I'm trying to use the TVLA assessment provided by Chipwhisperer on my FPGA board. (Clone of the repo tagged as 5.1.3) They provide the PA_TVLA_1-Performing_TVLA_Testing_for_Crypto_Validation.ipynb Jupyterplaybook for that. I modified it to initialize the FPGA but the rest of the flow is identical being the capturing of the traces and analyzing them.
The code which does the analysis and errors out.
import holoviews as hv
hv.extension('bokeh')
import numpy as np
import scipy
import scipy.stats
project = cw.open_project('projects/MyProject.cwp')
fixedpy = [0xda, 0x39, 0xa3, 0xee, 0x5e, 0x6b, 0x4b, 0x0d, 0x32, 0x55, 0xbf, 0xef, 0x95, 0x60, 0x18, 0x90]
testouts = []
num_traces = len(project.traces)
num_points = len(project.waves[0])
print(num_traces, num_points)
curve = hv.Curve([])
def do_the_ttvla(project, ntraces=-1):
global curve, line
if ntraces == -1:
ntraces = int(num_traces / 2)
if ntraces * 2 > num_traces:
raise ValueError("Invalid ntraces")
for g in range(0, 2):
group = [(list(project.textins[i]) == fixedpy) for i in range(g*ntraces, g*ntraces+ntraces)]
trace = np.zeros((ntraces, num_points))
for n in range(g*ntraces, g*ntraces+ntraces):
trace[n - g*ntraces][:] = project.waves[n]
testout = welch_ttest(group, trace)
curve *= hv.Curve(testout)
testouts.extend(testout)
curve *= hv.Path([(0, -4.5), (num_points, -4.5)]).opts(color="black") * \
hv.Path([(0, 4.5), (num_points, 4.5)]).opts(color="black")
def welch_ttest(group, traces):
import warnings
# Compute Welch's t-statistic at each point in time
# Here, group[] must only contain booleans (True/False)
traces_true = traces[np.where(np.array(group))]
traces_false = traces[np.where(~np.array(group))]
if len(traces_true) == 0:
traces_true = np.array([[np.nan for _ in range(len(traces[0]))]])
if len(traces_false) == 0:
traces_false = np.array([[np.nan for _ in range(len(traces[0]))]])
with warnings.catch_warnings():
warnings.simplefilter("ignore")
ttrace = scipy.stats.ttest_ind(traces_true, traces_false, axis=0, equal_var=False)[0]
return np.nan_to_num(ttrace)
do_the_ttvla(project)
(curve).opts(height=600, width=600)
When I run this code I get the following errors:
WARNING:param.BokehRenderer: Use method 'params' via param namespace
WARNING:param.BokehRenderer:Use method 'params' via param namespace
---------------------------------------------------------------------------
RecursionError Traceback (most recent call last)
<ipython-input-14-8f71252adeef> in <module>
53 return np.nan_to_num(ttrace)
54
---> 55 do_the_ttvla(project)
56 (curve).opts(height=600, width=600)
<ipython-input-14-8f71252adeef> in do_the_ttvla(project, ntraces)
29
30 testout = welch_ttest(group, trace)
---> 31 curve *= hv.Curve(testout)
32 testouts.extend(testout)
33
~/.local/lib/python3.7/site-packages/holoviews/core/overlay.py in __mul__(self, other)
41 return NotImplemented
42
---> 43 return Overlay([self, other])
44
45
~/.local/lib/python3.7/site-packages/holoviews/core/overlay.py in __init__(self, items, group, label, **params)
141 self.__dict__['_group'] = group
142 self.__dict__['_label'] = label
--> 143 super(Overlay, self).__init__(items, **params)
144
145 def __getitem__(self, key):
~/.local/lib/python3.7/site-packages/holoviews/core/dimension.py in __init__(self, items, identifier, parent, **kwargs)
1327 if items and all(isinstance(item, Dimensioned) for item in items):
1328 items = self._process_items(items)
-> 1329 params = {p: kwargs.pop(p) for p in list(self.params().keys())+['id', 'plot_id'] if p in kwargs}
1330
1331 AttrTree.__init__(self, items, identifier, parent, **kwargs)
~/.local/lib/python3.7/site-packages/param/parameterized.py in inner(*args, **kwargs)
1328 get_logger(name=args[0].__class__.__name__).log(
1329 WARNING, 'Use method %r via param namespace ' % fn.__name__)
-> 1330 return fn(*args, **kwargs)
1331
1332 inner.__doc__= "Inspect .param.%s method for the full docstring" % fn.__name__
~/.local/lib/python3.7/site-packages/param/parameterized.py in params(cls, parameter_name)
2765 @Parameters.deprecate
2766 def params(cls,parameter_name=None):
-> 2767 return cls.param.params(parameter_name=parameter_name)
2768
2769 @classmethod
~/.local/lib/python3.7/site-packages/param/parameterized.py in params(self_, parameter_name)
1422 superclasses.
