# coding: utf-8
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#
# Copyright (c) 2017 European Synchrotron Radiation Facility
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"""This module defines widgets used by _NXdataView.
"""
__authors__ = ["P. Knobel"]
__license__ = "MIT"
__date__ = "27/06/2017"

import numpy

from silx.gui import qt
from silx.gui.data.NumpyAxesSelector import NumpyAxesSelector
from silx.gui.plot import Plot1D, Plot2D, StackView

from silx.math.calibration import ArrayCalibration, NoCalibration, LinearCalibration


class ArrayCurvePlot(qt.QWidget):
    """
    Widget for plotting a curve from a multi-dimensional signal array
    and a 1D axis array.

    The signal array can have an arbitrary number of dimensions, the only
    limitation being that the last dimension must have the same length as
    the axis array.

    The widget provides sliders to select indices on the first (n - 1)
    dimensions of the signal array, and buttons to add/replace selected
    curves to the plot.

    This widget also handles simple 2D or 3D scatter plots (third dimension
    displayed as colour of points).
    """
    def __init__(self, parent=None):
        """

        :param parent: Parent QWidget
        """
        super(ArrayCurvePlot, self).__init__(parent)

        self.__signal = None
        self.__signal_name = None
        self.__signal_errors = None
        self.__axis = None
        self.__axis_name = None
        self.__axis_errors = None
        self.__values = None

        self.__first_curve_added = False

        self._plot = Plot1D(self)
        self._plot.setDefaultColormap(   # for scatters
                {"name": "viridis",
                 "vmin": 0., "vmax": 1.,   # ignored (autoscale) but mandatory
                 "normalization": "linear",
                 "autoscale": True})

        self.selectorDock = qt.QDockWidget("Data selector", self._plot)
        # not closable
        self.selectorDock.setFeatures(qt.QDockWidget.DockWidgetMovable |
                                qt.QDockWidget.DockWidgetFloatable)
        self._selector = NumpyAxesSelector(self.selectorDock)
        self._selector.setNamedAxesSelectorVisibility(False)
        self.__selector_is_connected = False
        self.selectorDock.setWidget(self._selector)
        self._plot.addTabbedDockWidget(self.selectorDock)

        layout = qt.QGridLayout()
        layout.setContentsMargins(0, 0, 0, 0)
        layout.addWidget(self._plot,  0, 0)

        self.setLayout(layout)

    def setCurveData(self, y, x=None, values=None,
                     yerror=None, xerror=None,
                     ylabel=None, xlabel=None, title=None):
        """

        :param y: dataset to be represented by the y (vertical) axis.
            For a scatter, this must be a 1D array and x and values must be
            1-D arrays of the same size.
            In other cases, it can be a n-D array whose last dimension must
            have the same length as x (and values must be None)
        :param x: 1-D dataset used as the curve's x values. If provided,
            its lengths must be equal to the length of the last dimension of
            ``y`` (and equal to the length of ``value``, for a scatter plot).
        :param values: Values, to be provided for a x-y-value scatter plot.
            This will be used to compute the color map and assign colors
            to the points.
        :param yerror: 1-D dataset of errors for y, or None
        :param xerror: 1-D dataset of errors for x, or None
        :param ylabel: Label for Y axis
        :param xlabel: Label for X axis
        :param title: Graph title
        """
        self.__signal = y
        self.__signal_name = ylabel
        self.__signal_errors = yerror
        self.__axis = x
        self.__axis_name = xlabel
        self.__axis_errors = xerror
        self.__values = values

        if self.__selector_is_connected:
            self._selector.selectionChanged.disconnect(self._updateCurve)
            self.__selector_is_connected = False
        self._selector.setData(y)
        self._selector.setAxisNames([ylabel or "Y"])

        if len(y.shape) < 2:
            self.selectorDock.hide()
        else:
            self.selectorDock.show()

        self._plot.setGraphTitle(title or "")
        self._plot.getXAxis().setLabel(self.__axis_name or "X")
        self._plot.getYAxis().setLabel(self.__signal_name or "Y")
        self._updateCurve()

        if not self.__selector_is_connected:
            self._selector.selectionChanged.connect(self._updateCurve)
            self.__selector_is_connected = True

