Merge branch 'master' into TheKitty-patch-118

Author: ladyada

Adafruit_Feather_Sense/feather_sense_sensor_demo.py

@@ -0,0 +1,48 @@
+"""Sensor demo for Adafruit Feather Sense. Prints data from each of the sensors."""
+import time
+import array
+import math
+import board
+import audiobusio
+import adafruit_apds9960.apds9960
+import adafruit_bmp280
+import adafruit_lis3mdl
+import adafruit_lsm6ds
+import adafruit_sht31d
+
+i2c = board.I2C()
+
+apds9960 = adafruit_apds9960.apds9960.APDS9960(i2c)
+bmp280 = adafruit_bmp280.Adafruit_BMP280_I2C(i2c)
+lis3mdl = adafruit_lis3mdl.LIS3MDL(i2c)
+lsm6ds33 = adafruit_lsm6ds.LSM6DS33(i2c)
+sht31d = adafruit_sht31d.SHT31D(i2c)
+microphone = audiobusio.PDMIn(board.MICROPHONE_CLOCK, board.MICROPHONE_DATA,
+                              sample_rate=16000, bit_depth=16)
+
+def normalized_rms(values):
+    minbuf = int(sum(values) / len(values))
+    return math.sqrt(sum(float(sample - minbuf) *
+                         (sample - minbuf) for sample in values) / len(values))
+
+apds9960.enable_proximity = True
+apds9960.enable_color = True
+bmp280.sea_level_pressure = 1013.25
+
+while True:
+    samples = array.array('H', [0] * 160)
+    microphone.record(samples, len(samples))
+
+    print("\nFeather Sense Sensor Demo")
+    print("---------------------------------------------")
+    print("Proximity:", apds9960.proximity())
+    print("Red: {}, Green: {}, Blue: {}, Clear: {}".format(*apds9960.color_data))
+    print("Temperature: {:.1f} C".format(bmp280.temperature))
+    print("Barometric pressure:", bmp280.pressure)
+    print("Altitude: {:.1f} m".format(bmp280.altitude))
+    print("Magnetic: {:.3f} {:.3f} {:.3f} uTesla".format(*lis3mdl.magnetic))
+    print("Acceleration: {:.2f} {:.2f} {:.2f} m/s^2".format(*lsm6ds33.acceleration))
+    print("Gyro: {:.2f} {:.2f} {:.2f} dps".format(*lsm6ds33.gyro))
+    print("Humidity: {:.1f} %".format(sht31d.relative_humidity))
+    print("Sound level:", normalized_rms(samples))
+    time.sleep(0.3)

ulab_Crunch_Numbers_Fast/benchmark.py

@@ -0,0 +1,40 @@
+import time
+import math
+import ulab
+import ulab.numerical
+
+def mean(values):
+    return sum(values) / len(values)
+
+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 normalized_rms_ulab(values):
+    minbuf = ulab.numerical.mean(values)
+    values = values - minbuf
+    samples_sum = ulab.numerical.sum(values * values)
+    return math.sqrt(samples_sum / len(values))
+
+
+# Instead of using sensor data, we generate some data
+# The amplitude is 5000 so the rms should be around 5000/1.414 = 3536
+nums_list = [int(8000 + math.sin(i) * 5000) for i in range(100)]
+nums_array = ulab.array(nums_list)
+
+def timeit(s, f, n=100):
+    t0 = time.monotonic_ns()
+    for _ in range(n):
+        x = f()
+    t1 = time.monotonic_ns()
+    r = (t1 - t0) * 1e-6 / n
+    print("%-20s : %8.3fms [result=%f]" % (s, r, x))
+
+print("Computing the RMS value of 100 numbers")
+timeit("traditional", lambda: normalized_rms(nums_list))
+timeit("ulab", lambda: normalized_rms_ulab(nums_array))

