Add a sample notebook. Refactor regression out.

xlap.yml

@@ -112,10 +112,6 @@ durations:
         Start: PrrtSendEnd
         Stop: LinkTransmitStart
         Source: sender
-    Encoding:
-        Start: PrrtEncodeStart
-        Stop: PrrtEncodeEnd
-        Source: sender
 
     ReceiverIPC:
         Start: PrrtReturnPackage

xlap/analyse/__init__.py

 import math
-import numpy as np
+
 import matplotlib.pyplot as plt
 
 plt.rcParams["figure.figsize"] = (16, 9)
@@ -10,54 +10,21 @@ plt.rcParams.update({'figure.autolayout': True})
 
 
 
-def trace(df, title, export=False):
-    fig, ax = plt.subplots(figsize=(8, 4.5))
-    plt.grid()
-
-    base = df["PrrtSendStart_T"]
-
-    sender_color = "#AAAAAA"
-    receiver_color = "#888888"
-
-    series = np.transpose(np.array([
-        ["PrrtSendStart_T", "PrrtDeliver_T", "black", "EndToEnd"],
-        ["PrrtSendStart_T", "LinkTransmitEnd_T", sender_color, "SenderTotal"],
-        ["PrrtSendStart_T", "PrrtSendEnd_T", sender_color, "Send"],
-        ["PrrtSendStart_T", "PrrtSubmitPackage_T", sender_color, "Submit"],
-        ["PrrtSubmitPackage_T", "PrrtTransmitStart_T", sender_color, "SenderIPC"],
-        ["PrrtSubmitPackage_T", "PrrtSendEnd_T", sender_color, "Enqueue"],
-        ["PrrtSendEnd_T", "LinkTransmitStart_T", sender_color, "SenderEnqueued"],
-        ["PrrtTransmitStart_T", "PrrtTransmitEnd_T", sender_color, "PrrtTransmit"],
-        ["LinkTransmitStart_T", "LinkTransmitEnd_T", sender_color, "LinkTransmit"],
-        ["LinkReceive_T", "PrrtDeliver_T", receiver_color, "ReceiverTotal"],
-        # ["DecodeStart_T", "DecodeEnd_T", receiver_color, "Decoding"],
-        ["HandlePacketStart_T", "HandlePacketEnd_T", receiver_color, "HandlePacket"],
-        ["PrrtReturnPackage_T", "PrrtReceivePackage_T", receiver_color, "ReceiverIPC"],
-        ["SendFeedbackStart_T", "SendFeedbackEnd_T", receiver_color, "Feedback"],
-    ]))
-    n = series.shape[1]
-    starts = df[series[0]] - base
-    ends = df[series[1]] - base
-    plt.hlines(range(n), starts, ends, series[2], linewidths=[5])
-    plt.xlabel("Time [us]")
-    fig.canvas.draw()
-
-    ax.set_yticklabels(series[3])
-    ax.yaxis.set_ticks(np.arange(0, n, 1))
-
-    if export:
-        plt.savefig(title)
-    plt.show()
-
-
-def box(df_data, export=False, title=None):
-    ax = df_data.plot.box(vert=False, grid=True)
+def box(data_frame, export=False, file_name=None):
+    """
+    Display a boxplot for the durations contained in data_frame.
+    :param data_frame:
+    :param export:
+    :param file_name:
+    :return:
+    """
+    ax = data_frame.plot.box(vert=False, grid=True)
     fig = ax.get_figure()
     ax.set_yticklabels(list(map(lambda x: x.get_text().replace("_D", ""), ax.get_yticklabels())))
     plt.xlabel("Time [us]")
     fig.set_size_inches(8, 4.5, forward=True)
-    if export and title is not None:
-        fig.savefig(title)
+    if export and file_name is not None:
+        fig.savefig(file_name)
 
 
 def describe_table(df):
@@ -87,7 +54,7 @@ def correlation(df_data, title="Correlation.pdf"):
 
     i = 0
     for column in columns:
-        ax = df_data.plot.scatter(ax=axes[i // cols, i % cols], y="EndToEndTime", x=column, grid=True, marker="+",
+        ax = df_data.plot.scatter(ax=axes[i // cols, i % cols], y="EndToEnd_D", x=column, grid=True, marker="+",
                                   color="black")
         ax.set_ylabel("EndToEnd [us]")
         ax.margins(0.1, 0.1)

xlap/analyse/common.py

@@ -18,7 +18,7 @@ def _filter(x, durations, source):
 def extract_durations(config):
     durations = config["durations"]
 
