def std_h(
x,
y,
z=1.96,
z_inner=0.675,
color="tab:blue",
label="",
style="o",
alpha=1.0,
ax=None,
):
"""Draw horizontal standard deviation intervals.
Parameters
----------
x : {numpy.array, pandas.core.series.Series}
The vector of data for which the standard deviation interval is sought.
y : int
The location along the y-axis at which the vertical interval is placed.
z_inner : float, 0.675 by default
The number of standard deviations from the mean for the inner bound.
color : string, 'tab:blue' by default
The color of the rug.
label : string, '' (empty) by default
The label within a potential legend.
style : string, 'o' by default
The shape of the mean point.
alpha : float, 1.0 by default
The transparency of the color. Values between 0 (transparent) and 1 (opague) are allowed.
ax : matplotlib.pyplot.Axes, None by default
The axis onto which the box is drawn. If left as None,
matplotlib.pyplot.gca() is called to get the current `Axes`.
Returns
-------
out : matplotlib.pyplot.Axes
The `Axes` onto which the box was drawn.
"""
x, _, ax = check_data(x, None, ax)
xbar, std = np.mean(x), np.std(x)
lw_mid, uw_mid = xbar - z_inner * std, xbar + z_inner * std
lw, uw = xbar - z * std, xbar + z * std
line_h(y, lw, uw, color=color, alpha=alpha)
line_h(y, lw_mid, uw_mid, lw=4, color=color, alpha=alpha)
out = point(xbar,
y,
color=color,
label=label,
size=2,
style=style,
alpha=alpha)
return out
def box_h(x,
y,
color="tab:blue",
label="",
style="o",
alpha=1.0,
ax=None,
**kws):
"""Draw horizontal box plot.
Parameters
----------
x : {numpy.array, pandas.core.series.Series}
The vector of data for which the standard five number summary
is sought.
y : scalar
The location along the x-axis at which the vertical box is placed.
color : string, 'tab:blue' by default
The color of the box.
label : string, '' (empty) by default
The label within a potential legend.
style : string, 'o' by default
The shape of the median within the box.
alpha : float, 1.0 by default
The transparency of the color. Values between 0 (transparent) and 1 (opague) are allowed.
ax : matplotlib.pyplot.Axes, None by default
The axis onto which the box is drawn. If left as None,
matplotlib.pyplot.gca() is called to get the current `Axes`.
Returns
-------
out : matplotlib.pyplot.Axes
The `Axes` onto which the box was drawn.
"""
x, _, ax = check_data(x, None, ax)
q1, q2, q3, lw, uw = _bx(x)
line_h(y, lw, uw, size=2, color=color, alpha=alpha)
line_h(y, q1, q3, size=5, color=color, alpha=alpha)
u_outs = x[np.where(x > uw)]
l_outs = x[np.where(x < lw)]
point(u_outs,
np.repeat(y, u_outs.size),
style="*",
color=color,
alpha=alpha)
point(l_outs,
np.repeat(y, l_outs.size),
style="*",
color=color,
alpha=alpha)
out = point(q2,
y,
size=2,
style=style,
color=color,
label=label,
alpha=alpha)
return out
def percentile_h(x,
y,
outer=0.8,
inner=0.5,
color="tab:blue",
label="",
style="o",
alpha=1,
ax=None,
**kws):
"""Draw horizontal percentile interval.
Parameters
----------
x : {numpy.array, pandas.core.series.Series}
The vector of data for which the `outer` percentile interval is sought.
y : int
The location along the y-axis at which the interval is placed.
outer : float, 0.8 by default
The outer interval percentage.
inner : float, 0.5 by default
The inner interval percentage.
color : string, 'tab:blue' by default
The color of the box.
label : string, '' (empty) by default
The label within a potential legend.
style : string, 'o' by default
The shape of the median within the box.
alpha : float, 1.0 by default
The transparency of the color. Values between 0 (transparent) and 1 (opague) are allowed.
ax : matplotlib.pyplot.Axes, None by default
The axis onto which the box is drawn. If left as None,
matplotlib.pyplot.gca() is called to get the current `Axes`.
