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#!/bin/bash

# Copyright (c) 2015 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:
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

# This aptly-named script verifies and fixes time ordering
# problems with Makefile.{am,in} aclocal.m4 configure* files.

set -eu
#set -vx

touch=""
commit=""
comma_v=""
aclocal=""
optimize=""

# The old autowank scheme used "touch <foo> ; sleep 1"
# to ensure differentiable, ordered timestamps. Worked, but
# took N seconds given N files to fix. We have an example
# which wastes multiple minutes given the old scheme.
#
# This version generates a sequence of timestamps 
# starting an hour ago. That gives us
# lots to play with, in case some obnoxious program feels the need
# to complain about timestamps in the future.

# If we're in UTC+N land, generate UTC+(N+1) 
# If we're in UTC-N land, generate UTC-(N-1)

my_tz=`date +%z`
sign=`echo $my_tz | sed -n -e 's/^\(.\{1\}\).*$/\1/p'`
t=`echo $my_tz | sed -n -e 's/^\(.\{1\}\)//p'`
tz_hour=`echo $t | sed -n -e 's/^\(.\{2\}\).*$/\1/p'`
tz_hour=`echo $tz_hour | sed 's/^0//'`

if [ $sign = "-" ] ; then
    sign="+"
    let tz_hour=$tz_hour+1
    if [[ $tz_hour -ge "24" ]] ; then
        tz_hour=0
    fi
else
    sign="-"
    let tz_hour=$tz_hour-1 || true
    if [[ $tz_hour -lt "0" ]] ; then
        tz_hour=23
    fi
fi

# Timestamp, an hour ago:
ts_begin=`TZ=UTC${sign}${tz_hour} date +%Y%m%d%H%M.%S`

# break into constituent parts
year=`echo $ts_begin | sed -n -e 's/^\(.\{4\}\).*$/\1/p'`
t=`echo $ts_begin | sed -n -e 's/^\(.\{4\}\)//p'`
month=`echo $t | sed -n -e 's/^\(.\{2\}\).*$/\1/p'`
t=`echo $t | sed -n -e 's/^\(.\{2\}\)//p'`
day=`echo $t | sed -n -e 's/^\(.\{2\}\).*$/\1/p'`
t=`echo $t | sed -n -e 's/^\(.\{2\}\)//p'`
hour=`echo $t | sed -n -e 's/^\(.\{2\}\).*$/\1/p'`
t=`echo $t | sed -n -e 's/^\(.\{2\}\)//p'`
min=`echo $t | sed -n -e 's/^\(.\{2\}\).*$/\1/p'`
t=`echo $t | sed -n -e 's/^\(.\{2\}\)//p'`
sec=`echo $t | sed -n -e 's/\.//p'`

# How many days in the current month?
# Good until someone changes the calendar rules
days_in_current_month() {
    if [[ $month -eq 9 || $month -eq 4 \
        || $month -eq 6 || $month -eq 11 ]] ; then
	return 30;
    fi
    if [[ $month -eq 2 ]] ; then
	let t=($year/400)*400
	if [[ $t -eq $year ]] ; then
	    return 29;
	fi
	let t=($year/100)*100
	if [[ $t -eq $year ]] ; then
	    return 28;
	fi
	let t=($year/4)*4
	if [[ $t -eq $year ]] ; then
	    return 29;
	fi
	return 28;
    fi
    return 31;
}

