import collections
import operator
import vaex.vaexfast
import threading
import matplotlib
import numpy as np
import scipy.ndimage
import matplotlib.colors
import traceback

import vaex
import vaex.delayed
import vaex.ui.storage
import vaex.ui.undo
import vaex.ui.colormaps
import vaex.grids
from vaex.ui.icons import iconfile
import vaex.utils
import vaex.promise
import vaex.ui.qt as dialogs

__author__ = 'maartenbreddels'

import copy
import functools
import time
from vaex.ui.qt import *
import logging
import astropy.units
try:
    import healpy
except BaseException:
    healpy = None

import vaex.dataset
import vaex.ui.completer

# from attrdict import AttrDict
from .plot_windows import AttrDict


logger = logging.getLogger("vaex.ui.layer")

storage_expressions = vaex.ui.storage.Storage("expressions")


class multilayer_attrsetter(object):
    def __init__(self, layer, name):
        self.layer = layer
        self.name = name

    def __call__(self, value):
        if QtGui.QApplication.keyboardModifiers() == QtCore.Qt.ShiftModifier:
            for layer in self.layer.plot_window.layers:
                setattr(layer, self.name, value)
        else:
            setattr(self.layer, self.name, value)


# options.define_options("grid_size", int, validator=options.is_power_of_two)
class LinkButton(QtGui.QToolButton):
    def __init__(self, title, dataset, axis_index, parent):
        super(LinkButton, self).__init__(parent)
        self.setToolTip("link this axes with others (experimental and unstable)")
        self.plot = parent
        self.dataset = dataset
        self.axis_index = axis_index
        self.setText(title)
        # self.setAcceptDrops(True)
        # self.disconnect_icon = QtGui.QIcon(iconfile('network-disconnect-2'))
        # self.connect_icon = QtGui.QIcon(iconfile('network-connect-3'))
        self.disconnect_icon = QtGui.QIcon(iconfile('link_break'))
        self.connect_icon = QtGui.QIcon(iconfile('link'))
        # self.setIcon(self.disconnect_icon)

        # self.action_link_global = QtGui.QAction(self.connect_icon, '&Global link', self)
        # self.action_unlink = QtGui.QAction(self.connect_icon, '&Unlink', self)
        # self.menu = QtGui.QMenu()
        # self.menu.addAction(self.action_link_global)
        # self.menu.addAction(self.action_unlink)
        # self.action_link_global.triggered.connect(self.onLinkGlobal)
        self.setToolTip("Link or unlink axis. When an axis is linked, changing an axis (like zooming) will update all axis of plots that have the same (and linked) axis.")
        self.setToolButtonStyle(QtCore.Qt.ToolButtonIconOnly)
        self.setIcon(self.disconnect_icon)
        # self.setDefaultAction(self.action_link_global)
        self.setCheckable(True)
        self.setChecked(False)
        self.clicked.connect(self.onToggleLink)
        # self.setMenu(self.menu)
        self.link = None

    def onToggleLink(self):
        if self.isChecked():
            logger.debug("connected link")
            self.link = self.dataset.link(self.plot.expressions[self.axis_index], self)
            self.setIcon(self.connect_icon)
        else:
            logger.debug("disconnecting link")
            self.dataset.unlink(self.link, self)
            self.link = None
            self.setIcon(self.disconnect_icon)

    def onLinkGlobal(self):
        self.link = self.dataset.link(self.plot.expressions[self.axis_index], self)
        logger.debug("made global link: %r" % self.link)
        # self.parent.links[self.axis_index] = self.linkHandle

    def onChangeRangeShow(self, range_):
        logger.debug("received range show change for plot=%r, axis_index %r, range=%r" % (self.plot, self.axis_index, range_))
        self.plot.ranges_show[self.axis_index] = range_

    def onChangeRange(self, range_):
        logger.debug("received range change for plot=%r, axis_index %r, range=%r" % (self.plot, self.axis_index, range_))
        self.plot.ranges[self.axis_index] = range_

    def onCompute(self):
        logger.debug("received compute for plot=%r, axis_index %r" % (self.plot, self.axis_index))
        self.plot.compute()

    def onPlot(self):
        logger.debug("received plot command for plot=%r, axis_index %r" % (self.plot, self.axis_index))
        self.plot.plot()

    def onLinkLimits(self, min, max):
        self.plot.expressions[self.axis_index] = expression

    def onChangeExpression(self, expression):
        logger.debug("received change expression for plot=%r, axis_index %r, expression=%r" % (self.plot, self.axis_index, expression))
        self.plot.expressions[self.axis_index] = expression
        self.plot.axisboxes[self.axis_index].lineEdit().setText(expression)

    def _dragEnterEvent(self, e):
        print(e.mimeData())
        print(e.mimeData().text())
        if e.mimeData().hasFormat('text/plain'):
            e.accept()

        else:
            e.ignore()

    def dropEvent(self, e):
        position = e.pos()
        # self.button.move(position)
        print("do", e.mimeData().text())
        e.setDropAction(QtCore.Qt.MoveAction)
        e.accept()

    def _mousePressEvent(self, e):

        super(LinkButton, self).mousePressEvent(e)

        if e.button() == QtCore.Qt.LeftButton:
            print('press')

    def _mouseMoveEvent(self, e):
        if e.buttons() != QtCore.Qt.LeftButton:
            return

        mimeData = QtCore.QMimeData()

        drag = QtGui.QDrag(self)
        drag.setMimeData(mimeData)
        drag.setHotSpot(e.pos() - self.rect().topLeft())
        mimeData.setText("blaat")

        dropAction = drag.start(QtCore.Qt.MoveAction)


class LayerTable(object):
    def __init__(self, plot_window, name, dataset, expressions, axis_names, options, figure, canvas, ranges_grid=None):
        """
        :type tasks: list[Task]
        :type dataset: Dataset
        :type plot_window: PlotDialog
        """
        self.plot_window = plot_window
        self.name = name
        self.dataset = dataset
        self.axis_names = axis_names

        self.state = AttrDict()

        self.state.ranges_grid = ranges_grid
        self.state.title = options.get("title")

        self.range_level = None
        self.options = options
        self.state.expressions = expressions
        self.dimensions = len(self.state.expressions)
        self.state.vector_expressions = [None, ] * (1 if self.dimensions == 1 else 3)
        self.figure = figure
        self.canvas = canvas
        self.widget_build = False
        self.grid_vector = None

        self._can_plot = False  # when every process went though ok, this is True
        self._needs_update = True

        self.widget = None  # each layer has a widget, atm only a qt widget is implemented

        self.reset_progressbar()

        self.state.weight = self.options.get("weight", self.dataset.get_column_names()[0])
        self.state.statistic = self.options.get("statistic", "count")
        self.state.weight_count = self.options.get("weight_count", "*")
        self.state.amplitudes = {}
        self.state.amplitudes["count"] = "log10(grid)"
        self.state.amplitudes["mean"] = "grid"
        self.state.amplitudes["sum"] = "grid"
        self.state.amplitudes["std"] = "grid"
        self.state.amplitudes["var"] = "grid"
        self.state.amplitudes["min"] = "grid"
        self.state.amplitudes["max"] = "grid"
        self.state.show_disjoined = False
        self.state.dataset_path = self.dataset.path
        self.state.name = self.dataset.name

        self.compute_counter = 0
        self.sequence_index = 0
        self.state.alpha = float(self.options.get("alpha", "1."))
        self.state.style = options.get("style", "histogram")
        # self.color = self.options.get("color")
        self.level_min = 0.
        self.level_max = 1.
        # self.use_intensity = bool(self.options.get("use_intensity", True))

        self.coordinates_picked_row = None

        self.layer_slice_source = None  # the layer we link to for slicing
        self.slice_axis = []  # list of booleans, which axis we listen to

        # we keep a list of vaex.dataset.Task, so that we can cancel, listen
        # to progress etc
        self.tasks = []
        self._task_signals = []

        self._histogram_counter = 0  # TODO: until we can cancel the server, we have to fix it with a counter

        self.state.colormap = "PaulT_plusmin"  # "binary"
        self.state.colormap_vector = "binary"
        if "lim" in self.options:
            for i in range(self.dimensions):
                self.state.ranges_grid[i] = eval(self.options["lim"])
        if "ranges" in self.options:
            ranges = self.options["ranges"]
            if isinstance(self.options["ranges"], str):
                ranges = eval(ranges)
            for i in range(self.dimensions):
                self.state.ranges_grid[i] = ranges[i]
        if "xlim" in self.options:
            self.state.ranges_grid[0] = eval(self.options["xlim"])
        if "ylim" in self.options:
            self.state.ranges_grid[1] = eval(self.options["ylim"])
        if "zlim" in self.options:
            self.state.ranges_grid[2] = eval(self.options["zlim"])
        if "aspect" in self.options:
            self.aspect = eval(self.options["aspect"])
            self.action_aspect_lock_one.setChecked(True)
        if "compact" in self.options:
            value = self.options["compact"]
            if value in ["ultra", "+"]:
                self.action_mini_mode_ultra.trigger()
            else:
                self.action_mini_mode_normal.trigger()

        self.first_time = True

        self.state.show_disjoined = False  # show p(x,y) as p(x)p(y)

        if self.state.ranges_grid is None:
            self.submit_job_minmax()

        # self.dataset.mask_listeners.append(self.onSelectMask)
        self.dataset.signal_selection_changed.connect(self.on_selection_changed)
        self.dataset.signal_column_changed.connect(self.on_column_changed)
        self.dataset.signal_variable_changed.connect(self.on_variable_changed)
        # self.dataset.signal_selection_changed.
        # self.dataset.row_selection_listeners.append(self.onSelectRow)
        self.dataset.signal_pick.connect(self.on_pick)
        self.dataset.signal_sequence_index_change.connect(self.on_sequence_changed)
        # self.dataset.serie_index_selection_listeners.append(self.onSerieIndexSelect)
        self.plot_density = self.plot_density_imshow
        self.signal_expression_change = vaex.events.Signal("expression_change")
        self.signal_plot_dirty = vaex.events.Signal("plot_dirty")
        self.signal_plot_update = vaex.events.Signal("plot_update")
        self.signal_needs_update = vaex.events.Signal("needs update")
        # self.dataset.signal_pick.connect(self.on)

    def __repr__(self):
        classname = self.__class__.__module__ + "." + self.__class__.__name__
        return "<%s(name=%r, expressions=%r)> instance at 0x%x" % (classname, self.name, self.state.expressions, id(self))

    def amplitude_label(self):
        unit_expression = None
        what_units = None
        statistics = self.statistic
        if statistics in ["mean", "sum", "std", "min", "max", "median"]:
            unit_expression = self.weight
        if statistics in ["var"]:
            unit_expression = "(%s) * (%s)" % (self.weight, self.weight)
        if unit_expression:
            unit = self.dataset.unit(unit_expression)
            if unit:
                what_units = unit.to_string('latex_inline')
        label = "%s(%s)" % (self.statistic, self.weight if self.statistic is not "count" else self.weight_count)
        label = self.amplitude.replace("grid", label)
        if what_units:
            label += " (%s)" % what_units
        return label

    def restore_state(self, state):
        logger.debug("restoring layer %r to state %r ", self, state)
        self.state = AttrDict(state)
        for dim in range(self.dimensions):
            logger.debug("set expression[%i] to %s", dim, self.state.expressions[dim])
            self.set_expression(self.state.expressions[dim], dim)
        for dim in range(self.vector_dimensions):
            logger.debug("set vector expression[%i] to %s", dim, self.state.vector_expressions[dim])
            self.set_vector_expression(self.state.vector_expressions[dim], dim)
        # logger.debug("set weight expression to %s", dim, self.state.weight_expression)
        # self.set_weight_expression(self.state.weight_expression)
        #
        # make sure it's refected in the gui
        self.amplitude = self.amplitude
        self.weight = self.weight
        self.weight_count = self.weight_count
        self.statistic = self.statistic

        self.colorbar_checkbox.set_value(self.state.colorbar)
        for dim in range(self.dimensions):
            self.option_output_unit[dim].set_value(self.state.output_units[dim])
        self.option_label_x.set_value(self.state.labels[0])
        self.option_label_y.set_value(self.state.labels[1])

        logger.debug("remove history change")
        self.plot_window.queue_history_change(None)

    def flag_needs_update(self):
        self._needs_update = True
        self.signal_needs_update.emit()

    def get_needs_update(self):
        return self._needs_update

    @property
    def x(self):
        """x expression"""
        return self.state.expressions[0]

    @x.setter
    def x(self, value):
        logger.debug("setting self.state.expressions[0] to %s" % value)
        self.set_expression(value, 0)

    @property
    def y(self):
        """y expression"""
        return self.state.expressions[1]

    @y.setter
    def y(self, value):
        logger.debug("setting self.state.expressions[1] to %s" % value)
        self.set_expression(value, 1)

    @property
    def z(self):
        """y expression"""
        return self.state.expressions[2]

    @y.setter
    def z(self, value):
        logger.debug("setting self.state.expressions[2] to %s" % value)
        self.set_expression(value, 2)

    @property
    def vx(self):
        """vector x expression"""
        return self.state.vector_expressions[0]

    @vx.setter
    def vx(self, value):
        logger.debug("setting self.state.vector_expressions[0] to %s" % value)
        self.set_vector_expression(value, 0)

    @property
    def vy(self):
        """vector y expression"""
        return self.state.vector_expressions[1]

    @vy.setter
    def vy(self, value):
        logger.debug("setting self.state.vector_expressions[1] to %s" % value)
        self.set_vector_expression(value, 1)

    @property
    def vz(self):
        """vector z expression"""
        return self.state.vector_expressions[2]

    @vz.setter
    def vz(self, value):
        logger.debug("setting self.state.vector_expressions[2] to %s" % value)
        self.set_vector_expression(value, 2)

    @property
    def statistic(self):
        """vector z expression"""
        return self.state.statistic

    @statistic.setter
    def statistic(self, value):
        logger.debug("setting self.state.statistic to %s" % value)
        self.state.statistic = value
        if self.option_statistic.combobox.currentText() != value:
            self.option_statistic.set_value(value)
        self.check_statistics_weights()
        self.amplitude = self.amplitude  # trigger setting the right text
        self.plot_window.queue_history_change("changed statistic to %s" % (value))

    @property
    def amplitude(self):
        """amplitude expression"""
        # return self.amplitude
        return self.state.amplitudes[self.statistic]

    @amplitude.setter
    def amplitude(self, value):
        logger.debug("setting self.amplitude to %s" % value)
        self.state.amplitudes[self.statistic] = value
        self.amplitude_box.lineEdit().setText(value)
        # self.plot_window.queue_update()
        self.signal_plot_dirty.emit()
        self.plot_window.queue_history_change("changed amplitude to %s" % (value))

    def set_range(self, min, max, dimension=0):
        # was_equal = list(self.plot_window.state.ranges_viewport[dimension]) == [min, max]
        if min is None or max is None:
            self.state.ranges_grid[dimension] = None
        else:
            self.state.ranges_grid[dimension] = [min, max]
        # self.plot_window.state.ranges_viewport[dimension] = list(self.state.ranges_grid[dimension])
        # self.plot_window.set_range(min, max, dimension=dimension)
        if dimension == 0:
            self.option_xrange.set_value((min, max), update=False)
        if dimension == 1:
            self.option_yrange.set_value((min, max), update=False)
        if dimension == 2:
            self.option_zrange.set_value((min, max), update=False)
        # return not was_equal

    def get_range(self, dimension=0):
        return list(self.state.ranges_grid[dimension]) if self.state.ranges_grid[dimension] is not None else None