1423 """
-> 1424 pdict = self_.objects(instance='existing')
1425 if parameter_name is None:
1426 return pdict
~/.local/lib/python3.7/site-packages/param/parameterized.py in objects(self_, instance)
1511 if instance and self_.self is not None:
1512 if instance == 'existing':
-> 1513 if getattr(self_.self, 'initialized', False) and self_.self._instance__params:
1514 return dict(pdict, **self_.self._instance__params)
1515 return pdict
~/.local/lib/python3.7/site-packages/holoviews/core/tree.py in __getattr__(self, identifier)
254 sanitized = identifier
255
--> 256 if sanitized in self.children:
257 return self.__dict__[sanitized]
258
... last 1 frames repeated, from the frame below ...
~/.local/lib/python3.7/site-packages/holoviews/core/tree.py in __getattr__(self, identifier)
254 sanitized = identifier
255
--> 256 if sanitized in self.children:
257 return self.__dict__[sanitized]
258
RecursionError: maximum recursion depth exceeded in comparison
I don't really understand what is going wrong, it seems to be some kind of parameter passing, but it is in the library itself so I'm expecting that something changed?
Update:
Contents of project.traces:
[[memmap([ 0.015625 , -0.00585938, -0.00097656, 0.00878906, 0.015625 ,
-0.12402344, -0.11132812, -0.05664062, -0.00097656, -0.09863281,
-0.06640625, -0.00976562, 0.03613281, -0.08007812, -0.06542969,
-0.01660156, 0.02050781, -0.10351562, -0.08105469, -0.02734375,
0.02246094, -0.09765625, -0.07324219, -0.01855469, 0.02832031,
-0.09082031, -0.06933594, -0.01757812, 0.02832031, -0.08789062,
-0.06542969, -0.015625 , 0.02832031, -0.09179688, -0.06933594,
-0.01855469, 0.02734375, -0.09765625, -0.06933594, -0.01855469,
0.02929688, -0.09667969, -0.06933594, -0.01660156, 0.03222656,
-0.0859375 , -0.05566406, -0.01171875, 0.03417969, -0.10058594,
-0.07421875, -0.02246094, 0.02636719, 0.03125 , 0.04882812,
0.05078125, 0.04980469, 0. , -0.00488281, -0.00195312,
0.01269531, -0.00878906, 0.00097656, 0.01464844, 0.03027344,
0.00390625, 0.00683594, 0.015625 , 0.02539062, -0.01074219,
-0.00683594, 0.0078125 , 0.02246094, -0.00585938, 0. ,
0.01269531, 0.02441406, -0.00390625, -0.00195312, 0.01269531,
0.02148438, -0.00195312, 0.00292969, 0.01464844, 0.02441406,
-0.0078125 , -0.00292969, 0.00976562, 0.02050781, -0.00488281,
-0.00195312, 0.01171875, 0.02148438, -0.00878906, -0.00488281,
0.00683594, 0.02246094, -0.00097656, 0.00683594, 0.01660156,
0.02441406, -0.01171875, -0.00585938, 0.00488281, 0.02050781,
-0.00878906, 0. , 0.01074219, 0.02539062, -0.00390625,
0.00195312, 0.00976562, 0.02246094, -0.0078125 , -0.00097656,
0.00878906, 0.02050781, -0.00878906, -0.00390625, 0.00683594,
0.02148438, -0.00683594, 0. , 0.00976562, 0.02246094,
-0.01269531, -0.00488281, 0.00683594, 0.02148438])
