New simple_charts utility

Signed-off-by: colramos-amd <colramos@amd.com>

src/omniperf_analyze/utils/simple_charts.py

@@ -0,0 +1,119 @@
+##############################################################################bl
+# MIT License
+#
+# Copyright (c) 2021 - 2023 Advanced Micro Devices, Inc. All Rights Reserved.
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in all
+# copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+# SOFTWARE.
+##############################################################################el
+
+import plotly.express as px
+import pandas as pd
+
+
+# Notes:
+#   This file includes implementation of a few simple but common charts in CLI.
+#   We try to auto-size the layout to cover most of the cases as default. If it
+#   doesn't work, apply style config in yaml for each dashboard.
+
+
+def simple_bar(df, title: str = None, id=None, style: dict = None, orientation="h"):
+    """
+    Plot data with simple bar chart
+    """
+
+    # TODO: handle None properly
+    if "Metric" in df.columns and ("Count" in df.columns or "Value" in df.columns):
+        detected_label = "Count" if "Count" in df.columns else "Value"
+        df[detected_label] = [
+            x.astype(int) if x != "" else int(0) for x in df[detected_label]
+        ]
+    else:
+        raise NameError("simple_bar: No Metric or Count in df columns!")
+
+    # Assign figure characteristics
+    range_color = style.get("range_color", None)
+    label_txt = style.get("label_txt", None)
+    xrange = style.get("xrange", None)
+    if label_txt is not None:
+        label_txt = label_txt.strip("()")
+        try:
+            label_txt = label_txt.replace("+ $normUnit", df["Unit"][0])
+        except KeyError:
+            print("No units found in df. Auto labeling.")
+
+    # Overrides for figure chatacteristics
+    if id == 1701.1:
+        label_txt = "%"
+        range_color = [0, 100]
+        xrange = [0, 110]
+    if id == 1701.2:
+        label_txt = "Gb/s"
+        range_color = [0, 1638]
+        xrange = [0, 1638]
+
+    fig = px.bar(
+        df,
+        title=title,
+        x=detected_label,
+        y="Metric",
+        color=detected_label,
+        range_color=range_color,
+        labels={detected_label: label_txt},
+        orientation=orientation,
+    ).update_xaxes(range=xrange)
+
+    return fig
+
+
+def simple_multi_bar(df, title=None, id=None):
+    """
+    Plot data with simple multiple bar chart
+    """
+
+    # TODO: handle Nan and None properly
+    if "Metric" in df.columns and "Avg" in df.columns:
+        df["Avg"] = [x.astype(int) if x != "" else int(0) for x in df["Avg"]]
+    else:
+        raise NameError("simple_multi_bar: No Metric or Count in df columns!")
+
+    dfigs = []
+    nested_bar = {}
+    df_unit = df["Unit"][0]
+    if id == 1604:
+        nested_bar = {"NC": {}, "UC": {}, "RW": {}, "CC": {}}
+        for index, row in df.iterrows():
+            nested_bar[row["Coherency"]][row["Xfer"]] = row["Avg"]
+    if id == 1704:
+        nested_bar = {"Read": {}, "Write": {}}
+        for index, row in df.iterrows():
+            nested_bar[row["Transaction"]][row["Type"]] = row["Avg"]
+
+    for group, metric in nested_bar.items():
+        dfigs.append(
+            px.bar(
+                title=group,
+                x=metric.values(),
+                y=metric.keys(),
+                labels={"x": df_unit, "y": ""},
+                text=metric.values(),
+            )
+            .update_xaxes(showgrid=False, rangemode="nonnegative")
+            .update_yaxes(showgrid=False)
+        )
+    return dfigs