    @property
    def xlim(self):
        """vector z expression"""
        return self.get_range(0)

    @xlim.setter
    def xlim(self, value):
        vmin, vmax = value
        self.plot_window.set_range(vmin, vmax, 0)
        self.update()

    @property
    def ylim(self):
        """vector z expression"""
        return self.get_range(1)

    @ylim.setter
    def ylim(self, value):
        vmin, vmax = value
        self.plot_window.set_range(vmin, vmax, 1)
        self.update()

    @property
    def zlim(self):
        """vector z expression"""
        return self.get_range(2)

    @xlim.setter
    def zlim(self, value):
        vmin, vmax = value
        self.plot_window.set_range(vmin, vmax, 2)
        self.update()

    @property
    def weight_count(self):
        return self.state.weight_count

    @weight_count.setter
    def weight_count(self, expression):
        if expression is not None:
            expression = expression.strip()
        if expression == "":
            expression = None
        widget = self.option_weight_count.combobox
        if expression:
            if expression != "*":  # * is special
                try:
                    self.dataset.validate_expression(expression)
                except Exception as e:
                    self.error_in_field(widget, "weight", e)
                    return
        self.state.weight_count = expression
        self.plot_window.queue_history_change("changed weight expression to %s" % (expression))
        if widget.currentText() != expression:
            widget.setCurrentIndex(self.option_weight_count.options.index(expression))
            self.range_level = None
            self.plot_window.range_level_show = None
            self.update()

    @property
    def weight(self):
        return self.state.weight

    @weight.setter
    def weight(self, expression):
        if expression is not None:
            expression = expression.strip()
        if expression == "":
            expression = None
        widget = self.option_weight_statistic.combobox
        if expression:
            try:
                self.dataset.validate_expression(expression)
            except Exception as e:
                self.error_in_field(widget, "weight", e)
                return
        self.state.weight = expression
        self.plot_window.queue_history_change("changed weight expression to %s" % (expression))
        if widget.currentText() != expression:
            widget.lineEdit().setText(expression)
            self.range_level = None
            self.plot_window.range_level_show = None
            self.update()

    def removed(self):
        # self.dataset.mask_listeners.remove(self.onSelectMask)
        self.dataset.signal_selection_changed.disconnect(self.on_selection_changed)
        self.dataset.signal_pick.disconnect(self.on_pick)
        self.dataset.signal_sequence_index_change.disconnect(self.on_sequence_changed)
        # self.dataset.row_selection_listeners.remove(self.onSelectRow)
        # self.dataset.serie_index_selection_listeners.remove(self.onSerieIndexSelect)
        for plugin in self.plugins:
            plugin.clean_up()

    def create_grid_map(self, gridsize, use_selection):
        return {"counts": self.temp_grid, "weighted": None, "weightx": None, "weighty": None, "weightz": None}

    def create_grid_map_(self, gridsize, use_selection):
        locals = {}
        for name in list(self.grids.grids.keys()):
            grid = self.grids.grids[name]
            if name == "counts" or (grid.weight_expression is not None and len(grid.weight_expression) > 0):
                if grid.max_size >= gridsize:
                    locals[name] = grid.get_data(gridsize, use_selection=use_selection, disjoined=self.plot_window.show_disjoined)
                    # import vaex.kld
                    # print("Mutual information", name,  gridsize, self.state.expressions, vaex.kld.mutual_information(locals[name]))
            else:
                locals[name] = None
        for d, name in zip(list(range(self.dimensions)), "xyzw"):
            width = self.state.ranges_grid[d][1] - self.state.ranges_grid[d][0]
            offset = self.state.ranges_grid[d][0]
            x = (np.arange(0, gridsize) + 0.5) / float(gridsize) * width + offset
            locals[name] = x
        return locals

    def eval_amplitude(self, expression, locals):
        amplitude = None
        locals = dict(locals)
        if "gf" not in locals:
            locals["gf"] = scipy.ndimage.gaussian_filter
        counts = locals["counts"]
        if self.dimensions == 2:
            peak_columns = np.apply_along_axis(np.nanmax, 1, counts)
            peak_columns[peak_columns == 0] = 1.
            peak_columns = peak_columns.reshape((1, -1))  # .T
            locals["peak_columns"] = peak_columns

            sum_columns = np.apply_along_axis(np.nansum, 1, counts)
            sum_columns[sum_columns == 0] = 1.
            sum_columns = sum_columns.reshape((1, -1))  # .T
            locals["sum_columns"] = sum_columns

            peak_rows = np.apply_along_axis(np.nanmax, 0, counts)
            peak_rows[peak_rows == 0] = 1.
            peak_rows = peak_rows.reshape((-1, 1))  # .T
            locals["peak_rows"] = peak_rows

            sum_rows = np.apply_along_axis(np.nansum, 0, counts)
            sum_rows[sum_rows == 0] = 1.
            sum_rows = sum_rows.reshape((-1, 1))  # .T
            locals["sum_rows"] = sum_rows

        weighted = locals["weighted"]
        if weighted is None:
            locals["average"] = None
        else:
            average = weighted / counts
            average[counts == 0] = np.nan
            locals["average"] = average
        globals = np.__dict__
        amplitude = eval(expression, globals, locals)
        return amplitude

    def error_dialog(self, widget, name, exception):
        dialogs.dialog_error(widget, "Error", "%s: %r" % (name, exception))

    def error_in_field(self, widget, name, exception):
        dialogs.dialog_error(widget, "Error in expression", "Invalid expression for field %s: %r" % (name, exception))
        # self.current_tooltip = QtGui.QToolTip.showText(widget.mapToGlobal(QtCore.QPoint(0, 0)), "Error: " + str(exception), widget)
        # self.current_tooltip = QtGui.QToolTip.showText(widget.mapToGlobal(QtCore.QPoint(0, 0)), "Error: " + str(exception), widget)

    def plot_scatter(self, axes_list):
        for ax in axes_list:
            # TODO: support multiple axes with the axis index
            x = self.dataset.evaluate(self.x)
            y = self.dataset.evaluate(self.y)
            ax.scatter(x, y, alpha=self.state.alpha, color=self.color)
            row = self.dataset.get_current_row()
            if row is not None:
                ax.scatter([x[row]], [y[row]], alpha=self.state.alpha, color=self.color_alt)

    def plot_schlegel(self, axes_list, stack_image):
        if not hasattr(self, "schlegel_map"):
            self.schlegel_map = healpy.read_map('data/lambda_sfd_ebv.fits', nest=False)
        xlim, ylim = self.plot_window.state.ranges_viewport
        phis = np.linspace(np.deg2rad(xlim[0]), np.deg2rad(xlim[1]), self.plot_window.state.grid_size)  # + np.pi/2.
        thetas = np.pi - np.linspace(np.deg2rad(ylim[1]) + np.pi / 2., np.deg2rad(ylim[0]) + np.pi / 2., self.plot_window.state.grid_size)
        # phis = (np.linspace(0, 2*np.pi, 256) - np.pi) % (2*np.pi)
        thetas, phis = np.meshgrid(thetas, phis)

        pix = healpy.ang2pix(512, thetas, phis)
        I = self.schlegel_map[pix].T[::-1, :]
        I = self._normalize_values(np.log(I))
        self.schlegel_projected = I
        rgb = self._to_rgb(I, color=self.color)
        axes_list[0].rgb_images.append(rgb)
        # print "SCHL" * 1000
        # plt.imshow(np.log(schlegel_map[pix].T))

    def plot(self, axes_list, stack_image):
        if self._can_plot:
            logger.debug("begin plot: %r, style: %r", self, self.state.style)
        else:
            logger.debug("cannot plot layer: %r" % self)
            return

        if not self.visible:
            return
        if self.state.style == "scatter":
            self.plot_scatter(axes_list)
            return
            # return
        logger.debug("total sum of amplitude grid: %s", np.nansum(self.amplitude_grid_view))

        if self.dimensions == 1:
            mask = ~(np.isnan(self.amplitude_grid_view) | np.isinf(self.amplitude_grid_view))
            if np.sum(mask) == 0:
                self.range_level = None
            else:
                values = self.amplitude_grid_view * 1.
                # def nancumsum()
                if self._cumulative:
                    values[~mask] = 0
                    values = np.cumsum(values)
                if self._normalize:
                    if self._cumulative:
                        values /= values[-1]
                    else:
                        values /= np.sum(values[mask])  # TODO: take dx into account?

                if self.dataset.has_selection():
                    mask_selected = ~(np.isnan(self.amplitude_grid_selection_view) | np.isinf(self.amplitude_grid_selection_view))
                    values_selected = self.amplitude_grid_selection_view * 1.
                    if self._cumulative:
                        values_selected[~mask_selected] = 0
                        values_selected = np.cumsum(values_selected)
                    if self._normalize:
                        if self._cumulative:
                            values_selected /= values_selected[-1]
                        else:
                            values_selected /= np.sum(values_selected[mask_selected])  # TODO: take dx into account?
                width = self.state.ranges_grid[0][1] - self.state.ranges_grid[0][0]
                x = np.arange(0, self.plot_window.state.grid_size) / float(self.plot_window.state.grid_size) * width + self.state.ranges_grid[0][0]  # + width/(Nvector/2.)
                delta = x[1] - x[0]
                for axes in axes_list:
                    if self.show in ["total+selection", "total"]:
                        if self.display_type == "bar":
                            axes.bar(x, values, width=delta, align='center', alpha=self.state.alpha, color=self.color)
                        else:
                            dx = x[1] - x[0]
                            x2 = list(np.ravel(list(zip(x, x + dx))))
                            x2p = [x[0]] + x2 + [x[-1] + dx]
                            y = values
                            y2 = list(np.ravel(list(zip(y, y))))
                            y2p = [0] + y2 + [0]
                            axes.plot(x2p, y2p, alpha=self.state.alpha, color=self.color)
                    if self.show in ["total+selection", "selection"]:
                        if self.dataset.has_selection():
                            if self.display_type == "bar":
                                axes.bar(x, values_selected, width=delta, align='center', color=self.color_alt, alpha=0.6 * self.state.alpha)
                            else:
                                dx = x[1] - x[0]
                                x2 = list(np.ravel(list(zip(x, x + dx))))
                                x2p = [x[0]] + x2 + [x[-1] + dx]
                                y = values_selected
                                y2 = list(np.ravel(list(zip(y, y))))
                                y2p = [0] + y2 + [0]
                                axes.plot(x2p, y2p, drawstyle="steps-mid", alpha=self.state.alpha, color=self.color_alt)

                    # 3if self.coordinates_picked_row is not None:
                    index = self.dataset.get_current_row()
                    logger.debug("current row: %r" % index)
                    if index is not None:
                        x = self.subspace.row(index)
                        axes.axvline(x[axes.xaxis_index], color="red")

        # if self.dimensions == 2:
        # #for axes in axes_list:
        # assert len(axes_list) == 1
        # self.plot_density(axes_list[0], self.amplitude_grid, self.amplitude_grid_selection, stack_image)
        if self.dimensions >= 2:
            # for vector we only use the selected map, maybe later also show the full dataset
            # grid_map_vector = self.create_grid_map(self.plot_window.state.vector_grid_size, use_selection)

            self.vector_grid = None
            if 1:  # any(self.state.vector_expressions):
                grid_vector = self.grid_vector
                if self.layer_slice_source:
                    grid_vector = grid_vector.slice(self.slice_selection_grid)
                vector_grids = None
                if any(self.state.vector_expressions):
                    vector_counts = grid_vector.evaluate("countx")  # TODO: what should the mask be..
                    vector_mask = vector_counts > 0
                    if grid_vector.evaluate("sumx") is not None:
                        vector_x = grid_vector.evaluate("x")
                        vx = grid_vector.evaluate("sumx/countx")
                        if self.vectors_subtract_mean:
                            vx -= vx[vector_mask].mean()
                    else:
                        vector_x = None
                        vx = None
                    if grid_vector.evaluate("sumy") is not None:
                        vector_y = grid_vector.evaluate("y")
                        vy = grid_vector.evaluate("sumy/county")
                        if self.vectors_subtract_mean:
                            vy -= vy[vector_mask].mean()
                    else:
                        vector_y = None
                        vy = None
                    if grid_vector.evaluate("sumz") is not None:
                        if self.dimensions >= 3:
                            vector_z = grid_vector.evaluate("z")
                        else:
                            vector_z = None
                        vz = grid_vector.evaluate("sumz/countz")
                        if self.vectors_subtract_mean:
                            vz -= vz[vector_mask].mean()
                    else:
                        vector_z = None
                        vz = None
                    logger.debug("vx=%s vy=%s vz=%s", vx, vy, vz)
                    if vx is not None and vy is not None and vz is not None:
                        self.vector_grid = np.zeros((4, ) + ((vx.shape[0],) * 3), dtype=np.float32)
                        self.vector_grid[0] = vx.T
                        self.vector_grid[1] = vy.T
                        self.vector_grid[2] = vz.T
                        self.vector_grid[3] = vector_counts.T
                        self.vector_grid = np.swapaxes(self.vector_grid, 0, 3)
                        self.vector_grid = self.vector_grid * 1.

                    self.vector_grids = vector_grids = [vx, vy, vz]
                    vector_positions = [vector_x, vector_y, vector_z]

                for axes in axes_list:
                    # if 0:
                    # create marginalized grid
                    all_axes = list(range(self.dimensions))
                    # all_axes.remove(self.dimensions-1-axes.xaxis_index)
                    # all_axes.remove(self.dimensions-1-axes.yaxis_index)
                    all_axes.remove(axes.xaxis_index)
                    all_axes.remove(axes.yaxis_index)

                    # if 1:
                    # grid_map_2d = {key:None if grid is None else (grid if grid.ndim != 3 else vaex.utils.multisum(grid, all_axes)) for key, grid in list(grid_map.items())}
                    # grid_context = self.grid_vector
                    # amplitude = grid_context(self.amplitude, locals=grid_map_2d)

