import os
import math
import bisect
import logging

try:
    import matplotlib.pyplot as plt
except ImportError:
    plt = None

import wally
from wally import charts
from wally.utils import parse_creds, ssize_to_b
from wally.statistic import round_3_digit, round_deviation
from wally.suits.io.results_loader import process_disk_info
from wally.meta_info import total_lab_info, collect_lab_data


logger = logging.getLogger("wally.report")


class DiskInfo(object):
    def __init__(self):
        self.direct_iops_r_max = 0
        self.direct_iops_w_max = 0
        self.rws4k_10ms = 0
        self.rws4k_30ms = 0
        self.rws4k_100ms = 0
        self.bw_write_max = 0
        self.bw_read_max = 0


report_funcs = []


def report(name, required_fields):
    def closure(func):
        report_funcs.append((required_fields.split(","), name, func))
        return func
    return closure


def linearity_report(processed_results, path, lab_info):
    names = {}
    for tp1 in ('rand', 'seq'):
        for oper in ('read', 'write'):
            for sync in ('sync', 'direct', 'async'):
                sq = (tp1, oper, sync)
                name = "{0} {1} {2}".format(*sq)
                names["".join(word[0] for word in sq)] = name

    colors = ['red', 'green', 'blue', 'cyan',
              'magenta', 'black', 'yellow', 'burlywood']
    markers = ['*', '^', 'x', 'o', '+', '.']
    color = 0
    marker = 0

    plot_data = {}

    name_pref = 'linearity_test_rrd'

    for res in processed_results.values():
        if res.name.startswith(name_pref):
            iotime = 1000000. / res.iops
            iotime_max = iotime * (1 + res.dev * 3)
            bsize = ssize_to_b(res.raw['blocksize'])
            plot_data[bsize] = (iotime, iotime_max)

    min_sz = min(plot_data)
    min_iotime, _ = plot_data.pop(min_sz)

    x = []
    y = []
    e = []

    for k, (v, vmax) in sorted(plot_data.items()):
        # y.append(math.log10(v - min_iotime))
        # x.append(math.log10(k))
        # e.append(y[-1] - math.log10(vmax - min_iotime))
        y.append(v - min_iotime)
        x.append(k)
        e.append(y[-1] - (vmax - min_iotime))

    print e

    tp = 'rrd'
    plt.errorbar(x, y, e, linestyle='None', label=names[tp],
                 color=colors[color], ecolor="black",
                 marker=markers[marker])
    plt.yscale('log')
    plt.xscale('log')
    plt.show()

    # ynew = approximate_line(ax, ay, ax, True)
    # plt.plot(ax, ynew, color=colors[color])
    # color += 1
    # marker += 1
    # plt.legend(loc=2)
    # plt.title("Linearity test by %i dots" % (len(vals)))


if plt:
    linearity_report = report('linearity', 'linearity_test')(linearity_report)


def render_hdd_html(dest, info, lab_description):
    very_root_dir = os.path.dirname(os.path.dirname(wally.__file__))
    templ_dir = os.path.join(very_root_dir, 'report_templates')
    templ_file = os.path.join(templ_dir, "report_hdd.html")
    templ = open(templ_file, 'r').read()

    for name, val in info.__dict__.items():
        if not name.startswith('__'):
            if val is None:
                info.__dict__[name] = '-'
            else:
                info.__dict__[name] = round_3_digit(val)

    data = info.__dict__.copy()
    for k, v in data.items():
        if v is None:
            data[k] = "-"

    report = templ.format(lab_info=lab_description, **data)
    open(dest, 'w').write(report)


def render_ceph_html(dest, info, lab_description):
    very_root_dir = os.path.dirname(os.path.dirname(wally.__file__))
    templ_dir = os.path.join(very_root_dir, 'report_templates')
    templ_file = os.path.join(templ_dir, "report_ceph.html")
    templ = open(templ_file, 'r').read()

    for name, val in info.__dict__.items():
        if not name.startswith('__') and isinstance(val, (int, long, float)):
            setattr(info, name, round_3_digit(val))

    data = info.__dict__.copy()
    for k, v in data.items():
        if v is None:
            data[k] = "-"

