KIKIMR-19287: add task_stats_drawing script

1 files changed, 394 insertions, 0 deletions

diff --git a/contrib/python/matplotlib/py3/mpl_toolkits/axisartist/angle_helper.py b/contrib/python/matplotlib/py3/mpl_toolkits/axisartist/angle_helper.py
new file mode 100644
index 0000000000..1786cd70bc
--- /dev/null
+++ b/contrib/python/matplotlib/py3/mpl_toolkits/axisartist/angle_helper.py
@@ -0,0 +1,394 @@
+import numpy as np
+import math
+
+from mpl_toolkits.axisartist.grid_finder import ExtremeFinderSimple
+
+
+def select_step_degree(dv):
+
+    degree_limits_ = [1.5, 3, 7, 13, 20, 40, 70, 120, 270, 520]
+    degree_steps_  = [1,   2, 5, 10, 15, 30, 45,  90, 180, 360]
+    degree_factors = [1.] * len(degree_steps_)
+
+    minsec_limits_ = [1.5, 2.5, 3.5, 8, 11, 18, 25, 45]
+    minsec_steps_  = [1,   2,   3,   5, 10, 15, 20, 30]
+
+    minute_limits_ = np.array(minsec_limits_) / 60
+    minute_factors = [60.] * len(minute_limits_)
+
+    second_limits_ = np.array(minsec_limits_) / 3600
+    second_factors = [3600.] * len(second_limits_)
+
+    degree_limits = [*second_limits_, *minute_limits_, *degree_limits_]
+    degree_steps = [*minsec_steps_, *minsec_steps_, *degree_steps_]
+    degree_factors = [*second_factors, *minute_factors, *degree_factors]
+
+    n = np.searchsorted(degree_limits, dv)
+    step = degree_steps[n]
+    factor = degree_factors[n]
+
+    return step, factor
+
+
+def select_step_hour(dv):
+
+    hour_limits_ = [1.5, 2.5, 3.5, 5, 7, 10, 15, 21, 36]
+    hour_steps_  = [1,   2,   3,   4, 6,  8, 12, 18, 24]
+    hour_factors = [1.] * len(hour_steps_)
+
+    minsec_limits_ = [1.5, 2.5, 3.5, 4.5, 5.5, 8, 11, 14, 18, 25, 45]
+    minsec_steps_  = [1,   2,   3,   4,   5,   6, 10, 12, 15, 20, 30]
+
+    minute_limits_ = np.array(minsec_limits_) / 60
+    minute_factors = [60.] * len(minute_limits_)
+
+    second_limits_ = np.array(minsec_limits_) / 3600
+    second_factors = [3600.] * len(second_limits_)
+
+    hour_limits = [*second_limits_, *minute_limits_, *hour_limits_]
+    hour_steps = [*minsec_steps_, *minsec_steps_, *hour_steps_]
+    hour_factors = [*second_factors, *minute_factors, *hour_factors]
+
+    n = np.searchsorted(hour_limits, dv)
+    step = hour_steps[n]
+    factor = hour_factors[n]
+
+    return step, factor
+
+
+def select_step_sub(dv):
+
+    # subarcsec or degree
+    tmp = 10.**(int(math.log10(dv))-1.)
+
+    factor = 1./tmp
+
+    if 1.5*tmp >= dv:
+        step = 1
+    elif 3.*tmp >= dv:
+        step = 2
+    elif 7.*tmp >= dv:
+        step = 5
+    else:
+        step = 1
+        factor = 0.1*factor
+
+    return step, factor
+
+
+def select_step(v1, v2, nv, hour=False, include_last=True,
+                threshold_factor=3600.):
+
+    if v1 > v2:
+        v1, v2 = v2, v1
+
+    dv = (v2 - v1) / nv
+
+    if hour:
+        _select_step = select_step_hour
+        cycle = 24.
