Report: Add vsap
[csit.git] / resources / tools / presentation / generator_plots.py
index 42f450e..8161a5a 100644 (file)
@@ -1,4 +1,4 @@
-# Copyright (c) 2020 Cisco and/or its affiliates.
+# Copyright (c) 2021 Cisco and/or its affiliates.
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at:
@@ -20,6 +20,7 @@ import logging
 
 from collections import OrderedDict
 from copy import deepcopy
+from math import log
 
 import hdrh.histogram
 import hdrh.codec
@@ -60,6 +61,10 @@ COLORS = (
 
 REGEX_NIC = re.compile(r'(\d*ge\dp\d\D*\d*[a-z]*)-')
 
+# This value depends on latency stream rate (9001 pps) and duration (5s).
+# Keep it slightly higher to ensure rounding errors to not remove tick mark.
+PERCENTILE_MAX = 99.999501
+
 
 def generate_plots(spec, data):
     """Generate all plots specified in the specification file.
@@ -76,14 +81,17 @@ def generate_plots(spec, data):
         u"plot_tsa_name": plot_tsa_name,
         u"plot_http_server_perf_box": plot_http_server_perf_box,
         u"plot_nf_heatmap": plot_nf_heatmap,
-        u"plot_hdrh_lat_by_percentile": plot_hdrh_lat_by_percentile
+        u"plot_hdrh_lat_by_percentile": plot_hdrh_lat_by_percentile,
+        u"plot_hdrh_lat_by_percentile_x_log": plot_hdrh_lat_by_percentile_x_log,
+        u"plot_mrr_box_name": plot_mrr_box_name,
+        u"plot_ndrpdr_box_name": plot_ndrpdr_box_name
     }
 
     logging.info(u"Generating the plots ...")
     for index, plot in enumerate(spec.plots):
         try:
             logging.info(f"  Plot nr {index + 1}: {plot.get(u'title', u'')}")
-            plot[u"limits"] = spec.configuration[u"limits"]
+            plot[u"limits"] = spec.environment[u"limits"]
             generator[plot[u"algorithm"]](plot, data)
             logging.info(u"  Done.")
         except NameError as err:
@@ -171,14 +179,10 @@ def plot_hdrh_lat_by_percentile(plot, input_data):
 
             for color, graph in enumerate(graphs):
                 for idx, direction in enumerate((u"direction1", u"direction2")):
-                    xaxis = [0.0, ]
-                    yaxis = [0.0, ]
-                    hovertext = [
-                        f"<b>{desc[graph]}</b><br>"
-                        f"Direction: {(u'W-E', u'E-W')[idx % 2]}<br>"
-                        f"Percentile: 0.0%<br>"
-                        f"Latency: 0.0uSec"
-                    ]
+                    previous_x = 0.0
+                    xaxis = list()
+                    yaxis = list()
+                    hovertext = list()
                     try:
                         decoded = hdrh.histogram.HdrHistogram.decode(
                             test[u"latency"][graph][direction][u"hdrh"]
@@ -191,16 +195,25 @@ def plot_hdrh_lat_by_percentile(plot, input_data):
 
                     for item in decoded.get_recorded_iterator():
                         percentile = item.percentile_level_iterated_to
-                        if percentile > 99.9:
-                            continue
+                        xaxis.append(previous_x)
+                        yaxis.append(item.value_iterated_to)
+                        hovertext.append(
+                            f"<b>{desc[graph]}</b><br>"
+                            f"Direction: {(u'W-E', u'E-W')[idx % 2]}<br>"
+                            f"Percentile: "
+                            f"{previous_x:.5f}-{percentile:.5f}%<br>"
+                            f"Latency: {item.value_iterated_to}uSec"
+                        )
                         xaxis.append(percentile)
                         yaxis.append(item.value_iterated_to)
                         hovertext.append(
                             f"<b>{desc[graph]}</b><br>"
                             f"Direction: {(u'W-E', u'E-W')[idx % 2]}<br>"
-                            f"Percentile: {percentile:.5f}%<br>"
+                            f"Percentile: "
+                            f"{previous_x:.5f}-{percentile:.5f}%<br>"
                             f"Latency: {item.value_iterated_to}uSec"
                         )
+                        previous_x = percentile
                     fig.add_trace(
                         plgo.Scatter(
                             x=xaxis,
@@ -211,7 +224,178 @@ def plot_hdrh_lat_by_percentile(plot, input_data):
                             showlegend=bool(idx),
                             line=dict(
                                 color=COLORS[color],
-                                dash=u"dash" if idx % 2 else u"solid"
+                                dash=u"solid",
+                                width=1 if idx % 2 else 2
+                            ),
+                            hovertext=hovertext,
+                            hoverinfo=u"text"
+                        )
+                    )
+
+            layout[u"title"][u"text"] = f"<b>Latency:</b> {name}"
+            fig.update_layout(layout)
+
+            # Create plot
+            file_name = f"{plot[u'output-file']}-{name_link}.html"
+            logging.info(f"    Writing file {file_name}")
+
+            try:
+                # Export Plot
+                ploff.plot(fig, show_link=False, auto_open=False,
+                           filename=file_name)
+                # Add link to the file:
+                if file_links and target_links:
+                    with open(file_links, u"a") as file_handler:
+                        file_handler.write(
+                            f"- `{name_link} "
+                            f"<{target_links}/{file_name.split(u'/')[-1]}>`_\n"
+                        )
+            except FileNotFoundError as err:
+                logging.error(
+                    f"Not possible to write the link to the file "
+                    f"{file_links}\n{err}"
+                )
+            except PlotlyError as err:
+                logging.error(f"   Finished with error: {repr(err)}")
+
+        except hdrh.codec.HdrLengthException as err:
+            logging.warning(repr(err))
+            continue
+
+        except (ValueError, KeyError) as err:
+            logging.warning(repr(err))
+            continue
+
+
+def plot_hdrh_lat_by_percentile_x_log(plot, input_data):
+    """Generate the plot(s) with algorithm: plot_hdrh_lat_by_percentile_x_log
+    specified in the specification file.
+
+    :param plot: Plot to generate.
+    :param input_data: Data to process.
+    :type plot: pandas.Series
+    :type input_data: InputData
+    """
+
+    # Transform the data
+    logging.info(
+        f"    Creating the data set for the {plot.get(u'type', u'')} "
+        f"{plot.get(u'title', u'')}."
+    )
+    if plot.get(u"include", None):
+        data = input_data.filter_tests_by_name(
+            plot,
+            params=[u"name", u"latency", u"parent", u"tags", u"type"]
+        )[0][0]
+    elif plot.get(u"filter", None):
+        data = input_data.filter_data(
+            plot,
+            params=[u"name", u"latency", u"parent", u"tags", u"type"],
+            continue_on_error=True
+        )[0][0]
+    else:
+        job = list(plot[u"data"].keys())[0]
+        build = str(plot[u"data"][job][0])
+        data = input_data.tests(job, build)
+
+    if data is None or len(data) == 0:
+        logging.error(u"No data.")
+        return
+
+    desc = {
+        u"LAT0": u"No-load.",
+        u"PDR10": u"Low-load, 10% PDR.",
+        u"PDR50": u"Mid-load, 50% PDR.",
+        u"PDR90": u"High-load, 90% PDR.",
+        u"PDR": u"Full-load, 100% PDR.",
+        u"NDR10": u"Low-load, 10% NDR.",
+        u"NDR50": u"Mid-load, 50% NDR.",
+        u"NDR90": u"High-load, 90% NDR.",
+        u"NDR": u"Full-load, 100% NDR."
+    }
+
+    graphs = [
+        u"LAT0",
+        u"PDR10",
+        u"PDR50",
+        u"PDR90"
+    ]
+
+    file_links = plot.get(u"output-file-links", None)
+    target_links = plot.get(u"target-links", None)
+
+    for test in data:
+        try:
+            if test[u"type"] not in (u"NDRPDR",):
+                logging.warning(f"Invalid test type: {test[u'type']}")
+                continue
+            name = re.sub(REGEX_NIC, u"", test[u"parent"].
+                          replace(u'-ndrpdr', u'').replace(u'2n1l-', u''))
+            try:
+                nic = re.search(REGEX_NIC, test[u"parent"]).group(1)
+            except (IndexError, AttributeError, KeyError, ValueError):
+                nic = u""
+            name_link = f"{nic}-{test[u'name']}".replace(u'-ndrpdr', u'')
+
+            logging.info(f"    Generating the graph: {name_link}")
+
+            fig = plgo.Figure()
+            layout = deepcopy(plot[u"layout"])
+
+            for color, graph in enumerate(graphs):
+                for idx, direction in enumerate((u"direction1", u"direction2")):
+                    previous_x = 0.0
+                    prev_perc = 0.0
+                    xaxis = list()
+                    yaxis = list()
+                    hovertext = list()
+                    try:
+                        decoded = hdrh.histogram.HdrHistogram.decode(
+                            test[u"latency"][graph][direction][u"hdrh"]
+                        )
+                    except (hdrh.codec.HdrLengthException, TypeError):
+                        logging.warning(
+                            f"No data for direction {(u'W-E', u'E-W')[idx % 2]}"
+                        )
+                        continue
+
+                    for item in decoded.get_recorded_iterator():
+                        # The real value is "percentile".
+                        # For 100%, we cut that down to "x_perc" to avoid
+                        # infinity.
+                        percentile = item.percentile_level_iterated_to
+                        x_perc = min(percentile, PERCENTILE_MAX)
+                        xaxis.append(previous_x)
+                        yaxis.append(item.value_iterated_to)
+                        hovertext.append(
+                            f"<b>{desc[graph]}</b><br>"
+                            f"Direction: {(u'W-E', u'E-W')[idx % 2]}<br>"
+                            f"Percentile: {prev_perc:.5f}-{percentile:.5f}%<br>"
+                            f"Latency: {item.value_iterated_to}uSec"
+                        )
+                        next_x = 100.0 / (100.0 - x_perc)
+                        xaxis.append(next_x)
+                        yaxis.append(item.value_iterated_to)
+                        hovertext.append(
+                            f"<b>{desc[graph]}</b><br>"
+                            f"Direction: {(u'W-E', u'E-W')[idx % 2]}<br>"
+                            f"Percentile: {prev_perc:.5f}-{percentile:.5f}%<br>"
+                            f"Latency: {item.value_iterated_to}uSec"
+                        )
+                        previous_x = next_x
+                        prev_perc = percentile
+                    fig.add_trace(
+                        plgo.Scatter(
+                            x=xaxis,
+                            y=yaxis,
+                            name=desc[graph],
+                            mode=u"lines",
+                            legendgroup=desc[graph],
+                            showlegend=not(bool(idx)),
+                            line=dict(
+                                color=COLORS[color],
+                                dash=u"solid",
+                                width=1 if idx % 2 else 2
                             ),
                             hovertext=hovertext,
                             hoverinfo=u"text"
@@ -219,6 +403,8 @@ def plot_hdrh_lat_by_percentile(plot, input_data):
                     )
 