array([218, 57, 163, 238, 94, 107, 75, 13, 50, 85, 191, 239, 149,
96, 24, 144], dtype=uint8)
array([141, 157, 50, 188, 136, 137, 251, 6, 244, 97, 191, 105, 144,
241, 195, 197], dtype=uint8)
array([ 1, 35, 69, 103, 137, 171, 205, 239, 18, 52, 86, 120, 154,
188, 222, 240], dtype=uint8) ]
[memmap([ 0.015625 , -0.01757812, -0.00878906, -0.00292969, 0.01269531,
-0.1015625 , -0.0859375 , -0.04492188, 0.00488281, -0.09570312,
-0.06347656, -0.01757812, 0.02832031, -0.10058594, -0.07910156,
-0.03125 , 0.01855469, -0.09960938, -0.07324219, -0.02441406,
0.02441406, -0.09179688, -0.06835938, -0.02246094, 0.0234375 ,
-0.10546875, -0.08300781, -0.03125 , 0.0234375 , -0.09277344,
-0.06738281, -0.015625 , 0.02636719, -0.08984375, -0.06933594,
-0.02148438, 0.02441406, -0.09375 , -0.07128906, -0.02050781,
0.02636719, -0.09863281, -0.07519531, -0.02050781, 0.02636719,
-0.08691406, -0.05957031, -0.01171875, 0.03125 , -0.09375 ,
-0.07324219, -0.02050781, 0.02539062, 0.02929688, 0.04199219,
0.04882812, 0.04589844, -0.00292969, -0.01074219, -0.00292969,
0.00878906, -0.01171875, -0.00390625, 0.01269531, 0.02539062,
0.00292969, 0.00488281, 0.01367188, 0.02148438, -0.01171875,
-0.00976562, 0.00488281, 0.02050781, -0.00976562, -0.00292969,
0.00976562, 0.02441406, -0.00488281, -0.00195312, 0.00878906,
0.02148438, -0.00390625, 0.00195312, 0.01171875, 0.02246094,
-0.01171875, -0.00390625, 0.00585938, 0.02050781, -0.01171875,
-0.00292969, 0.00878906, 0.0234375 , -0.01367188, -0.00488281,
0.00683594, 0.02148438, -0.00292969, 0.00585938, 0.01269531,
0.0234375 , -0.01464844, -0.0078125 , 0.00292969, 0.01660156,
-0.00976562, 0. , 0.01074219, 0.0234375 , -0.00488281,
-0.00097656, 0.00976562, 0.02050781, -0.0078125 , -0.00097656,
0.00878906, 0.01953125, -0.01074219, -0.00585938, 0.0078125 ,
0.02050781, -0.00585938, -0.00292969, 0.00878906, 0.02246094,
-0.01464844, -0.0078125 , 0.00488281, 0.01953125])
array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], dtype=uint8)
array([ 66, 199, 111, 134, 28, 147, 211, 45, 55, 54, 186, 57, 92,
200, 179, 128], dtype=uint8)
array([ 1, 35, 69, 103, 137, 171, 205, 239, 18, 52, 86, 120, 154,
188, 222, 240], dtype=uint8) ]
[memmap([ 0.02050781, -0.00976562, -0.00292969, 0.01074219, 0.02246094,
-0.00683594, -0.00292969, 0.00683594, 0.02148438, -0.12109375,
-0.10253906, -0.04589844, 0.01074219, -0.09472656, -0.06347656,
-0.00488281, 0.04003906, -0.07714844, -0.0625 , -0.01269531,
0.02929688, -0.09960938, -0.07519531, -0.02148438, 0.03027344,
-0.07714844, -0.05175781, -0.00585938, 0.03808594, -0.08105469,
-0.06347656, -0.01464844, 0.03125 , -0.08886719, -0.06542969,
-0.01464844, 0.03515625, -0.09277344, -0.07128906, -0.01757812,
0.03613281, -0.08691406, -0.05957031, -0.00976562, 0.03808594,