ulab_Crunch_Numbers_Fast/cluebarometer.py

@@ -0,0 +1,175 @@
+import time
+
+import adafruit_bmp280
+import board
+import displayio
+import ulab
+import ulab.filter
+
+# Blank the screen.  Scrolling text causes unwanted delays.
+d = displayio.Group()
+board.DISPLAY.show(d)
+
+# Sampling rate: 16Hz
+# Cutoff frequency: 0.16Hz
+# Transition bandwidth: 0.16Hz
+# Window type: Hamming
+# Filter has 311 coefficients
+taps = ulab.array([
+    -0.000050679794726066, -0.000041099278318167, -0.000031279920668665,
+    -0.000021183486597150, -0.000010770285292045, +0.000000000000000000,
+    +0.000011167446754809, +0.000022770999889941, +0.000034847558259864,
+    +0.000047431049079466, +0.000060551498686721, +0.000074234108254511,
+    +0.000088498343199344, +0.000103357045109305, +0.000118815575023601,
+    +0.000134870996840645, +0.000151511309510219, +0.000168714736477861,
+    +0.000186449080596567, +0.000204671152403140, +0.000223326279275218,
+    +0.000242347902542027, +0.000261657269119383, +0.000281163223679941,
+    +0.000300762106756334, +0.000320337763510928, +0.000339761667195315,
+    +0.000358893160569588, +0.000377579817760222, +0.000395657928211038,
+    +0.000412953103529159, +0.000429281007152519, +0.000444448205872873,
+    +0.000458253141344113, +0.000470487218795955, +0.000480936009263626,
+    +0.000489380560741255, +0.000495598812776238, +0.000499367108150093,
+    +0.000500461794444300, +0.000498660907473236, +0.000493745927786584,
+    +0.000485503600706003, +0.000473727809671115, +0.000458221492033063,
+    +0.000438798585855176, +0.000415285995764155, +0.000387525565446236,
+    +0.000355376044004699, +0.000318715033091691, +0.000277440901501588,
+    +0.000231474653767861, +0.000180761739242710, +0.000125273788160487,
+    +0.000065010261293197, +0.000000000000000000, -0.000069697336247377,
+    -0.000143989957415198, -0.000222752767634882, -0.000305826338672358,
+    -0.000393016043088374, -0.000484091357342654, -0.000578785344322494,
+    -0.000676794323931742, -0.000777777739462615, -0.000881358226495441,
+    -0.000987121890034750, -0.001094618794499868, -0.001203363670049808,
+    -0.001312836837542114, -0.001422485353209744, -0.001531724372895900,
+    -0.001639938734420840, -0.001746484755374530, -0.001850692242341569,
+    -0.001951866706278179, -0.002049291777482158, -0.002142231812333790,
+    -0.002229934682745978, -0.002311634738053158, -0.002386555927898205,
+    -0.002453915073551964, -0.002512925274028313, -0.002562799432345805,
+    -0.002602753886341418, -0.002632012127569287, -0.002649808591023194,
+    -0.002655392497711921, -0.002648031731496151, -0.002627016731069257,
+    -0.002591664377536210, -0.002541321857718479, -0.002475370483091317,
+    -0.002393229444145817, -0.002294359479963247, -0.002178266442894981,
+    -0.002044504738458277, -0.001892680620886388, -0.001722455325210333,
+    -0.001533548017297868, -0.001325738543930948, -0.001098869965763655,
+    -0.000852850856865069, -0.000587657355512251, -0.000303334951952833,
+    +0.000000000000000001, +0.000322159059450752, +0.000662880773589522,
+    +0.001021830060775982, +0.001398597909331569, +0.001792701398335994,
+    +0.002203584045179127, +0.002630616483032971, +0.003073097469789485,
+    +0.003530255228366684, +0.004001249116626688, +0.004485171623483914,
+    +0.004981050686118591, +0.005487852321559077, +0.006004483564265146,
+    +0.006529795699742466, +0.007062587782654920, +0.007601610426384373,
+    +0.008145569849526276, +0.008693132163411565, +0.009242927883419039,
+    +0.009793556645595150, +0.010343592108937170, +0.010891587022627668,
+    +0.011436078436539264, +0.011975593032464911, +0.012508652552774892,
+    +0.013033779302562583, +0.013549501700820601, +0.014054359855790191,
+    +0.014546911139352909, +0.015025735735186426, +0.015489442135386880,
+    +0.015936672560369614, +0.016366108277098043, +0.016776474791055797,
+    +0.017166546887869318, +0.017535153501103896, +0.017881182383493146,
+    +0.018203584559716979, +0.018501378539810983, +0.018773654273367416,
+    +0.019019576825867947, +0.019238389759765797, +0.019429418204303113,
+    +0.019592071599501125, +0.019725846101288819, +0.019830326636332028,
+    +0.019905188596781104, +0.019950199166862841, +0.019965218274992248,
+    +0.019950199166862841, +0.019905188596781104, +0.019830326636332028,
+    +0.019725846101288819, +0.019592071599501125, +0.019429418204303113,
+    +0.019238389759765800, +0.019019576825867947, +0.018773654273367420,
+    +0.018501378539810983, +0.018203584559716979, +0.017881182383493149,
+    +0.017535153501103892, +0.017166546887869318, +0.016776474791055797,
+    +0.016366108277098043, +0.015936672560369614, +0.015489442135386881,
+    +0.015025735735186426, +0.014546911139352912, +0.014054359855790193,
+    +0.013549501700820601, +0.013033779302562583, +0.012508652552774890,
+    +0.011975593032464912, +0.011436078436539264, +0.010891587022627668,
+    +0.010343592108937174, +0.009793556645595150, +0.009242927883419041,
