def make_1D_control_box(title): """ init docstring Parameters ---------- name : str Name of the control widget """ self = None ctl_box = ControlContainer(title) ctl_box.create_pairspinner('x_shift', init_min=0, init_max=100, init_step=.1) ctl_box.create_pairspinner('y_shift', init_min=0, init_max=100, init_step=.1) # declare a checkbox to turn on/off auto-scaling functionality autoscale_box = QtGui.QCheckBox(parent=self) ctl_box._add_widget('auto_scale', autoscale_box) ctl_box.create_combobox('cmap_combo', key_list=datad.keys()) # declare button to clear data from plot _btn_dataclear = QtGui.QPushButton("clear data", parent=self) ctl_box._add_widget('clear', _btn_dataclear) # padding to make it look nice ctl_box.addStretch() return ctl_box
# Authors: Frederic Petit <*****@*****.**>, # Gael Varoquaux <*****@*****.**> # Copyright (c) 2007-2020, Enthought, Inc. # License: BSD Style. import os import numpy as np from matplotlib.cm import datad, get_cmap from matplotlib._cm_listed import cmaps from mayavi.core import lut as destination_module from apptools.persistence import state_pickler target_dir = os.path.dirname(destination_module.__file__) values = np.linspace(0., 1., 256) lut_dic = {} # Some of the cmaps are listed in cm.datad, and others in _cm_listed.cmaps cmap_names = datad.keys() cmap_names.extend(cmaps.keys()) for name in cmap_names: if name.endswith('_r'): continue lut_dic[name] = get_cmap(name)(values.copy()) out_name = os.path.join(target_dir, 'pylab_luts.pkl') state_pickler.dump(lut_dic, out_name)
# @QtCore.Slot(object, tuple) def sl_update_limit_func(self, limit_func, new_limits): """ Updates the type of limit computation function used """ self._xsection.set_limit_func(limit_func, new_limits) @QtCore.Slot(tuple) def sl_update_color_limits(self, new_limits): """ Update the values passed to the limit computation function """ self._xsection.update_color_limits(new_limits) _CMAPS = datad.keys() _CMAPS.sort() class StackScannerWidget(QtGui.QWidget): """ This object contains the CrossSectionViewer (2D Image Display) and finish the doc string... """ # set up the signals sig_update_cmap = QtCore.Signal(str) sig_update_image = QtCore.Signal(np.ndarray) sig_update_norm = QtCore.Signal(matplotlib.colors.Normalize) sig_update_limit_function = QtCore.Signal(object, tuple) sig_update_color_limits = QtCore.Signal(tuple)
# Authors: Frederic Petit <*****@*****.**>, # Gael Varoquaux <*****@*****.**> # Copyright (c) 2007-2009, Enthought, Inc. # License: BSD Style. import os import numpy as np from matplotlib.cm import datad, get_cmap from matplotlib._cm_listed import cmaps from mayavi.core import lut as destination_module from apptools.persistence import state_pickler target_dir = os.path.dirname(destination_module.__file__) values = np.linspace(0., 1., 256) lut_dic = {} # Some of the cmaps are listed in cm.datad, and others in _cm_listed.cmaps cmap_names = datad.keys() cmap_names.extend(cmaps.keys()) for name in cmap_names: if name.endswith('_r'): continue lut_dic[name] = get_cmap(name)(values.copy()) out_name = os.path.join(target_dir, 'pylab_luts.pkl') state_pickler.dump(lut_dic, out_name)
Typed, Dict) import numpy as np import sys from bubblegum.backend.mpl.cross_section_2d import (CrossSection, fullrange_limit_factory, absolute_limit_factory, percentile_limit_factory) from dataportal.muxer import DataMuggler, DmImgSequence from datetime import datetime from matplotlib.figure import Figure from matplotlib import colors from .histogram_model import HistogramModel # create the colormap list from matplotlib.cm import datad mpl_colors = datad.keys() mpl_colors.sort() mpl_colors.pop(mpl_colors.index('jet')) mpl_colors.pop(mpl_colors.index('jet_r')) interpolation = [ 'none', 'nearest', 'bilinear', 'bicubic', 'spline16', 'spline36', 'hanning', 'hamming', 'hermite', 'kaiser', 'quadric', 'catrom', 'gaussian', 'bessel', 'mitchell', 'sinc', 'lanczos' ] import logging logger = logging.getLogger(__name__) __author__ = 'edill'
#!/usr/bin/env python """ Script used to create lut lists used by mayavi from matplotlib colormaps. This requires matlplotlib to be installed and should not be ran by the user, but only once in a while to synchronize with MPL developpement. """ # Authors: Frederic Petit <*****@*****.**>, # Gael Varoquaux <*****@*****.**> # Copyright (c) 2007-2009, Enthought, Inc. # License: BSD Style. import os import numpy as np from matplotlib.cm import datad, get_cmap from enthought.mayavi.core import lut as destination_module from enthought.persistence import state_pickler target_dir = os.path.dirname(destination_module.__file__) values = np.linspace(0., 1., 256) lut_dic = {} for name in datad.keys(): if name.endswith('_r'): continue lut_dic[name] = get_cmap(name)(values.copy()) out_name = os.path.join(target_dir, 'pylab_luts.pkl') state_pickler.dump(lut_dic, out_name)
""" Script used to create lut lists used by mayavi from matplotlib colormaps. This requires matlplotlib to be installed and should not be ran by the user, but only once in a while to synchronize with MPL developpement. """ # Authors: Frederic Petit <*****@*****.**>, # Gael Varoquaux <*****@*****.**> # Copyright (c) 2007-2009, Enthought, Inc. # License: BSD Style. import os import numpy as np from matplotlib.cm import datad, get_cmap from enthought.mayavi.core import lut as destination_module from enthought.persistence import state_pickler target_dir = os.path.dirname(destination_module.__file__) values = np.linspace(0., 1., 256) lut_dic = {} for name in datad.keys(): if name.endswith('_r'): continue lut_dic[name] = get_cmap(name)(values.copy()) out_name = os.path.join(target_dir, 'pylab_luts.pkl') state_pickler.dump(lut_dic, out_name)