# The next timestamp to issue via touch
# A real hemorrhoid because bash isnt easily convinced
# that 08 is a decimal number
next_ts() {
    sec=`echo $sec | sed 's/^0//'`
    let sec=$sec+1
    if [[ "$sec" -lt "60" ]] ; then
        if [[ "$sec" -lt "10" ]] ; then
            sec=0$sec
        fi
	return 0;
    fi
    sec="00"
    min=`echo $min | sed 's/^0//'`
    let min=$min+1
    if [[ "$min" -lt "60" ]] ; then
        if [[ "$min" -lt "10" ]] ; then
            min=0$min
        fi
	return 0;
    fi
    min="00"
    hour=`echo $hour | sed 's/^0//'`
    let hour=$hour+1
    if [[ "$hour" -lt "24" ]] ; then
        if [[ "$hour" -lt "10" ]] ; then
            hour=0$hour
        fi
	return 0;
    fi
    hour="00"
    days_in_current_month
    days_in_month=$?
    if [[ "$day" -lt "$days_in_month" ]] ; then
        day=`echo $day | sed 's/^0//'`
	let day=$day+1
        if [[ "$day" -lt "10" ]] ; then
            day=0$day
        fi
	return 0;
    fi
    day="01"
    month=`echo $month | sed 's/^0//'`
    let month=$month+1
    if [[ "$month" -lt "13" ]] ; then
        if [[ "$month" -lt "10" ]] ; then
            month=0$month
        fi
	return 0;
    fi
    month="01"
    let year=$year+1
    return 0;
}

while [ $# != 0 ] ; do
  case "$1" in
    (--commav) comma_v=",v" ;;
    (--touch) touch=yes ;;
    (--aclocal) aclocal=yes ;;
    (--nooptimize) optimize="" ;;
    (--commit=*) commit="$1" ;;
    (*) echo "$0: usage [--touch|--commit|]" > /dev/stderr
        exit 17 ;;
  esac
  shift
done

if [ "${aclocal}" != "" ] ; then
    if [ -f aclocal.m4 ] ; then
        echo touching aclocal.m4
        sleep 1
        touch aclocal.m4
    else
        echo aclocal.m4 not found
    fi
fi

if [ "${comma_v}" != "" -a "${commit}" != "" ] ; then
  echo "No, you may NOT molest ,v files directly.  Go away." > /dev/stderr
  exit 1
fi

function touchme ()
{
  local victim="${1}"
  shift
  local touchmebaby=""
  local sein="is"
  local newer="no"
  local older="no"

  if [ ! -r "$victim" ] ; then
    return
  fi

  while [ $# != 0 ] ; do
    if [ "${1}" -nt "${victim}" ] ; then
        newer="yes"
    fi
    if [ "${1}" -ot "${victim}" ] ; then
        older="yes"
    fi
    if [ "${newer}" = "no" -a "${older}" = "no" ] ; then
        newer="yes"
    fi

    if [ "${newer}" = "yes" ] ; then
      if [ "${touchmebaby}" = "" ] ; then
        touchmebaby="${1}"
      else
        sein="are"
        touchmebaby="${touchmebaby} ${1}"
      fi
    fi
    shift
  done
  if [ -n "${touchmebaby}" ] ; then
    echo "*** ${touchmebaby} ${sein} newer than ${victim}  "
    if [ -n "${touch}" ] ; then
      # 
      # This is the old version, in case something backfires...
      if [ "${optimize}" != "yes" ] ; then 
          echo "Fixing " ;touch -c "$victim" ; sleep 1
      else
          echo "Fixing "
      # echo touch -c -t $year$month$day$hour$min.$sec "$victim"
          touch -c -t $year$month$day$hour$min.$sec "$victim"
          next_ts
      fi
    fi
  fi
}

makefileins="`/usr/bin/find . -name Attic -prune -o -name Makefile.in${comma_v}`"

# aclocal.m4 depends on ***/Makefile.am, configure.ac, acinclude.m4, *.m4 crap
touchme aclocal.m4${comma_v} \
        `/usr/bin/find . -name Attic -prune -o -name Makefile.am${comma_v}` \
        "configure.in${comma_v}" "configure.ac${comma_v}" \
        "acinclude.m4${comma_v}"

# Makefile.in must be newer than Makefile.am
for f in $makefileins ; do
  d="`dirname ${f}`"
  touchme "${d}/Makefile.in${comma_v}" "${d}/Makefile.am${comma_v}"
done