Returns
-------
out : matplotlib.pyplot.Axes
The `Axes` onto which the box was drawn.
"""
x, _, ax = check_data(x, None, ax)
alpha_l, alpha_lm = (1 - outer) / 2, (1 - inner) / 2
l, lm, m, um, u = alpha_l, alpha_lm, 0.5, 1 - alpha_lm, 1 - alpha_l
q_l, q_lm, q_m, q_um, q_u = np.percentile(
x,
np.array([l, lm, m, um, u]) * 100)
line_h(y, q_l, q_u, size=2, color=color, alpha=alpha)
line_h(y, q_lm, q_um, size=5, color=color, alpha=alpha)
out = point(q_m,
y,
size=2,
style=style,
color=color,
label=label,
alpha=alpha)
return out
def lag(x,
lag=1,
color="tab:blue",
label="",
style="o",
size=1.0,
alpha=1.0,
ax=None,
**kws):
"""Draw lag plot.
Parameters
----------
x : {numpy.array, pandas.core.series.Series}
The location along the x-axis at which the lags are drawn.
lag : float, 1 by default
The lag of the plot.
color : string, 'tab:blue' by default
The color of the box.
label : string, '' (empty) by default
The label within a potential legend.
size : int, 1 by default
The size of the points to draw. In matplotlib terms, this is equivalent to mpl.rcParam['lines.markersize'] = 6**(size + 1).
style : string, 'o' by default
The shape of the median within the box.
alpha : float, 1.0 by default
The transparency of the color. Values between 0 (transparent) and 1 (opague) are allowed.
ax : matplotlib.pyplot.Axes, None by default
The axis onto which the box is drawn. If left as None,
matplotlib.pyplot.gca() is called to get the current `Axes`.
Returns
-------
out : matplotlib.pyplot.Axes
The `Axes` onto which the box was drawn.
"""
x, _, ax = check_data(x, None, ax)
y1 = x[:-lag]
y2 = x[lag:]
out = point(y1,
y2,
color=color,
label=label,
style=style,
size=size,
alpha=alpha,
ax=ax,
**kws)
return out
def mad(
x,
y,
z=1.96,
z_inner=0.675,
color="tab:blue",
label="",
style="o",
alpha=1.0,
ax=None,
):
"""Draw vertical median absolute deviation intervals.
Parameters
----------
x : int
The location along the x-axis at which the vertical interval is placed.
y : {numpy.array, pandas.core.series.Series}
The vector of data for which the standard deviation is sought.
z : float, 1.96 by default
The number of standard deviations from the mean for the outer bound.
z_inner : float, 0.675 by default
The number of standard deviations from the mean for the inner bound.
color : string, 'tab:blue' by default
The color of the rug.
label : string, '' (empty) by default
The label within a potential legend.
style : string, 'o' by default
The shape of the mean point.
alpha : float, 1.0 by default
The transparency of the color. Values between 0 (transparent) and 1 (opague) are allowed.
ax : matplotlib.pyplot.Axes, None by default
The axis onto which the box is drawn. If left as None,
matplotlib.pyplot.gca() is called to get the current `Axes`.
Returns
-------
out : matplotlib.pyplot.Axes
The `Axes` onto which the box was drawn.
"""
_, y, ax = check_data(None, y, ax)
med, mad = np.median(y), mad_std(y) / norm.ppf(0.75)
lw_mid, uw_mid = med - z_inner * mad, med + z_inner * mad
lw, uw = med - z * mad, med + z * mad
line_v(x, lw, uw, size=2, color=color, alpha=alpha)
line_v(x, lw_mid, uw_mid, size=5, color=color, alpha=alpha)
out = point(x,
med,
size=2,
style=style,
color=color,
label=label,
alpha=alpha)
return out