axegon

import numpy as np
import matplotlib.pyplot as plt

with open('samples.bin', 'rb') as f:
    raw_data = np.fromfile(f, dtype=np.uint8)

iq_data = raw_data.astype(np.float32) - 127.5
iq_data /= 127.5

i_data = iq_data[0::2]

axegon

SETUP

Use a virtualenv if possible.

1. Install the requirements: pip install -r requirements.txt
2. Set the two environmental variables GHTOKEN and BLEEPBLOOP:

GHTOKEN = https://github.com/settings/tokens
BLEEPBLOOP = WHATEVER_YOU_WANT,_USED_FOR_SALT

axegon

>>> import string
>>> string.letters
'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ'
>>> help(string)

>>> string.letters
'ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz'
>>> reload(string)
<module 'string' from '/usr/lib64/python2.7/string.pyc'>
>>> string.letters

axegon

axegon

import tensorflow as tf
import numpy as np
splits = [1, 4, 4, 7, 8, 8]
x = tf.RaggedTensor.from_row_splits(values=np.random.choice(20,10).tolist(), row_splits=splits)
y = tf.RaggedTensor.from_row_splits(values=np.random.choice(20,10).tolist(), row_splits=splits)
print((x+y).to_list())

axegon

import numpy as np
import tensorflow as tf
 
np.random.seed(42)
 
x = tf.constant(np.random.rand(3,3))
y = tf.constant(np.random.rand(3,3))

@tf.function
def matmul(x, y):

axegon

import numpy as np
import tensorflow as tf
 
np.random.seed(42)
 
x = tf.constant(np.random.rand(3,3))
y = tf.constant(np.random.rand(3,3))
result = tf.matmul(x, y)
tf.global_variables_initializer()