code formatting updates
Signed-off-by: Karl W Schulz <karl.schulz@amd.com>
[ROCm/rocprofiler-compute commit: 79b877d679]
Цей коміт міститься в:
зафіксовано
Karl W. Schulz
джерело
abdaee0a2d
коміт
4bfcf9b8a8
@@ -34,7 +34,8 @@ pd.set_option(
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"mode.chained_assignment", None
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) # ignore SettingWithCopyWarning pandas warning
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IS_DARK = True #TODO: Remove hardcoded in favor of class property
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IS_DARK = True # TODO: Remove hardcoded in favor of class property
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##################
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# HELPER FUNCTIONS
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@@ -168,31 +169,31 @@ def build_bar_chart(display_df, table_config, barchart_elements, norm_filt):
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)
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# L2 Cache per channel
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# elif table_config["id"] in barchart_elements["l2_cache_per_chan"]:
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# nested_bar = {}
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# channels = []
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# for colName, colData in display_df.items():
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# if colName == "Channel":
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# channels = list(colData.values)
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# else:
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# display_df[colName] = [
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# x.astype(float) if x != "" and x != None else float(0)
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# for x in display_df[colName]
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# ]
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# nested_bar[colName] = list(display_df[colName])
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# for group, metric in nested_bar.items():
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# d_figs.append(
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# px.bar(
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# title=group[0 : group.rfind("(")],
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# x=channels,
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# y=metric,
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# labels={
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# "x": "Channel",
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# "y": group[group.rfind("(") + 1 : len(group) - 1].replace(
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# "per", norm_filt
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# ),
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# },
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# ).update_yaxes(rangemode="nonnegative")
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# )
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# nested_bar = {}
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# channels = []
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# for colName, colData in display_df.items():
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# if colName == "Channel":
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# channels = list(colData.values)
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# else:
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# display_df[colName] = [
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# x.astype(float) if x != "" and x != None else float(0)
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# for x in display_df[colName]
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# ]
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# nested_bar[colName] = list(display_df[colName])
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# for group, metric in nested_bar.items():
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# d_figs.append(
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# px.bar(
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# title=group[0 : group.rfind("(")],
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# x=channels,
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# y=metric,
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# labels={
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# "x": "Channel",
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# "y": group[group.rfind("(") + 1 : len(group) - 1].replace(
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# "per", norm_filt
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# ),
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# },
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# ).update_yaxes(rangemode="nonnegative")
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# )
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# Speed-of-light bar chart
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elif table_config["id"] in barchart_elements["sol"]:
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@@ -376,4 +377,4 @@ def build_table_chart(
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# print("DATA: \n", display_df.to_dict('records'))
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d_figs.append(d_t)
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return d_figs
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# print(d_t.columns)
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# print(d_t.columns)
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Посилання в новій задачі
Заблокувати користувача