# Makefile.in depends on aclocal.m4
for f in $makefileins ; do
  d="`dirname $f`"
  touchme "${d}/Makefile.in${comma_v}" "aclocal.m4${comma_v}"
done

# config.in must be newer than aclocal.m4 and configure.ac
if [ -f "config.in${comma_v}" ] ; then
  touchme "config.in${comma_v}" "aclocal.m4${comma_v}" \
                                "configure.ac${comma_v}" \
                                "configure.in${comma_v}"
fi

# config.h.in (or More Thoroughly Modern configh.in)
# must be newer than aclocal.m4 and (obsolete) acconfig.h
for c_h_in in config.h.in configh.in ; do
  if [ -f "${c_h_in}${comma_v}" ]; then
    touchme "${c_h_in}${comma_v}" "aclocal.m4${comma_v}" "acconfig.h${comma_v}"
    #>>>> WTF?  Why?  This is nonsensical
    ## ***/Makefile.in must be newer than config.h.in
    #for f in $makefileins ; do
    #  touchme "$f" "${c_h_in}${comma_v}"
    #done
  fi
done

# configure must be newer than everything
# touchme configure $makefileins -- why would this be needed?
touchme "configure${comma_v}" "aclocal.m4${comma_v}" "acconfig.h${comma_v}" \
                              "config.in${comma_v}" "config.h.in${comma_v}" \
                              "configh.in${comma_v}"

if [ -n "${commit}" ] ; then
  commit="${commit:9}" # strip off "--commit="
  # First ***/Makefile.am,
  # configure.in, configure.ac,
  # ***/*.m4
  # acconfig.h
  cvs commit -m "${commit}" \
             `for f in ${makefileins} ; do \
                [ -f "$${f%.in}.am" ] && echo "$${f%.in}.am" ; \
              done` \
             `[ -f configure.in ] && echo configure.in` \
             `[ -f configure.ac ] && echo configure.ac` \
             `[ -f acconfig.h ] && echo acconfig.h` \
             `/usr/bin/find . -name '*.m4' -mindepth 2`

  # Next aclocal.m4
  [ -f "aclocal.m4" ] && cvs commit -m "${commit}" aclocal.m4

  # Next config.in, config.h.in, configh.in
  [ -f "config.in" ] && cvs commit -m "${commit}" config.in
  [ -f "config.h.in" ] && cvs commit -m "${commit}" config.h.in
  [ -f "configh.in" ] && cvs commit -m "${commit}" configh.in

  # Last ***/Makefile.in, configure
  cvs commit -m "${commit}" ${makefileins} configure
fi
ound-color: #fff0f0 } /* Literal.String.Symbol */ .highlight .bp { color: #003388 } /* Name.Builtin.Pseudo */ .highlight .fm { color: #0066bb; font-weight: bold } /* Name.Function.Magic */ .highlight .vc { color: #336699 } /* Name.Variable.Class */ .highlight .vg { color: #dd7700 } /* Name.Variable.Global */ .highlight .vi { color: #3333bb } /* Name.Variable.Instance */ .highlight .vm { color: #336699 } /* Name.Variable.Magic */ .highlight .il { color: #0000DD; font-weight: bold } /* Literal.Number.Integer.Long */ }
# Copyright (c) 2020 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:
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

"""Algorithms to generate plots.
"""


import re
import logging

from collections import OrderedDict
from copy import deepcopy

import hdrh.histogram
import hdrh.codec
import pandas as pd
import plotly.offline as ploff
import plotly.graph_objs as plgo

from plotly.exceptions import PlotlyError

from pal_utils import mean, stdev


COLORS = (
    u"#1A1110",
    u"#DA2647",
    u"#214FC6",
    u"#01786F",
    u"#BD8260",
    u"#FFD12A",
    u"#A6E7FF",
    u"#738276",
    u"#C95A49",
    u"#FC5A8D",
    u"#CEC8EF",
    u"#391285",
    u"#6F2DA8",
    u"#FF878D",
    u"#45A27D",
    u"#FFD0B9",
    u"#FD5240",
    u"#DB91EF",
    u"#44D7A8",
    u"#4F86F7",
    u"#84DE02",
    u"#FFCFF1",
    u"#614051"
)

REGEX_NIC = re.compile(r'(\d*ge\dp\d\D*\d*[a-z]*)-')


def generate_plots(spec, data):
    """Generate all plots specified in the specification file.