                    # grid = self.grid_main.marginal2d(self.dimensions-1-axes.xaxis_index, self.dimensions-1-axes.yaxis_index)
                    grid = self.grid_main.marginal2d(axes.xaxis_index, axes.yaxis_index)
                    if self.state.show_disjoined:
                        grid = grid.disjoined()
                    try:
                        amplitude = grid.evaluate(self.amplitude)
                    except Exception as e:
                        self.error_in_field(self.amplitude_box, "amplitude of layer %s" % self.name, e)
                        return
                    if self.dataset.has_selection():
                        # grid_map_selection_2d = {key:None if grid is None else (grid if grid.ndim != 3 else vaex.utils.multisum(grid, all_axes)) for key, grid in list(grid_map_selection.items())}
                        # grid_selection = self.grid_main_selection.marginal2d(self.dimensions-1-axes.xaxis_index, self.dimensions-1-axes.yaxis_index)
                        grid_selection = self.grid_main_selection.marginal2d(axes.xaxis_index, axes.yaxis_index)
                        if self.state.show_disjoined:
                            grid_selection = grid_selection.disjoined()
                        amplitude_selection = grid_selection.evaluate(self.amplitude)
                    else:
                        amplitude_selection = None
                    # print("total amplit")
                    self.plot_density(axes, amplitude, amplitude_selection, stack_image)

                    if len(all_axes) > 2:
                        other_axis = all_axes[0]
                        assert len(all_axes) == 1, ">3d not supported"
                    else:
                        other_axis = 2

                    if vector_grids:
                        # vector_grids[vector_grids==np.inf] = np.nan
                        U = vector_grids[axes.xaxis_index]
                        V = vector_grids[axes.yaxis_index]
                        W = vector_grids[other_axis]
                        vx = None if U is None else vaex.utils.multisum(U, all_axes)
                        vy = None if V is None else vaex.utils.multisum(V, all_axes)
                        vz = None if W is None else vaex.utils.multisum(W, all_axes)
                        vector_counts_2d = vaex.utils.multisum(vector_counts, all_axes)
                        if vx is not None and vy is not None:
                            count_max = vector_counts_2d.max()
                            mask = (vector_counts_2d > (self.vector_level_min * count_max)) & \
                                (vector_counts_2d <= (self.vector_level_max * count_max))
                            x = vector_positions[axes.xaxis_index]
                            y = vector_positions[axes.yaxis_index]
                            x2d, y2d = np.meshgrid(x, y)
                            # x2d, y2d = x2d.T, y2d.T
                            # mask = mask.T
                            colors, colormap = None, None
                            if True:
                                if self.vector_auto_scale:
                                    length = np.nanmean(np.sqrt(vx[mask]**2 + vy[mask]**2))  # / 1.5
                                    logger.debug("auto scaling using length: %r", length)
                                    vx[mask] /= length
                                    vy[mask] /= length

                                scale = self.plot_window.state.vector_grid_size / self.vector_scale
                                width = self.vector_head_width * 0.1 / self.plot_window.state.vector_grid_size
                                xsign = 1 if self.state.ranges_grid[0][0] <= self.state.ranges_grid[0][1] else -1
                                ysign = 1 if self.state.ranges_grid[1][0] <= self.state.ranges_grid[1][1] else -1
                                if vz is not None and self.vectors_color_code_3rd:
                                    colors = vz
                                    colormap = self.state.colormap_vector
                                    axes.quiver(x2d[mask.T], y2d[mask.T], vx.T[mask.T] * xsign, vy.T[mask.T] * ysign, colors[mask], cmap=colormap, scale_units="width", scale=scale, width=width)
                                else:
                                    axes.quiver(x2d[mask.T], y2d[mask.T], vx.T[mask.T] * xsign, vy.T[mask.T] * ysign, color=self.color, scale_units="width", scale=scale, width=width)
                                logger.debug("quiver: %s", self.vector_scale)
                                colors = None
        if 0:  # if self.coordinates_picked_row is not None:
            if self.dimensions >= 2:
                for axes in axes_list:
                    axes.scatter([self.coordinates_picked_row[axes.xaxis_index]], [self.coordinates_picked_row[axes.yaxis_index]], color='red')

        if self.dimensions >= 2:
            for axes in axes_list:
                index = self.dataset.get_current_row()
                logger.debug("current row: %r" % index)
                if index is not None:
                    x = self.subspace.row(index)
                    axes.scatter([x[axes.xaxis_index]], [x[axes.yaxis_index]], color='red')

    def getVariableDict(self):
        return {}  # TODO: remove this? of replace

    def _normalize_values(self, amplitude):
        I = amplitude * 1.  # self.contrast(amplitude)
        # scale to [0,1]
        mask = ~(np.isnan(I) | np.isinf(I))
        if np.sum(mask) == 0:
            return np.zeros(I.shape, dtype=np.float64)
        I -= I[mask].min()
        I /= I[mask].max()
        return I

    def _to_rgb(self, intensity, color, pre_alpha=1.):
        I = intensity
        mask = ~(np.isnan(I) | np.isinf(I))
        if np.sum(mask) == 0:
            return np.zeros(I.shape + (4,), dtype=np.float64)
        minvalue = I[mask].min()
        maxvalue = I[mask].max()
        if minvalue == maxvalue:
            return np.zeros(I.shape + (4,), dtype=np.float64)
        I -= minvalue
        I /= maxvalue

        # scale [min, max] to [0, 1]
        I -= self.level_min
        I /= (self.level_max - self.level_min)

        # if self.color is not None:

        alpha_mask = (mask) & (I > 0)
        if self.display_type == "solid":
            color_tuple = matplotlib.colors.colorConverter.to_rgb(color)
            rgba = np.zeros(I.shape + (4,), dtype=np.float64)
            rgba[alpha_mask, 0:3] = np.array(color_tuple)
        else:
            cmap = matplotlib.cm.cmap_d[self.state.colormap]
            rgba = cmap(I * 1.00)
            rgba[..., 3] = (np.clip((I**1.0) * self.state.alpha, 0, 1))
        if self.transparancy == "intensity":
            rgba[..., 3] = (np.clip((I**1.0) * self.state.alpha, 0, 1)) * self.state.alpha * pre_alpha
        elif self.transparancy == "constant":
            rgba[alpha_mask, 3] = 1. * self.state.alpha * pre_alpha
            rgba[~alpha_mask, 3] = 0
        elif self.transparancy == "none":
            rgba[..., 3] = pre_alpha
        else:
            raise NotImplemented
        return rgba

    def plot_density_imshow(self, axes, amplitude, amplitude_selection, stack_image):
        if not self.visible:
            return
        ranges = []
        for minimum, maximum in self.state.ranges_grid:
            ranges.append(minimum)
            ranges.append(maximum)
        use_selection = amplitude_selection is not None
        # if isinstance(self.state.colormap, basestring):

        levels = (np.arange(self.contour_count) + 1.) / (self.contour_count + 1)
        levels = np.linspace(self.level_min, self.level_max, self.contour_count)
        ranges = list(self.state.ranges_grid[0]) + list(self.state.ranges_grid[1])

        amplitude_marginalized = amplitude
        amplitude_marginalized_selected = amplitude_selection
        mask = ~(np.isnan(amplitude_marginalized) | np.isinf(amplitude_marginalized))
        if np.sum(mask) == 0:  # if nothing to show
            vmin, vmax = 0, 1
        else:
            vmin, vmax = amplitude_marginalized[mask].min(), amplitude_marginalized[mask].max()
        self.level_ranges = [vmin + self.level_min * (vmax - vmin), vmin + self.level_max * (vmax - vmin)]
        logger.debug("level ranges: %r" % self.level_ranges)

        if self.display_type == "contour":
            if self.contour_count > 0:
                if self.show == "total+selection":
                    if use_selection and self.show:
                        axes.contour(self._normalize_values(amplitude_marginalized).T, origin="lower", extent=ranges, levels=levels, linewidths=1, colors=self.color, alpha=0.4 * self.state.alpha)
                        axes.contour(self._normalize_values(amplitude_marginalized_selected).T, origin="lower", extent=ranges, levels=levels, linewidths=1, colors=self.color_alt, alpha=self.state.alpha)
                    else:
                        axes.contour(self._normalize_values(amplitude_marginalized).T, origin="lower", extent=ranges, levels=levels, linewidths=1, colors=self.color, alpha=self.state.alpha)
                elif self.show == "total":
                    axes.contour(self._normalize_values(amplitude_marginalized).T, origin="lower", extent=ranges, levels=levels, linewidths=1, colors=self.color, alpha=self.state.alpha)
                elif self.show == "selection":
                    axes.contour(self._normalize_values(amplitude_marginalized_selected).T, origin="lower", extent=ranges, levels=levels, linewidths=1, colors=self.color_alt, alpha=self.state.alpha)
        else:
            if self.show == "total+selection":
                I = self._normalize_values(amplitude_marginalized)
                axes.rgb_images.append(self._to_rgb(I, color=self.color, pre_alpha=0.4 if use_selection else 1.0))
                if use_selection:
                    I = self._normalize_values(amplitude_marginalized_selected)
                    axes.rgb_images.append(self._to_rgb(I, color=self.color_alt))
            elif self.show == "total":
                I = self._normalize_values(amplitude_marginalized)
                axes.rgb_images.append(self._to_rgb(I, color=self.color))
            elif self.show == "selection" and amplitude_marginalized_selected is not None:
                I = self._normalize_values(amplitude_marginalized_selected)
                axes.rgb_images.append(self._to_rgb(I, color=self.color_alt))

    def on_selection_changed(self, dataset, selection_name):
        self.check_selection_undo_redo()
        # self.plot_window.queue_update(layer=self)
        self.update()
        # self.add_jobs()
        # self.label_selection_info_update()
        # self.plot()

    def on_column_changed(self, dataset, column, type):
        self.update()

    def on_variable_changed(self, dataset, column, type):
        self.update()

    def on_pick(self, dataset, row):
        self.coordinates_picked_row = None
        # self.plot()
        self.signal_plot_dirty.emit(self)

    def on_sequence_changed(self, sequence_index):
        if sequence_index != self.sequence_index:  # avoid unneeded event
            self.sequence_index = sequence_index
            # self.seriesbox.setCurrentIndex(self.sequence_index)
        else:
            self.sequence_index = sequence_index
        # self.compute()
        # self.signal_plot_update.emit(delay=0)
        # self.add_jobs()
        # self.plot_window.queue_update(layer=self)
        self.update()

    def get_options(self):
        options = collections.OrderedDict()
        # options["type-names"] = map(str.strip, self.names.split(","))
        options["expressions"] = self.state.expressions
        options["weight"] = self.state.weight
        options["weight_count"] = self.state.weight_count
        options["amplitude"] = self.amplitude
        options["ranges_grid"] = self.state.ranges_grid
        options["vx"] = self.vx
        if self.dimensions > 1:
            options["vy"] = self.vy
            options["vz"] = self.vz
        for plugin in self.plugins:
            options.update(plugin.get_options())
        # since options contains reference (like a list of expressions)
        # changes in the gui might reflect previously stored options
        options = copy.deepcopy(options)
        return dict(options)

    def apply_options(self, options, update=True):
        # map = {"expressions",}
        recognize = "expressions weight weight_count amplitude_expression ranges_grid aspect vx vy vz".split()
        for key in recognize:
            if key in list(options.keys()):
                value = options[key]
                setattr(self, key, copy.copy(value))
                if key == "amplitude":
                    self.amplitude_box.lineEdit().setText(value)
                if key == "weight":
                    self.weight = value
                if key == "weight":
                    self.weight_count = value
                if key == "vx":
                    self.weight_x_box.lineEdit().setText(value or "")
                if key == "vy":
                    self.weight_y_box.lineEdit().setText(value or "")
                if key == "vz":
                    self.weight_z_box.lineEdit().setText(value or "")
                if key == "expressions":
                    for expr, box in zip(value, self.axisboxes):
                        box.lineEdit().setText(expr)
        for plugin in self.plugins:
            plugin.apply_options(options)
        for key in list(options.keys()):
            if key not in recognize:
                logger.error("option %s not recognized, ignored" % key)
        if update:
            # self.plot_window.queue_update()
            self.update()

    def plug_toolbar(self, callback, order):
        self.plugin_queue_toolbar.append((callback, order))

    def plug_page(self, callback, pagename, pageorder, order):
        self.plugin_queue_page.append((callback, pagename, pageorder, order))

    def plug_grids(self, callback_define, callback_draw):
        self.plugin_grids_defines.append(callback_define)
        self.plugin_grids_draw.append(callback_draw)

    def apply_mask(self, mask):
        # TODO: how to treat this when there is a server
        if self.dataset.is_local():
            self.dataset._set_mask(mask)
            self.execute()
        self.check_selection_undo_redo()
        # self.label_selection_info_update()

    def execute(self):
        error_text = self.dataset.executor.execute()
        if error_text is not None:
            logger.error("error while executing: %r" % error_text)
            dialogs.dialog_error(self.plot_window, "Error when executing", error_text)

    def message(self, *args, **kwargs):
        pass

    def on_error(self, exception):
        logger.exception("unhandled error occured: %r", exception)
        self.finished_tasks()
        traceback.print_exc()
        raise exception

    def add_task(self, task):
        self._task_signals.append(task.signal_progress.connect(self._layer_progress))
        self.tasks.append(task)
        return task

    def _layer_progress(self, fraction):
        total_fraction = 0
        for task in self.tasks:
            total_fraction += task.progress_fraction
        fraction = total_fraction / len(self.tasks)
        self.plot_window.set_layer_progress(self, fraction)
        return True

    def get_progress_fraction(self):
        return self.progressbar.fraction
        total_fraction = 0
        for task in self.tasks:
            total_fraction += task.progress_fraction
        fraction = total_fraction / len(self.tasks)
        return fraction

    def finished_tasks(self):
        for task, signal in zip(self.tasks, self._task_signals):
            task.signal_progress.disconnect(signal)
        self.tasks = []
        self._task_signals = []

    def cancel_tasks(self):
        self.progressbar.cancel()
        logger.info("cancelling tasks for layer %r", self)
        for task in self.tasks:
            task.cancel()
        self.finished_tasks()

    def reset_progressbar(self):
        def update(fraction):
            return self.plot_window.set_layer_progress(self, fraction)
        self.progressbar = vaex.utils.progressbars(False, next=update, name="layer")

    def add_tasks_ranges(self):
        logger.info("adding ranges jobs for layer: %r, previous ranges_grid = %r", self, self.state.ranges_grid)
        assert not self.tasks, "still were tasks in queue: %r for %r" % (self.tasks, self)
        self.reset_progressbar()
        missing = False
        # TODO, optimize for the case when some dimensions are already known
        for range in self.state.ranges_grid:
            if range is None:
                missing = True
            else:
                vmin, vmax = range
                if vmin is None or vmax is None:
                    missing = True
        self.subspace = self.dataset(*self.state.expressions, delay=True)
        # subspace_ranges = self.subspace
        all_expressions = self.state.expressions
        if self.layer_slice_source:
            all_expressions = self.state.expressions + self.layer_slice_source.expressions
            # self.subspace = self.dataset(*all_expressions, delay=True)

        if missing:
            logger.debug("first we calculate min max for this layer")
            # return self.add_task(subspace_ranges.minmax()).then(self.got_limits, self.on_error).then(None, self.on_error)
            return self.dataset.minmax(all_expressions, delay=True, progress=self.progressbar.add(name="for minmaxes")).then(self.got_limits, self.on_error).then(None, self.on_error)
        else:
            # self.got_limits(self.state.ranges_grid)
            return vaex.promise.Promise.fulfilled(self)

    def got_limits(self, limits):
        logger.debug("got limits %r for layer %r" % (limits, self))
        self.state.ranges_grid = np.array(limits).tolist()  # for this class we need it to be a list
        self.finished_tasks()
        return self

    def add_tasks_histograms(self):
        self._histogram_counter += 1
        assert not self.tasks

        self.reset_progressbar()
        all_expressions = self.state.expressions
        if self.layer_slice_source:
            all_expressions = self.state.expressions + self.layer_slice_source.expressions
            # self.subspace = self.dataset(*all_expressions, delay=True)

        histogram_counter = self._histogram_counter
        self._can_plot = False
        promises = []
        self.grid_main = vaex.grids.GridScope(globals=np.__dict__)
        self.grid_main_selection = vaex.grids.GridScope(globals=np.__dict__)
        self.grid_vector = vaex.grids.GridScope(globals=np.__dict__)

        ranges = np.array(self.state.ranges_grid)
        if self.layer_slice_source:
            ranges = np.array(self.state.ranges_grid + self.layer_slice_source.ranges_grid)
        ranges = np.array(ranges)
        # add the main grid

        f = getattr(self.dataset, self.statistic)
        args = []
        if self.statistic == "count":
            args.append(self.weight_count)
        elif self.statistic in ["sum", "mean", "std", "var", "min", "max"]:
            args.append(self.weight)
        histogram_promise = f(*args, binby=all_expressions, limits=ranges, shape=self.plot_window.state.grid_size, progress=self.progressbar.add(self.statistic), delay=True)\
            .then(self.grid_main.setter("grid"))\
            .then(None, self.on_error)
        promises.append(histogram_promise)

        if self.dataset.has_selection():
            # histogram_promise = self.add_task(self.subspace.selected().histogram(limits=ranges, size=self.plot_window.state.grid_size))\
            # .then(self.grid_main_selection.setter("counts"))\
            # .then(None, self.on_error)
            # promises.append(histogram_promise)
            histogram_promise = f(*args, binby=all_expressions, limits=ranges, shape=self.plot_window.state.grid_size,
                                  progress=self.progressbar.add(self.statistic), delay=True, selection=True) \
                .then(self.grid_main_selection.setter("grid")) \
                .then(None, self.on_error)
            promises.append(histogram_promise)

