fixing utf-8 for html and add TMA version (#38)

README.md

@@ -2,7 +2,7 @@
 
 [Quick Start](#quick-start-requires-perf-installed) | [Output](#output) | [Requirements](#requirements) | [Build from source](#build-from-source) | [Caveats](#caveats) | [How to contribute](#how-to-contribute)
 
-PerfSpect is a system performance characterization tool built on top of linux perf. It contains two parts
+PerfSpect is a system performance characterization tool built on top of linux perf. Most metrics and events come from [perfmon](https://github.com/intel/perfmon) and [TMA v4.5](https://www.intel.com/content/www/us/en/docs/vtune-profiler/cookbook/2023-1/top-down-microarchitecture-analysis-method.html). It contains two parts:
 
 perf-collect: Collects harware events
 

_version.txt

@@ -1 +1 @@
-1.2.11
+1.2.12

perf-collect.py

@@ -362,7 +362,7 @@ def validate_file(fname):
         start = time.time()
         subprocess.call(perfargs)  # nosec
         end = time.time()
-        if end - start < 5:
+        if end - start < 5.2:
             logging.warning(
                 "PerfSpect was run for less than 5 seconds, some events make be zero because they didn't get scheduled"
             )

perf-postprocess.py

@@ -584,7 +584,7 @@ def write_html(time_series_df, perf_mode, out_file_path):
         crash("Unknown application type")
 
     html = ""
-    with open(html_file, "r") as f_html:
+    with open(html_file, "r", encoding="utf-8") as f_html:
         html = f_html.read()
 
     # only show TMA if system-wide mode
@@ -618,7 +618,9 @@ def write_html(time_series_df, perf_mode, out_file_path):
         ]:
             html = html.replace(number[0], str(avg.loc[number[1], 0]))
 
-    with open(os.path.splitext(out_file_path)[0] + ".html", "w") as file:
+    with open(
+        os.path.splitext(out_file_path)[0] + ".html", "w", encoding="utf-8"
+    ) as file:
         file.write(html)
 
 
@@ -657,7 +659,7 @@ def generate_metrics(
     group_to_start_end_indexes = {}
     for time_slice, item in time_slice_groups:
         time_slice_float = float(time_slice)
-        if time_slice_float - prev_time_slice < 5:
+        if time_slice_float - prev_time_slice < 4.5:
             logging.warning("throwing out last sample because it was too short")
             continue
         time_slice_df = time_slice_groups.get_group(time_slice).copy()