    :param spec: Specification read from the specification file.
    :param data: Data to process.
    :type spec: Specification
    :type data: InputData
    """

    generator = {
        u"plot_nf_reconf_box_name": plot_nf_reconf_box_name,
        u"plot_perf_box_name": plot_perf_box_name,
        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
    }

    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"]
            generator[plot[u"algorithm"]](plot, data)
            logging.info(u"  Done.")
        except NameError as err:
            logging.error(
                f"Probably algorithm {plot[u'algorithm']} is not defined: "
                f"{repr(err)}"
            )
    logging.info(u"Done.")


def plot_hdrh_lat_by_percentile(plot, input_data):
    """Generate the plot(s) with algorithm: plot_hdrh_lat_by_percentile
    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")):
                    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"
                    ]
                    try:
                        decoded = hdrh.histogram.HdrHistogram.decode(
                            test[u"latency"][graph][direction][u"hdrh"]
                        )
                    except hdrh.codec.HdrLengthException:
                        logging.warning(
                            f"No data for direction {(u'W-E', u'E-W')[idx % 2]}"
                        )
                        continue

                    for item in decoded.get_recorded_iterator():
                        percentile = item.percentile_level_iterated_to
                        if percentile > 99.9:
                            continue
                        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"Latency: {item.value_iterated_to}uSec"
                        )
                    fig.add_trace(
                        plgo.Scatter(
                            x=xaxis,
                            y=yaxis,
                            name=desc[graph],
                            mode=u"lines",
                            legendgroup=desc[graph],
                            showlegend=bool(idx),
                            line=dict(
                                color=COLORS[color],
                                dash=u"dash" if idx % 2 else u"solid"
                            ),
                            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_nf_reconf_box_name(plot, input_data):
    """Generate the plot(s) with algorithm: plot_nf_reconf_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
    """

    # Transform the data
    logging.info(
        f"    Creating the 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

    # 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


def plot_perf_box_name(plot, input_data):
    """Generate the plot(s) with algorithm: plot_perf_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
    """

    # 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"throughput", u"gbps", u"result", u"parent", u"tags", u"type"])
    if data is None:
        logging.error(u"No 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", ):
                        test_type = u"NDRPDR"

                        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:
                        continue

                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()
    y_max = list()
    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''))
        kwargs = dict(
            x=[str(i + 1) + u'.'] * len(df_y[col]),
            y=[y / 1e6 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"{tst_name}"
            ),
            hoverinfo=u"y+name"
        )
        if test_type in (u"SOAK", ):
            kwargs[u"boxpoints"] = u"all"

        traces.append(plgo.Box(**kwargs))

        try:
            val_max = max(df_y[col])
            if val_max:
                y_max.append(int(val_max / 1e6) + 2)
        except (ValueError, TypeError) as err:
            logging.error(repr(err))
            continue

    try:
        # Create plot
        layout = deepcopy(plot[u"layout"])
        if layout.get(u"title", None):
            if test_type in (u"HOSTSTACK", ):
                layout[u"title"] = f"<b>Bandwidth:</b> {layout[u'title']}"
            else:
                layout[u"title"] = f"<b>Throughput:</b> {layout[u'title']}"
        if y_max:
            layout[u"yaxis"][u"range"] = [0, max(y_max)]
        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


def plot_tsa_name(plot, input_data):
    """Generate the plot(s) with algorithm:
    plot_tsa_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
    """