+    else:
+        _select_step = select_step_degree
+        cycle = 360.
+
+    # for degree
+    if dv > 1 / threshold_factor:
+        step, factor = _select_step(dv)
+    else:
+        step, factor = select_step_sub(dv*threshold_factor)
+
+        factor = factor * threshold_factor
+
+    levs = np.arange(np.floor(v1 * factor / step),
+                     np.ceil(v2 * factor / step) + 0.5,
+                     dtype=int) * step
+
+    # n : number of valid levels. If there is a cycle, e.g., [0, 90, 180,
+    # 270, 360], the grid line needs to be extended from 0 to 360, so
+    # we need to return the whole array. However, the last level (360)
+    # needs to be ignored often. In this case, so we return n=4.
+
+    n = len(levs)
+
+    # we need to check the range of values
+    # for example, -90 to 90, 0 to 360,
+
+    if factor == 1. and levs[-1] >= levs[0] + cycle:  # check for cycle
+        nv = int(cycle / step)
+        if include_last:
+            levs = levs[0] + np.arange(0, nv+1, 1) * step
+        else:
+            levs = levs[0] + np.arange(0, nv, 1) * step
+
+        n = len(levs)
+
+    return np.array(levs), n, factor
+
+
+def select_step24(v1, v2, nv, include_last=True, threshold_factor=3600):
+    v1, v2 = v1 / 15, v2 / 15
+    levs, n, factor = select_step(v1, v2, nv, hour=True,
+                                  include_last=include_last,
+                                  threshold_factor=threshold_factor)
+    return levs * 15, n, factor
+
+
+def select_step360(v1, v2, nv, include_last=True, threshold_factor=3600):
+    return select_step(v1, v2, nv, hour=False,
+                       include_last=include_last,
+                       threshold_factor=threshold_factor)
+
+
+class LocatorBase:
+    def __init__(self, nbins, include_last=True):
+        self.nbins = nbins
+        self._include_last = include_last
+
+    def set_params(self, nbins=None):
+        if nbins is not None:
+            self.nbins = int(nbins)
+
+
+class LocatorHMS(LocatorBase):
+    def __call__(self, v1, v2):
+        return select_step24(v1, v2, self.nbins, self._include_last)
+
+
+class LocatorHM(LocatorBase):
+    def __call__(self, v1, v2):
+        return select_step24(v1, v2, self.nbins, self._include_last,
+                             threshold_factor=60)
+
+
+class LocatorH(LocatorBase):
+    def __call__(self, v1, v2):
+        return select_step24(v1, v2, self.nbins, self._include_last,
+                             threshold_factor=1)
+
+
+class LocatorDMS(LocatorBase):
+    def __call__(self, v1, v2):
+        return select_step360(v1, v2, self.nbins, self._include_last)
+
+
+class LocatorDM(LocatorBase):
+    def __call__(self, v1, v2):
+        return select_step360(v1, v2, self.nbins, self._include_last,
+                              threshold_factor=60)
+
+
+class LocatorD(LocatorBase):
+    def __call__(self, v1, v2):
+        return select_step360(v1, v2, self.nbins, self._include_last,
+                              threshold_factor=1)
+
+
+class FormatterDMS:
+    deg_mark = r"^{\circ}"
+    min_mark = r"^{\prime}"
+    sec_mark = r"^{\prime\prime}"
+
+    fmt_d = "$%d" + deg_mark + "$"
+    fmt_ds = r"$%d.%s" + deg_mark + "$"
+
+    # %s for sign
+    fmt_d_m = r"$%s%d" + deg_mark + r"\,%02d" + min_mark + "$"
+    fmt_d_ms = r"$%s%d" + deg_mark + r"\,%02d.%s" + min_mark + "$"
+
+    fmt_d_m_partial = "$%s%d" + deg_mark + r"\,%02d" + min_mark + r"\,"
+    fmt_s_partial = "%02d" + sec_mark + "$"
+    fmt_ss_partial = "%02d.%s" + sec_mark + "$"
+
+    def _get_number_fraction(self, factor):
+        ## check for fractional numbers
+        number_fraction = None
+        # check for 60
+
+        for threshold in [1, 60, 3600]:
+            if factor <= threshold:
+                break
+
+            d = factor // threshold