            @vaex.delayed
            def update_count(count):
                self.label_selection_info_update(count)
            update_count(self.dataset.count(selection=True, delay=True))
        else:
            self.label_selection_info_update(None)

        # the vector fields only use the selection if there is one, otherwise the whole dataset
        selection = False
        if self.dataset.has_selection():
            selection = True

        for i, expression in enumerate(self.state.vector_expressions):
            name = "xyzw"[i]

            # add arrays x y z which container the centers of the bins
            if i < self.dimensions:
                gridsize = self.plot_window.state.vector_grid_size
                width = self.state.ranges_grid[i][1] - self.state.ranges_grid[i][0]
                offset = self.state.ranges_grid[i][0]
                x = (np.arange(0, gridsize) + 0.5) / float(gridsize) * width + offset
                self.grid_vector[name] = x

            if self.state.vector_expressions[i]:
                # histogram_vector_promise = self.add_task(subspace.histogram(limits=ranges
                # , weight=self.state.vector_expressions[i], size=self.plot_window.state.vector_grid_size))\
                # .then(self.grid_vector.setter("weight"+name))\
                # .then(None, self.on_error)
                histogram_vector_promise = self.dataset.sum(self.state.vector_expressions[i],
                                                            binby=all_expressions, limits=ranges,
                                                            shape=self.plot_window.state.vector_grid_size,
                                                            progress=self.progressbar.add("sum of " + self.state.vector_expressions[i]), delay=True, selection=selection) \
                    .then(self.grid_vector.setter("sum" + name)) \
                    .then(None, self.on_error)
                promises.append(histogram_vector_promise)

                histogram_vector_promise = self.dataset.count(self.state.vector_expressions[i],
                                                              binby=all_expressions, limits=ranges,
                                                              shape=self.plot_window.state.vector_grid_size,
                                                              progress=self.progressbar.add("sum of " + self.state.vector_expressions[i]), delay=True, selection=selection) \
                    .then(self.grid_vector.setter("count" + name)) \
                    .then(None, self.on_error)
                promises.append(histogram_vector_promise)
            else:
                self.grid_vector["sum" + name] = None
                self.grid_vector["count" + name] = None

        # if any(self.state.vector_expressions):
        # histogram_vector_promise = self.add_task(subspace.histogram(limits=ranges
        # ,size=self.plot_window.state.vector_grid_size))\
        # .then(self.grid_vector.setter("counts"))\
        # .then(None, self.on_error)
        # promises.append(histogram_vector_promise)

        # else:
        # for name in "xyz":
        # self.grid_vector["weight" +name] = None

        def check_counter(arg):
            if histogram_counter == self._histogram_counter:
                self.got_grids(arg)
            else:
                logger.debug
                # raise ValueError, "histogram counter got update, cancel redraw etc"
            return arg

        return vaex.promise.listPromise(promises).then(check_counter)  # .then(None, error_counter)\
        # .then(self.got_grids)\
        # .then(None, self.on_error)

    def got_grids(self, *args):
        logger.debug("got grids for layer %r" % (self, ))
        self.finished_tasks()
        self.calculate_amplitudes()
        if 0:  # TODO: enable again with postfixes like M, insteads of long numbers
            counts = self.grid_main.evaluate("counts")
            visible = np.sum(counts)
            total = len(self.dataset)
            fraction = float(visible) / total
            self.label_visible.setText("{:,} of {:,} ({}) visible".format(visible, total, fraction * 100))
        self._needs_update = False
        return self

    def slice_amplitudes(self):
        slice = self.layer_slice_source is not None
        if False:  # slice:
            extra_axes = tuple(range(self.subspace.dimension)[len(self.state.expressions):])
            logger.debug("sum over axes: %r", extra_axes)
            msum = vaex.utils.multisum
            logger.debug("shape of grid: %r", self.amplitude_grid[..., self.slice_selection_grid].shape)
            self.amplitude_grid_view = np.sum(self.amplitude_grid[..., self.slice_selection_grid], axis=-1)
            if self.amplitude_grid_selection is not None:
                self.amplitude_grid_selection_view = np.sum(self.amplitude_grid_selection[..., self.slice_selection_grid], axis=-1)
            else:
                self.amplitude_grid_selection_view = None
        # else:
        self.amplitude_grid_view = self.amplitude_grid
        self.amplitude_grid_selection_view = self.amplitude_grid_selection

    def calculate_amplitudes(self):
        logger.debug("calculating amplitudes (in thread %r)" % threading.currentThread())

        slice = self.layer_slice_source is not None

        try:
            grid = self.grid_main
            if self.state.style == "schlegel":
                # self.plot_schlegel(axes_list, stack_image)
                if not hasattr(self, "schlegel_map"):
                    self.schlegel_map = healpy.read_map('data/lambda_sfd_ebv.fits', nest=False)
                xlim, ylim = self.plot_window.state.ranges_viewport
                phis = np.linspace(np.deg2rad(xlim[0]), np.deg2rad(xlim[1]), self.plot_window.state.grid_size)  # + np.pi/2.
                thetas = np.pi - np.linspace(np.deg2rad(ylim[1]) + np.pi / 2., np.deg2rad(ylim[0]) + np.pi / 2., self.plot_window.state.grid_size)
                # phis = (np.linspace(0, 2*np.pi, 256) - np.pi) % (2*np.pi)
                thetas, phis = np.meshgrid(thetas, phis)

                pix = healpy.ang2pix(512, thetas, phis)
                grid["counts"] = self.schlegel_map[pix].T[::-1, :]
                # self.amplitude_grid_selection = None

            if slice:
                grid = grid.slice(self.slice_selection_grid)
            if self.state.show_disjoined:
                grid = grid.disjoined()
            self.amplitude_grid = grid.evaluate(self.amplitude)
        except Exception as e:
            logger.exception("amplitude field")
            # traceback.print_exc()
            # print self.error_in_field
            self.error_in_field(self.amplitude_box, "amplitude of layer %s" % self.name, e)
            return
        self.amplitude_grid_selection = None
        logger.debug("shape of amplitude grid: %r" % (self.amplitude_grid.shape, ))
        if self.dataset.has_selection():
            grid = self.grid_main_selection
            if slice:
                grid = grid.slice(self.slice_selection_grid)
            if self.state.show_disjoined:
                grid = grid.disjoined()
            self.amplitude_grid_selection = grid.evaluate(self.amplitude)

        vmin = None
        vmax = None

        def getminmax(grid, vmin, vmax):
            mask = ~(np.isnan(grid) | np.isinf(grid))
            values = grid
            if self.dimensions == 1:
                # DRY, same code in plot(..)
                values = grid * 1.  # copy grid
                if self._cumulative:
                    values[~mask] = 0
                    values = np.cumsum(values)
                if self._normalize:
                    if self._cumulative:
                        values /= values[-1]
                    else:
                        values /= np.sum(values[mask])  # TODO: take dx into account?
            if mask.sum() > 0:
                newvmin = values[mask].min()
                newvmax = values[mask].max()
                vmin = min(newvmin, vmin) if vmin is not None else newvmin
                vmax = max(newvmax, vmax) if vmax is not None else newvmax
            return vmin, vmax
        self.range_level = vmin, vmax = getminmax(self.amplitude_grid, vmin, vmax)
        logger.debug("range_level: %r" % [vmin, vmax])
        if self.dataset.has_selection():
            self.range_level = getminmax(self.amplitude_grid_selection, vmin, vmax)
            logger.debug("range_level update: %r" % ([vmin, vmax], ))
        self.slice_amplitudes()
        self._can_plot = True

    def build_widget_qt(self, parent):
        self.widget_build = True

        # create plugins
        self.plugin_grids_defines = []
        self.plugin_grids_draw = []
        self.plugin_queue_toolbar = []  # list of tuples (callback, order)
        self.plugin_queue_page = []
        self.plugins = [cls(parent, self) for cls in vaex.ui.plugin.PluginLayer.registry if cls.useon(self.plot_window.__class__)]
        logger.debug("PLUGINS: %r " % self.plugins)
        self.plugins_map = {plugin.name: plugin for plugin in self.plugins}
        # self.plugin_zoom = plugin.zoom.ZoomPlugin(self)

        self.toolbox = QtGui.QToolBox(parent)
        self.toolbox.setMinimumWidth(250)

        self.plug_page(self.page_main, "Main", 1., 1.)
        self.plug_page(self.page_visual, "Visual", 1.5, 1.)
        self.plug_page(self.page_annotate, "Annotate", 1.75, 1.)
        if self.dimensions >= 2:
            self.plug_page(self.page_vector, "Vector field", 2., 1.)
        else:
            self.vector_dimensions = 0
            self.vector_names = "vx vy vz".split()[:self.vector_dimensions]

        # self.plug_page(self.page_display, "Display", 3., 1.)
        self.plug_page(self.page_selection, "Selection", 3.5, 1.)
        if self.plot_window.enable_slicing:
            self.plug_page(self.page_slice, "Slicing", 3.75, 1.)

        # first get unique page orders
        logger.debug("setting up layer plugins")
        pageorders = {}
        for callback, pagename, pageorder, order in self.plugin_queue_page:
            pageorders[pagename] = pageorder
        self.pages = {}
        for pagename, order in sorted(list(pageorders.items()), key=operator.itemgetter(1)):
            page_frame = QtGui.QFrame(self.toolbox)
            self.pages[pagename] = page_frame
            self.toolbox.addItem(page_frame, pagename)
            logger.debug("created page: " + pagename)
        for pagename, order in sorted(list(pageorders.items()), key=operator.itemgetter(1)):
            logger.debug("filling page: %sr %r" % (pagename, [x for x in self.plugin_queue_page if x[1] == pagename]))
            for callback, pagename_, pageorder, order in sorted([x for x in self.plugin_queue_page if x[1] == pagename], key=operator.itemgetter(3)):
                logger.debug("filling page: " + pagename + " order=" + str(order) + " callback=" + str(callback))
                callback(self.pages[pagename])
        page_name = self.options.get("page", "Main")
        page_frame = self.pages.get(page_name, None)
        if page_frame:
            self.toolbox.setCurrentWidget(page_frame)
        logger.debug("done setting up layer plugins")

        self.widget = self.toolbox

        if "selection" in self.options:
            raise NotImplementedError("selection meaning changed")
            # filename = self.options["selection"]
            # mask = np.load(filename)
            # action = vaex.ui.undo.ActionMask(self.dataset.undo_manager, "selection from %s" % filename, mask, self.apply_mask)
            # action.do()
            # self.apply_mask(mask)
            # self.dataset.selectMask(mask)

        if "slice_link" in self.options:
            window_name, layer_name = self.options["slice_link"].split(".")
            matches = [window for window in self.plot_window.app.windows if window.name == window_name]
            logger.debug("matching windows for slice_link: %r", matches)
            if matches:
                window = matches[0]
                matches = [layer for layer in window.layers if layer.name == layer_name]
                logger.debug("matching layers for slice_link: %r", matches)
                if matches:
                    layer = matches[0]
                    self.slice_link(layer)

        return self.toolbox

    def grab_layer_control(self, new_parent):
        # no need to take action
        # self.widget_layer_control = page_widget = QtGui.QGroupBox(self.name, parent)
        self.page_visual_groupbox_layout.addWidget(self.page_widget_visual)
        return self.page_visual_groupbox

    def release_layer_control(self, current_parent):
        self.page_visual_groupbox.setParent(None)
        self.page_visual_layout.addWidget(self.page_widget_visual)

    def _build_widget_qt_layer_control(self, parent):
        self.widget_layer_control = page_widget = QtGui.QGroupBox(self.name, parent)
        # self.widget_layer_control.setFlat(True)

        self.layout_layer_control = QtGui.QGridLayout()
        self.widget_layer_control.setLayout(self.layout_layer_control)
        self.layout_layer_control.setSpacing(0)
        self.layout_layer_control.setContentsMargins(0, 0, 0, 0)

        row = 0

    def get_expression_list(self):
        return self.dataset.get_column_names(virtual=True)

    def onExpressionChanged(self, axis_index):
        text = str(self.axisboxes[axis_index].lineEdit().text())
        if text == self.state.expressions[axis_index]:
            logger.debug("same expression, will not update")
        else:
            self.set_expression(text, axis_index)

    def set_expression(self, expression, index):
        self.state.expressions[index] = expression
        try:
            self.dataset.validate_expression(expression)
        except Exception as e:
            logger.exception("error in expression")
            self.error_in_field(self.axisboxes[index], self.axis_names[index], e)
            return
        self.axisboxes[index].lineEdit().setText(expression)
        self.plot_window.queue_history_change("changed expression %s to %s" % (self.axis_names[index], expression))
        # TODO: range reset as option?
        self.state.ranges_grid[index] = None
        self.plot_window.state.ranges_viewport[index] = None
        # TODO: how to handle axis lock.. ?
        if not self.plot_window.state.axis_lock:
            self.state.ranges_grid[index] = None
        linkButton = self.linkButtons[index]
        link = linkButton.link
        if link:
            logger.debug("sending link messages")
            link.sendRanges(self.ranges[index], linkButton)
            link.sendRangesShow(self.ranges_show[index], linkButton)
            link.sendExpression(self.state.expressions[index], linkButton)
            vaex.dataset.Link.sendCompute([link], [linkButton])
        else:
            logger.debug("not linked")
        # let any event handler deal with redraw etc
        self.coordinates_picked_row = None
        # self.add_jobs()
        # self.plot_window.queue_update()
        self.update()
        # self.execute()
        # self.signal_expression_change.emit(self, axis_index, text)
        # self.compute()
        # error_text = self.dataset.executor.execute()
        # if error_text:
        # dialog_error(self, "Error in expression", "Error: " +error_text)

