hardware by purchasing
+products from Adafruit!
+
+Written by Dave Astels for Adafruit Industries
+Copyright (c) 2018 Adafruit Industries
+Licensed under the MIT license.
+
+All text above must be included in any redistribution.
+"""
+
+import time
+import math
+import array
+import board
+import audiobusio
+import simpleio
+from adafruit_circuitplayground.express import cpx
+
+# Exponential scaling factor.
+# Should probably be in range -10 .. 10 to be reasonable.
+CURVE = 2
+SCALE_EXPONENT = math.pow(10, CURVE * -0.1)
+
+# Number of samples to read at once.
+NUM_SAMPLES = 90
+
+# the trigger threshhold
+THRESHOLD = 6
+
+left_ear = simpleio.Servo(board.A1)
+right_ear = simpleio.Servo(board.A2)
+
+cpx.pixels.fill((0, 0, 0))
+left_ear.angle = 0
+right_ear.angle = 0
+
+# Restrict value to be between floor and ceiling.
+
+def constrain(value, floor, ceiling):
+    return max(floor, min(value, ceiling))
+
+
+def log_scale(input_value, input_min, input_max, output_min, output_max):
+    normalized_input_value = (input_value - input_min) / \
+                             (input_max - input_min)
+    return output_min + \
+        math.pow(normalized_input_value, SCALE_EXPONENT) \
+        * (output_max - output_min)
+
+
+# Remove DC bias before computing RMS.
+
+def normalized_rms(values):
+    minbuf = int(mean(values))
+    samples_sum = sum(
+        float(sample - minbuf) * (sample - minbuf)
+        for sample in values
+    )
+
+    return math.sqrt(samples_sum / len(values))
+
+
+def mean(values):
+    return sum(values) / len(values)
+
+
+mic = audiobusio.PDMIn(board.MICROPHONE_CLOCK, board.MICROPHONE_DATA,
+                       sample_rate=16000, bit_depth=16)
+
+
+# Record an initial sample to calibrate. Assume it's quiet when we start.
+samples = array.array('H', [0] * NUM_SAMPLES)
+mic.record(samples, len(samples))
+# Set lowest level to expect, plus a little.
+input_floor = normalized_rms(samples) + 10
+
+# Corresponds to sensitivity: lower means ears perk up at lower volumes
+# Adjust this as you see fit.
+input_ceiling = input_floor + 750
+
+ears_up = False
+
+while True:
+    samples_read = mic.record(samples, len(samples))
+    if samples_read < NUM_SAMPLES:
+        print("MISSING SAMPLES, only: {0}".format(samples_read))
+    magnitude = normalized_rms(samples)
+    # You might want to print this to see the values.
+    # print(magnitude)
+
+    # Compute scaled logarithmic reading in the range 0 to 10
+    c = log_scale(constrain(magnitude, input_floor, input_ceiling),
+                  input_floor, input_ceiling, 0, 10)
+
+
+    if c >= THRESHOLD and not ears_up:
+        ears_up = True
+        left_ear.angle = 90
+        right_ear.angle = 90
+        time.sleep(1.0)
+    elif c < THRESHOLD and ears_up:
+        ears_up = False
+        left_ear.angle = 0
+        right_ear.angle = 0
+        time.sleep(1.0)
+    else:
+        time.sleep(0.1)