-    durations_send = [_dn(x) for x in durations if _filter(x, durations, "sender")]
-    durations_recv = [_dn(x) for x in durations if _filter(x, durations, "receiver")]
+    durations_send = [x for x in durations if _filter(x, durations, "sender")]
+    durations_recv = [x for x in durations if _filter(x, durations, "receiver")]
 
-    return ["EndToEndTime", "Sender_D"] + durations_send + ["Receiver_D"] + durations_recv
+    return ["EndToEnd", "Sender"] + durations_send + ["Receiver"] + durations_recv

xlap/analyse/jitter.py

@@ -5,9 +5,9 @@ from xlap.analyse import box
 
 
 def jitter_causes(df, durations, export=False, file_name=None):
-    stats = df["EndToEndTime"].describe()
+    stats = df["EndToEnd_D"].describe()
     threshold = get_outlier_threshold(stats)
-    outliers = df[df["EndToEndTime"] > threshold]
+    outliers = df[df["EndToEnd_D"] > threshold]
 
     reasons = [d + "_D" for d in durations.keys()]
 
@@ -33,8 +33,8 @@ def trace_jitter(data_frame, export=False, file_name=None):
     """
     Displays (and saves) a stacked boxplot of durations.
     """
-    thresh = get_outlier_threshold(data_frame["EndToEndTime"].describe())
-    df_no_outliers = data_frame[data_frame["EndToEndTime"] <= thresh]
+    thresh = get_outlier_threshold(data_frame["EndToEnd_D"].describe())
+    df_no_outliers = data_frame[data_frame["EndToEnd_D"] <= thresh]
     box(df_no_outliers, export, file_name)
     print("{} / {} are no outliers.".format(len(df_no_outliers), len(data_frame)))
     fig = plt.gcf()
@@ -45,4 +45,4 @@ def trace_jitter(data_frame, export=False, file_name=None):
 def prep(df, config):
     plt.rcParams["figure.figsize"] = (16, 9)
     plt.rcParams.update({'figure.autolayout': True})
-    return df[extract_durations(config)]
+    return df[[x + "_D" for x in extract_durations(config)]]

xlap/analyse/trace.py

+import numpy as np
+import matplotlib.pyplot as plt
+
+from xlap.analyse.common import extract_durations
+
+
+def _create_line(config):
+    tr = config["time_reference"]
+    color = {
+        "sender": "#AAAAAA",
+        "receiver": "#888888",
+        "e2e": "black"
+    }
+
+    def _creator(duration_name):
+        if duration_name == "EndToEnd":
+            return [tr["sender"]["Start"] + "_T", tr["receiver"]["Stop"] + "_T", color["e2e"], "EndToEnd"]
+        elif duration_name == "Sender":
+            return [tr["sender"]["Start"] + "_T", tr["sender"]["Stop"] + "_T", color["sender"], "Sender"]
+        elif duration_name == "Receiver":
+            return [tr["receiver"]["Start"] + "_T", tr["receiver"]["Stop"] + "_T", color["receiver"], "Receiver"]
+        else:
+            duration = config["durations"][duration_name]
+            return [duration["Start"] + "_T", duration["Stop"] + "_T", color[duration["Source"]], duration_name]
+
+    return _creator
+
+
+def trace(data_frame, config, export=False, file_name="TraceJitter.pdf"):
+    """
+
+    :param data_frame:
+    :param config:
+    :param export:
+    :param file_name:
+    :return:
+    """
+
+    fig, ax = plt.subplots(figsize=(8, 4.5))
+    plt.grid()
+
+    line_creator = _create_line(config)
+
+    durations = [line_creator(x) for x in extract_durations(config)]
+
+    series = np.transpose(np.array(durations))
+    n = series.shape[1]
+
+    # Starts and Ends
+    tr = config["time_reference"]
+    base = data_frame[tr["sender"]["Start"] + "_T"]
+    starts = data_frame[series[0]] - base
+    ends = data_frame[series[1]] - base
+
+    plt.hlines(range(n), starts, ends, series[2], linewidths=[5])
+    plt.xlabel("Time [us]")
+    fig.canvas.draw()
+
+    ax.set_yticklabels(series[3])
+    ax.yaxis.set_ticks(np.arange(0, n, 1))
+
+    if export:
+        plt.savefig(file_name)
+    plt.show()

xlap/parse.py

@@ -76,7 +76,7 @@ def evaluate(sender_file, receiver_file, config, kind=0):
         df[name + "Cycles"] = diff
         df[name + "_D"] = diff * df[duration["Source"].capitalize() + "Cycle_D"]
 
-    df["EndToEndTime"] = df["Sender_D"] + df["Receiver_D"]
+    df["EndToEnd_D"] = df["Sender_D"] + df["Receiver_D"]
 
     return df