-0.07324219, -0.04394531, -0.00390625, 0.03710938, -0.09765625,
-0.07617188, -0.02148438, 0.03027344, 0.03808594, 0.0546875 ,
0.05859375, 0.05371094, 0.00683594, -0.00292969, 0.00292969,
0.01367188, -0.00488281, 0.00390625, 0.01953125, 0.03222656,
0.00878906, 0.01171875, 0.02050781, 0.02832031, -0.00488281,
-0.00097656, 0.01269531, 0.02636719, -0.00097656, 0.00390625,
0.01757812, 0.03027344, 0.00097656, 0.00292969, 0.01660156,
0.02539062, 0.00488281, 0.00488281, 0.01953125, 0.02832031,
-0.00195312, 0.00097656, 0.01367188, 0.02636719, 0. ,
0.00488281, 0.015625 , 0.02832031, -0.00488281, 0. ,
0.01367188, 0.02734375, 0.00488281, 0.01269531, 0.01855469,
0.03125 , -0.00683594, -0.00195312, 0.00878906, 0.02539062,
-0.00195312, 0.00683594, 0.01660156, 0.02929688, 0.00097656,
0.0078125 , 0.01464844, 0.02734375, -0.00390625, 0.00390625,
0.01269531, 0.02734375, -0.00488281, 0.00097656, 0.01367188,
0.02441406, 0. , 0.00390625, 0.01757812, 0.02636719,
-0.00878906, -0.00097656, 0.01171875, 0.02441406])
array([ 66, 199, 111, 134, 28, 147, 211, 45, 55, 54, 186, 57, 92,
200, 179, 128], dtype=uint8)
array([ 81, 246, 159, 240, 211, 199, 82, 114, 237, 178, 37, 123, 8,
239, 165, 187], dtype=uint8)
array([ 1, 35, 69, 103, 137, 171, 205, 239, 18, 52, 86, 120, 154,
188, 222, 240], dtype=uint8) ]
[memmap([ 0.01074219, -0.02246094, -0.01660156, -0.00195312, 0.01074219,
-0.12988281, -0.11621094, -0.05761719, -0.00097656, -0.10253906,
-0.07128906, -0.01269531, 0.03027344, -0.08886719, -0.07128906,
-0.02246094, 0.015625 , -0.11035156, -0.08691406, -0.02832031,
0.01953125, -0.10742188, -0.08007812, -0.02246094, 0.02246094,
-0.09667969, -0.07324219, -0.02246094, 0.02441406, -0.09277344,
-0.0703125 , -0.01855469, 0.0234375 , -0.09375 , -0.07421875,
-0.02246094, 0.02441406, -0.09863281, -0.07519531, -0.02050781,
0.02734375, -0.09667969, -0.07421875, -0.02148438, 0.02539062,
-0.08398438, -0.06054688, -0.01269531, 0.02832031, -0.09960938,
-0.08007812, -0.02832031, 0.02246094, 0.02929688, 0.04589844,
0.04589844, 0.04589844, -0.00195312, -0.00976562, -0.00488281,
0.00878906, -0.015625 , -0.00292969, 0.00976562, 0.02636719,
0. , 0.00585938, 0.01171875, 0.02246094, -0.01464844,
-0.00683594, 0.00195312, 0.02050781, -0.01269531, -0.00097656,
0.00976562, 0.0234375 , -0.00976562, -0.00292969, 0.00585938,
0.02050781, -0.00683594, 0.00097656, 0.00878906, 0.02246094,
-0.01367188, -0.00683594, 0.00488281, 0.01855469, -0.01074219,
-0.00390625, 0.0078125 , 0.01855469, -0.01171875, -0.00976562,
0.00488281, 0.01953125, -0.00097656, 0.00390625, 0.01367188,
0.02050781, -0.01171875, -0.00878906, 0.00292969, 0.015625 ,
-0.00878906, -0.00390625, 0.01074219, 0.02050781, -0.00488281,
-0.00390625, 0.00976562, 0.01660156, -0.00878906, -0.00390625,