             layout[u"title"][u"text"] = f"<b>Latency:</b> {name}"
+            x_max = log(100.0 / (100.0 - PERCENTILE_MAX), 10)
+            layout[u"xaxis"][u"range"] = [0, x_max]
             fig.update_layout(layout)
 
             # Create plot
@@ -275,82 +461,93 @@ def plot_nf_reconf_box_name(plot, input_data):
         logging.error(u"No data.")
         return
 
-    # Prepare the data for the plot
-    y_vals = OrderedDict()
-    loss = dict()
-    for job in data:
-        for build in job:
-            for test in build:
-                if y_vals.get(test[u"parent"], None) is None:
-                    y_vals[test[u"parent"]] = list()
-                    loss[test[u"parent"]] = list()
-                try:
-                    y_vals[test[u"parent"]].append(test[u"result"][u"time"])
-                    loss[test[u"parent"]].append(test[u"result"][u"loss"])
-                except (KeyError, TypeError):
-                    y_vals[test[u"parent"]].append(None)
-
-    # Add None to the lists with missing data
-    max_len = 0
-    nr_of_samples = list()
-    for val in y_vals.values():
-        if len(val) > max_len:
-            max_len = len(val)
-        nr_of_samples.append(len(val))
-    for val in y_vals.values():
-        if len(val) < max_len:
-            val.extend([None for _ in range(max_len - len(val))])
-
-    # Add plot traces
-    traces = list()
-    df_y = pd.DataFrame(y_vals)
-    df_y.head()
-    for i, col in enumerate(df_y.columns):
-        tst_name = re.sub(REGEX_NIC, u"",
-                          col.lower().replace(u'-ndrpdr', u'').
-                          replace(u'2n1l-', u''))
-
-        traces.append(plgo.Box(
-            x=[str(i + 1) + u'.'] * len(df_y[col]),
-            y=[y if y else None for y in df_y[col]],
-            name=(
-                f"{i + 1}. "
-                f"({nr_of_samples[i]:02d} "
-                f"run{u's' if nr_of_samples[i] > 1 else u''}, "
-                f"packets lost average: {mean(loss[col]):.1f}) "
-                f"{u'-'.join(tst_name.split(u'-')[3:-2])}"
-            ),
-            hoverinfo=u"y+name"
-        ))
-    try:
-        # Create plot
-        layout = deepcopy(plot[u"layout"])
-        layout[u"title"] = f"<b>Time Lost:</b> {layout[u'title']}"
-        layout[u"yaxis"][u"title"] = u"<b>Effective Blocked Time [s]</b>"
-        layout[u"legend"][u"font"][u"size"] = 14
-        layout[u"yaxis"].pop(u"range")
-        plpl = plgo.Figure(data=traces, layout=layout)
-
-        # Export Plot
-        file_type = plot.get(u"output-file-type", u".html")
-        logging.info(f"    Writing file {plot[u'output-file']}{file_type}.")
-        ploff.plot(
-            plpl,
-            show_link=False,
-            auto_open=False,
-            filename=f"{plot[u'output-file']}{file_type}"
-        )
-    except PlotlyError as err:
-        logging.error(
-            f"   Finished with error: {repr(err)}".replace(u"\n", u" ")
-        )
-        return
+    for core in plot.get(u"core", tuple()):
+        # Prepare the data for the plot
+        y_vals = OrderedDict()
+        loss = dict()
+        for item in plot.get(u"include", tuple()):
+            reg_ex = re.compile(str(item.format(core=core)).lower())
+            for job in data:
+                for build in job:
+                    for test_id, test in build.iteritems():
+                        if not re.match(reg_ex, str(test_id).lower()):
+                            continue
+                        if y_vals.get(test[u"parent"], None) is None:
+                            y_vals[test[u"parent"]] = list()
+                            loss[test[u"parent"]] = list()
+                        try:
+                            y_vals[test[u"parent"]].append(
+                                test[u"result"][u"time"]
+                            )
+                            loss[test[u"parent"]].append(
+                                test[u"result"][u"loss"]
+                            )
+                        except (KeyError, TypeError):
+                            y_vals[test[u"parent"]].append(None)
+
+        # Add None to the lists with missing data
+        max_len = 0
+        nr_of_samples = list()
+        for val in y_vals.values():
+            if len(val) > max_len:
+                max_len = len(val)
+            nr_of_samples.append(len(val))
+        for val in y_vals.values():
+            if len(val) < max_len:
+                val.extend([None for _ in range(max_len - len(val))])
+
+        # Add plot traces
+        traces = list()
+        df_y = pd.DataFrame(y_vals)
+        df_y.head()
+        for i, col in enumerate(df_y.columns):
+            tst_name = re.sub(
+                REGEX_NIC, u"",
+                col.lower().replace(u'-reconf', u'').replace(u'2n1l-', u'').
+                replace(u'2n-', u'').replace(u'-testpmd', u'')
+            )
+            traces.append(plgo.Box(
+                x=[str(i + 1) + u'.'] * len(df_y[col]),
+                y=df_y[col],
+                name=(
+                    f"{i + 1}. "
+                    f"({nr_of_samples[i]:02d} "
+                    f"run{u's' if nr_of_samples[i] > 1 else u''}, "
+                    f"packets lost average: {mean(loss[col]):.1f}) "
+                    f"{u'-'.join(tst_name.split(u'-')[2:])}"
+                ),
+                hoverinfo=u"y+name"
+            ))
+        try:
+            # Create plot
+            layout = deepcopy(plot[u"layout"])
+            layout[u"title"] = f"<b>Time Lost:</b> {layout[u'title']}"
+            layout[u"yaxis"][u"title"] = u"<b>Effective Blocked Time [s]</b>"
+            layout[u"legend"][u"font"][u"size"] = 14
+            layout[u"yaxis"].pop(u"range")
+            plpl = plgo.Figure(data=traces, layout=layout)
+
+            # Export Plot
+            file_name = f"{plot[u'output-file'].format(core=core)}.html"
+            logging.info(f"    Writing file {file_name}")
+            ploff.plot(
+                plpl,
+                show_link=False,
+                auto_open=False,
+                filename=file_name
+            )
+        except PlotlyError as err:
+            logging.error(
+                f"   Finished with error: {repr(err)}".replace(u"\n", u" ")
+            )
 
 
 def plot_perf_box_name(plot, input_data):
     """Generate the plot(s) with algorithm: plot_perf_box_name
     specified in the specification file.
 
