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actlib_dataflow_neuro
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plotting in ex bugs

This commit is contained in:
alexmadison 2022-02-28 15:44:24 +01:00
parent e21e132d8b
commit 94109bb157
1 changed files with 7 additions and 1 deletions
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8
test/prsim_plot.py
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@ -117,6 +117,7 @@ Use -exclude='regex' to specify signals to exclude (or -ex).""")
''' '''
Since times are random, need to convert them to an index. Since times are random, need to convert them to an index.
''' '''
if not (int(time) in unique_times): return None
out = np.argwhere(unique_times == int(time)) out = np.argwhere(unique_times == int(time))
return out[0][0] return out[0][0]
@ -125,6 +126,7 @@ Use -exclude='regex' to specify signals to exclude (or -ex).""")
Handles signal name ordering. Handles signal name ordering.
Assume ordered like unique_sigs for now Assume ordered like unique_sigs for now
''' '''
if not (sig in unique_sigs): return None
out = np.argwhere(unique_sigs == sig) out = np.argwhere(unique_sigs == sig)
return out[0][0] return out[0][0]
@ -205,14 +207,18 @@ Use -exclude='regex' to specify signals to exclude (or -ex).""")
for a in asserts: for a in asserts:
print(a) print(a)
time = int(a[0]) time = int(a[0])
if not time in unique_times:
time = unique_times[np.argwhere((unique_times-time) < 0)[-1]]
index = time_to_index(time) index = time_to_index(time)
ax.axvline(index+0.5, c = "red", lw = 2) ax.axvline(index+0.5, c = "red", lw = 2)
ax.text(index+0.5, -1, a[1], rotation = 90, ha = "center", va = "bottom", c = "red") ax.text(index+0.5, -1, a[1], rotation = 90, ha = "center", va = "bottom", c = "red")
# Find echoed statements of the form "[digits] text" # Find echoed statements of the form "[digits] text"
echoes = re.findall(r"\t *(\d+) [^\t]*\n(\[\d+\].+)", f) echoes = re.findall(r"\t *(\d+) [^\t]*\n(\[\d*\].+)", f)
for a in echoes: for a in echoes:
time = int(a[0]) time = int(a[0])
if not time in unique_times:
time = unique_times[np.argwhere((unique_times-time) < 0)[-1]]
index = time_to_index(time) index = time_to_index(time)
c = "xkcd:bright purple" c = "xkcd:bright purple"
ax.axvline(index+0.5, c = c, lw = 2) ax.axvline(index+0.5, c = c, lw = 2)