0.00683594, 0.01953125, -0.01171875, -0.00683594, 0.00585938,
0.01855469, -0.00683594, -0.00292969, 0.00878906, 0.02050781,
-0.015625 , -0.01074219, 0.00390625, 0.01855469])
array([218, 57, 163, 238, 94, 107, 75, 13, 50, 85, 191, 239, 149,
96, 24, 144], dtype=uint8)
array([141, 157, 50, 188, 136, 137, 251, 6, 244, 97, 191, 105, 144,
241, 195, 197], dtype=uint8)
array([ 1, 35, 69, 103, 137, 171, 205, 239, 18, 52, 86, 120, 154,
188, 222, 240], dtype=uint8) ]
[memmap([ 0.0234375 , -0.01171875, -0.00585938, 0.00488281, 0.01953125,
-0.09765625, -0.08886719, -0.04199219, 0.01171875, -0.09277344,
-0.06640625, -0.01367188, 0.03613281, -0.07714844, -0.05957031,
-0.01367188, 0.03027344, -0.09472656, -0.07324219, -0.02246094,
0.02929688, -0.09472656, -0.0703125 , -0.01660156, 0.03417969,
-0.08886719, -0.06347656, -0.015625 , 0.03417969, -0.08105469,
-0.05859375, -0.01074219, 0.03515625, -0.0859375 , -0.06542969,
-0.01464844, 0.03320312, -0.09277344, -0.06542969, -0.01367188,
0.03417969, -0.08984375, -0.06542969, -0.01269531, 0.03417969,
-0.07421875, -0.05175781, -0.00390625, 0.03613281, -0.09179688,
-0.07226562, -0.01660156, 0.03222656, 0.0390625 , 0.05273438,
0.05957031, 0.05371094, 0.00585938, -0.00292969, 0.00488281,
0.01367188, -0.00488281, 0.00390625, 0.02050781, 0.03320312,
0.00878906, 0.00878906, 0.02050781, 0.03027344, -0.00488281,
-0.00292969, 0.01367188, 0.02636719, -0.00292969, 0.00488281,
0.01855469, 0.02929688, 0. , 0.00488281, 0.01757812,
0.02929688, 0.00195312, 0.00878906, 0.01855469, 0.02929688,
-0.00488281, 0.00292969, 0.01367188, 0.02832031, -0.00292969,
0.00390625, 0.01464844, 0.03027344, -0.00488281, 0.00195312,
0.01269531, 0.02734375, 0.00390625, 0.01269531, 0.01855469,
0.03222656, -0.00683594, -0.00097656, 0.00976562, 0.02539062,
-0.00292969, 0.00683594, 0.01855469, 0.03027344, 0.00097656,
0.0078125 , 0.01464844, 0.02636719, -0.00292969, 0.00390625,
0.01367188, 0.02636719, -0.00292969, 0. , 0.01464844,
0.02636719, 0. , 0.00488281, 0.01660156, 0.02832031,
-0.00488281, -0.00097656, 0.01367188, 0.02539062])
array([218, 57, 163, 238, 94, 107, 75, 13, 50, 85, 191, 239, 149,
96, 24, 144], dtype=uint8)
array([141, 157, 50, 188, 136, 137, 251, 6, 244, 97, 191, 105, 144,
241, 195, 197], dtype=uint8)
array([ 1, 35, 69, 103, 137, 171, 205, 239, 18, 52, 86, 120, 154,
188, 222, 240], dtype=uint8) ]
[memmap([ 0.02050781, -0.00683594, -0.00488281, 0.00878906, 0.01855469,
-0.11132812, -0.09472656, -0.04394531, 0.00976562, -0.09863281,
-0.06835938, -0.01269531, 0.03417969, -0.0859375 , -0.06542969,
-0.01855469, 0.02734375, -0.10058594, -0.07910156, -0.0234375 ,
0.02636719, -0.09277344, -0.06738281, -0.01464844, 0.03320312,
-0.08398438, -0.06347656, -0.015625 , 0.03222656, -0.07910156,
