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authorViliam Luc <vluc@cisco.com>2022-01-19 15:29:23 +0100
committerViliam Luc <vluc@cisco.com>2022-01-19 16:20:38 +0100
commit3a443e358985f9d90e0ce1a5e9295a28349f26de (patch)
treebecb492218e6177e2caab951cfb469e5d5e18d89 /resources
parent9744be3170135285c6d7017134e5ae70e75d9afb (diff)
trending: fix empty regressions and progressions
Signed-off-by: Viliam Luc <vluc@cisco.com> Change-Id: I1405c5d1dbf9e137afbc5fd5d9f83ea572613ea9
Diffstat (limited to 'resources')
-rw-r--r--resources/tools/presentation/generator_cpta.py10
1 files changed, 5 insertions, 5 deletions
diff --git a/resources/tools/presentation/generator_cpta.py b/resources/tools/presentation/generator_cpta.py
index fafa8638a4..b4ff42e4e4 100644
--- a/resources/tools/presentation/generator_cpta.py
+++ b/resources/tools/presentation/generator_cpta.py
@@ -883,8 +883,8 @@ def _generate_all_charts(spec, input_data):
if tb in file and u"performance-trending-dashboard" in \
file and u"txt" in file:
file_to_read = f"{spec.cpta[u'output-file']}/{file}"
- with open(f"{file_to_read}", u"rt") as input:
- data = data + input.readlines()
+ with open(f"{file_to_read}", u"rt") as f_in:
+ data = data + f_in.readlines()
for test_name, classification in job_data.items():
if classification != u"normal":
@@ -896,7 +896,7 @@ def _generate_all_charts(spec, input_data):
test_name = test_name.split("-", 1)
tst = test_name[1].split(".")[-1]
nic = test_name[0].split(".")[-1]
- frmsize = tst.split("-")[0].upper()
+ frmsize = tst.split("-")[0]
tst = u"-".join(tst.split("-")[1:])
tst_name = f"{nic}-{frmsize}-{tst}"
if len(tst) > max_len.tst:
@@ -943,7 +943,7 @@ def _generate_all_charts(spec, input_data):
f"{u' ' * (max_len.tst - len(test_reg_lst[idx]))} "
f"{nic_reg_lst[idx]}"
f"{u' ' * (max_len.nic - len(nic_reg_lst[idx]))} "
- f"{frmsize_reg_lst[idx]}"
+ f"{frmsize_reg_lst[idx].upper()}"
f"{u' ' * (max_len.frmsize - len(frmsize_reg_lst[idx]))} "
f"{trend_reg_lst[idx]}"
f"{u' ' * (max_len.trend - len(str(trend_reg_lst[idx])))} "
@@ -971,7 +971,7 @@ def _generate_all_charts(spec, input_data):
f"{u' ' * (max_len.tst - len(test_prog_lst[idx]))} "
f"{nic_prog_lst[idx]}"
f"{u' ' * (max_len.nic - len(nic_prog_lst[idx]))} "
- f"{frmsize_prog_lst[idx]}"
+ f"{frmsize_prog_lst[idx].upper()}"
f"{u' ' * (max_len.frmsize - len(frmsize_prog_lst[idx]))} "
f"{trend_prog_lst[idx]}"
f"{u' ' * (max_len.trend -len(str(trend_prog_lst[idx])))} "