+    Use only for soak and hoststack tests.
+
     :param plot: Plot to generate.
     :param input_data: Data to process.
     :type plot: pandas.Series
@@ -370,64 +567,63 @@ def plot_perf_box_name(plot, input_data):
         return
 
     # Prepare the data for the plot
-    plot_title = plot.get(u"title", u"").lower()
-
-    if u"-gbps" in plot_title:
-        value = u"gbps"
-        multiplier = 1e6
-    else:
-        value = u"throughput"
-        multiplier = 1.0
     y_vals = OrderedDict()
     test_type = u""
-    for job in data:
-        for build in job:
-            for test in build:
-                if y_vals.get(test[u"parent"], None) is None:
-                    y_vals[test[u"parent"]] = list()
-                try:
-                    if test[u"type"] in (u"NDRPDR", u"CPS"):
-                        test_type = test[u"type"]
-
-                        if u"-pdr" in plot_title:
-                            ttype = u"PDR"
-                        elif u"-ndr" in plot_title:
-                            ttype = u"NDR"
-                        else:
-                            raise RuntimeError(
-                                u"Wrong title. No information about test type. "
-                                u"Add '-ndr' or '-pdr' to the test title."
-                            )
-
-                        y_vals[test[u"parent"]].append(
-                            test[value][ttype][u"LOWER"] * multiplier
-                        )
-
-                    elif test[u"type"] in (u"SOAK", ):
-                        y_vals[test[u"parent"]].\
-                            append(test[u"throughput"][u"LOWER"])
-                        test_type = u"SOAK"
-
-                    elif test[u"type"] in (u"HOSTSTACK", ):
-                        if u"LDPRELOAD" in test[u"tags"]:
-                            y_vals[test[u"parent"]].append(
-                                float(test[u"result"][u"bits_per_second"]) / 1e3
-                            )
-                        elif u"VPPECHO" in test[u"tags"]:
-                            y_vals[test[u"parent"]].append(
-                                (float(test[u"result"][u"client"][u"tx_data"])
-                                 * 8 / 1e3) /
-                                ((float(test[u"result"][u"client"][u"time"]) +
-                                  float(test[u"result"][u"server"][u"time"])) /
-                                 2)
-                            )
-                        test_type = u"HOSTSTACK"
 
-                    else:
+    for item in plot.get(u"include", tuple()):
+        reg_ex = re.compile(str(item).lower())
+        for job in data:
+            for build in job:
+                for test_id, test in build.iteritems():
+                    if not re.match(reg_ex, str(test_id).lower()):
                         continue
+                    if y_vals.get(test[u"parent"], None) is None:
+                        y_vals[test[u"parent"]] = list()
+                    try:
+                        if test[u"type"] in (u"SOAK",):
+                            y_vals[test[u"parent"]]. \
+                                append(test[u"throughput"][u"LOWER"])
+                            test_type = u"SOAK"
+
+                        elif test[u"type"] in (u"HOSTSTACK",):
+                            if u"LDPRELOAD" in test[u"tags"]:
+                                y_vals[test[u"parent"]].append(
+                                    float(
+                                        test[u"result"][u"bits_per_second"]
+                                    ) / 1e3
+                                )
+                            elif u"VPPECHO" in test[u"tags"]:
+                                y_vals[test[u"parent"]].append(
+                                    (float(
+                                        test[u"result"][u"client"][u"tx_data"]
+                                    ) * 8 / 1e3) /
+                                    ((float(
+                                        test[u"result"][u"client"][u"time"]
+                                    ) +
+                                      float(
+                                          test[u"result"][u"server"][u"time"])
+                                      ) / 2)
+                                )
+                            test_type = u"HOSTSTACK"
+
+                        elif test[u"type"] in (u"LDP_NGINX",):
+                            if u"TCP_CPS" in test[u"tags"]:
+                                test_type = u"VSAP_CPS"
+                                y_vals[test[u"parent"]].append(
+                                    test[u"result"][u"cps"] / 1e6
+                                )
+                            elif u"TCP_RPS" in test[u"tags"]:
+                                test_type = u"VSAP_RPS"
+                                y_vals[test[u"parent"]].append(
+                                    test[u"result"][u"rps"] / 1e6
+                                )
+                            else:
+                                continue
+                        else:
+                            continue
 
-                except (KeyError, TypeError):
-                    y_vals[test[u"parent"]].append(None)
+                    except (KeyError, TypeError):
+                        y_vals[test[u"parent"]].append(None)
 
     # Add None to the lists with missing data
     max_len = 0
@@ -477,8 +673,14 @@ def plot_perf_box_name(plot, input_data):
         # Create plot
         layout = deepcopy(plot[u"layout"])
         if layout.get(u"title", None):
-            if test_type in (u"HOSTSTACK", u"CPS"):
+            if test_type in (u"HOSTSTACK", ):
                 layout[u"title"] = f"<b>Bandwidth:</b> {layout[u'title']}"
+            elif test_type == u"VSAP_CPS":
+                layout[u"title"] = f"<b>CPS:</b> {layout[u'title']}"
+                layout[u"yaxis"][u"title"] = u"<b>Connection Rate [Mcps]</b>"
+            elif test_type == u"VSAP_RPS":
+                layout[u"title"] = f"<b>RPS:</b> {layout[u'title']}"
+                layout[u"yaxis"][u"title"] = u"<b>Connection Rate [Mrps]</b>"
             else:
                 layout[u"title"] = f"<b>Throughput:</b> {layout[u'title']}"
         if y_max:
@@ -500,9 +702,8 @@ def plot_perf_box_name(plot, input_data):
         return
 
 
-def plot_tsa_name(plot, input_data):
-    """Generate the plot(s) with algorithm:
-    plot_tsa_name
+def plot_ndrpdr_box_name(plot, input_data):
+    """Generate the plot(s) with algorithm: plot_ndrpdr_box_name
     specified in the specification file.
 
     :param plot: Plot to generate.
@@ -512,9 +713,9 @@ def plot_tsa_name(plot, input_data):
     """
 
     # Transform the data
-    plot_title = plot.get(u"title", u"")
     logging.info(
-        f"    Creating data set for the {plot.get(u'type', u'')} {plot_title}."
+        f"    Creating data set for the {plot.get(u'type', u'')} "
+        f"{plot.get(u'title', u'')}."
     )
     data = input_data.filter_tests_by_name(
         plot,
@@ -524,335 +725,556 @@ def plot_tsa_name(plot, input_data):
         logging.error(u"No data.")
         return
 
-    plot_title = plot_title.lower()
-
-    if u"-gbps" in plot_title:
+    if u"-gbps" in plot.get(u"title", u"").lower():
         value = u"gbps"
-        h_unit = u"Gbps"
         multiplier = 1e6
     else:
         value = u"throughput"
-        h_unit = u"Mpps"
         multiplier = 1.0
 
-    y_vals = OrderedDict()
-    for job in data:
-        for build in job:
-            for test in build:
-                if y_vals.get(test[u"parent"], None) is None:
-                    y_vals[test[u"parent"]] = {
-                        u"1": list(),
-                        u"2": list(),
-                        u"4": list()
-                    }
-                try:
-                    if test[u"type"] not in (u"NDRPDR",):
-                        continue
+    test_type = u""
 
-                    if u"-pdr" in plot_title:
-                        ttype = u"PDR"
-                    elif u"-ndr" in plot_title:
-                        ttype = u"NDR"
+    for ttype in plot.get(u"test-type", (u"ndr", u"pdr")):
+        for core in plot.get(u"core", tuple()):
+            # Prepare the data for the plot
+            data_x = list()
+            data_y = OrderedDict()
+            data_y_max = list()
+            idx = 1
+            for item in plot.get(u"include", tuple()):
+                reg_ex = re.compile(str(item.format(core=core)).lower())
+                for job in data:
+                    for build in job:
+                        for test_id, test in build.iteritems():
+                            if not re.match(reg_ex, str(test_id).lower()):
+                                continue
+                            if data_y.get(test[u"parent"], None) is None:
+                                data_y[test[u"parent"]] = list()
+                                test_type = test[u"type"]
+                                data_x.append(idx)
+                                idx += 1
+                            try:
+                                data_y[test[u"parent"]].append(
+                                    test[value][ttype.upper()][u"LOWER"] *
+                                    multiplier
+                                )
+                            except (KeyError, TypeError):
+                                pass
+
+            # Add plot traces
+            traces = list()
+            for idx, (key, vals) in enumerate(data_y.items()):
+                name = re.sub(
+                    REGEX_NIC, u'', key.lower().replace(u'-ndrpdr', u'').
+                    replace(u'2n1l-', u'')
+                )
+                traces.append(
+                    plgo.Box(
+                        x=[data_x[idx], ] * len(data_x),
+                        y=[y / 1e6 if y else None for y in vals],
+                        name=(
+                            f"{idx+1}."
+                            f"({len(vals):02d} "
+                            f"run"
+                            f"{u's' if len(vals) > 1 else u''}) "
+                            f"{name}"
+                        ),
+                        hoverinfo=u"y+name"
+                    )
+                )
+                try:
+                    data_y_max.append(max(vals))
+                except ValueError as err:
+                    logging.warning(f"No values to use.\n{err!r}")
+            try:
+                # Create plot
+                layout = deepcopy(plot[u"layout"])
+                if layout.get(u"title", None):
+                    layout[u"title"] = \
+                        layout[u'title'].format(core=core, test_type=ttype)
+                    if test_type in (u"CPS", ):
+                        layout[u"title"] = f"<b>CPS:</b> {layout[u'title']}"
                     else:
-                        continue
+                        layout[u"title"] = \
+                            f"<b>Throughput:</b> {layout[u'title']}"
+                if data_y_max:
+                    layout[u"yaxis"][u"range"] = [0, max(data_y_max) / 1e6 + 1]
+                plpl = plgo.Figure(data=traces, layout=layout)
 