    def _updateCurve(self):
        y = self._selector.selectedData()
        x = self.__axis
        if x is None:
            x = numpy.arange(len(y))
        elif numpy.isscalar(x) or len(x) == 1:
            # constant axis
            x = x * numpy.ones_like(y)
        elif len(x) == 2 and len(y) != 2:
            # linear calibration a + b * x
            x = x[0] + x[1] * numpy.arange(len(y))
        legend = self.__signal_name + "["
        for sl in self._selector.selection():
            if sl == slice(None):
                legend += ":, "
            else:
                legend += str(sl) + ", "
        legend = legend[:-2] + "]"
        if self.__signal_errors is not None:
            y_errors = self.__signal_errors[self._selector.selection()]
        else:
            y_errors = None

        self._plot.remove(kind=("curve", "scatter"))

        # values: x-y-v scatter
        if self.__values is not None:
            self._plot.addScatter(x, y, self.__values,
                                  legend=legend,
                                  xerror=self.__axis_errors,
                                  yerror=y_errors)

        # x monotonically increasing: curve
        elif numpy.all(numpy.diff(x) > 0):
            self._plot.addCurve(x, y, legend=legend,
                                xerror=self.__axis_errors,
                                yerror=y_errors)

        # scatter
        else:
            self._plot.addScatter(x, y, value=numpy.ones_like(y),
                                  legend=legend,
                                  xerror=self.__axis_errors,
                                  yerror=y_errors)
        self._plot.resetZoom()
        self._plot.getXAxis().setLabel(self.__axis_name)
        self._plot.getYAxis().setLabel(self.__signal_name)

    def clear(self):
        self._plot.clear()


class ArrayImagePlot(qt.QWidget):
    """
    Widget for plotting an image from a multi-dimensional signal array
    and two 1D axes array.

    The signal array can have an arbitrary number of dimensions, the only
    limitation being that the last two dimensions must have the same length as
    the axes arrays.

    Sliders are provided to select indices on the first (n - 2) dimensions of
    the signal array, and the plot is updated to show the image corresponding
    to the selection.

    If one or both of the axes does not have regularly spaced values, the
    the image is plotted as a coloured scatter plot.
    """
    def __init__(self, parent=None):
        """

        :param parent: Parent QWidget
        """
        super(ArrayImagePlot, self).__init__(parent)

        self.__signal = None
        self.__signal_name = None
        self.__x_axis = None
        self.__x_axis_name = None
        self.__y_axis = None
        self.__y_axis_name = None

        self._plot = Plot2D(self)
        self._plot.setDefaultColormap(
                {"name": "viridis",
                 "vmin": 0., "vmax": 1.,   # ignored (autoscale) but mandatory
                 "normalization": "linear",
                 "autoscale": True})

        self.selectorDock = qt.QDockWidget("Data selector", self._plot)
        # not closable
        self.selectorDock.setFeatures(qt.QDockWidget.DockWidgetMovable |
                                      qt.QDockWidget.DockWidgetFloatable)
        self._legend = qt.QLabel(self)
        self._selector = NumpyAxesSelector(self.selectorDock)
        self._selector.setNamedAxesSelectorVisibility(False)
        self.__selector_is_connected = False

        layout = qt.QVBoxLayout()
        layout.addWidget(self._plot)
        layout.addWidget(self._legend)
        self.selectorDock.setWidget(self._selector)
        self._plot.addTabbedDockWidget(self.selectorDock)

        self.setLayout(layout)

    def setImageData(self, signal,
                     x_axis=None, y_axis=None,
                     signal_name=None,
                     xlabel=None, ylabel=None,
                     title=None):
        """

        :param signal: n-D dataset, whose last 2 dimensions are used as the
            image's values.
        :param x_axis: 1-D dataset used as the image's x coordinates. If
            provided, its lengths must be equal to the length of the last
            dimension of ``signal``.
        :param y_axis: 1-D dataset used as the image's y. If provided,
            its lengths must be equal to the length of the 2nd to last
            dimension of ``signal``.
        :param signal_name: Label used in the legend
        :param xlabel: Label for X axis
        :param ylabel: Label for Y axis
        :param title: Graph title
        """
        if self.__selector_is_connected:
            self._selector.selectionChanged.disconnect(self._updateImage)
            self.__selector_is_connected = False