+    +0.008693132163411567, +0.008145569849526276, +0.007601610426384373,
+    +0.007062587782654920, +0.006529795699742466, +0.006004483564265146,
+    +0.005487852321559078, +0.004981050686118592, +0.004485171623483914,
+    +0.004001249116626688, +0.003530255228366684, +0.003073097469789486,
+    +0.002630616483032971, +0.002203584045179127, +0.001792701398335993,
+    +0.001398597909331569, +0.001021830060775982, +0.000662880773589522,
+    +0.000322159059450752, +0.000000000000000001, -0.000303334951952833,
+    -0.000587657355512251, -0.000852850856865070, -0.001098869965763655,
+    -0.001325738543930948, -0.001533548017297868, -0.001722455325210333,
+    -0.001892680620886389, -0.002044504738458278, -0.002178266442894981,
+    -0.002294359479963247, -0.002393229444145818, -0.002475370483091317,
+    -0.002541321857718479, -0.002591664377536210, -0.002627016731069256,
+    -0.002648031731496151, -0.002655392497711923, -0.002649808591023195,
+    -0.002632012127569288, -0.002602753886341418, -0.002562799432345805,
+    -0.002512925274028314, -0.002453915073551965, -0.002386555927898205,
+    -0.002311634738053157, -0.002229934682745978, -0.002142231812333790,
+    -0.002049291777482159, -0.001951866706278179, -0.001850692242341569,
+    -0.001746484755374531, -0.001639938734420841, -0.001531724372895900,
+    -0.001422485353209745, -0.001312836837542114, -0.001203363670049807,
+    -0.001094618794499867, -0.000987121890034750, -0.000881358226495441,
+    -0.000777777739462615, -0.000676794323931742, -0.000578785344322494,
+    -0.000484091357342654, -0.000393016043088375, -0.000305826338672358,
+    -0.000222752767634882, -0.000143989957415198, -0.000069697336247377,
+    +0.000000000000000000, +0.000065010261293198, +0.000125273788160487,
+    +0.000180761739242710, +0.000231474653767861, +0.000277440901501588,
+    +0.000318715033091691, +0.000355376044004699, +0.000387525565446236,
+    +0.000415285995764155, +0.000438798585855176, +0.000458221492033064,
+    +0.000473727809671115, +0.000485503600706004, +0.000493745927786584,
+    +0.000498660907473236, +0.000500461794444300, +0.000499367108150093,
+    +0.000495598812776237, +0.000489380560741255, +0.000480936009263626,
+    +0.000470487218795956, +0.000458253141344114, +0.000444448205872873,
+    +0.000429281007152519, +0.000412953103529159, +0.000395657928211038,
+    +0.000377579817760223, +0.000358893160569588, +0.000339761667195315,
+    +0.000320337763510927, +0.000300762106756335, +0.000281163223679941,
+    +0.000261657269119383, +0.000242347902542027, +0.000223326279275218,
+    +0.000204671152403140, +0.000186449080596567, +0.000168714736477861,
+    +0.000151511309510219, +0.000134870996840645, +0.000118815575023601,
+    +0.000103357045109305, +0.000088498343199344, +0.000074234108254511,
+    +0.000060551498686721, +0.000047431049079466, +0.000034847558259864,
+    +0.000022770999889941, +0.000011167446754809, +0.000000000000000000,
+    -0.000010770285292045, -0.000021183486597150, -0.000031279920668665,
+    -0.000041099278318167, -0.000050679794726066,
+])
+
+# How often we are going to poll the sensor (If you change this, you need
+# to change the filter above and the integration time below)
+dt = 62500000 # 16Hz, 62.5ms
+
+# Wait until after deadline_ns has passed
+def sleep_deadline(deadline_ns):
+    while time.monotonic_ns() < deadline_ns:
+        pass
+
+
+# Initialize our sensor
+i2c = board.I2C()
+sensor = adafruit_bmp280.Adafruit_BMP280_I2C(i2c)
+sensor.standby_period = adafruit_bmp280.STANDBY_TC_1000
+# Disable in-sensor filtering, because we want to show how it's done in
+# CircuitPython
+sensor.iir_filter = adafruit_bmp280.IIR_FILTER_DISABLE
+sensor.overscan_pressure = adafruit_bmp280.OVERSCAN_X1
+
+# And our data structures
+# The most recent data samples, equal in number to the filter taps
+data = ulab.zeros(len(taps))
+t0 = deadline = time.monotonic_ns()
+n = 0
+# Take an initial reading to subtract off later, so that the graph in mu
+# accentuates the small short term changes in pressure rather than the large
+# DC offset of around 980
+offset = sensor.pressure
+
+while True:
+    deadline += dt
+    sleep_deadline(deadline)
+    # Move the trace near the origin so small differences can be seen in the mu
+    # plot window .. you wouldn't do this subtraction step if you are really
+    # interested in absolute barometric pressure.
+    value = sensor.pressure - offset
+    if n == 0:
+        # The first time, fill the filter with the initial value
+        data = data + value
+    else:
+        # Otherwise, add it as the next sample
+        ulab.numerical.roll(data, 1)
+        data[-1] = value
+    filtered = ulab.numerical.sum(data * taps)
+    # Actually print every 10th value.  This prints about 1.6 values per
+    # second.  You can print values more quickly by removing the 'if' and
+    # making the print unconditional, or change the frequency of prints up
+    # or down by changing the number '10'.
+    if n % 10 == 0:
+        print((filtered, value))
+    n += 1