    # 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

    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

                    if u"-pdr" in plot_title:
                        ttype = u"PDR"
                    elif u"-ndr" in plot_title:
                        ttype = u"NDR"
                    else:
                        continue

                    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

    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 = plot[u"limits"][u"pci"][u"pci-g3-x8"]
    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'')
                )
                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"]
        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

    traces = list()
    annotations = list()
    x_vals = [1, 2, 4]

    # Limits:
    if u"-gbps" not in plot_title:
        try:
            threshold = 1.1 * max(y_max)  # 10%
        except ValueError as err:
            logging.error(err)
            return
        nic_limit /= 1e6
        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)

        lnk_limit /= 1e6
        if lnk_limit < threshold:
            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[-2],
                    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[-2],
                ),
                align=u"left",
                showarrow=False
            ))
            y_max.append(lnk_limit)

        pci_limit /= 1e6
        if (pci_limit < threshold and
                (pci_limit < lnk_limit * 0.95 or lnk_limit > lnk_limit * 1.05)):
            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[-3],
                    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[-3],
                ),
                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"
                )
            )
            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)}")

    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)

        # 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


def plot_http_server_perf_box(plot, input_data):
    """Generate the plot(s) with algorithm: plot_http_server_perf_box
    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'')}."
    )
    data = input_data.filter_data(plot)
    if data is None:
        logging.error(u"No data.")
        return

    # Prepare the data for the plot
    y_vals = dict()
    for job in data:
        for build in job:
            for test in build:
                if y_vals.get(test[u"name"], None) is None:
                    y_vals[test[u"name"]] = list()
                try:
                    y_vals[test[u"name"]].append(test[u"result"])
                except (KeyError, TypeError):
                    y_vals[test[u"name"]].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):
        name = \
            f"{i + 1}. " \
            f"({nr_of_samples[i]:02d} " \
            f"run{u's' if nr_of_samples[i] > 1 else u''}) " \
            f"{col.lower().replace(u'-ndrpdr', u'')}"
        if len(name) > 50:
            name_lst = name.split(u'-')
            name = u""
            split_name = True
            for segment in name_lst:
                if (len(name) + len(segment) + 1) > 50 and split_name:
                    name += u"<br>    "
                    split_name = False
                name += segment + u'-'
            name = name[:-1]

        traces.append(plgo.Box(x=[str(i + 1) + u'.'] * len(df_y[col]),
                               y=df_y[col],
                               name=name,
                               **plot[u"traces"]))
    try:
        # Create plot
        plpl = plgo.Figure(data=traces, layout=plot[u"layout"])

        # Export Plot
        logging.info(
            f"    Writing file {plot[u'output-file']}"
            f"{plot[u'output-file-type']}."
        )
        ploff.plot(
            plpl,
            show_link=False,
            auto_open=False,
            filename=f"{plot[u'output-file']}{plot[u'output-file-type']}"
        )
    except PlotlyError as err:
        logging.error(
            f"   Finished with error: {repr(err)}".replace(u"\n", u" ")
        )
        return


def plot_nf_heatmap(plot, input_data):
    """Generate the plot(s) with algorithm: plot_nf_heatmap
    specified in the specification file.

    :param plot: Plot to generate.
    :param input_data: Data to process.
    :type plot: pandas.Series
    :type input_data: InputData
    """

    regex_cn = re.compile(r'^(\d*)R(\d*)C$')
    regex_test_name = re.compile(r'^.*-(\d+ch|\d+pl)-'
                                 r'(\d+mif|\d+vh)-'
                                 r'(\d+vm\d+t|\d+dcr\d+t|\d+dcr\d+c).*$')
    vals = dict()

    # Transform the data
    logging.info(
        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:
        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 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""),
                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([
                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

    layout[u"annotations"] = annotations
    layout[u'updatemenus'] = updatemenus

    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