-                    if u"1C" in test[u"tags"]:
-                        y_vals[test[u"parent"]][u"1"]. \
-                            append(test[value][ttype][u"LOWER"] * multiplier)
-                    elif u"2C" in test[u"tags"]:
-                        y_vals[test[u"parent"]][u"2"]. \
-                            append(test[value][ttype][u"LOWER"] * multiplier)
-                    elif u"4C" in test[u"tags"]:
-                        y_vals[test[u"parent"]][u"4"]. \
-                            append(test[value][ttype][u"LOWER"] * multiplier)
-                except (KeyError, TypeError):
-                    pass
+                # Export Plot
+                file_name = (
+                    f"{plot[u'output-file'].format(core=core, test_type=ttype)}"
+                    f".html"
+                )
+                logging.info(f"    Writing file {file_name}")
+                ploff.plot(
+                    plpl,
+                    show_link=False,
+                    auto_open=False,
+                    filename=file_name
+                )
+            except PlotlyError as err:
+                logging.error(
+                    f"   Finished with error: {repr(err)}".replace(u"\n", u" ")
+                )
+
+
+def plot_mrr_box_name(plot, input_data):
+    """Generate the plot(s) with algorithm: plot_mrr_box_name
+    specified in the specification file.
+
+    :param plot: Plot to generate.
+    :param input_data: Data to process.
+    :type plot: pandas.Series
+    :type input_data: InputData
+    """
 
-    if not y_vals:
-        logging.warning(f"No data for the plot {plot.get(u'title', u'')}")
+    # Transform the data
+    logging.info(
+        f"    Creating data set for the {plot.get(u'type', u'')} "
+        f"{plot.get(u'title', u'')}."
+    )
+    data = input_data.filter_tests_by_name(
+        plot,
+        params=[u"result", u"parent", u"tags", u"type"]
+    )
+    if data is None:
+        logging.error(u"No data.")
         return
 
-    y_1c_max = dict()
-    for test_name, test_vals in y_vals.items():
-        for key, test_val in test_vals.items():
-            if test_val:
-                avg_val = sum(test_val) / len(test_val)
-                y_vals[test_name][key] = [avg_val, len(test_val)]
-                ideal = avg_val / (int(key) * 1e6)
-                if test_name not in y_1c_max or ideal > y_1c_max[test_name]:
-                    y_1c_max[test_name] = ideal
-
-    vals = OrderedDict()
-    y_max = list()
-    nic_limit = 0
-    lnk_limit = 0
-    pci_limit = 0
-    for test_name, test_vals in y_vals.items():
+    for core in plot.get(u"core", tuple()):
+        # Prepare the data for the plot
+        data_x = list()
+        data_names = list()
+        data_y = list()
+        data_y_max = list()
+        idx = 1
+        for item in plot.get(u"include", tuple()):
+            reg_ex = re.compile(str(item.format(core=core)).lower())
+            for job in data:
+                for build in job:
+                    for test_id, test in build.iteritems():
+                        if not re.match(reg_ex, str(test_id).lower()):
+                            continue
+                        try:
+                            data_x.append(idx)
+                            name = re.sub(
+                                REGEX_NIC, u'', test[u'parent'].lower().
+                                replace(u'-mrr', u'').replace(u'2n1l-', u'')
+                            )
+                            data_y.append(test[u"result"][u"samples"])
+                            data_names.append(
+                                f"{idx}."
+                                f"({len(data_y[-1]):02d} "
+                                f"run{u's' if len(data_y[-1]) > 1 else u''}) "
+                                f"{name}"
+                            )
+                            data_y_max.append(max(data_y[-1]))
+                            idx += 1
+                        except (KeyError, TypeError):
+                            pass
+
+        # Add plot traces
+        traces = list()
+        for idx, x_item in enumerate(data_x):
+            traces.append(
+                plgo.Box(
+                    x=[x_item, ] * len(data_y[idx]),
+                    y=data_y[idx],
+                    name=data_names[idx],
+                    hoverinfo=u"y+name"
+                )
+            )
+
         try:
-            if test_vals[u"1"][1]:
-                name = re.sub(
-                    REGEX_NIC,
-                    u"",
-                    test_name.replace(u'-ndrpdr', u'').replace(u'2n1l-', u'')
+            # Create plot
+            layout = deepcopy(plot[u"layout"])
+            if layout.get(u"title", None):
+                layout[u"title"] = (
+                    f"<b>Throughput:</b> {layout[u'title'].format(core=core)}"
                 )
-                vals[name] = OrderedDict()
-                y_val_1 = test_vals[u"1"][0] / 1e6
-                y_val_2 = test_vals[u"2"][0] / 1e6 if test_vals[u"2"][0] \
-                    else None
-                y_val_4 = test_vals[u"4"][0] / 1e6 if test_vals[u"4"][0] \
-                    else None
-
-                vals[name][u"val"] = [y_val_1, y_val_2, y_val_4]
-                vals[name][u"rel"] = [1.0, None, None]
-                vals[name][u"ideal"] = [
-                    y_1c_max[test_name],
-                    y_1c_max[test_name] * 2,
-                    y_1c_max[test_name] * 4
-                ]
-                vals[name][u"diff"] = [
-                    (y_val_1 - y_1c_max[test_name]) * 100 / y_val_1, None, None
-                ]
-                vals[name][u"count"] = [
-                    test_vals[u"1"][1],
-                    test_vals[u"2"][1],
-                    test_vals[u"4"][1]
-                ]
+            if data_y_max:
+                layout[u"yaxis"][u"range"] = [0, max(data_y_max) + 1]
+            plpl = plgo.Figure(data=traces, layout=layout)
 
-                try:
-                    val_max = max(vals[name][u"val"])
-                except ValueError as err:
-                    logging.error(repr(err))
-                    continue
-                if val_max:
-                    y_max.append(val_max)
-
-                if y_val_2:
-                    vals[name][u"rel"][1] = round(y_val_2 / y_val_1, 2)
-                    vals[name][u"diff"][1] = \
-                        (y_val_2 - vals[name][u"ideal"][1]) * 100 / y_val_2
-                if y_val_4:
-                    vals[name][u"rel"][2] = round(y_val_4 / y_val_1, 2)
-                    vals[name][u"diff"][2] = \
-                        (y_val_4 - vals[name][u"ideal"][2]) * 100 / y_val_4
-        except IndexError as err:
-            logging.warning(f"No data for {test_name}")
-            logging.warning(repr(err))
+            # Export Plot
+            file_name = f"{plot[u'output-file'].format(core=core)}.html"
+            logging.info(f"    Writing file {file_name}")
+            ploff.plot(
+                plpl,
+                show_link=False,
+                auto_open=False,
+                filename=file_name
+            )
+        except PlotlyError as err:
+            logging.error(
+                f"   Finished with error: {repr(err)}".replace(u"\n", u" ")
+            )
 
-        # Limits:
-        if u"x520" in test_name:
-            limit = plot[u"limits"][u"nic"][u"x520"]
-        elif u"x710" in test_name:
-            limit = plot[u"limits"][u"nic"][u"x710"]
-        elif u"xxv710" in test_name:
-            limit = plot[u"limits"][u"nic"][u"xxv710"]
-        elif u"xl710" in test_name:
-            limit = plot[u"limits"][u"nic"][u"xl710"]
-        elif u"x553" in test_name:
-            limit = plot[u"limits"][u"nic"][u"x553"]
-        elif u"cx556a" in test_name:
-            limit = plot[u"limits"][u"nic"][u"cx556a"]
-        else:
-            limit = 0
-        if limit > nic_limit:
-            nic_limit = limit
-
-        mul = 2 if u"ge2p" in test_name else 1
-        if u"10ge" in test_name:
-            limit = plot[u"limits"][u"link"][u"10ge"] * mul
-        elif u"25ge" in test_name:
-            limit = plot[u"limits"][u"link"][u"25ge"] * mul
-        elif u"40ge" in test_name:
-            limit = plot[u"limits"][u"link"][u"40ge"] * mul
-        elif u"100ge" in test_name:
-            limit = plot[u"limits"][u"link"][u"100ge"] * mul
-        else:
-            limit = 0
-        if limit > lnk_limit:
-            lnk_limit = limit
-
-        if u"cx556a" in test_name:
-            limit = plot[u"limits"][u"pci"][u"pci-g3-x8"]
-        else:
-            limit = plot[u"limits"][u"pci"][u"pci-g3-x16"]
-        if limit > pci_limit:
-            pci_limit = limit
 