    # def onWeightExpr(self):
    # 	text = str(self.weight_box.lineEdit().text())
    # 	if (text == self.state.weight_expression) or (text == "" and self.state.weight_expression == None):
    # 		logger.debug("same weight expression, will not update")
    # 		return
    # 	else:
    # 		self.set_weight_expression(text)
    #
    # def set_weight_expression(self, expression):
    # 	expression = expression or ""
    # 	if expression.strip() == "":
    # 		self.state.weight_expression = None
    # 	else:
    # 		self.state.weight_expression = expression
    # 	if expression:
    # 		try:
    # 			self.dataset.validate_expression(expression)
    # 		except Exception as e:
    # 			self.error_in_field(self.weight_box, "weight", e)
    # 			return
    # 	self.weight_box.lineEdit().setText(expression)
    # 	self.plot_window.queue_history_change("changed weight expression to %s" % (expression))
    # 	self.range_level = None
    # 	self.plot_window.range_level_show = None
    # 	#self.plot_window.queue_update(layer=self)
    # 	self.update()
    # 	#self.add_jobs()
    # 	#self.execute()
    # 	#self.plot()

    def onTitleExpr(self):
        self.title_expression = str(self.title_box.lineEdit().text())
        self.plot()

    def onWeightXExpr(self):
        text = str(self.weight_x_box.lineEdit().text())
        self.set_vector_expression(text, 0)

    def onWeightYExpr(self):
        text = str(self.weight_y_box.lineEdit().text())
        self.set_vector_expression(text, 1)

    def onWeightZExpr(self):
        text = str(self.weight_z_box.lineEdit().text())
        self.set_vector_expression(text, 2)

    def set_vector_expression(self, expression, axis_index):
        # is we set the text to "", check if some of the grids are existing, and simply 'disable' the and replot
        # otherwise check if it changed, if it did, see if we should do the grid computation, since
        # if only 1 grid is defined, we don't need it
        name = "xyz"[axis_index]
        weight_name = ("weight" + name)
        if (not expression) or expression.strip() == "":
            expression = ""
        self.vector_boxes[axis_index].lineEdit().setText(expression)
        if expression == self.state.vector_expressions[axis_index]:
            logger.debug("same vector_expression[%d], will not update", axis_index)
            return

        self.state.vector_expressions[axis_index] = expression
        if expression:
            try:
                self.dataset.validate_expression(expression)
            except Exception as e:
                self.error_in_field(self.weight_x_box, "v" + name, e)
                return

        self.plot_window.queue_history_change("changed vector expression %s to %s" % (name, expression))
        if expression is None:
            if self.grid_vector and weight_name in self.grid_vector and self.grid_vector[weight_name] is not None:
                logger.debug("avoided update due to change in vector_expression[%d]", axis_index)
                self.grid_vector[weight_name] = None
                self.plot_window.queue_replot()
                self.plot_window.queue_push_full_state()
                return

        self.range_level = None
        self.plot_window.range_level_show = None

        logger.debug("current vector expressions: %r" % self.state.vector_expressions)
        non_none_expressions = [k for k in self.state.vector_expressions if k is not None and len(k) > 0]
        if len(non_none_expressions) >= 2:
            logger.debug("do an update due to change in vector_expression[%d]" % axis_index)
            # self.add_jobs()
            # self.execute()
            # self.plot_window.queue_update(layer=self)
            self.update()
        else:
            self.plot_window.queue_push_full_state()

    def onAmplitudeExpr(self):
        text = str(self.amplitude_box.lineEdit().text())
        if len(text) == 0 or text == self.amplitude:
            logger.debug("same expression, skip")
            return
        self.amplitude = text
        self.calculate_amplitudes()
        self.plot_window.calculate_range_level_show()
        self.plot_window.plot()
        # self.plot()

    def check_statistics_weights(self):
        self.option_weight_count.setVisible(self.statistic == "count")
        self.option_weight_statistic.setVisible(self.statistic in ["mean", "sum", "std", "var", "min", "max"])

    def page_main(self, page):
        self.frame_options_main = page  # QtGui.QFrame(self)
        self.layout_frame_options_main = QtGui.QVBoxLayout()
        self.frame_options_main.setLayout(self.layout_frame_options_main)
        self.layout_frame_options_main.setSpacing(0)
        self.layout_frame_options_main.setContentsMargins(0, 0, 0, 0)
        self.layout_frame_options_main.setAlignment(QtCore.Qt.AlignTop)

        self.button_layout = QtGui.QVBoxLayout()
        if self.dimensions > 1:
            self.buttonFlipXY = QtGui.QPushButton("exchange x and y")

            def flipXY():
                self.state.expressions.reverse()
                self.state.ranges_grid.reverse()
                # TODO: how to handle layers?
                self.plot_window.state.ranges_viewport.reverse()
                for box, expr in zip(self.axisboxes, self.state.expressions):
                    box.lineEdit().setText(expr)
                # self.plot_window.queue_update() # only update thislayer??
                self.update()
                self.execute()
            self.buttonFlipXY.clicked.connect(flipXY)
            self.button_layout.addWidget(self.buttonFlipXY, 0.)
            self.buttonFlipXY.setAutoDefault(False)
            self.button_flip_colormap = QtGui.QPushButton("exchange colormaps")

            def flip_colormap():
                index1 = self.colormap_box.currentIndex()
                index2 = self.colormap_vector_box.currentIndex()
                self.colormap_box.setCurrentIndex(index2)
                self.colormap_vector_box.setCurrentIndex(index1)
            self.button_flip_colormap.clicked.connect(flip_colormap)
            self.button_layout.addWidget(self.button_flip_colormap)
            self.button_flip_colormap.setAutoDefault(False)
        self.layout_frame_options_main.addLayout(self.button_layout, 0)

        self.axisboxes = []
        self.onExpressionChangedPartials = []
        axis_index = 0

        self.grid_layout = QtGui.QGridLayout()
        # self.grid_layout.setColumnStretch(2, 1)
        self.grid_layout.setColumnStretch(1, 1)
        self.grid_layout.setSpacing(0)
        self.grid_layout.setContentsMargins(2, 1, 2, 1)
        self.grid_layout.setAlignment(QtCore.Qt.AlignTop)
        # row = 0
        self.linkButtons = []
        for axis_name in self.axis_names:
            row = axis_index
            axisbox = vaex.ui.completer.ExpressionCombobox(page, self.dataset, variables=True)  # $QtGui.QComboBox(page)
            # $axisbox.setEditable(True)
            # axisbox.setMinimumContentsLength(10)
            # self.form_layout.addRow(axis_name + '-axis:', axisbox)
            self.grid_layout.addWidget(QtGui.QLabel(axis_name + '-axis:', page), row, 0)
            self.grid_layout.addWidget(axisbox, row, 1)
            linkButton = LinkButton("link", self.dataset, axis_index, page)
            self.linkButtons.append(linkButton)
            linkButton.setChecked(True)
            linkButton.setVisible(False)
            # obove doesn't fire event, do manually
            # linkButton.onToggleLink()
            if 1:
                functionButton = QtGui.QToolButton(page)
                functionButton.setIcon(QtGui.QIcon(iconfile('edit-mathematics')))
                menu = QtGui.QMenu()
                functionButton.setMenu(menu)
                functionButton.setPopupMode(QtGui.QToolButton.InstantPopup)
                # link_action = QtGui.QAction(QtGui.QIcon(iconfile('network-connect-3')), '&Link axis', self)
                # unlink_action = QtGui.QAction(QtGui.QIcon(iconfile('network-disconnect-2')), '&Unlink axis', self)
                templates = ["log10(%s)", "sqrt(%s)", "1/(%s)", "abs(%s)"]

                for template in templates:
                    action = QtGui.QAction(template % "...", page)

                    def add(checked=None, axis_index=axis_index, template=template):
                        logger.debug("adding template %r to axis %r" % (template, axis_index))
                        expression = self.state.expressions[axis_index].strip()
                        if "#" in expression:
                            expression = expression[:expression.index("#")].strip()
                        self.state.expressions[axis_index] = template % expression
                        # this doesn't cause an event causing jobs to be added?
                        self.axisboxes[axis_index].lineEdit().setText(self.state.expressions[axis_index])
                        self.state.ranges_grid[axis_index] = None
                        self.coordinates_picked_row = None
                        if not self.plot_window.state.axis_lock:
                            self.plot_window.state.ranges_viewport[axis_index] = None
                        # to add them
                        # self.add_jobs()
                        # self.execute()
                        self.update()
                    action.triggered.connect(add)
                    menu.addAction(action)
                self.grid_layout.addWidget(functionButton, row, 2, QtCore.Qt.AlignLeft)
                # menu.addAction(unlink_action)
                # self.grid_layout.addWidget(functionButton, row, 2)
            # self.grid_layout.addWidget(linkButton, row, 0)
            # if axis_index == 0:
            extra_expressions = []
            expressionList = self.get_expression_list()
            for prefix in ["", "v", "v_"]:
                names = "x y z".split()
                allin = True
                for name in names:
                    if prefix + name not in expressionList:
                        allin = False
                # if all items found, add it
                # if allin:
                # expression = "l2(%s) # l2 norm" % (",".join([prefix+name for name in names]))
                # extra_expressions.append(expression)

                if 0:  # this gives too much clutter
                    for name1 in names:
                        for name2 in names:
                            if name1 != name2:
                                if name1 in expressionList and name2 in expressionList:
                                    expression = "d(%s)" % (",".join([prefix + name for name in [name1, name2]]))
                                    extra_expressions.append(expression)

            axisbox.addItems(extra_expressions + self.get_expression_list())
            # axisbox.setCurrentIndex(self.state.expressions[axis_index])
            # axisbox.currentIndexChanged.connect(functools.partial(self.onAxis, axis_index=axis_index))
            axisbox.lineEdit().setText(self.state.expressions[axis_index])
            # keep a list to be able to disconnect
            self.onExpressionChangedPartials.append(functools.partial(self.onExpressionChanged, axis_index=axis_index))
            axisbox.lineEdit().editingFinished.connect(self.onExpressionChangedPartials[axis_index])
            # if the combox pulldown is clicked, execute the same command
            axisbox.currentIndexChanged.connect(lambda _, axis_index=axis_index: self.onExpressionChangedPartials[axis_index]())
            axis_index += 1
            self.axisboxes.append(axisbox)
        row += 1
        self.layout_frame_options_main.addLayout(self.grid_layout, 0)
        # self.layout_frame_options_main.addLayout(self.form_layout, 0) # TODO: form layout can be removed?

        self.option_statistic = Option(page, "Statistic", ["count", "mean", "sum", "std", "var", "min", "max"], getter=attrgetter(self, "statistic"), setter=attrsetter(self, "statistic"), update=self.update)
        row = self.option_statistic.add_to_grid_layout(row, self.grid_layout)

        self.option_weight_count = Option(page, "Weight", ["*"] + self.dataset.get_column_names(virtual=True), getter=attrgetter(self, "weight_count"), setter=attrsetter(self, "weight_count"), update=self.update)
        row = self.option_weight_count.add_to_grid_layout(row, self.grid_layout)

        self.option_weight_statistic = Codeline(page, "Weight", self.dataset.get_column_names(virtual=True), getter=attrgetter(self, "weight"), setter=attrsetter(self, "weight"), update=self.update)
        row = self.option_weight_statistic.add_to_grid_layout(row, self.grid_layout)

        self.check_statistics_weights()

        self.transform = "log10(grid)"
        # self.option_transform = Codeline(page, "Amplitude", ["grid", "log10(grid)", "log10(grid+1)", "sqrt(grid)"], getter=attrgetter(self, "transform"), setter=attrsetter(self, "transform"), update=self.signal_plot_dirty.emit)
        # row = self.option_transform .add_to_grid_layout(row, self.grid_layout)

        self.amplitude_box = QtGui.QComboBox(page)
        self.amplitude_box.setEditable(True)
        if "amplitude" in self.options:
            self.amplitude_box.addItems([self.options["amplitude"]])
        if self.dimensions == 1:
            self.amplitude_box.addItems(["grid", "log10(grid)"])
        else:
            self.amplitude_box.addItems(["log10(grid)", "grid"])
        # self.amplitude_box.addItems(["log(counts) if weighted is None else average", "counts", "counts**2", "average", "sqrt(counts)"])
        self.amplitude_box.addItems(["log(grid+1)"])
        self.amplitude_box.addItems(["gf(log(grid+1),1)"])
        self.amplitude_box.addItems(["gf(log(grid+1),2)"])
        self.amplitude_box.addItems(["dog(grid, 2, 2.1)"])
        if 0:
            self.amplitude_box.addItems(["counts/peak_columns # divide by peak value in every row"])
            self.amplitude_box.addItems(["counts/sum_columns # normalize columns"])
            self.amplitude_box.addItems(["counts/peak_rows # divide by peak value in every row"])
            self.amplitude_box.addItems(["counts/sum_rows # normalize rows"])
            self.amplitude_box.addItems(["log(counts/peak_columns)"])
            self.amplitude_box.addItems(["log(counts/sum_columns)"])
            self.amplitude_box.addItems(["log(counts/peak_rows)"])
            self.amplitude_box.addItems(["log(counts/sum_rows)"])
            self.amplitude_box.addItems(["abs(fft.fftshift(fft.fft2(counts))) # 2d fft"])
            self.amplitude_box.addItems(["abs(fft.fft(counts, axis=1)) # ffts along y axis"])
            self.amplitude_box.addItems(["abs(fft.fft(counts, axis=0)) # ffts along x axis"])
        self.amplitude_box.setMinimumContentsLength(10)
        self.grid_layout.addWidget(QtGui.QLabel("amplitude="), row, 0)
        self.grid_layout.addWidget(self.amplitude_box, row, 1, QtCore.Qt.AlignLeft)
        # self.amplitude_box.lineEdit().editingFinished.connect(self.onAmplitudeExpr)
        # self.amplitude_box.currentIndexChanged.connect(lambda _: self.onAmplitudeExpr())

        def onchange(*args, **kwargs):
            self.onAmplitudeExpr()

        def onchange_line(*args, **kwargs):
            if len(str(self.amplitude_box.lineEdit().text())) == 0:
                self.onAmplitudeExpr()
        # self.amplitude_box.currentIndexChanged.connect(functools.partial(onchange, event="currentIndexChanged"))
        # self.amplitude_box.editTextChanged.connect(functools.partial(onchange, event="editTextChanged"))
        # self.amplitude_box.lineEdit().editingFinished.connect(functools.partial(onchange, event="editingFinished"))

