def __init__(self, type="KDE", **kwargs):
self.uod = kwargs.get("uod", None)
"""Universe of discourse"""
self.data = []
data = kwargs.get("data", None)
self.type = type
"""
If type is histogram, the PDF is discrete
If type is KDE the PDF is continuous
"""
self.bins = kwargs.get("bins", None)
"""Number of bins on a discrete PDF"""
self.labels = kwargs.get("bins_labels", None)
"""Bins labels on a discrete PDF"""
if self.type == "KDE":
self.kde = kde.KernelSmoothing(h=kwargs.get("h", 0.5),
kernel=kwargs.get(
"kernel", "epanechnikov"))
if data is not None and self.uod is None:
_min = np.nanmin(data)
_min = _min * .7 if _min > 0 else _min * 1.3
_max = np.nanmax(data)
_max = _max * 1.3 if _max > 0 else _max * .7
self.uod = [_min, _max]
self.nbins = kwargs.get("num_bins", 100)
if self.bins is None:
self.bins = np.linspace(int(self.uod[0]), int(self.uod[1]),
int(self.nbins)).tolist()
self.labels = [str(k) for k in self.bins]
if self.uod is not None:
self.resolution = (self.uod[1] - self.uod[0]) / self.nbins
self.bin_index = SortedCollection.SortedCollection(
iterable=sorted(self.bins))
self.quantile_index = None
self.distribution = {}
self.cdf = None
self.qtl = None
self.count = 0
for k in self.bins:
self.distribution[k] = 0
if data is not None:
self.append(data)
self.name = kwargs.get("name", "")
def __init__(self, type="KDE", **kwargs):
self.uod = kwargs.get("uod", None)
self.data = []
self.type = type
self.bins = kwargs.get("bins", None)
self.labels = kwargs.get("bins_labels", None)
data = kwargs.get("data", None)
if self.type == "KDE":
self.kde = kde.KernelSmoothing(
kwargs.get("h", 0.5), kwargs.get("kernel", "epanechnikov"))
_min = np.nanmin(data)
_min = _min * .7 if _min > 0 else _min * 1.3
_max = np.nanmax(data)
_max = _max * 1.3 if _max > 0 else _max * .7
self.uod = [_min, _max]
self.nbins = kwargs.get("num_bins", 100)
if self.bins is None:
self.bins = np.linspace(int(self.uod[0]), int(self.uod[1]),
int(self.nbins)).tolist()
self.labels = [str(k) for k in self.bins]
if self.uod is not None:
self.resolution = (self.uod[1] - self.uod[0]) / self.nbins
self.bin_index = SortedCollection.SortedCollection(
iterable=sorted(self.bins))
self.quantile_index = None
self.distribution = {}
self.cdf = None
self.qtl = None
self.count = 0
for k in self.bins:
self.distribution[k] = 0
if data is not None:
self.append(data)
self.name = kwargs.get("name", "")