-    traces = list()
-    annotations = list()
-    x_vals = [1, 2, 4]
-
-    # Limits:
-    if u"-gbps" not in plot_title:
-        nic_limit /= 1e6
-        lnk_limit /= 1e6
-        pci_limit /= 1e6
-        min_limit = min((nic_limit, lnk_limit, pci_limit))
-        if nic_limit == min_limit:
-            traces.append(plgo.Scatter(
-                x=x_vals,
-                y=[nic_limit, ] * len(x_vals),
-                name=f"NIC: {nic_limit:.2f}Mpps",
-                showlegend=False,
-                mode=u"lines",
-                line=dict(
-                    dash=u"dot",
-                    color=COLORS[-1],
-                    width=1),
-                hoverinfo=u"none"
-            ))
-            annotations.append(dict(
-                x=1,
-                y=nic_limit,
-                xref=u"x",
-                yref=u"y",
-                xanchor=u"left",
-                yanchor=u"bottom",
-                text=f"NIC: {nic_limit:.2f}Mpps",
-                font=dict(
-                    size=14,
-                    color=COLORS[-1],
-                ),
-                align=u"left",
-                showarrow=False
-            ))
-            y_max.append(nic_limit)
-        elif lnk_limit == min_limit:
-            traces.append(plgo.Scatter(
-                x=x_vals,
-                y=[lnk_limit, ] * len(x_vals),
-                name=f"Link: {lnk_limit:.2f}Mpps",
-                showlegend=False,
-                mode=u"lines",
-                line=dict(
-                    dash=u"dot",
-                    color=COLORS[-1],
-                    width=1),
-                hoverinfo=u"none"
-            ))
-            annotations.append(dict(
-                x=1,
-                y=lnk_limit,
-                xref=u"x",
-                yref=u"y",
-                xanchor=u"left",
-                yanchor=u"bottom",
-                text=f"Link: {lnk_limit:.2f}Mpps",
-                font=dict(
-                    size=14,
-                    color=COLORS[-1],
-                ),
-                align=u"left",
-                showarrow=False
-            ))
-            y_max.append(lnk_limit)
-        elif pci_limit == min_limit:
-            traces.append(plgo.Scatter(
-                x=x_vals,
-                y=[pci_limit, ] * len(x_vals),
-                name=f"PCIe: {pci_limit:.2f}Mpps",
-                showlegend=False,
-                mode=u"lines",
-                line=dict(
-                    dash=u"dot",
-                    color=COLORS[-1],
-                    width=1),
-                hoverinfo=u"none"
-            ))
-            annotations.append(dict(
-                x=1,
-                y=pci_limit,
-                xref=u"x",
-                yref=u"y",
-                xanchor=u"left",
-                yanchor=u"bottom",
-                text=f"PCIe: {pci_limit:.2f}Mpps",
-                font=dict(
-                    size=14,
-                    color=COLORS[-1],
-                ),
-                align=u"left",
-                showarrow=False
-            ))
-            y_max.append(pci_limit)
+def plot_tsa_name(plot, input_data):
+    """Generate the plot(s) with algorithm:
+    plot_tsa_name
+    specified in the specification file.
 