        # this event is also fired when the line edit is finished, except when an empty entry is given
        self.amplitude_box.currentIndexChanged.connect(onchange)
        self.amplitude_box.lineEdit().editingFinished.connect(functools.partial(onchange_line, event="editingFinished"))

        self.amplitude = str(self.amplitude_box.lineEdit().text())

        row += 1

        if 0:  # TODO: this should go out of layer...
            self.title_box = QtGui.QComboBox(page)
            self.title_box.setEditable(True)
            self.title_box.addItems([""] + self.getTitleExpressionList())
            self.title_box.setMinimumContentsLength(10)
            self.grid_layout.addWidget(QtGui.QLabel("title="), row, 0)
            self.grid_layout.addWidget(self.title_box, row, 1)
            self.title_box.lineEdit().editingFinished.connect(self.onTitleExpr)
            self.title_box.currentIndexChanged.connect(lambda _: self.onTitleExpr())
            self.title_expression = str(self.title_box.lineEdit().text())
            row += 1

        if 0:
            self.weight_box = vaex.ui.completer.ExpressionCombobox(page, self.dataset, variables=True)  # QtGui.QComboBox(page)
            self.weight_box.setEditable(True)
            self.weight_box.addItems([self.options.get("weight", "")] + self.get_expression_list())
            self.weight_box.setMinimumContentsLength(10)
            self.grid_layout.addWidget(QtGui.QLabel("weight="), row, 0)
            self.grid_layout.addWidget(self.weight_box, row, 1)
            self.weight_box.lineEdit().editingFinished.connect(self.onWeightExpr)
            self.weight_box.currentIndexChanged.connect(lambda _: self.onWeightExpr())
            self.state.weight_expression = str(self.weight_box.lineEdit().text())
            if len(self.state.weight_expression.strip()) == 0:
                self.state.weight_expression = None
            row += 1

        if 0:
            self.flip_x = False
            ucd_x = self.dataset.ucds.get(self.x)
            if ucd_x and ("pos.galactic.lon" in ucd_x or "pos.eq.ra" in ucd_x):
                self.flip_x = True

            self.checkbox_flip_x = Checkbox(page, "flip_x", getter=attrgetter(self, "flip_x"), setter=attrsetter(self, "flip_x"), update=self.signal_plot_dirty.emit)
            row = self.checkbox_flip_x.add_to_grid_layout(row, self.grid_layout, 1)

            self.flip_y = False
            ucd_x = self.dataset.ucds.get(self.y)
            # if ucd_x and ("pos.galactic.lon" in ucd_x or "pos.eq.ra" in ucd_x):
            # self.flip_x = True

            self.checkbox_flip_y = Checkbox(page, "flip_y", getter=attrgetter(self, "flip_y"), setter=attrsetter(self, "flip_y"), update=self.signal_plot_dirty.emit)
            row = self.checkbox_flip_y.add_to_grid_layout(row, self.grid_layout, 1)

        self.option_xrange = RangeOption(page, "x-range", [0], lambda: self.get_range(0), lambda value: self.plot_window.set_range(value[0], value[1], 0), update=self.update)
        row = self.option_xrange.add_to_grid_layout(row, self.grid_layout)

        if self.dimensions >= 2:
            self.option_yrange = RangeOption(page, "y-range", [0], lambda: self.get_range(1), lambda value: self.plot_window.set_range(value[0], value[1], 1), update=self.update)
            row = self.option_yrange.add_to_grid_layout(row, self.grid_layout)
        if self.dimensions >= 3:
            self.option_zrange = RangeOption(page, "z-range", [0], lambda: self.get_range(2), lambda value: self.plot_window.set_range(value[0], value[1], 2), update=self.update)
            row = self.option_zrange.add_to_grid_layout(row, self.grid_layout)

        self.state.output_units = []
        self.option_output_unit = []
        for dim in range(self.dimensions):
            name = "unit" + self.axis_names[dim]
            self.state.output_units.append(self.options.get(name, ""))

            def get(dim=dim):
                return self.state.output_units[dim]

            def set(value, dim=dim, name=name):
                if not value:
                    self.state.output_units[dim] = ""
                    self.plot_window.queue_history_change("changed %s to default" % name)
                    self.plot_window.queue_push_full_state()
                else:
                    try:
                        unit_output = astropy.units.Unit(value)
                        unit_input = self.dataset.unit(self.state.expressions[dim])
                        unit_input.to(unit_output)
                        self.plot_window.queue_history_change("changed %s to %s" % (name, value))
                        self.plot_window.queue_push_full_state()
                    except Exception as e:
                        self.error_dialog(self.option_output_unit[dim].textfield, "Error converting units", e)
                    else:
                        self.state.output_units[dim] = value
            self.option_output_unit.append(
                dialogs.TextOption(page, name, get(), placeholder="output units", getter=get, setter=set, update=self.signal_plot_dirty.emit)
            )
            self.option_output_unit[-1].set_unit_completer()
            row = self.option_output_unit[-1].add_to_grid_layout(row, self.grid_layout)

        if 0:
            self.grid_layout.addWidget(QtGui.QLabel("visible:"), row, 0)
            self.label_visible = QtGui.QLabel("", page)
            self.grid_layout.addWidget(self.label_visible, row, 1)

        row += 1

    def page_visual(self, page):

        # this widget is used for the layer control, it is wrapped around the page_widget
        self.page_visual_groupbox = QtGui.QGroupBox(self.name)
        self.page_visual_groupbox_layout = QtGui.QVBoxLayout(page)
        self.page_visual_groupbox_layout.setAlignment(QtCore.Qt.AlignTop)
        self.page_visual_groupbox_layout.setSpacing(0)
        self.page_visual_groupbox_layout.setContentsMargins(0, 0, 0, 0)
        self.page_visual_groupbox.setLayout(self.page_visual_groupbox_layout)

        self.page_visual_widget = page  # refactor, change -> page_X to fill_page_X and use page_X for the wiget

        self.page_visual_layout = layout = QtGui.QVBoxLayout(page)
        layout.setAlignment(QtCore.Qt.AlignTop)
        layout.setSpacing(0)
        layout.setContentsMargins(0, 0, 0, 0)
        page.setLayout(layout)

        # put all children in one parent widget to easily move them (for layer control)
        self.page_widget_visual = page_widget = QtGui.QWidget(page)
        layout.addWidget(page_widget)

        grid_layout = QtGui.QGridLayout()
        grid_layout.setColumnStretch(2, 1)
        page_widget.setLayout(grid_layout)
        grid_layout.setAlignment(QtCore.Qt.AlignTop)
        grid_layout.setSpacing(0)
        grid_layout.setContentsMargins(0, 0, 0, 0)

        row = 1

        self.visible = True
        self.checkbox_visible = Checkbox(page_widget, "visible", getter=attrgetter(self, "visible"), setter=attrsetter(self, "visible"), update=self.signal_plot_dirty.emit)
        row = self.checkbox_visible.add_to_grid_layout(row, grid_layout)

        # self.checkbox_intensity_as_opacity = Checkbox(page_widget, "use_intensity", getter=attrgetter(self, "use_intensity"), setter=attrsetter(self, "use_intensity"), update=self.signal_plot_dirty.emit)
        # row = self.checkbox_intensity_as_opacity.add_to_grid_layout(row, grid_layout)

        if self.dimensions <= 3:
            show_options = ["total+selection", "total", "selection"]
            self.show = self.options.get("show", "total+selection")
            self.option_show = Option(page_widget, "show", show_options, getter=attrgetter(self, "show"), setter=attrsetter(self, "show"), update=self.signal_plot_dirty.emit)
            row = self.option_show.add_to_grid_layout(row, grid_layout)

        if self.dimensions >= 2:
            transparancies = ["intensity", "constant", "none"]
            self.transparancy = self.options.get("transparancy", "constant")
            self.option_transparancy = Option(page_widget, "transparancy", transparancies, getter=attrgetter(self, "transparancy"), setter=attrsetter(self, "transparancy"), update=self.signal_plot_dirty.emit)
            row = self.option_transparancy.add_to_grid_layout(row, grid_layout)

        self.slider_layer_alpha = Slider(page_widget, "opacity", 0, 1, 1000, getter=attrgetter(self.state, "alpha"), setter=attrsetter(self, "alpha"), update=self.signal_plot_dirty.emit)
        row = self.slider_layer_alpha.add_to_grid_layout(row, grid_layout)

        if self.dimensions >= 2:
            self.slider_layer_level_min = Slider(page_widget, "level_min", 0, 1, 1000, getter=attrgetter(self, "level_min"), setter=attrsetter(self, "level_min"), update=self.signal_plot_dirty.emit)
            row = self.slider_layer_level_min.add_to_grid_layout(row, grid_layout)

            self.slider_layer_level_max = Slider(page_widget, "level_max", 0, 1, 1000, getter=attrgetter(self, "level_max"), setter=attrsetter(self, "level_max"), update=self.signal_plot_dirty.emit)
            row = self.slider_layer_level_max.add_to_grid_layout(row, grid_layout)

            self.display_type = self.options.get("display_type", "colormap")
            self.option_display_type = Option(page_widget, "display", ["colormap", "solid", "contour"], getter=attrgetter(self, "display_type"), setter=attrsetter(self, "display_type"), update=self.signal_plot_dirty.emit)
            row = self.option_display_type.add_to_grid_layout(row, grid_layout)

        colors = ["red", "green", "blue", "orange", "cyan", "magenta", "black", "gold", "purple"]
        default_color = colors[self.plot_window.layers.index(self)]
        self.color = self.options.get("color", default_color)
        self.option_solid_color = Option(page_widget, "color", colors, getter=attrgetter(self, "color"), setter=attrsetter(self, "color"), update=self.signal_plot_dirty.emit)
        row = self.option_solid_color.add_to_grid_layout(row, grid_layout)

        colors = ["red", "green", "blue", "orange", "cyan", "magenta", "black", "gold", "purple"]
        default_color = colors[-1 - self.plot_window.layers.index(self)]
        self.color_alt = self.options.get("color_alt", default_color)
        self.option_solid_color_alt = Option(page_widget, "color_alt", colors, getter=attrgetter(self, "color_alt"), setter=attrsetter(self, "color_alt"), update=self.signal_plot_dirty.emit)
        row = self.option_solid_color_alt.add_to_grid_layout(row, grid_layout)

        if self.dimensions == 1:

            self.display_type = self.options.get("display_type", "bar")
            self.option_display_type = Option(page_widget, "display", ["bar", "line"], getter=attrgetter(self, "display_type"), setter=attrsetter(self, "display_type"), update=self.signal_plot_dirty.emit)
            row = self.option_display_type.add_to_grid_layout(row, grid_layout)

            def update():
                self.plot_window.state.range_level_show = None
                self.calculate_amplitudes()
                self.signal_plot_dirty.emit()
            self._normalize = eval(self.options.get("normalize", "False"))
            self.checkbox_normalize = Checkbox(page_widget, "normalize", getter=attrgetter(self, "_normalize"), setter=attrsetter(self, "_normalize"), update=update)
            row = self.checkbox_normalize.add_to_grid_layout(row, grid_layout)

            self._cumulative = eval(self.options.get("cumulative", "False"))
            self.checkbox_cumulative = Checkbox(page_widget, "cumulative", getter=attrgetter(self, "_cumulative"), setter=attrsetter(self, "_cumulative"), update=update)
            row = self.checkbox_cumulative.add_to_grid_layout(row, grid_layout)

        if self.dimensions > 1:
            vaex.ui.colormaps.process_colormaps()
            self.colormap_box = QtGui.QComboBox(page_widget)
            self.colormap_box.setIconSize(QtCore.QSize(16, 16))
            model = QtGui.QStandardItemModel(self.colormap_box)
            for colormap_name in vaex.ui.colormaps.colormaps:
                colormap = matplotlib.cm.get_cmap(colormap_name)
                pixmap = vaex.ui.colormaps.colormap_pixmap[colormap_name]
                icon = QtGui.QIcon(pixmap)
                item = QtGui.QStandardItem(icon, colormap_name)
                model.appendRow(item)
            self.colormap_box.setModel(model)
            # self.form_layout.addRow("colormap=", self.colormap_box)
            self.label_colormap = QtGui.QLabel("colormap=")
            grid_layout.addWidget(self.label_colormap, row, 0)
            grid_layout.addWidget(self.colormap_box, row, 1, QtCore.Qt.AlignLeft)

            def onColorMap(index):
                colormap_name = str(self.colormap_box.itemText(index))
                logger.debug("selected colormap: %r" % colormap_name)
                self.state.colormap = colormap_name
                if hasattr(self, "widget_volume"):
                    self.plugins_map["transferfunction"].tool.colormap = self.state.colormap
                    self.plugins_map["transferfunction"].tool.update()
                    self.widget_volume.colormap_index = index
                    self.widget_volume.update()
                # self.plot()
                self.signal_plot_dirty.emit(self)
            cmapnames = "cmap colormap colourmap".split()
            if not set(cmapnames).isdisjoint(self.options):
                for name in cmapnames:
                    if name in self.options:
                        break
                cmap = self.options[name]
                if cmap not in vaex.ui.colormaps.colormaps:
                    colormaps_sorted = sorted(vaex.ui.colormaps.colormaps)
                    colormaps_string = " ".join(colormaps_sorted)
                    dialogs.dialog_error(self, "Wrong colormap name", "colormap {cmap} does not exist, choose between: {colormaps_string}".format(**locals()))
                    index = 0
                else:
                    index = vaex.ui.colormaps.colormaps.index(cmap)
                self.colormap_box.setCurrentIndex(index)
                self.state.colormap = vaex.ui.colormaps.colormaps[index]
            self.colormap_box.currentIndexChanged.connect(onColorMap)

        row += 1

        self.contour_count = int(self.options.get("contour_count", 4))
        self.slider_contour_count = Slider(page_widget, "contour_count", 0, 20, 20, getter=attrgetter(self, "contour_count"), setter=attrsetter(self, "contour_count"), update=self.signal_plot_dirty.emit, format="{0:<3d}", numeric_type=int)
        row = self.slider_contour_count.add_to_grid_layout(row, grid_layout)

    def page_annotate(self, page):
        # self.frame_options_vector2d = page #QtGui.QFrame(self)
        # self.layout_frame_options_vector2d =  QtGui.QVBoxLayout()
        # self.frame_options_vector2d.setLayout(self.layout_frame_options_vector2d)
        # self.layout_frame_options_vector2d.setSpacing(0)
        # self.layout_frame_options_vector2d.setContentsMargins(0,0,0,0)
        # self.layout_frame_options_vector2d.setAlignment(QtCore.Qt.AlignTop)

        self.grid_layout_annotate = QtGui.QGridLayout()
        self.grid_layout_annotate.setColumnStretch(1, 1)
        self.grid_layout_annotate.setSpacing(0)
        self.grid_layout_annotate.setContentsMargins(2, 1, 2, 1)
        self.grid_layout_annotate.setAlignment(QtCore.Qt.AlignTop)
        page.setLayout(self.grid_layout_annotate)
        row = 0

        def get():
            return self.state.title

        def set(value):
            self.state.title = value
            self.plot_window.queue_history_change("changed title to %s" % (value))
            self.plot_window.queue_push_full_state()
        # def default():
        # #return "default label"
        # return self.plot_window.get_default_label(0)
        self.option_title = TextOption(page, "title", self.state.title, None, get, set, self.signal_plot_dirty.emit)
        row = self.option_title.add_to_grid_layout(row, self.grid_layout_annotate)