+            int_log_d = int(np.floor(np.log10(d)))
+            if 10**int_log_d == d and d != 1:
+                number_fraction = int_log_d
+                factor = factor // 10**int_log_d
+                return factor, number_fraction
+
+        return factor, number_fraction
+
+    def __call__(self, direction, factor, values):
+        if len(values) == 0:
+            return []
+
+        ss = np.sign(values)
+        signs = ["-" if v < 0 else "" for v in values]
+
+        factor, number_fraction = self._get_number_fraction(factor)
+
+        values = np.abs(values)
+
+        if number_fraction is not None:
+            values, frac_part = divmod(values, 10 ** number_fraction)
+            frac_fmt = "%%0%dd" % (number_fraction,)
+            frac_str = [frac_fmt % (f1,) for f1 in frac_part]
+
+        if factor == 1:
+            if number_fraction is None:
+                return [self.fmt_d % (s * int(v),) for s, v in zip(ss, values)]
+            else:
+                return [self.fmt_ds % (s * int(v), f1)
+                        for s, v, f1 in zip(ss, values, frac_str)]
+        elif factor == 60:
+            deg_part, min_part = divmod(values, 60)
+            if number_fraction is None:
+                return [self.fmt_d_m % (s1, d1, m1)
+                        for s1, d1, m1 in zip(signs, deg_part, min_part)]
+            else:
+                return [self.fmt_d_ms % (s, d1, m1, f1)
+                        for s, d1, m1, f1
+                        in zip(signs, deg_part, min_part, frac_str)]
+
+        elif factor == 3600:
+            if ss[-1] == -1:
+                inverse_order = True
+                values = values[::-1]
+                signs = signs[::-1]
+            else:
+                inverse_order = False
+
+            l_hm_old = ""
+            r = []
+
+            deg_part, min_part_ = divmod(values, 3600)
+            min_part, sec_part = divmod(min_part_, 60)
+
+            if number_fraction is None:
+                sec_str = [self.fmt_s_partial % (s1,) for s1 in sec_part]
+            else:
+                sec_str = [self.fmt_ss_partial % (s1, f1)
+                           for s1, f1 in zip(sec_part, frac_str)]
+
+            for s, d1, m1, s1 in zip(signs, deg_part, min_part, sec_str):
+                l_hm = self.fmt_d_m_partial % (s, d1, m1)
+                if l_hm != l_hm_old:
+                    l_hm_old = l_hm
+                    l = l_hm + s1
+                else:
+                    l = "$" + s + s1
+                r.append(l)
+
+            if inverse_order:
+                return r[::-1]
+            else:
+                return r
+
+        else:  # factor > 3600.
+            return [r"$%s^{\circ}$" % v for v in ss*values]
+
+
+class FormatterHMS(FormatterDMS):
+    deg_mark = r"^\mathrm{h}"
+    min_mark = r"^\mathrm{m}"
+    sec_mark = r"^\mathrm{s}"
+
+    fmt_d = "$%d" + deg_mark + "$"
+    fmt_ds = r"$%d.%s" + deg_mark + "$"
+
+    # %s for sign
+    fmt_d_m = r"$%s%d" + deg_mark + r"\,%02d" + min_mark+"$"
+    fmt_d_ms = r"$%s%d" + deg_mark + r"\,%02d.%s" + min_mark+"$"
+
+    fmt_d_m_partial = "$%s%d" + deg_mark + r"\,%02d" + min_mark + r"\,"
+    fmt_s_partial = "%02d" + sec_mark + "$"
+    fmt_ss_partial = "%02d.%s" + sec_mark + "$"
+
+    def __call__(self, direction, factor, values):  # hour
+        return super().__call__(direction, factor, np.asarray(values) / 15)
+
+
+class ExtremeFinderCycle(ExtremeFinderSimple):
+    # docstring inherited
+
+    def __init__(self, nx, ny,
+                 lon_cycle=360., lat_cycle=None,
+                 lon_minmax=None, lat_minmax=(-90, 90)):
+        """
+        This subclass handles the case where one or both coordinates should be
+        taken modulo 360, or be restricted to not exceed a specific range.