        self.__signal = signal
        self.__signal_name = signal_name or ""
        self.__x_axis = x_axis
        self.__x_axis_name = xlabel
        self.__y_axis = y_axis
        self.__y_axis_name = ylabel

        self._selector.setData(signal)
        self._selector.setAxisNames([ylabel or "Y", xlabel or "X"])

        if len(signal.shape) < 3:
            self.selectorDock.hide()
        else:
            self.selectorDock.show()

        self._plot.setGraphTitle(title or "")
        self._plot.getXAxis().setLabel(self.__x_axis_name or "X")
        self._plot.getYAxis().setLabel(self.__y_axis_name or "Y")

        self._updateImage()

        if not self.__selector_is_connected:
            self._selector.selectionChanged.connect(self._updateImage)
            self.__selector_is_connected = True

    def _updateImage(self):
        legend = self.__signal_name + "["
        for sl in self._selector.selection():
            if sl == slice(None):
                legend += ":, "
            else:
                legend += str(sl) + ", "
        legend = legend[:-2] + "]"
        self._legend.setText("Displayed data: " + legend)

        img = self._selector.selectedData()
        x_axis = self.__x_axis
        y_axis = self.__y_axis

        if x_axis is None and y_axis is None:
            xcalib = NoCalibration()
            ycalib = NoCalibration()
        else:
            if x_axis is None:
                # no calibration
                x_axis = numpy.arange(img.shape[-1])
            elif numpy.isscalar(x_axis) or len(x_axis) == 1:
                # constant axis
                x_axis = x_axis * numpy.ones((img.shape[-1], ))
            elif len(x_axis) == 2:
                # linear calibration
                x_axis = x_axis[0] * numpy.arange(img.shape[-1]) + x_axis[1]

            if y_axis is None:
                y_axis = numpy.arange(img.shape[-2])
            elif numpy.isscalar(y_axis) or len(y_axis) == 1:
                y_axis = y_axis * numpy.ones((img.shape[-2], ))
            elif len(y_axis) == 2:
                y_axis = y_axis[0] * numpy.arange(img.shape[-2]) + y_axis[1]

            xcalib = ArrayCalibration(x_axis)
            ycalib = ArrayCalibration(y_axis)

        self._plot.remove(kind=("scatter", "image"))
        if xcalib.is_affine() and ycalib.is_affine():
            # regular image
            xorigin, xscale = xcalib(0), xcalib.get_slope()
            yorigin, yscale = ycalib(0), ycalib.get_slope()
            origin = (xorigin, yorigin)
            scale = (xscale, yscale)

            self._plot.addImage(img, legend=legend,
                                origin=origin, scale=scale)
        else:
            scatterx, scattery = numpy.meshgrid(x_axis, y_axis)
            self._plot.addScatter(numpy.ravel(scatterx),
                                  numpy.ravel(scattery),
                                  numpy.ravel(img),
                                  legend=legend)
        self._plot.getXAxis().setLabel(self.__x_axis_name)
        self._plot.getYAxis().setLabel(self.__y_axis_name)
        self._plot.resetZoom()

    def clear(self):
        self._plot.clear()


class ArrayStackPlot(qt.QWidget):
    """
    Widget for plotting a n-D array (n >= 3) as a stack of images.
    Three axis arrays can be provided to calibrate the axes.

    The signal array can have an arbitrary number of dimensions, the only
    limitation being that the last 3 dimensions must have the same length as
    the axes arrays.

    Sliders are provided to select indices on the first (n - 3) dimensions of
    the signal array, and the plot is updated to load the stack corresponding
    to the selection.
    """
    def __init__(self, parent=None):
        """

        :param parent: Parent QWidget
        """
        super(ArrayStackPlot, self).__init__(parent)

        self.__signal = None
        self.__signal_name = None
        # the Z, Y, X axes apply to the last three dimensions of the signal
        # (in that order)
        self.__z_axis = None
        self.__z_axis_name = None
        self.__y_axis = None
        self.__y_axis_name = None
        self.__x_axis = None
        self.__x_axis_name = None

        self._stack_view = StackView(self)
        self._hline = qt.QFrame(self)
        self._hline.setFrameStyle(qt.QFrame.HLine)
        self._hline.setFrameShadow(qt.QFrame.Sunken)
        self._legend = qt.QLabel(self)
        self._selector = NumpyAxesSelector(self)
        self._selector.setNamedAxesSelectorVisibility(False)
        self.__selector_is_connected = False

        layout = qt.QVBoxLayout()
        layout.addWidget(self._stack_view)
        layout.addWidget(self._hline)
        layout.addWidget(self._legend)
        layout.addWidget(self._selector)

        self.setLayout(layout)

    def setStackData(self, signal,
                     x_axis=None, y_axis=None, z_axis=None,
                     signal_name=None,
                     xlabel=None, ylabel=None, zlabel=None,
                     title=None):
        """

