scripts/perf: extract SKT section to new file
PCM cpu measure give as result 1306 columns, we want check only ones which contains SKTdata and SKTtraffic values. Signed-off-by: Maciej Wawryk <maciejx.wawryk@intel.com> Change-Id: I52b6781a7ff99e0d894f7f1c2b25b655fa274eb1 Reviewed-on: https://review.spdk.io/gerrit/c/spdk/spdk/+/946 Reviewed-by: Shuhei Matsumoto <shuhei.matsumoto.xt@hitachi.com> Reviewed-by: Karol Latecki <karol.latecki@intel.com> Reviewed-by: Tomasz Zawadzki <tomasz.zawadzki@intel.com> Tested-by: SPDK CI Jenkins <sys_sgci@intel.com>
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@ -13,6 +13,7 @@ import time
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import uuid
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import uuid
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import rpc
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import rpc
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import rpc.client
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import rpc.client
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import pandas as pd
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from common import *
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from common import *
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@ -193,6 +194,11 @@ class Target(Server):
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time.sleep(self.pcm_delay)
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time.sleep(self.pcm_delay)
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subprocess.run("%s/pcm.x %s -i=%s -csv=%s/%s" % (self.pcm_dir, self.pcm_interval, self.pcm_count,
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subprocess.run("%s/pcm.x %s -i=%s -csv=%s/%s" % (self.pcm_dir, self.pcm_interval, self.pcm_count,
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results_dir, pcm_file_name), shell=True, check=True)
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results_dir, pcm_file_name), shell=True, check=True)
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df = pd.read_csv(os.path.join(results_dir, pcm_file_name), header=[0, 1])
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df = df.rename(columns=lambda x: re.sub(r'Unnamed:[\w\s]*$', '', x))
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skt = df.loc[:, df.columns.get_level_values(1).isin({'UPI0', 'UPI1', 'UPI2'})]
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skt_pcm_file_name = "_".join(["skt", pcm_file_name])
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skt.to_csv(os.path.join(results_dir, skt_pcm_file_name), index=False)
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class Initiator(Server):
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class Initiator(Server):
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