+
+        Parameters
+        ----------
+        nx, ny : int
+            The number of samples in each direction.
+
+        lon_cycle, lat_cycle : 360 or None
+            If not None, values in the corresponding direction are taken modulo
+            *lon_cycle* or *lat_cycle*; in theory this can be any number but
+            the implementation actually assumes that it is 360 (if not None);
+            other values give nonsensical results.
+
+            This is done by "unwrapping" the transformed grid coordinates so
+            that jumps are less than a half-cycle; then normalizing the span to
+            no more than a full cycle.
+
+            For example, if values are in the union of the [0, 2] and
+            [358, 360] intervals (typically, angles measured modulo 360), the
+            values in the second interval are normalized to [-2, 0] instead so
+            that the values now cover [-2, 2].  If values are in a range of
+            [5, 1000], this gets normalized to [5, 365].
+
+        lon_minmax, lat_minmax : (float, float) or None
+            If not None, the computed bounding box is clipped to the given
+            range in the corresponding direction.
+        """
+        self.nx, self.ny = nx, ny
+        self.lon_cycle, self.lat_cycle = lon_cycle, lat_cycle
+        self.lon_minmax = lon_minmax
+        self.lat_minmax = lat_minmax
+
+    def __call__(self, transform_xy, x1, y1, x2, y2):
+        # docstring inherited
+        x, y = np.meshgrid(
+            np.linspace(x1, x2, self.nx), np.linspace(y1, y2, self.ny))
+        lon, lat = transform_xy(np.ravel(x), np.ravel(y))
+
+        # iron out jumps, but algorithm should be improved.
+        # This is just naive way of doing and my fail for some cases.
+        # Consider replacing this with numpy.unwrap
+        # We are ignoring invalid warnings. They are triggered when
+        # comparing arrays with NaNs using > We are already handling
+        # that correctly using np.nanmin and np.nanmax
+        with np.errstate(invalid='ignore'):
+            if self.lon_cycle is not None:
+                lon0 = np.nanmin(lon)
+                lon -= 360. * ((lon - lon0) > 180.)
+            if self.lat_cycle is not None:
+                lat0 = np.nanmin(lat)
+                lat -= 360. * ((lat - lat0) > 180.)
+
+        lon_min, lon_max = np.nanmin(lon), np.nanmax(lon)
+        lat_min, lat_max = np.nanmin(lat), np.nanmax(lat)
+
+        lon_min, lon_max, lat_min, lat_max = \
+            self._add_pad(lon_min, lon_max, lat_min, lat_max)
+
+        # check cycle
+        if self.lon_cycle:
+            lon_max = min(lon_max, lon_min + self.lon_cycle)
+        if self.lat_cycle:
+            lat_max = min(lat_max, lat_min + self.lat_cycle)
+
+        if self.lon_minmax is not None:
+            min0 = self.lon_minmax[0]
+            lon_min = max(min0, lon_min)
+            max0 = self.lon_minmax[1]
+            lon_max = min(max0, lon_max)
+
+        if self.lat_minmax is not None:
+            min0 = self.lat_minmax[0]
+            lat_min = max(min0, lat_min)
+            max0 = self.lat_minmax[1]
+            lat_max = min(max0, lat_max)
+
+        return lon_min, lon_max, lat_min, lat_max