        :param signal: n-D dataset, whose last 3 dimensions are used as the
            3D stack values.
        :param x_axis: 1-D dataset used as the image's x coordinates. If
            provided, its lengths must be equal to the length of the last
            dimension of ``signal``.
        :param y_axis: 1-D dataset used as the image's y. If provided,
            its lengths must be equal to the length of the 2nd to last
            dimension of ``signal``.
        :param z_axis: 1-D dataset used as the image's z. If provided,
            its lengths must be equal to the length of the 3rd to last
            dimension of ``signal``.
        :param signal_name: Label used in the legend
        :param xlabel: Label for X axis
        :param ylabel: Label for Y axis
        :param zlabel: Label for Z axis
        :param title: Graph title
        """
        if self.__selector_is_connected:
            self._selector.selectionChanged.disconnect(self._updateStack)
            self.__selector_is_connected = False

        self.__signal = signal
        self.__signal_name = signal_name or ""
        self.__x_axis = x_axis
        self.__x_axis_name = xlabel
        self.__y_axis = y_axis
        self.__y_axis_name = ylabel
        self.__z_axis = z_axis
        self.__z_axis_name = zlabel

        self._selector.setData(signal)
        self._selector.setAxisNames([ylabel or "Y", xlabel or "X", zlabel or "Z"])

        self._stack_view.setGraphTitle(title or "")
        # by default, the z axis is the image position (dimension not plotted)
        self._stack_view.getPlot().getXAxis().setLabel(self.__x_axis_name or "X")
        self._stack_view.getPlot().getYAxis().setLabel(self.__y_axis_name or "Y")

        self._updateStack()

        ndims = len(signal.shape)
        self._stack_view.setFirstStackDimension(ndims - 3)

        # the legend label shows the selection slice producing the volume
        # (only interesting for ndim > 3)
        if ndims > 3:
            self._selector.setVisible(True)
            self._legend.setVisible(True)
            self._hline.setVisible(True)
        else:
            self._selector.setVisible(False)
            self._legend.setVisible(False)
            self._hline.setVisible(False)

        if not self.__selector_is_connected:
            self._selector.selectionChanged.connect(self._updateStack)
            self.__selector_is_connected = True

    @staticmethod
    def _get_origin_scale(axis):
        """Assuming axis is a regularly spaced 1D array,
        return a tuple (origin, scale) where:
            - origin = axis[0]
            - scale = (axis[n-1] - axis[0]) / (n -1)
        :param axis: 1D numpy array
        :return: Tuple (axis[0], (axis[-1] - axis[0]) / (len(axis) - 1))
        """
        return axis[0], (axis[-1] - axis[0]) / (len(axis) - 1)

    def _updateStack(self):
        """Update displayed stack according to the current axes selector
        data."""
        stk = self._selector.selectedData()
        x_axis = self.__x_axis
        y_axis = self.__y_axis
        z_axis = self.__z_axis

        calibrations = []
        for axis in [z_axis, y_axis, x_axis]:

            if axis is None:
                calibrations.append(NoCalibration())
            elif len(axis) == 2:
                calibrations.append(
                        LinearCalibration(y_intercept=axis[0],
                                          slope=axis[1]))
            else:
                calibrations.append(ArrayCalibration(axis))

        legend = self.__signal_name + "["
        for sl in self._selector.selection():
            if sl == slice(None):
                legend += ":, "
            else:
                legend += str(sl) + ", "
        legend = legend[:-2] + "]"
        self._legend.setText("Displayed data: " + legend)

        self._stack_view.setStack(stk, calibrations=calibrations)
        self._stack_view.setLabels(
                labels=[self.__z_axis_name,
                        self.__y_axis_name,
                        self.__x_axis_name])

    def clear(self):
        self._stack_view.clear()