        self.state.labels = []

        self.state.labels.append(self.options.get("label_x"))

        def get():
            return self.state.labels[0]

        def set(value):
            self.state.labels[0] = value
            self.plot_window.queue_history_change("changed label_x to %s" % (value))
            self.plot_window.queue_push_full_state()

        def default():
            # return "default label"
            return self.plot_window.get_default_label(0)
        self.option_label_x = TextOption(page, "label_x", self.state.labels[0], default, get, set, self.signal_plot_dirty.emit)
        row = self.option_label_x.add_to_grid_layout(row, self.grid_layout_annotate)

        self.state.labels.append(self.options.get("label_y"))

        def get():
            return self.state.labels[1]

        def set(value):
            self.state.labels[1] = value
            self.plot_window.queue_history_change("changed label_y to %s" % (value))
            self.plot_window.queue_push_full_state()

        def default():
            # return "default label"
            return self.plot_window.get_default_label(1)
        self.option_label_y = TextOption(page, "label_y", self.state.labels[1], default, get, set, self.signal_plot_dirty.emit)
        row = self.option_label_y.add_to_grid_layout(row, self.grid_layout_annotate)

        if self.dimensions > 2:
            self.state.labels.append(self.options.get("label_z"))

            def get():
                return self.state.labels[2]

            def set(value):
                self.state.labels[2] = value
                self.plot_window.queue_history_change("changed label_z to %s" % (value))
                self.plot_window.queue_push_full_state()

            def default():
                # return "default label"
                return self.plot_window.get_default_label(2)
            self.option_label_z = TextOption(page, "label_z", self.state.labels[2], default, get, set, self.signal_plot_dirty.emit)
            row = self.option_label_z.add_to_grid_layout(row, self.grid_layout_annotate)

        def get():
            return self.state.colorbar

        def set(value):
            self.state.colorbar = value
            self.plot_window.queue_history_change("enabled colorbar" if value else "disabled colorbar")
            self.plot_window.queue_push_full_state()
        self.state.colorbar = eval(self.options.get("colorbar", "True"))
        self.colorbar_checkbox = Checkbox(page, "colorbar", getter=get, setter=set, update=self.signal_plot_dirty.emit)
        row = self.colorbar_checkbox.add_to_grid_layout(row, self.grid_layout_annotate)

    def page_slice(self, page):
        class PageWrapper(object):
            def __init__(self, layer, page_widget):
                self.layer = layer
                self.page_widget = page_widget
                self.layout_page = QtGui.QVBoxLayout()
                self.page_widget.setLayout(self.layout_page)
                self.layout_page.setSpacing(0)
                self.layout_page.setContentsMargins(0, 0, 0, 0)
                self.layout_page.setAlignment(QtCore.Qt.AlignTop)
                self.row = 0

                self.grid_layout = QtGui.QGridLayout()
                self.grid_layout.setColumnStretch(2, 1)
                self.layout_page.addLayout(self.grid_layout)

            def add(self, name, widget):
                self.grid_layout.addWidget(QtGui.QLabel(name), self.row, 0)
                self.grid_layout.addWidget(widget, self.row, 1)
                self.row += 1

            def add_slider_linear(self, name, value, min, max, steps=1000):
                def getter():
                    return getattr(self.layer, name)

                def setter(value):
                    setattr(self.layer, name, value)
                slider = Slider(self.page_widget, name, min, max, steps, getter, setter)
                self.row = slider.add_to_grid_layout(self.row, self.grid_layout)

        page = PageWrapper(self, page)
        self.menu_button_slice_link = QtGui.QPushButton("No link", page.page_widget)
        self.menu_slice_link = QtGui.QMenu()
        self.menu_button_slice_link.setMenu(self.menu_slice_link)

        action = QtGui.QAction("unlink", self.menu_slice_link)
        action.triggered.connect(lambda *x: self.slice_unlink())
        self.menu_slice_link.addAction(action)

        for window in self.plot_window.app.windows:
            layers = [layer for layer in window.layers if layer.dataset == self.dataset]
            if layers:
                menu_window = QtGui.QMenu(window.name, self.menu_slice_link)
                self.menu_slice_link.addMenu(menu_window)
                # self.menu_slice_link.add
                for layer in window.layers:
                    # menu_layer = QtGui.QMenu(layer.name)
                    action = QtGui.QAction(layer.name, self.menu_slice_link)

                    def on_link(ignore=None, layer=layer):
                        self.slice_link(layer)
                    action.triggered.connect(on_link)
                    menu_window.addAction(action)
                # self.menu_slice_link.

        page.add("slice_link", self.menu_button_slice_link)
        self.signal_slice_change = vaex.events.Signal("slice changed")

        self._slice_radius = 0.1
        page.add_slider_linear("slice_radius", self.slice_radius, 0.0, 1.0)

    @property
    def slice_radius(self): return self._slice_radius

    @slice_radius.setter
    def slice_radius(self, value):
        self._slice_radius = value
        self.plot_window.slice_radius = value
        self.plot_window.setMode(self.plot_window.lastAction)

    def slice_link(self, layer):
        if self.plot_window.state.grid_size != layer.plot_window.state.grid_size:
            msg = "Source layer has a gridsize of %d, while the linked layer has a gridsize of %d, only linking with equal gridsize is supported" % (self.plot_window.state.grid_size, layer.plot_window.state.grid_size)
            dialogs.dialog_error(self.plot_window, "Unequal gridsize", msg)
            return
        dim = self.plot_window.dimensions * layer.plot_window.dimensions
        bytes_required = (layer.plot_window.state.grid_size ** dim) * 8
        if memory_check_ok(self.plot_window, bytes_required):
            name = layer.plot_window.name + "." + layer.name
            self.menu_button_slice_link.setText(name)
            self.slice_unlink()

            self.layer_slice_source = layer
            self.slice_axis = [True] * layer.dimensions
            shape = (layer.plot_window.state.grid_size, ) * layer.dimensions
            self.slice_selection_grid = np.ones(shape, dtype=bool)
            self.layer_slice_source.signal_slice_change.connect(self.on_slice_change)
            self.layer_slice_source.signal_needs_update.connect(self.on_slice_source_needs_update)
            self.update()

    def slice_unlink(self):
        if self.layer_slice_source is not None:
            self.layer_slice_source.signal_slice_change.disconnect(self.on_slice_change)
            self.layer_slice_source.signal_needs_update.disconnect(self.on_slice_source_needs_update)
            self.layer_slice_source = None
            self.update()

    def on_slice_source_needs_update(self):
        self.update()

    def on_slice_change(self, selection_grid, clicked):
        self.slice_selection_grid = selection_grid
        self.calculate_amplitudes()
        self.signal_plot_dirty.emit()

    def page_selection(self, page):
        self.layout_page_selection = QtGui.QVBoxLayout()
        page.setLayout(self.layout_page_selection)
        self.layout_page_selection.setSpacing(0)
        self.layout_page_selection.setContentsMargins(0, 0, 0, 0)
        self.layout_page_selection.setAlignment(QtCore.Qt.AlignTop)

        # button_layout = QtGui.QVBoxLayout()

        self.button_selection_undo = QtGui.QPushButton(QtGui.QIcon(iconfile('undo')), "Undo", page)
        self.button_selection_redo = QtGui.QPushButton(QtGui.QIcon(iconfile('redo')), "Redo", page)
        self.layout_page_selection.addWidget(self.button_selection_undo)
        self.layout_page_selection.addWidget(self.button_selection_redo)

        def on_undo(checked=False):
            self.dataset.selection_undo()
            self.check_selection_undo_redo()

        def on_redo(checked=False):
            self.dataset.selection_redo()
            self.check_selection_undo_redo()
        self.button_selection_undo.clicked.connect(on_undo)
        self.button_selection_redo.clicked.connect(on_redo)
        self.check_selection_undo_redo()

        self.label_selection_info = QtGui.QLabel("should not see me", page)
        self.layout_page_selection.addWidget(self.label_selection_info)
        # self.label_selection_info_update()

        def on_select_expression():
            logger.debug("making selection by expression")
            all = storage_expressions.get_all("selection", self.dataset)
            expressions = []
            for stored in all:
                for ex in stored["options"]["expressions"]:
                    if ex not in expressions:
                        expressions.append(ex)
            for column in self.dataset.get_column_names():
                ex = "%s < 0" % column
                if ex not in expressions:
                    expressions.append(ex)
            cancelled = False
            while not cancelled:
                expression = dialogs.choose(self.plot_window, "Give expression", "Expression for selection: ", expressions, 0, True)
                if not expression:
                    cancelled = True
                else:
                    expression = str(expression)
                    try:
                        self.dataset.validate_expression(expression)
                    except Exception as e:
                        expressions[0] = expression
                        self.error_in_field(self.button_selection_expression, "selection", e)
                        continue

                    if expression not in expressions:
                        expressions.insert(0, expression)
                    # dialog_info(self.plot_window, "expr", expression)
                    storage_expressions.add("", "selection", self.dataset, {"expressions": expressions})

                    mode = self.plot_window.select_mode
                    self.dataset.select(expression, mode)
                    self.update()
                    # mask = self.dataset.mask
                    # action = vaex.ui.undo.ActionMask(self.dataset.undo_manager, "expression: " + expression, mask, self.apply_mask)
                    # action.do()

                    self.check_selection_undo_redo()
                    return

                    mask = np.zeros(self.dataset._fraction_length, dtype=bool)
                    t0 = time.time()

                    def select(info, blockmask):
                        self.message("selection at %.1f%% (%.2fs)" % (info.percentage, time.time() - t0), index=40)
                        QtCore.QCoreApplication.instance().processEvents()
                        mask[info.i1:info.i2] = self.plot_window.select_mode(None if self.dataset.mask is None else self.dataset.mask[info.i1:info.i2], blockmask == 1)
                        # if info.last:
                        # self.message("selection %.2fs" % (time.time() - t0), index=40)

                    # layer = self.current_layer
                    # if layer is not None:
                    if 1:
                        self.dataset.evaluate(select, expression, **self.getVariableDict())

                        # self.plot_window.checkUndoRedo()
                        # self.setMode(self.lastAction)

        self.button_selection_expression = QtGui.QPushButton(QtGui.QIcon(iconfile('undo')), "Add expression", page)
        self.button_selection_expression.clicked.connect(on_select_expression)
        self.layout_page_selection.addWidget(self.button_selection_expression)

    def label_selection_info_update(self, count):
        # TODO: support this again
        # return
        if count is None:
            self.label_selection_info.setText("no selection")
        else:
            N_sel = int(count)
            N_total = len(self.dataset)
            self.label_selection_info.setText("selected {:,} ({:.2f}%)".format(N_sel, N_sel * 100. / float(N_total)))

    def check_selection_undo_redo(self):
        # if self.widget_build:
        # self.button_selection_undo.setEnabled(self.dataset.undo_manager.can_undo())
        # self.button_selection_redo.setEnabled(self.dataset.undo_manager.can_redo())
        self.button_selection_undo.setEnabled(self.dataset.selection_can_undo())
        self.button_selection_redo.setEnabled(self.dataset.selection_can_redo())

    def page_display(self, page):

        self.frame_options_visuals = page  # QtGui.QFrame(self)
        self.layout_frame_options_visuals = QtGui.QVBoxLayout()
        self.frame_options_visuals.setLayout(self.layout_frame_options_visuals)
        self.layout_frame_options_visuals.setAlignment(QtCore.Qt.AlignTop)

        if self.dimensions > 1:
            if 0:  # TODO: reimplement contrast
                self.action_group_constrast = QtGui.QActionGroup(self)
                self.action_image_contrast = QtGui.QAction(QtGui.QIcon(iconfile('contrast')), '&Contrast', self)
                self.action_image_contrast_auto = QtGui.QAction(QtGui.QIcon(iconfile('contrast')), '&Contrast', self)
                self.toolbar2.addAction(self.action_image_contrast)

                self.action_image_contrast.triggered.connect(self.onActionContrast)
                self.contrast_list = [self.contrast_none, functools.partial(self.contrast_none_auto, percentage=0.1), functools.partial(self.contrast_none_auto, percentage=1), functools.partial(self.contrast_none_auto, percentage=5)]
            self.contrast = self.contrast_none

            if 1:
                self.slider_gamma = QtGui.QSlider(page)
                self.label_gamma = QtGui.QLabel("...", self.frame_options_visuals)
                self.layout_frame_options_visuals.addWidget(self.label_gamma)
                self.layout_frame_options_visuals.addWidget(self.slider_gamma)
                self.slider_gamma.setRange(-100, 100)
                self.slider_gamma.valueChanged.connect(self.onGammaChange)
                self.slider_gamma.setValue(0)
                self.slider_gamma.setOrientation(QtCore.Qt.Horizontal)
                # self.slider_gamma.setMaximumWidth(100)
            self.image_gamma = 1.
            self.update_gamma_label()

            self.image_invert = False
            # self.action_image_invert = QtGui.QAction(QtGui.QIcon(iconfile('direction')), 'Invert image', self)
            # self.action_image_invert.setCheckable(True)
            # self.action_image_invert.triggered.connect(self.onActionImageInvert)
            # self.toolbar2.addAction(self.action_image_invert)
            self.button_image_invert = QtGui.QPushButton(QtGui.QIcon(iconfile('direction')), 'Invert image', self.frame_options_visuals)
            self.button_image_invert.setCheckable(True)
            self.button_image_invert.setAutoDefault(False)
            self.button_image_invert.clicked.connect(self.onActionImageInvert)
            self.layout_frame_options_visuals.addWidget(self.button_image_invert)

    def create_slider(self, parent, label_text, value_min, value_max, getter, setter, value_steps=1000, format=" {0:<0.3f}", transform=lambda x: x, inverse=lambda x: x):
        label = QtGui.QLabel(label_text, parent)
        label_value = QtGui.QLabel(label_text, parent)
        slider = QtGui.QSlider(parent)
        slider.setOrientation(QtCore.Qt.Horizontal)
        slider.setRange(0, value_steps)

        def update_text():
            # label.setText("mean/sigma: {0:<0.3f}/{1:.3g} opacity: {2:.3g}".format(self.tool.function_means[i], self.tool.function_sigmas[i], self.tool.function_opacities[i]))
            label_value.setText(format.format(getter()))

        def on_change(index, slider=slider):
            value = index / float(value_steps) * (inverse(value_max) - inverse(value_min)) + inverse(value_min)
            setter(transform(value))
            update_text()
        slider.setValue((inverse(getter()) - inverse(value_min)) / (inverse(value_max) - inverse(value_min)	) * value_steps)
        update_text()
        slider.valueChanged.connect(on_change)
        return label, slider, label_value

    def create_checkbox(self, parent, label, getter, setter):
        checkbox = QtGui.QCheckBox(label, parent)
        checkbox.setChecked(getter())

        def stateChanged(state):
            value = state == QtCore.Qt.Checked
            setter(value)