-    # Perfect and measured:
-    cidx = 0
-    for name, val in vals.items():
-        hovertext = list()
-        try:
-            for idx in range(len(val[u"val"])):
-                htext = ""
-                if isinstance(val[u"val"][idx], float):
-                    htext += (
-                        f"No. of Runs: {val[u'count'][idx]}<br>"
-                        f"Mean: {val[u'val'][idx]:.2f}{h_unit}<br>"
+    :param plot: Plot to generate.
+    :param input_data: Data to process.
+    :type plot: pandas.Series
+    :type input_data: InputData
+    """
+
+    # Transform the data
+    plot_title = plot.get(u"title", u"")
+    logging.info(
+        f"    Creating data set for the {plot.get(u'type', u'')} {plot_title}."
+    )
+    data = input_data.filter_tests_by_name(
+        plot,
+        params=[u"throughput", u"gbps", u"parent", u"tags", u"type"]
+    )
+    if data is None:
+        logging.error(u"No data.")
+        return
+
+    plot_title = plot_title.lower()
+
+    if u"-gbps" in plot_title:
+        value = u"gbps"
+        h_unit = u"Gbps"
+        multiplier = 1e6
+    else:
+        value = u"throughput"
+        h_unit = u"Mpps"
+        multiplier = 1.0
+
+    for ttype in plot.get(u"test-type", (u"ndr", u"pdr")):
+        y_vals = OrderedDict()
+        for item in plot.get(u"include", tuple()):
+            reg_ex = re.compile(str(item).lower())
+            for job in data:
+                for build in job:
+                    for test_id, test in build.iteritems():
+                        if re.match(reg_ex, str(test_id).lower()):
+                            if y_vals.get(test[u"parent"], None) is None:
+                                y_vals[test[u"parent"]] = {
+                                    u"1": list(),
+                                    u"2": list(),
+                                    u"4": list()
+                                }
+                            try:
+                                if test[u"type"] not in (u"NDRPDR", u"CPS"):
+                                    continue
+
+                                if u"1C" in test[u"tags"]:
+                                    y_vals[test[u"parent"]][u"1"].append(
+                                        test[value][ttype.upper()][u"LOWER"] *
+                                        multiplier
+                                    )
+                                elif u"2C" in test[u"tags"]:
+                                    y_vals[test[u"parent"]][u"2"].append(
+                                        test[value][ttype.upper()][u"LOWER"] *
+                                        multiplier
+                                    )
+                                elif u"4C" in test[u"tags"]:
+                                    y_vals[test[u"parent"]][u"4"].append(
+                                        test[value][ttype.upper()][u"LOWER"] *
+                                        multiplier
+                                    )
+                            except (KeyError, TypeError):
+                                pass
+
+        if not y_vals:
+            logging.warning(f"No data for the plot {plot.get(u'title', u'')}")
+            return
+
+        y_1c_max = dict()
+        for test_name, test_vals in y_vals.items():
+            for key, test_val in test_vals.items():
+                if test_val:
+                    avg_val = sum(test_val) / len(test_val)
+                    y_vals[test_name][key] = [avg_val, len(test_val)]
+                    ideal = avg_val / (int(key) * 1e6)
+                    if test_name not in y_1c_max or ideal > y_1c_max[test_name]:
+                        y_1c_max[test_name] = ideal
+
+        vals = OrderedDict()
+        y_max = list()
+        nic_limit = 0
+        lnk_limit = 0
+        pci_limit = 0
+        for test_name, test_vals in y_vals.items():
+            try:
+                if test_vals[u"1"][1]:
+                    name = re.sub(
+                        REGEX_NIC,
+                        u"",
+                        test_name.replace(u'-ndrpdr', u'').
+                        replace(u'2n1l-', u'')
                     )
-                if isinstance(val[u"diff"][idx], float):
-                    htext += f"Diff: {round(val[u'diff'][idx]):.0f}%<br>"
-                if isinstance(val[u"rel"][idx], float):
-                    htext += f"Speedup: {val[u'rel'][idx]:.2f}"
-                hovertext.append(htext)
-            traces.append(
-                plgo.Scatter(
+                    vals[name] = OrderedDict()
+                    y_val_1 = test_vals[u"1"][0] / 1e6
+                    y_val_2 = test_vals[u"2"][0] / 1e6 if test_vals[u"2"][0] \
+                        else None
+                    y_val_4 = test_vals[u"4"][0] / 1e6 if test_vals[u"4"][0] \
+                        else None
+
+                    vals[name][u"val"] = [y_val_1, y_val_2, y_val_4]
+                    vals[name][u"rel"] = [1.0, None, None]
+                    vals[name][u"ideal"] = [
+                        y_1c_max[test_name],
+                        y_1c_max[test_name] * 2,
+                        y_1c_max[test_name] * 4
+                    ]
+                    vals[name][u"diff"] = [
+                        (y_val_1 - y_1c_max[test_name]) * 100 / y_val_1,
+                        None,
+                        None
+                    ]
+                    vals[name][u"count"] = [
+                        test_vals[u"1"][1],
+                        test_vals[u"2"][1],
+                        test_vals[u"4"][1]
+                    ]
+
+                    try:
+                        val_max = max(vals[name][u"val"])
+                    except ValueError as err:
+                        logging.error(repr(err))
+                        continue
+                    if val_max:
+                        y_max.append(val_max)
+
+                    if y_val_2:
+                        vals[name][u"rel"][1] = round(y_val_2 / y_val_1, 2)
+                        vals[name][u"diff"][1] = \
+                            (y_val_2 - vals[name][u"ideal"][1]) * 100 / y_val_2
+                    if y_val_4:
+                        vals[name][u"rel"][2] = round(y_val_4 / y_val_1, 2)
+                        vals[name][u"diff"][2] = \
+                            (y_val_4 - vals[name][u"ideal"][2]) * 100 / y_val_4
+            except IndexError as err:
+                logging.warning(f"No data for {test_name}")
+                logging.warning(repr(err))
+
+            # Limits:
+            if u"x520" in test_name:
+                limit = plot[u"limits"][u"nic"][u"x520"]
+            elif u"x710" in test_name:
+                limit = plot[u"limits"][u"nic"][u"x710"]
+            elif u"xxv710" in test_name:
+                limit = plot[u"limits"][u"nic"][u"xxv710"]
+            elif u"xl710" in test_name:
+                limit = plot[u"limits"][u"nic"][u"xl710"]
+            elif u"x553" in test_name:
+                limit = plot[u"limits"][u"nic"][u"x553"]
+            elif u"cx556a" in test_name:
+                limit = plot[u"limits"][u"nic"][u"cx556a"]
+            elif u"e810cq" in test_name:
+                limit = plot[u"limits"][u"nic"][u"e810cq"]
+            else:
+                limit = 0
+            if limit > nic_limit:
+                nic_limit = limit
+
+            mul = 2 if u"ge2p" in test_name else 1
+            if u"10ge" in test_name:
+                limit = plot[u"limits"][u"link"][u"10ge"] * mul
+            elif u"25ge" in test_name:
+                limit = plot[u"limits"][u"link"][u"25ge"] * mul
+            elif u"40ge" in test_name:
+                limit = plot[u"limits"][u"link"][u"40ge"] * mul
+            elif u"100ge" in test_name:
+                limit = plot[u"limits"][u"link"][u"100ge"] * mul
+            else:
+                limit = 0
+            if limit > lnk_limit:
+                lnk_limit = limit
+
+            if u"cx556a" in test_name:
+                limit = plot[u"limits"][u"pci"][u"pci-g3-x8"]
+            else:
+                limit = plot[u"limits"][u"pci"][u"pci-g3-x16"]
+            if limit > pci_limit:
+                pci_limit = limit
+
+        traces = list()
+        annotations = list()
+        x_vals = [1, 2, 4]
+
+        # Limits:
+        if u"-gbps" not in plot_title and u"-cps-" not in plot_title:
+            nic_limit /= 1e6
+            lnk_limit /= 1e6
+            pci_limit /= 1e6
+            min_limit = min((nic_limit, lnk_limit, pci_limit))
+            if nic_limit == min_limit:
+                traces.append(plgo.Scatter(
+                    x=x_vals,
+                    y=[nic_limit, ] * len(x_vals),
+                    name=f"NIC: {nic_limit:.2f}Mpps",
+                    showlegend=False,
+                    mode=u"lines",
+                    line=dict(
+                        dash=u"dot",
+                        color=COLORS[-1],
+                        width=1),
+                    hoverinfo=u"none"
+                ))
+                annotations.append(dict(
+                    x=1,
+                    y=nic_limit,
+                    xref=u"x",
+                    yref=u"y",
+                    xanchor=u"left",
+                    yanchor=u"bottom",
+                    text=f"NIC: {nic_limit:.2f}Mpps",
+                    font=dict(
+                        size=14,
+                        color=COLORS[-1],
+                    ),
+                    align=u"left",
+                    showarrow=False
+                ))
+                y_max.append(nic_limit)
+            elif lnk_limit == min_limit:
+                traces.append(plgo.Scatter(
                     x=x_vals,
-                    y=val[u"val"],
-                    name=name,
-                    legendgroup=name,
-                    mode=u"lines+markers",
+                    y=[lnk_limit, ] * len(x_vals),
+                    name=f"Link: {lnk_limit:.2f}Mpps",
+                    showlegend=False,
+                    mode=u"lines",
                     line=dict(
-                        color=COLORS[cidx],
-                        width=2),
-                    marker=dict(
-                        symbol=u"circle",
-                        size=10
+                        dash=u"dot",
+                        color=COLORS[-1],
+                        width=1),
+                    hoverinfo=u"none"
+                ))
+                annotations.append(dict(
+                    x=1,
+                    y=lnk_limit,
+                    xref=u"x",
+                    yref=u"y",
+                    xanchor=u"left",
+                    yanchor=u"bottom",
+                    text=f"Link: {lnk_limit:.2f}Mpps",
+                    font=dict(
+                        size=14,
+                        color=COLORS[-1],
                     ),
-                    text=hovertext,
-                    hoverinfo=u"text+name"
-                )
-            )
-            traces.append(
-                plgo.Scatter(
+                    align=u"left",
+                    showarrow=False
+                ))
+                y_max.append(lnk_limit)
+            elif pci_limit == min_limit:
+                traces.append(plgo.Scatter(
                     x=x_vals,
-                    y=val[u"ideal"],
-                    name=f"{name} perfect",
-                    legendgroup=name,
+                    y=[pci_limit, ] * len(x_vals),
+                    name=f"PCIe: {pci_limit:.2f}Mpps",
                     showlegend=False,
                     mode=u"lines",
                     line=dict(
-                        color=COLORS[cidx],
-                        width=2,
-                        dash=u"dash"),
-                    text=[f"Perfect: {y:.2f}Mpps" for y in val[u"ideal"]],
-                    hoverinfo=u"text"
+                        dash=u"dot",
+                        color=COLORS[-1],
+                        width=1),
+                    hoverinfo=u"none"
+                ))
+                annotations.append(dict(
+                    x=1,
+                    y=pci_limit,
+                    xref=u"x",
+                    yref=u"y",
+                    xanchor=u"left",
+                    yanchor=u"bottom",
+                    text=f"PCIe: {pci_limit:.2f}Mpps",
+                    font=dict(
+                        size=14,
+                        color=COLORS[-1],
+                    ),
+                    align=u"left",
+                    showarrow=False
+                ))
+                y_max.append(pci_limit)
+
+        # Perfect and measured:
+        cidx = 0
+        for name, val in vals.items():
+            hovertext = list()
+            try:
+                for idx in range(len(val[u"val"])):
+                    htext = ""
+                    if isinstance(val[u"val"][idx], float):
+                        htext += (
+                            f"No. of Runs: {val[u'count'][idx]}<br>"
+                            f"Mean: {val[u'val'][idx]:.2f}{h_unit}<br>"
+                        )
+                    if isinstance(val[u"diff"][idx], float):
+                        htext += f"Diff: {round(val[u'diff'][idx]):.0f}%<br>"
+                    if isinstance(val[u"rel"][idx], float):
+                        htext += f"Speedup: {val[u'rel'][idx]:.2f}"
+                    hovertext.append(htext)
+                traces.append(
+                    plgo.Scatter(
+                        x=x_vals,
+                        y=val[u"val"],
+                        name=name,
+                        legendgroup=name,
+                        mode=u"lines+markers",
+                        line=dict(
+                            color=COLORS[cidx],
+                            width=2),
+                        marker=dict(
+                            symbol=u"circle",
+                            size=10
+                        ),
+                        text=hovertext,
+                        hoverinfo=u"text+name"
+                    )
                 )
-            )
-            cidx += 1
-        except (IndexError, ValueError, KeyError) as err:
-            logging.warning(f"No data for {name}\n{repr(err)}")
-
-    try:
-        # Create plot
-        file_type = plot.get(u"output-file-type", u".html")
-        logging.info(f"    Writing file {plot[u'output-file']}{file_type}.")
-        layout = deepcopy(plot[u"layout"])
-        if layout.get(u"title", None):
-            layout[u"title"] = f"<b>Speedup Multi-core:</b> {layout[u'title']}"
-        layout[u"yaxis"][u"range"] = [0, int(max(y_max) * 1.1)]
-        layout[u"annotations"].extend(annotations)
-        plpl = plgo.Figure(data=traces, layout=layout)
+                traces.append(
+                    plgo.Scatter(
+                        x=x_vals,
+                        y=val[u"ideal"],
+                        name=f"{name} perfect",
+                        legendgroup=name,
+                        showlegend=False,
+                        mode=u"lines",
+                        line=dict(
+                            color=COLORS[cidx],
+                            width=2,
+                            dash=u"dash"),
+                        text=[f"Perfect: {y:.2f}Mpps" for y in val[u"ideal"]],
+                        hoverinfo=u"text"
+                    )
+                )
+                cidx += 1
+            except (IndexError, ValueError, KeyError) as err:
+                logging.warning(f"No data for {name}\n{repr(err)}")
 
-        # Export Plot
-        ploff.plot(
-            plpl,
-            show_link=False,
-            auto_open=False,
-            filename=f"{plot[u'output-file']}{file_type}"
-        )
-    except PlotlyError as err:
-        logging.error(
-            f"   Finished with error: {repr(err)}".replace(u"\n", u" ")
-        )
-        return
+        try:
+            # Create plot
+            file_name = f"{plot[u'output-file'].format(test_type=ttype)}.html"
+            logging.info(f"    Writing file {file_name}")
+            layout = deepcopy(plot[u"layout"])
+            if layout.get(u"title", None):
+                layout[u"title"] = (
+                    f"<b>Speedup Multi-core:</b> "
+                    f"{layout[u'title'].format(test_type=ttype)}"
+                )
+            layout[u"yaxis"][u"range"] = [0, int(max(y_max) * 1.1)]
+            layout[u"annotations"].extend(annotations)
+            plpl = plgo.Figure(data=traces, layout=layout)
+
+            # Export Plot
+            ploff.plot(
+                plpl,
+                show_link=False,
+                auto_open=False,
+                filename=file_name
+            )
+        except PlotlyError as err:
+            logging.error(
+                f"   Finished with error: {repr(err)}".replace(u"\n", u" ")
+            )
 
 
 def plot_http_server_perf_box(plot, input_data):
@@ -955,6 +1377,16 @@ def plot_nf_heatmap(plot, input_data):
     :type input_data: InputData
     """
 