-0.05859375, -0.01269531, 0.03222656, -0.09667969, -0.07519531,
-0.02441406, 0.03027344, -0.08691406, -0.05859375, -0.01074219,
0.03613281, -0.08886719, -0.06542969, -0.015625 , 0.03027344,
-0.08007812, -0.05273438, -0.00878906, 0.03417969, -0.08300781,
-0.0625 , -0.01464844, 0.03222656, 0.03125 , 0.04785156,
0.04882812, 0.04980469, 0.00390625, -0.00390625, 0.00097656,
0.01464844, -0.00488281, 0.00292969, 0.01855469, 0.02929688,
0.00683594, 0.00976562, 0.02050781, 0.02636719, -0.0078125 ,
-0.00292969, 0.01074219, 0.02441406, -0.00390625, 0. ,
0.015625 , 0.02636719, -0.00292969, 0.00195312, 0.01464844,
0.02441406, 0.00097656, 0.00683594, 0.015625 , 0.02636719,
-0.00585938, -0.00097656, 0.00976562, 0.02441406, -0.00390625,
0.00292969, 0.01464844, 0.02636719, -0.00683594, -0.00195312,
0.01171875, 0.02441406, 0.00292969, 0.00976562, 0.01953125,
0.02832031, -0.01074219, -0.00292969, 0.0078125 , 0.0234375 ,
-0.00585938, 0.00390625, 0.01464844, 0.02734375, -0.00195312,
0.00292969, 0.01367188, 0.02246094, -0.00390625, 0.00195312,
0.01171875, 0.0234375 , -0.00878906, -0.00195312, 0.01171875,
0.02441406, -0.00292969, 0. , 0.01464844, 0.02441406,
-0.00976562, -0.00488281, 0.00976562, 0.02246094])
array([ 81, 246, 159, 240, 211, 199, 82, 114, 237, 178, 37, 123, 8,
239, 165, 187], dtype=uint8)
array([252, 90, 157, 237, 176, 228, 231, 213, 184, 124, 217, 87, 234,
82, 192, 166], dtype=uint8)
array([ 1, 35, 69, 103, 137, 171, 205, 239, 18, 52, 86, 120, 154,
188, 222, 240], dtype=uint8) ]
[memmap([ 0.01855469, -0.01269531, -0.0078125 , 0.00292969, 0.015625 ,
-0.11425781, -0.10546875, -0.04980469, 0.00488281, -0.09375 ,
-0.06835938, -0.01171875, 0.03320312, -0.07714844, -0.06542969,
-0.01757812, 0.0234375 , -0.09667969, -0.08007812, -0.02441406,
0.02441406, -0.09472656, -0.07519531, -0.02148438, 0.03027344,
-0.08691406, -0.0703125 , -0.01757812, 0.02832031, -0.07910156,
-0.06542969, -0.01464844, 0.03027344, -0.0859375 , -0.0703125 ,
-0.01953125, 0.02832031, -0.09375 , -0.0703125 , -0.01757812,
0.03222656, -0.09179688, -0.06933594, -0.01855469, 0.03222656,
-0.078125 , -0.05371094, -0.01074219, 0.03417969, -0.09472656,
-0.07617188, -0.02246094, 0.02734375, 0.03417969, 0.04980469,
0.05175781, 0.04980469, 0.00097656, -0.00488281, -0.00292969,
0.01171875, -0.00976562, 0.00097656, 0.015625 , 0.03027344,
0.00683594, 0.0078125 , 0.015625 , 0.02441406, -0.01074219,
-0.00488281, 0.00878906, 0.02050781, -0.00488281, 0. ,
0.01464844, 0.02441406, -0.00097656, 0. , 0.01269531,
0.02246094, 0. , 0.00390625, 0.015625 , 0.0234375 ,
-0.00488281, -0.00097656, 0.00976562, 0.02246094, -0.00683594,
0.00097656, 0.01269531, 0.0234375 , -0.01074219, -0.00390625,
0.00976562, 0.02246094, -0.00195312, 0.00683594, 0.015625 ,