        checkbox.stateChanged.connect(stateChanged)
        return checkbox

    def page_vector(self, page):
        self.frame_options_vector2d = page  # QtGui.QFrame(self)
        self.layout_frame_options_vector2d = QtGui.QVBoxLayout()
        self.frame_options_vector2d.setLayout(self.layout_frame_options_vector2d)
        self.layout_frame_options_vector2d.setSpacing(0)
        self.layout_frame_options_vector2d.setContentsMargins(0, 0, 0, 0)
        self.layout_frame_options_vector2d.setAlignment(QtCore.Qt.AlignTop)

        self.grid_layout_vector = QtGui.QGridLayout()
        self.grid_layout_vector.setColumnStretch(2, 1)
        self.layout_frame_options_vector2d.addLayout(self.grid_layout_vector)

        row = 0

        self.vectors_subtract_mean = bool(eval(self.options.get("vsub_mean", "False")))

        def setter(value):
            self.vectors_subtract_mean = value
            # self.plot()
            self.signal_plot_dirty.emit()
        self.vector_subtract_mean_checkbox = self.create_checkbox(page, "subtract mean", lambda: self.vectors_subtract_mean, setter)
        self.grid_layout_vector.addWidget(self.vector_subtract_mean_checkbox, row, 1)
        row += 1

        self.vectors_color_code_3rd = bool(eval(self.options.get("vcolor_3rd", "True" if self.dimensions <= 2 else "False")))

        def setter(value):
            self.vectors_color_code_3rd = value
            # self.plot()
            self.signal_plot_dirty.emit()
        self.vectors_color_code_3rd_checkbox = self.create_checkbox(page, "color code 3rd axis", lambda: self.vectors_color_code_3rd, setter)
        self.grid_layout_vector.addWidget(self.vectors_color_code_3rd_checkbox, row, 1)
        row += 1

        self.vector_auto_scale = (eval(self.options.get("vector_auto_scale", "True")))

        def setter(value):
            self.vector_auto_scale = value
            # self.plot()
            self.signal_plot_dirty.emit()
        self.vector_auto_scale_checkbox = self.create_checkbox(page, "vector_auto_scale", lambda: self.vector_auto_scale, setter)
        self.grid_layout_vector.addWidget(self.vector_auto_scale_checkbox, row, 1)
        row += 1

        self.vector_level_min = float(eval(self.options.get("vector_level_min", "0")))
        self.slider_layer_level_min = Slider(page, "vector_level_min", 0, 1, 1000, getter=attrgetter(self, "vector_level_min"),
                                             setter=attrsetter(self, "vector_level_min"), update=self.signal_plot_dirty.emit,
                                             )  # inverse=lambda x: math.log10(x), transform=lambda x: 10**x)
        row = self.slider_layer_level_min.add_to_grid_layout(row, self.grid_layout_vector)

        self.vector_level_max = float(eval(self.options.get("vector_level_max", "1.0")))
        self.slider_layer_level_max = Slider(page, "vector_level_max", 0, 1, 1000, getter=attrgetter(self, "vector_level_max"),
                                             setter=attrsetter(self, "vector_level_max"), update=self.signal_plot_dirty.emit,
                                             )  # inverse=lambda x: math.log10(x), transform=lambda x: 10**x)
        row = self.slider_layer_level_max.add_to_grid_layout(row, self.grid_layout_vector)

        self.vector_scale = 1.
        self.slider_vector_scale = Slider(page, "vector_scale", 0.01, 100, 100, getter=attrgetter(self, "vector_scale"),
                                          setter=multilayer_attrsetter(self, "vector_scale"), update=self.signal_plot_dirty.emit, uselog=True)
        # format=" {0:>05.2f}", transform=lambda x: 10**x, inverse=lambda x: float(np.log10(x))
        # )#inverse=lambda x: math.log10(x), transform=lambda x: 10**x)
        row = self.slider_vector_scale.add_to_grid_layout(row, self.grid_layout_vector)

        self.vector_head_width = 1
        self.slider_vector_head_width = Slider(page, "vector_head_width", 0.01, 100, 100, getter=attrgetter(self, "vector_head_width"),
                                               setter=multilayer_attrsetter(self, "vector_head_width"), update=self.signal_plot_dirty.emit, uselog=True)
        # format=" {0:>05.2f}", transform=lambda x: 10**x, inverse=lambda x: float(np.log10(x))
        # )#inverse=lambda x: math.log10(x), transform=lambda x: 10**x)
        row = self.slider_vector_head_width.add_to_grid_layout(row, self.grid_layout_vector)

        self.vector_boxes = []
        if self.dimensions > -1:
            self.weight_x_box = vaex.ui.completer.ExpressionCombobox(page, self.dataset, variables=True)  # QtGui.QComboBox(page)
            self.weight_x_box.setMinimumContentsLength(10)
            self.weight_x_box.setEditable(True)
            # self.weight_x_box.addItems([self.options.get("vx", "")] + self.get_expression_list())
            self.weight_x_box.lineEdit().setText(self.options.get("vx", ""))
            self.weight_x_box.setMinimumContentsLength(10)
            self.grid_layout_vector.addWidget(QtGui.QLabel("vx="), row, 0)
            self.grid_layout_vector.addWidget(self.weight_x_box, row, 1)
            # def onWeightXExprLine(*args, **kwargs):
            # if len(str(self.weight_x_box.lineEdit().text())) == 0:
            # self.onWeightXExpr()
            self.weight_x_box.lineEdit().editingFinished.connect(lambda _=None: self.onWeightXExpr())
            self.weight_x_box.currentIndexChanged.connect(lambda _=None: self.onWeightXExpr())
            self.state.vector_expressions[0] = str(self.weight_x_box.lineEdit().text())
            self.vector_boxes.append(self.weight_x_box)
            if 0:
                for name in "x y z".split():
                    if name in self.state.expressions[0]:
                        for prefix in "v v_".split():
                            expression = (prefix + name)
                            if expression in self.get_expression_list():
                                self.weight_x_box.lineEdit().setText(expression)
                                self.state.vector_expressions[0] = expression

            row += 1

        if self.dimensions > -1:
            self.weight_y_box = vaex.ui.completer.ExpressionCombobox(page, self.dataset, variables=True)  # QtGui.QComboBox(page)
            self.weight_y_box.setEditable(True)
            # self.weight_y_box.addItems([self.options.get("vy", "")] + self.get_expression_list())
            self.weight_y_box.lineEdit().setText(self.options.get("vy", ""))
            self.weight_y_box.setMinimumContentsLength(10)
            self.grid_layout_vector.addWidget(QtGui.QLabel("vy="), row, 0)
            self.grid_layout_vector.addWidget(self.weight_y_box, row, 1)
            # def onWeightYExprLine(*args, **kwargs):
            # if len(str(self.weight_y_box.lineEdit().text())) == 0:
            # self.onWeightYExpr()
            self.weight_y_box.lineEdit().editingFinished.connect(lambda _=None: self.onWeightYExpr())
            self.weight_y_box.currentIndexChanged.connect(lambda _=None: self.onWeightYExpr())
            self.state.vector_expressions[1] = str(self.weight_y_box.lineEdit().text())
            self.vector_boxes.append(self.weight_y_box)
            if 0:
                for name in "x y z".split():
                    if self.dimensions > 1:
                        if name in self.state.expressions[1]:
                            for prefix in "v v_".split():
                                expression = (prefix + name)
                                if expression in self.get_expression_list():
                                    self.weight_y_box.lineEdit().setText(expression)
                                    self.state.vector_expressions[0] = expression

            row += 1

            self.weight_z_box = vaex.ui.completer.ExpressionCombobox(page, self.dataset, variables=True)  # QtGui.QComboBox(page)
            self.weight_z_box.setEditable(True)
            # self.weight_z_box.addItems([self.options.get("vz", "")] + self.get_expression_list())
            self.weight_z_box.lineEdit().setText(self.options.get("vz", ""))
            self.weight_z_box.setMinimumContentsLength(10)
            self.grid_layout_vector.addWidget(QtGui.QLabel("vz="), row, 0)
            self.grid_layout_vector.addWidget(self.weight_z_box, row, 1)
            # def onWeightZExprLine(*args, **kwargs):
            # if len(str(self.weight_z_box.lineEdit().text())) == 0:
            # self.onWeightZExpr()
            self.weight_z_box.lineEdit().editingFinished.connect(lambda _=None: self.onWeightZExpr())
            self.weight_z_box.currentIndexChanged.connect(lambda _=None: self.onWeightZExpr())
            self.state.vector_expressions[2] = str(self.weight_z_box.lineEdit().text())
            self.vector_boxes.append(self.weight_z_box)

            row += 1

        self.vector_dimensions = len(self.vector_boxes)
        self.vector_names = "vx vy vz".split()[:self.vector_dimensions]

        if self.dimensions > -1:
            vaex.ui.colormaps.process_colormaps()
            self.colormap_vector_box = QtGui.QComboBox(page)
            self.colormap_vector_box.setIconSize(QtCore.QSize(16, 16))
            model = QtGui.QStandardItemModel(self.colormap_vector_box)
            for colormap_name in vaex.ui.colormaps.colormaps:
                colormap = matplotlib.cm.get_cmap(colormap_name)
                pixmap = vaex.ui.colormaps.colormap_pixmap[colormap_name]
                icon = QtGui.QIcon(pixmap)
                item = QtGui.QStandardItem(icon, colormap_name)
                model.appendRow(item)
            self.colormap_vector_box.setModel(model)
            # self.form_layout.addRow("colormap=", self.colormap_vector_box)
            self.grid_layout_vector.addWidget(QtGui.QLabel("vz_cmap="), row, 0)
            self.grid_layout_vector.addWidget(self.colormap_vector_box, row, 1, QtCore.Qt.AlignLeft)

            def onColorMap(index):
                colormap_name = str(self.colormap_vector_box.itemText(index))
                logger.debug("selected colormap for vector: %r" % colormap_name)
                self.state.colormap_vector = colormap_name
                # self.plot()
                self.signal_plot_dirty.emit()

            cmapnames = "vz_cmap vz_colormap vz_colourmap".split()
            if not set(cmapnames).isdisjoint(self.options):
                for name in cmapnames:
                    if name in self.options:
                        break
                cmap = self.options[name]
                if cmap not in vaex.ui.colormaps.colormaps:
                    colormaps_sorted = sorted(vaex.ui.colormaps.colormaps)
                    colormaps_string = " ".join(colormaps_sorted)
                    dialog_error(self, "Wrong colormap name", "colormap {cmap} does not exist, choose between: {colormaps_string}".format(**locals()))
                    index = 0
                else:
                    index = vaex.ui.colormaps.colormaps.index(cmap)
                self.colormap_vector_box.setCurrentIndex(index)
                self.state.colormap_vector = vaex.ui.colormaps.colormaps[index]
            else:
                index = vaex.ui.colormaps.colormaps.index(self.state.colormap_vector)
                self.colormap_vector_box.setCurrentIndex(index)
            self.colormap_vector_box.currentIndexChanged.connect(onColorMap)

            row += 1

        # self.toolbox.addItem(self.frame_options_main, " Main")
        # self.toolbox.addItem(self.frame_options_vector2d, "Vector 2d")
        # self.toolbox.addItem(self.frame_options_visuals, "Display")
        # self.add_pages(self.toolbox)

        # self.form_layout = QtGui.QFormLayout()

        # self.setStatusBar(self.status_bar)
        # layout.setMargin(0)
        # self.grid_layout.setMargin(0)
        self.grid_layout.setHorizontalSpacing(0)
        self.grid_layout.setVerticalSpacing(0)
        self.grid_layout.setContentsMargins(0, 0, 0, 0)

        self.button_layout.setContentsMargins(0, 0, 0, 0)
        self.button_layout.setSpacing(0)
        # self.form_layout.setContentsMargins(0, 0, 0, 0)
        # self.form_layout.setSpacing(0)
        self.grid_layout.setContentsMargins(0, 0, 0, 0)
        self.messages = {}
        # super(self.__class__, self).afterLayout()

        # self.add_shortcut(self.action_fullscreen, "F")
        # self.add_shortcut(self.action_undo, "Ctrl+Z")
        # self.add_shortcut(self.action_redo, "Alt+Y")

        # self.add_shortcut(self.action_display_mode_both, "1")
        # self.add_shortcut(self.action_display_mode_full, "2")
        # self.add_shortcut(self.action_display_mode_selection, "3")
        # self.add_shortcut(self.action_display_mode_both_contour, "4")

        # if "zoom" in self.options:
        # factor = eval(self.options["zoom"])
        # self.zoom(factor)
        # self.checkUndoRedo()

    def onActionImageInvert(self, ignore=None):
        self.image_invert = self.button_image_invert.isChecked()
        self.plot()

    def update_gamma_label(self):
        text = "gamma=%.3f" % self.image_gamma
        self.label_gamma.setText(text)

    def onGammaChange(self, gamma_index):
        self.image_gamma = 10**(gamma_index / 100. / 2)
        self.update_gamma_label()
        self.queue_replot()

    def normalize(self, array):
        # return (array - np.nanmin(array)) / (np.nanmax(array) - np.nanmin(array))
        return array

    def image_post(self, array):
        return -array if self.image_invert else array

    def contrast_none(self, array):
        return self.image_post(self.normalize(array)**(self.image_gamma))

    def contrast_none_auto(self, array, percentage=1.):
        values = array.reshape(-1)
        mask = np.isinf(values)
        values = values[~mask]
        indices = np.argsort(values)
        min, max = np.nanmin(values), np.nanmax(values)
        N = len(values)
        i1, i2 = int(N * percentage / 100), int(N - N * percentage / 100)
        v1, v2 = values[indices[i1]], values[indices[i2]]
        return self.image_post(self.normalize(np.clip(array, v1, v2))**self.image_gamma)

    def onActionContrast(self):
        index = self.contrast_list.index(self.contrast)
        next_index = (index + 1) % len(self.contrast_list)
        self.contrast = self.contrast_list[next_index]
        self.plot()

    def validate_all_fields(self):
        for i in range(self.dimensions):
            logger.debug("validating %r", self.state.expressions[i])
            try:
                self.dataset.validate_expression(self.state.expressions[i])
            except Exception as e:
                self.error_in_field(self.axisboxes[i], self.axis_names[i], e)
                return False
        for i in range(self.vector_dimensions):
            logger.debug("validating %r", self.state.vector_expressions[i])
            try:
                if self.state.vector_expressions[i]:
                    self.dataset.validate_expression(self.state.vector_expressions[i])
            except Exception as e:
                self.error_in_field(self.vector_boxes[i], self.vector_names[i], e)
                return False

        try:
            if self.weight_count and self.weight_count.strip() != "*":
                self.dataset.validate_expression(self.weight_count)
        except Exception as e:
            self.error_in_field(self.option_weight_count.combobox, "weight", e)
            return False
        try:
            if self.weight:
                self.dataset.validate_expression(self.weight)
        except Exception as e:
            self.error_in_field(self.option_weight_statistic.combobox, "weight", e)
            return False
        return True

    def update(self):
        if self.validate_all_fields():
            self.flag_needs_update()
            self.plot_window.queue_update()

from vaex.dataset import Dataset
from vaex.tasks import Task
from vaex.ui.plot_windows import PlotDialog