    report = templ.format(lab_info=lab_description, **data)
    open(dest, 'w').write(report)


def io_chart(title, concurence, latv, iops_or_bw, iops_or_bw_dev,
             legend, fname):
    bar_data, bar_dev = iops_or_bw, iops_or_bw_dev
    legend = [legend]

    iops_or_bw_per_vm = []
    for i in range(len(concurence)):
        iops_or_bw_per_vm.append(iops_or_bw[i] / concurence[i])

    bar_dev_bottom = []
    bar_dev_top = []
    for i in range(len(bar_data)):
        bar_dev_top.append(bar_data[i] + bar_dev[i])
        bar_dev_bottom.append(bar_data[i] - bar_dev[i])

    latv = [lat / 1000 for lat in latv]
    ch = charts.render_vertical_bar(title, legend, [bar_data], [bar_dev_top],
                                    [bar_dev_bottom], file_name=fname,
                                    scale_x=concurence, label_x="clients",
                                    label_y=legend[0],
                                    lines=[
                                        (latv, "msec", "rr", "lat"),
                                        (iops_or_bw_per_vm, None, None,
                                         legend[0] + " per client")
                                    ])
    return str(ch)


def make_hdd_plots(processed_results, path):
    plots = [
        ('hdd_test_rrd4k', 'rand_read_4k', 'Random read 4k direct IOPS'),
        ('hdd_test_rws4k', 'rand_write_4k', 'Random write 4k sync IOPS')
    ]
    make_plots(processed_results, path, plots)


def make_ceph_plots(processed_results, path):
    plots = [
        ('ceph_test_rrd4k', 'rand_read_4k', 'Random read 4k direct IOPS'),
        ('ceph_test_rws4k', 'rand_write_4k', 'Random write 4k sync IOPS'),
        ('ceph_test_rrd16m', 'rand_read_16m', 'Random read 16m direct MiBps'),
        ('ceph_test_rwd16m', 'rand_write_16m',
            'Random write 16m direct MiBps'),
    ]
    make_plots(processed_results, path, plots)


def make_plots(processed_results, path, plots):
    for name_pref, fname, desc in plots:
        chart_data = []

        for res in processed_results.values():
            if res.name.startswith(name_pref):
                chart_data.append(res)

        if len(chart_data) == 0:
            raise ValueError("Can't found any date for " + name_pref)

        use_bw = ssize_to_b(chart_data[0].raw['blocksize']) > 16 * 1024

        chart_data.sort(key=lambda x: x.raw['concurence'])

        lat = [x.lat for x in chart_data]
        vm_count = x.meta['testnodes_count']
        concurence = [x.raw['concurence'] * vm_count for x in chart_data]

        if use_bw:
            data = [x.bw for x in chart_data]
            data_dev = [x.bw * x.dev for x in chart_data]
            name = "BW"
        else:
            data = [x.iops for x in chart_data]
            data_dev = [x.iops * x.dev for x in chart_data]
            name = "IOPS"

        io_chart(desc, concurence, lat, data, data_dev, name, fname)


def find_max_where(processed_results, sync_mode, blocksize, rw, iops=True):
    result = [0, 0]
    attr = 'iops' if iops else 'bw'
    for measurement in processed_results.values():
        ok = measurement.raw['sync_mode'] == sync_mode
        ok = ok and (measurement.raw['blocksize'] == blocksize)
        ok = ok and (measurement.raw['rw'] == rw)

        if ok:
            if getattr(measurement, attr) > result[0]:
                result = [getattr(measurement, attr), measurement.dev]
    return result


def get_disk_info(processed_results):
    di = DiskInfo()
    rws4k_iops_lat_th = []

    di.direct_iops_w_max = find_max_where(processed_results,
                                          'd', '4k', 'randwrite')
    di.direct_iops_r_max = find_max_where(processed_results,
                                          'd', '4k', 'randread')
    di.bw_write_max = find_max_where(processed_results,
                                     'd', '16m', 'randwrite', False)
    di.bw_read_max = find_max_where(processed_results,
                                    'd', '16m', 'randread', False)