+    def sort_by_int(value):
+        """Makes possible to sort a list of strings which represent integers.
+
+        :param value: Integer as a string.
+        :type value: str
+        :returns: Integer representation of input parameter 'value'.
+        :rtype: int
+        """
+        return int(value)
+
     regex_cn = re.compile(r'^(\d*)R(\d*)C$')
     regex_test_name = re.compile(r'^.*-(\d+ch|\d+pl)-'
                                  r'(\d+mif|\d+vh)-'
@@ -966,306 +1398,321 @@ def plot_nf_heatmap(plot, input_data):
         f"    Creating the data set for the {plot.get(u'type', u'')} "
         f"{plot.get(u'title', u'')}."
     )
-    data = input_data.filter_data(plot, continue_on_error=True)
-    if data is None or data.empty:
-        logging.error(u"No data.")
-        return
-
-    for job in data:
-        for build in job:
-            for test in build:
-                for tag in test[u"tags"]:
-                    groups = re.search(regex_cn, tag)
-                    if groups:
-                        chain = str(groups.group(1))
-                        node = str(groups.group(2))
-                        break
-                else:
-                    continue
-                groups = re.search(regex_test_name, test[u"name"])
-                if groups and len(groups.groups()) == 3:
-                    hover_name = (
-                        f"{str(groups.group(1))}-"
-                        f"{str(groups.group(2))}-"
-                        f"{str(groups.group(3))}"
-                    )
-                else:
-                    hover_name = u""
-                if vals.get(chain, None) is None:
-                    vals[chain] = dict()
-                if vals[chain].get(node, None) is None:
-                    vals[chain][node] = dict(
-                        name=hover_name,
-                        vals=list(),
-                        nr=None,
-                        mean=None,
-                        stdev=None
-                    )
-                try:
-                    if plot[u"include-tests"] == u"MRR":
-                        result = test[u"result"][u"receive-rate"]
-                    elif plot[u"include-tests"] == u"PDR":
-                        result = test[u"throughput"][u"PDR"][u"LOWER"]
-                    elif plot[u"include-tests"] == u"NDR":
-                        result = test[u"throughput"][u"NDR"][u"LOWER"]
-                    else:
-                        result = None
-                except TypeError:
-                    result = None
-
-                if result:
-                    vals[chain][node][u"vals"].append(result)
-
-    if not vals:
+    in_data = input_data.filter_tests_by_name(
+        plot,
+        continue_on_error=True,
+        params=[u"throughput", u"result", u"name", u"tags", u"type"]
+    )
+    if in_data is None or in_data.empty:
         logging.error(u"No data.")
         return
 
-    txt_chains = list()
-    txt_nodes = list()
-    for key_c in vals:
-        txt_chains.append(key_c)
-        for key_n in vals[key_c].keys():
-            txt_nodes.append(key_n)
-            if vals[key_c][key_n][u"vals"]:
-                vals[key_c][key_n][u"nr"] = len(vals[key_c][key_n][u"vals"])
-                vals[key_c][key_n][u"mean"] = \
-                    round(mean(vals[key_c][key_n][u"vals"]) / 1000000, 1)
-                vals[key_c][key_n][u"stdev"] = \
-                    round(stdev(vals[key_c][key_n][u"vals"]) / 1000000, 1)
-    txt_nodes = list(set(txt_nodes))
-
-    def sort_by_int(value):
-        """Makes possible to sort a list of strings which represent integers.
-
-        :param value: Integer as a string.
-        :type value: str
-        :returns: Integer representation of input parameter 'value'.
-        :rtype: int
-        """
-        return int(value)
-
-    txt_chains = sorted(txt_chains, key=sort_by_int)
-    txt_nodes = sorted(txt_nodes, key=sort_by_int)
-
-    chains = [i + 1 for i in range(len(txt_chains))]
-    nodes = [i + 1 for i in range(len(txt_nodes))]
-
-    data = [list() for _ in range(len(chains))]
-    for chain in chains:
-        for node in nodes:
-            try:
-                val = vals[txt_chains[chain - 1]][txt_nodes[node - 1]][u"mean"]
-            except (KeyError, IndexError):
-                val = None
-            data[chain - 1].append(val)
-
-    # Color scales:
-    my_green = [[0.0, u"rgb(235, 249, 242)"],
-                [1.0, u"rgb(45, 134, 89)"]]
-
-    my_blue = [[0.0, u"rgb(236, 242, 248)"],
-               [1.0, u"rgb(57, 115, 172)"]]
-
-    my_grey = [[0.0, u"rgb(230, 230, 230)"],
-               [1.0, u"rgb(102, 102, 102)"]]
-
-    hovertext = list()
-    annotations = list()
-
-    text = (u"Test: {name}<br>"
-            u"Runs: {nr}<br>"
-            u"Thput: {val}<br>"
-            u"StDev: {stdev}")
+    for ttype in plot.get(u"test-type", (u"ndr", u"pdr")):
+        for core in plot.get(u"core", tuple()):
+            for item in plot.get(u"include", tuple()):
+                reg_ex = re.compile(str(item.format(core=core)).lower())
+                for job in in_data:
+                    for build in job:
+                        for test_id, test in build.iteritems():
+                            if not re.match(reg_ex, str(test_id).lower()):
+                                continue
+                            for tag in test[u"tags"]:
+                                groups = re.search(regex_cn, tag)
+                                if groups:
+                                    chain = str(groups.group(1))
+                                    node = str(groups.group(2))
+                                    break
+                            else:
+                                continue
+                            groups = re.search(regex_test_name, test[u"name"])
+                            if groups and len(groups.groups()) == 3:
+                                hover_name = (
+                                    f"{str(groups.group(1))}-"
+                                    f"{str(groups.group(2))}-"
+                                    f"{str(groups.group(3))}"
+                                )
+                            else:
+                                hover_name = u""
+                            if vals.get(chain, None) is None:
+                                vals[chain] = dict()
+                            if vals[chain].get(node, None) is None:
+                                vals[chain][node] = dict(
+                                    name=hover_name,
+                                    vals=list(),
+                                    nr=None,
+                                    mean=None,
+                                    stdev=None
+                                )
+                            try:
+                                if ttype == u"mrr":
+                                    result = test[u"result"][u"receive-rate"]
+                                elif ttype == u"pdr":
+                                    result = \
+                                        test[u"throughput"][u"PDR"][u"LOWER"]
+                                elif ttype == u"ndr":
+                                    result = \
+                                        test[u"throughput"][u"NDR"][u"LOWER"]
+                                else:
+                                    result = None
+                            except TypeError:
+                                result = None
+
+                            if result:
+                                vals[chain][node][u"vals"].append(result)
+
+            if not vals:
+                logging.error(u"No data.")
+                return
+
+            txt_chains = list()
+            txt_nodes = list()
+            for key_c in vals:
+                txt_chains.append(key_c)
+                for key_n in vals[key_c].keys():
+                    txt_nodes.append(key_n)
+                    if vals[key_c][key_n][u"vals"]:
+                        vals[key_c][key_n][u"nr"] = \
+                            len(vals[key_c][key_n][u"vals"])
+                        vals[key_c][key_n][u"mean"] = \
+                            round(mean(vals[key_c][key_n][u"vals"]) / 1e6, 1)
+                        vals[key_c][key_n][u"stdev"] = \
+                            round(stdev(vals[key_c][key_n][u"vals"]) / 1e6, 1)
+            txt_nodes = list(set(txt_nodes))
+
+            txt_chains = sorted(txt_chains, key=sort_by_int)
+            txt_nodes = sorted(txt_nodes, key=sort_by_int)
+
+            chains = [i + 1 for i in range(len(txt_chains))]
+            nodes = [i + 1 for i in range(len(txt_nodes))]
+
+            data = [list() for _ in range(len(chains))]
+            for chain in chains:
+                for node in nodes:
+                    try:
+                        val = vals[txt_chains[chain - 1]] \
+                            [txt_nodes[node - 1]][u"mean"]
+                    except (KeyError, IndexError):
+                        val = None
+                    data[chain - 1].append(val)
+
+            # Color scales:
+            my_green = [[0.0, u"rgb(235, 249, 242)"],
+                        [1.0, u"rgb(45, 134, 89)"]]
+
+            my_blue = [[0.0, u"rgb(236, 242, 248)"],
+                       [1.0, u"rgb(57, 115, 172)"]]
+
+            my_grey = [[0.0, u"rgb(230, 230, 230)"],
+                       [1.0, u"rgb(102, 102, 102)"]]
+
+            hovertext = list()
+            annotations = list()
+
+            text = (u"Test: {name}<br>"
+                    u"Runs: {nr}<br>"
+                    u"Thput: {val}<br>"
+                    u"StDev: {stdev}")
+
+            for chain, _ in enumerate(txt_chains):
+                hover_line = list()
+                for node, _ in enumerate(txt_nodes):
+                    if data[chain][node] is not None:
+                        annotations.append(
+                            dict(
+                                x=node+1,
+                                y=chain+1,
+                                xref=u"x",
+                                yref=u"y",
+                                xanchor=u"center",
+                                yanchor=u"middle",
+                                text=str(data[chain][node]),
+                                font=dict(
+                                    size=14,
+                                ),
+                                align=u"center",
+                                showarrow=False
+                            )
+                        )
+                        hover_line.append(text.format(
+                            name=vals[txt_chains[chain]][txt_nodes[node]]
+                            [u"name"],
+                            nr=vals[txt_chains[chain]][txt_nodes[node]][u"nr"],
+                            val=data[chain][node],
+                            stdev=vals[txt_chains[chain]][txt_nodes[node]]
+                            [u"stdev"]
+                        ))
+                hovertext.append(hover_line)
+
+            traces = [
+                plgo.Heatmap(
+                    x=nodes,
+                    y=chains,
+                    z=data,
+                    colorbar=dict(
+                        title=plot.get(u"z-axis", u"{test_type}").
+                        format(test_type=ttype.upper()),
+                        titleside=u"right",
+                        titlefont=dict(
+                            size=16
+                        ),
+                        tickfont=dict(
+                            size=16,
+                        ),
+                        tickformat=u".1f",
+                        yanchor=u"bottom",
+                        y=-0.02,
+                        len=0.925,
+                    ),
+                    showscale=True,
+                    colorscale=my_green,
+                    text=hovertext,
+                    hoverinfo=u"text"
+                )
+            ]
 