0.02734375, -0.01269531, -0.00488281, 0.00683594, 0.02050781,
-0.0078125 , 0.00195312, 0.01269531, 0.02636719, -0.00683594,
0.00292969, 0.00976562, 0.0234375 , -0.00878906, 0. ,
0.01074219, 0.02246094, -0.01074219, -0.00390625, 0.0078125 ,
0.02148438, -0.00488281, 0.00097656, 0.01269531, 0.0234375 ,
-0.01269531, -0.0078125 , 0.0078125 , 0.02148438])
array([218, 57, 163, 238, 94, 107, 75, 13, 50, 85, 191, 239, 149,
96, 24, 144], dtype=uint8)
array([141, 157, 50, 188, 136, 137, 251, 6, 244, 97, 191, 105, 144,
241, 195, 197], dtype=uint8)
array([ 1, 35, 69, 103, 137, 171, 205, 239, 18, 52, 86, 120, 154,
188, 222, 240], dtype=uint8) ]]
Result truncated
Contents of project.waves[0] where waves is an <chipwhisperer.common.api.ProjectFormat.IndividualIterable object at 0x7fe48203b350>
[ 0.015625 -0.00585938 -0.00097656 0.00878906 0.015625 -0.12402344
-0.11132812 -0.05664062 -0.00097656 -0.09863281 -0.06640625 -0.00976562
0.03613281 -0.08007812 -0.06542969 -0.01660156 0.02050781 -0.10351562
-0.08105469 -0.02734375 0.02246094 -0.09765625 -0.07324219 -0.01855469
0.02832031 -0.09082031 -0.06933594 -0.01757812 0.02832031 -0.08789062
-0.06542969 -0.015625 0.02832031 -0.09179688 -0.06933594 -0.01855469
0.02734375 -0.09765625 -0.06933594 -0.01855469 0.02929688 -0.09667969
-0.06933594 -0.01660156 0.03222656 -0.0859375 -0.05566406 -0.01171875
0.03417969 -0.10058594 -0.07421875 -0.02246094 0.02636719 0.03125
0.04882812 0.05078125 0.04980469 0. -0.00488281 -0.00195312
0.01269531 -0.00878906 0.00097656 0.01464844 0.03027344 0.00390625
0.00683594 0.015625 0.02539062 -0.01074219 -0.00683594 0.0078125
0.02246094 -0.00585938 0. 0.01269531 0.02441406 -0.00390625
-0.00195312 0.01269531 0.02148438 -0.00195312 0.00292969 0.01464844
0.02441406 -0.0078125 -0.00292969 0.00976562 0.02050781 -0.00488281
-0.00195312 0.01171875 0.02148438 -0.00878906 -0.00488281 0.00683594
0.02246094 -0.00097656 0.00683594 0.01660156 0.02441406 -0.01171875
-0.00585938 0.00488281 0.02050781 -0.00878906 0. 0.01074219
0.02539062 -0.00390625 0.00195312 0.00976562 0.02246094 -0.0078125
-0.00097656 0.00878906 0.02050781 -0.00878906 -0.00390625 0.00683594
0.02148438 -0.00683594 0. 0.00976562 0.02246094 -0.01269531
-0.00488281 0.00683594 0.02148438]
Sample contents of project.textins[0]
[218 57 163 238 94 107 75 13 50 85 191 239 149 96 24 144]
The cw object is imported as import chipwhisperer as cw and is part of the chipwhisperer libary. It's function here is to allow for the traces that are already captured to be loaded into a set of arrays.
pip install --upgrade holoviews fixed the issue.
for the VM users facing the error, this won't work: Jupyter will crash at boot. I recommend downloading the "ChipWhisperer.Jupyter.holoviews.7z" VM on the release page (release tagged 5.5).