    for res in processed_results.values():
        if res.raw['sync_mode'] == 's' and res.raw['blocksize'] == '4k':
            if res.raw['rw'] != 'randwrite':
                continue
            rws4k_iops_lat_th.append((res.iops, res.lat,
                                      res.raw['concurence']))

    di.bw_write_max[0] /= 1000
    di.bw_read_max[0] /= 1000

    rws4k_iops_lat_th.sort(key=lambda (_1, _2, conc): conc)

    latv = [lat for _, lat, _ in rws4k_iops_lat_th]

    for tlatv_ms in [10, 30, 100]:
        tlat = tlatv_ms * 1000
        pos = bisect.bisect_left(latv, tlat)
        if 0 == pos:
            iops3 = 0
        elif pos == len(latv):
            iops3 = latv[-1]
        else:
            lat1 = latv[pos - 1]
            lat2 = latv[pos]

            th1 = rws4k_iops_lat_th[pos - 1][2]
            th2 = rws4k_iops_lat_th[pos][2]

            iops1 = rws4k_iops_lat_th[pos - 1][0]
            iops2 = rws4k_iops_lat_th[pos][0]

            th_lat_coef = (th2 - th1) / (lat2 - lat1)
            th3 = th_lat_coef * (tlat - lat1) + th1

            th_iops_coef = (iops2 - iops1) / (th2 - th1)
            iops3 = th_iops_coef * (th3 - th1) + iops1
        setattr(di, 'rws4k_{}ms'.format(tlatv_ms), int(iops3))

    hdi = DiskInfo()

    def pp(x):
        med, dev = round_deviation((x[0], x[1] * x[0]))
        # 3 sigma in %
        dev = int(float(dev) / med * 100)
        return (med, dev)

    hdi.direct_iops_r_max = pp(di.direct_iops_r_max)
    hdi.direct_iops_w_max = pp(di.direct_iops_w_max)
    hdi.bw_write_max = pp(di.bw_write_max)
    hdi.bw_read_max = pp(di.bw_read_max)

    hdi.rws4k_10ms = di.rws4k_10ms if 0 != di.rws4k_10ms else None
    hdi.rws4k_30ms = di.rws4k_30ms if 0 != di.rws4k_30ms else None
    hdi.rws4k_100ms = di.rws4k_100ms if 0 != di.rws4k_100ms else None
    return hdi


@report('HDD', 'hdd_test_rrd4k,hdd_test_rws4k')
def make_hdd_report(processed_results, path, lab_info):
    make_hdd_plots(processed_results, path)
    di = get_disk_info(processed_results)
    render_hdd_html(path, di, lab_info)


@report('Ceph', 'ceph_test')
def make_ceph_report(processed_results, path, lab_info):
    make_ceph_plots(processed_results, path)
    di = get_disk_info(processed_results)
    render_ceph_html(path, di, lab_info)


def make_io_report(results, path, lab_url=None, creds=None):
    lab_info = None

    # if lab_url is not None:
    #     username, password, tenant_name = parse_creds(creds)
    #     creds = {'username': username,
    #              'password': password,
    #              "tenant_name": tenant_name}
    #     try:
    #         data = collect_lab_data(lab_url, creds)
    #         lab_info = total_lab_info(data)
    #     except Exception as exc:
    #         logger.warning("Can't collect lab data: {0!s}".format(exc))

    if lab_info is None:
        lab_info = {
            "total_disk": "None",
            "total_memory": "None",
            "nodes_count": "None",
            "processor_count": "None"
        }

    try:
        processed_results = process_disk_info(results)
        res_fields = sorted(processed_results.keys())
        for fields, name, func in report_funcs:
            for field in fields:
                pos = bisect.bisect_left(res_fields, field)

                if pos == len(res_fields):
                    break

                if not res_fields[pos].startswith(field):
                    break
            else:
                hpath = path.format(name)
                logger.debug("Generatins report " + name + " into " + hpath)
                func(processed_results, hpath, lab_info)
                break
        else:
            logger.warning("No report generator found for this load")

    except Exception as exc:
        import traceback
        traceback.print_exc()
        logger.error("Failed to generate html report:" + str(exc))