## Rev / Oscilloscope

The given file consisted of three numpy arrays
* timestamp
* clock
* signal

The goal was to sample the signal on every rising edge of the clock signal into 0s and 1s. We can use `np.diff` to calculate derivative of the clock signal which will give us impulses on rising edge. We can use the index of those impulses to sample the message signal, apply thresholding and get the binary sequence.

#### Solve script

```python
import pickle
import numpy as np
import matplotlib.pyplot as plt

obj = pickle.load(open("./trace.pckl", "rb"))
arr1 = np.array(obj[1])
arr2 = np.array(obj[2])

#clamp valus
arr1[arr1 > 3] = 3
arr1[arr1 < 0] = 0

#clamp clock
arr2[arr2 < 0.5] = 0

lval = 13000
rval = 250000 + 13000

#derivative
arr1_d = np.diff(arr1)
arr1_d[arr1_d < 0] = 0

#sample index
samples_idx = arr1_d > 1

#filtering to remove repetitive points
filtered = [samples_idx[0]]
idxs = []
for i in range(len(arr1_d)):
if arr1_d[i] > 1 :
idxs.append(i)
for i in range(1, len(idxs)):
if idxs[i] - filtered[-1] > 50 :
filtered.append(idxs[i])

#extracting samples in arr5
arr5 = np.zeros(len(arr2)-1)
mask = np.array([False] * (len(arr2)-1))
mask[filtered] = True
arr5[(arr2[:-1] > 1) & (mask)] = 3
arr5[(arr2[:-1] < 1) & (mask)] = -1

#extracting points
mask2 = np.abs(arr5[lval: rval ]) > 0.5
points = arr5[lval : rval ][mask2]

#making bins of 9 bits
points = points[:-1].reshape(-1, 9)
points = (points > 0).astype("uint8")
bts = []
for i in points :
bts.append("".join(list(map(str, i.tolist()))))

val = []
for i in bts:
val.append(int(i[:-1], 2)) #take bits from index 0-7

print(bytes(val))
```