-    for chain, _ in enumerate(txt_chains):
-        hover_line = list()
-        for node, _ in enumerate(txt_nodes):
-            if data[chain][node] is not None:
+            for idx, item in enumerate(txt_nodes):
+                # X-axis, numbers:
                 annotations.append(
                     dict(
-                        x=node+1,
-                        y=chain+1,
+                        x=idx+1,
+                        y=0.05,
                         xref=u"x",
                         yref=u"y",
                         xanchor=u"center",
+                        yanchor=u"top",
+                        text=item,
+                        font=dict(
+                            size=16,
+                        ),
+                        align=u"center",
+                        showarrow=False
+                    )
+                )
+            for idx, item in enumerate(txt_chains):
+                # Y-axis, numbers:
+                annotations.append(
+                    dict(
+                        x=0.35,
+                        y=idx+1,
+                        xref=u"x",
+                        yref=u"y",
+                        xanchor=u"right",
                         yanchor=u"middle",
-                        text=str(data[chain][node]),
+                        text=item,
                         font=dict(
-                            size=14,
+                            size=16,
                         ),
                         align=u"center",
                         showarrow=False
                     )
                 )
-                hover_line.append(text.format(
-                    name=vals[txt_chains[chain]][txt_nodes[node]][u"name"],
-                    nr=vals[txt_chains[chain]][txt_nodes[node]][u"nr"],
-                    val=data[chain][node],
-                    stdev=vals[txt_chains[chain]][txt_nodes[node]][u"stdev"]))
-        hovertext.append(hover_line)
-
-    traces = [
-        plgo.Heatmap(
-            x=nodes,
-            y=chains,
-            z=data,
-            colorbar=dict(
-                title=plot.get(u"z-axis", u""),
-                titleside=u"right",
-                titlefont=dict(
-                    size=16
-                ),
-                tickfont=dict(
-                    size=16,
-                ),
-                tickformat=u".1f",
-                yanchor=u"bottom",
-                y=-0.02,
-                len=0.925,
-            ),
-            showscale=True,
-            colorscale=my_green,
-            text=hovertext,
-            hoverinfo=u"text"
-        )
-    ]
-
-    for idx, item in enumerate(txt_nodes):
-        # X-axis, numbers:
-        annotations.append(
-            dict(
-                x=idx+1,
-                y=0.05,
-                xref=u"x",
-                yref=u"y",
-                xanchor=u"center",
-                yanchor=u"top",
-                text=item,
-                font=dict(
-                    size=16,
-                ),
-                align=u"center",
-                showarrow=False
-            )
-        )
-    for idx, item in enumerate(txt_chains):
-        # Y-axis, numbers:
-        annotations.append(
-            dict(
-                x=0.35,
-                y=idx+1,
-                xref=u"x",
-                yref=u"y",
-                xanchor=u"right",
-                yanchor=u"middle",
-                text=item,
-                font=dict(
-                    size=16,
-                ),
-                align=u"center",
-                showarrow=False
-            )
-        )
-    # X-axis, title:
-    annotations.append(
-        dict(
-            x=0.55,
-            y=-0.15,
-            xref=u"paper",
-            yref=u"y",
-            xanchor=u"center",
-            yanchor=u"bottom",
-            text=plot.get(u"x-axis", u""),
-            font=dict(
-                size=16,
-            ),
-            align=u"center",
-            showarrow=False
-        )
-    )
-    # Y-axis, title:
-    annotations.append(
-        dict(
-            x=-0.1,
-            y=0.5,
-            xref=u"x",
-            yref=u"paper",
-            xanchor=u"center",
-            yanchor=u"middle",
-            text=plot.get(u"y-axis", u""),
-            font=dict(
-                size=16,
-            ),
-            align=u"center",
-            textangle=270,
-            showarrow=False
-        )
-    )
-    updatemenus = list([
-        dict(
-            x=1.0,
-            y=0.0,
-            xanchor=u"right",
-            yanchor=u"bottom",
-            direction=u"up",
-            buttons=list([
+            # X-axis, title:
+            annotations.append(
                 dict(
-                    args=[
-                        {
-                            u"colorscale": [my_green, ],
-                            u"reversescale": False
-                        }
-                    ],
-                    label=u"Green",
-                    method=u"update"
-                ),
+                    x=0.55,
+                    y=-0.15,
+                    xref=u"paper",
+                    yref=u"y",
+                    xanchor=u"center",
+                    yanchor=u"bottom",
+                    text=plot.get(u"x-axis", u""),
+                    font=dict(
+                        size=16,
+                    ),
+                    align=u"center",
+                    showarrow=False
+                )
+            )
+            # Y-axis, title:
+            annotations.append(
                 dict(
-                    args=[
-                        {
-                            u"colorscale": [my_blue, ],
-                            u"reversescale": False
-                        }
-                    ],
-                    label=u"Blue",
-                    method=u"update"
-                ),
+                    x=-0.1,
+                    y=0.5,
+                    xref=u"x",
+                    yref=u"paper",
+                    xanchor=u"center",
+                    yanchor=u"middle",
+                    text=plot.get(u"y-axis", u""),
+                    font=dict(
+                        size=16,
+                    ),
+                    align=u"center",
+                    textangle=270,
+                    showarrow=False
+                )
+            )
+            updatemenus = list([
                 dict(
-                    args=[
-                        {
-                            u"colorscale": [my_grey, ],
-                            u"reversescale": False
-                        }
-                    ],
-                    label=u"Grey",
-                    method=u"update"
+                    x=1.0,
+                    y=0.0,
+                    xanchor=u"right",
+                    yanchor=u"bottom",
+                    direction=u"up",
+                    buttons=list([
+                        dict(
+                            args=[
+                                {
+                                    u"colorscale": [my_green, ],
+                                    u"reversescale": False
+                                }
+                            ],
+                            label=u"Green",
+                            method=u"update"
+                        ),
+                        dict(
+                            args=[
+                                {
+                                    u"colorscale": [my_blue, ],
+                                    u"reversescale": False
+                                }
+                            ],
+                            label=u"Blue",
+                            method=u"update"
+                        ),
+                        dict(
+                            args=[
+                                {
+                                    u"colorscale": [my_grey, ],
+                                    u"reversescale": False
+                                }
+                            ],
+                            label=u"Grey",
+                            method=u"update"
+                        )
+                    ])
                 )
             ])
-        )
-    ])
 
-    try:
-        layout = deepcopy(plot[u"layout"])
-    except KeyError as err:
-        logging.error(f"Finished with error: No layout defined\n{repr(err)}")
-        return
+            try:
+                layout = deepcopy(plot[u"layout"])
+            except KeyError as err:
+                logging.error(
+                    f"Finished with error: No layout defined\n{repr(err)}"
+                )
+                return
 
-    layout[u"annotations"] = annotations
-    layout[u'updatemenus'] = updatemenus
+            layout[u"annotations"] = annotations
+            layout[u'updatemenus'] = updatemenus
+            if layout.get(u"title", None):
+                layout[u"title"] = layout[u'title'].replace(u"test_type", ttype)
 
-    try:
-        # Create plot
-        plpl = plgo.Figure(data=traces, layout=layout)
+            try:
+                # Create plot
+                plpl = plgo.Figure(data=traces, layout=layout)
 
-        # Export Plot
-        logging.info(f"    Writing file {plot[u'output-file']}.html")
-        ploff.plot(
-            plpl,
-            show_link=False,
-            auto_open=False,
-            filename=f"{plot[u'output-file']}.html"
-        )
-    except PlotlyError as err:
-        logging.error(
-            f"   Finished with error: {repr(err)}".replace(u"\n", u" ")
-        )
-        return
+                # Export Plot
+                file_name = (
+                    f"{plot[u'output-file'].format(core=core, test_type=ttype)}"
+                    f".html"
+                )
+                logging.info(f"    Writing file {file_name}")
+                ploff.plot(
+                    plpl,
+                    show_link=False,
+                    auto_open=False,
+                    filename=file_name
+                )
+            except PlotlyError as err:
+                logging.error(
+                    f"   Finished with error: {repr(err)}".replace(u"\n", u" ")
+                )