add histogram images from spipi

rpi_spi/code/spi_controller/pi_spi.py

 import spidev, time 
-# import numpy as np 
-# from plot_stamps import plot_stamps 
+import numpy as np 
+from plot_stamps import plot_stamps 
 
-bitrate = 10000000
+bitrate = 11000000
 
 print(f'rate {bitrate/1e6}MBit/s bit period should be {1000000000/bitrate}ns')
 
@@ -13,7 +13,7 @@ spi.mode = 0b10
 
 pck_len = 64
 stamp_count = 10000
-# stamps = np.zeros(stamp_count)
+stamps = np.zeros(stamp_count)
 
 test_pck = bytearray(pck_len)
 for b in range(len(test_pck)):
@@ -21,15 +21,14 @@ for b in range(len(test_pck)):
 
 print(test_pck)
 
-# TODO will be to finish making these plots, 
-# need to install pandas and numpy here w a venv 
-# for now I'm just going to turn the rate up until things go wrong 
 bonked = False 
+bonk_count = 0 
+
 for i in range(stamp_count):
-  if bonked:
-    break 
+  # if bonked:
+  #   break 
   ret = spi.xfer(test_pck)
-  # stamps[i] = time.perf_counter() * 1e6
+  stamps[i] = time.perf_counter() * 1e6
   start = -1 
   for j in range(len(ret)):
     if start == -1:
@@ -38,14 +37,17 @@ for i in range(stamp_count):
         continue 
     else:
       if ret[j] != j - start:
-        print(f'BONK at {i} char {j} {start} {ret[j]}')
-        print(ret)
+        # print(f'BONK at {i} char {j} {start} {ret[j]}')
+        # print(ret)
+        bonk_count += 1 
         bonked = True 
         break 
 
 spi.close() 
 
-# plot_stamps(stamps, stamp_count, pck_len)
+print(f"bonk {bonk_count} / {stamp_count}")
+
+plot_stamps(stamps, stamp_count, pck_len, bonk_count / stamp_count)
 
 # 1Mbit seems solid,
 # 2.5Mbit and we have very occasional starvation 

rpi_spi/code/spi_controller/plot_stamps.py

 import pandas as pd 
 import matplotlib.pyplot as plt 
 
-def plot_stamps(stamps, stamp_count, pck_len):
+def plot_stamps(stamps, stamp_count, pck_len, misses):
   # make df from stamps 
   df = pd.DataFrame({'timestamps': stamps})
 
@@ -17,7 +17,7 @@ def plot_stamps(stamps, stamp_count, pck_len):
   # Plotting
   fig, ax1 = plt.subplots(figsize=(11, 3))
 
-  ax1.set_xlim([50, 2000])
+  ax1.set_xlim([0, 1000])
 
   # Primary x-axis (time deltas)
   df['deltas'].plot(kind='hist', bins=50, ax=ax1)
@@ -26,6 +26,7 @@ def plot_stamps(stamps, stamp_count, pck_len):
 
   # get axis ticks to calculate equivalent bandwidths 
   x_ticks = ax1.get_xticks()
+  x_ticks = [100, 200, 300, 400, 500, 600, 700, 800, 900]
   ax1.set_xticks(x_ticks)
   bandwidths = [((pck_len * 8) * (1e6 / x)) / 1e6 for x in x_ticks]
   ticks = [] 
@@ -36,7 +37,7 @@ def plot_stamps(stamps, stamp_count, pck_len):
 
   ax1.set_xticklabels(ticks)
 
-  plt.title(f'Single-Source COBS Data Sink Deltas, pck_len={pck_len}')
+  plt.title(f'Single-Source COBS Data Sink Deltas, pck_len={pck_len}, miss={misses}')
 
   plt.tight_layout()