# coding: utf-8
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"""This module provides the :class:`Scatter` item of the :class:`Plot`.
"""
__authors__ = ["T. Vincent", "P. Knobel"]
__license__ = "MIT"
__date__ = "29/03/2017"
import logging
import numpy
from .core import Points, ColormapMixIn
_logger = logging.getLogger(__name__)
[docs]class Scatter(Points, ColormapMixIn):
"""Description of a scatter"""
_DEFAULT_SYMBOL = 'o'
"""Default symbol of the scatter plots"""
def __init__(self):
Points.__init__(self)
ColormapMixIn.__init__(self)
self._value = ()
def _addBackendRenderer(self, backend):
"""Update backend renderer"""
# Filter-out values <= 0
xFiltered, yFiltered, valueFiltered, xerror, yerror = self.getData(
copy=False, displayed=True)
if len(xFiltered) == 0:
return None # No data to display, do not add renderer to backend
cmap = self.getColormap()
rgbacolors = cmap.applyToData(self._value)
return backend.addCurve(xFiltered, yFiltered, self.getLegend(),
color=rgbacolors,
symbol=self.getSymbol(),
linewidth=0,
linestyle="",
yaxis='left',
xerror=xerror,
yerror=yerror,
z=self.getZValue(),
selectable=self.isSelectable(),
fill=False,
alpha=self.getAlpha(),
symbolsize=self.getSymbolSize())
def _logFilterData(self, xPositive, yPositive):
"""Filter out values with x or y <= 0 on log axes
:param bool xPositive: True to filter arrays according to X coords.
:param bool yPositive: True to filter arrays according to Y coords.
:return: The filtered arrays or unchanged object if not filtering needed
:rtype: (x, y, value, xerror, yerror)
"""
# overloaded from Points to filter also value.
value = self.getValueData(copy=False)
if xPositive or yPositive:
clipped = self._getClippingBoolArray(xPositive, yPositive)
if numpy.any(clipped):
# copy to keep original array and convert to float
value = numpy.array(value, copy=True, dtype=numpy.float)
value[clipped] = numpy.nan
x, y, xerror, yerror = Points._logFilterData(self, xPositive, yPositive)
return x, y, value, xerror, yerror
[docs] def getValueData(self, copy=True):
"""Returns the value assigned to the scatter data points.
:param copy: True (Default) to get a copy,
False to use internal representation (do not modify!)
:rtype: numpy.ndarray
"""
return numpy.array(self._value, copy=copy)
[docs] def getData(self, copy=True, displayed=False):
"""Returns the x, y coordinates and the value of the data points
:param copy: True (Default) to get a copy,
False to use internal representation (do not modify!)
:param bool displayed: True to only get curve points that are displayed
in the plot. Default: False.
Note: If plot has log scale, negative points
are not displayed.
:returns: (x, y, value, xerror, yerror)
:rtype: 5-tuple of numpy.ndarray
"""
if displayed:
data = self._getCachedData()
if data is not None:
assert len(data) == 5
return data
return (self.getXData(copy),
self.getYData(copy),
self.getValueData(copy),
self.getXErrorData(copy),
self.getYErrorData(copy))
# reimplemented from Points to handle `value`
[docs] def setData(self, x, y, value, xerror=None, yerror=None, copy=True):
"""Set the data of the scatter.
:param numpy.ndarray x: The data corresponding to the x coordinates.
:param numpy.ndarray y: The data corresponding to the y coordinates.
:param numpy.ndarray value: The data corresponding to the value of
the data points.
:param xerror: Values with the uncertainties on the x values
:type xerror: A float, or a numpy.ndarray of float32.
If it is an array, it can either be a 1D array of
same length as the data or a 2D array with 2 rows
of same length as the data: row 0 for positive errors,
row 1 for negative errors.
:param yerror: Values with the uncertainties on the y values
:type yerror: A float, or a numpy.ndarray of float32. See xerror.
:param bool copy: True make a copy of the data (default),
False to use provided arrays.
"""
value = numpy.array(value, copy=copy)
assert value.ndim == 1
assert len(x) == len(value)
self._value = value
# set x, y, xerror, yerror
# call self._updated + plot._invalidateDataRange()
Points.setData(self, x, y, xerror, yerror, copy)
