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# /*##########################################################################
#
# Copyright (c) 2016-2020 European Synchrotron Radiation Facility
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
# THE SOFTWARE.
#
# ###########################################################################*/
"""This script illustrates the use of :class:`silx.gui.plot3d.ScalarFieldView`.
It loads a 3D scalar data set from a file and displays iso-surfaces and
an interactive cutting plane.
It can also be started without providing a file.
"""
__authors__ = ["T. Vincent"]
__license__ = "MIT"
__date__ = "05/01/2017"
import argparse
import logging
import os.path
import sys
import numpy
from silx.gui import qt
from silx.gui.plot3d.ScalarFieldView import ScalarFieldView
from silx.gui.plot3d import SFViewParamTree
logging.basicConfig()
_logger = logging.getLogger(__name__)
import h5py
def load(filename):
"""Load 3D scalar field from file.
It supports 3D stack HDF5 files and numpy files.
:param str filename: Name of the file to open
and path in file for hdf5 file
:return: numpy.ndarray with 3 dimensions.
"""
if not os.path.isfile(filename.split("::")[0]):
raise IOError("No input file: %s" % filename)
if h5py.is_hdf5(filename.split("::")[0]):
if "::" not in filename:
raise ValueError("HDF5 path not provided: Use <filename>::<path> format")
filename, path = filename.split("::")
path, indices = path.split("#")[0], path.split("#")[1:]
with h5py.File(filename, mode="r") as f:
data = f[path]
# Loop through indices along first dimensions
for index in indices:
data = data[int(index)]
data = numpy.array(data, order="C", dtype="float32")
else: # Try with numpy
try:
data = numpy.load(filename)
except IOError:
raise IOError("Unsupported file format: %s" % filename)
if data.ndim != 3:
raise RuntimeError("Unsupported data set dimensions, only supports 3D datasets")
return data
def default_isolevel(data):
"""Compute a default isosurface level: mean + 1 std
:param numpy.ndarray data: The data to process
:rtype: float
"""
data = data[numpy.isfinite(data)]
if len(data) == 0:
return 0
else:
return numpy.mean(data) + numpy.std(data)
# Parse input arguments
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument(
"-l",
"--level",
nargs="?",
type=float,
default=float("nan"),
help="The value at which to generate the iso-surface",
)
parser.add_argument(
"-sx",
"--xscale",
nargs="?",
type=float,
default=1.0,
help="The scale of the data on the X axis",
)
parser.add_argument(
"-sy",
"--yscale",
nargs="?",
type=float,
default=1.0,
help="The scale of the data on the Y axis",
)
parser.add_argument(
"-sz",
"--zscale",
nargs="?",
type=float,
default=1.0,
help="The scale of the data on the Z axis",
)
parser.add_argument(
"-ox",
"--xoffset",
nargs="?",
type=float,
default=0.0,
help="The offset of the data on the X axis",
)
parser.add_argument(
"-oy",
"--yoffset",
nargs="?",
type=float,
default=0.0,
help="The offset of the data on the Y axis",
)
parser.add_argument(
"-oz",
"--zoffset",
nargs="?",
type=float,
default=0.0,
help="The offset of the data on the Z axis",
)
parser.add_argument(
"filename",
nargs="?",
default=None,
help="""Filename to open.
It supports 3D volume saved as .npy or in .h5 files.
It also support nD data set (n>=3) stored in a HDF5 file.
For HDF5, provide the filename and path as: <filename>::<path_in_file>.
If the data set has more than 3 dimensions, it is possible to choose a
3D data set as a subset by providing the indices along the first n-3
dimensions with '#':
<filename>::<path_in_file>#<1st_dim_index>...#<n-3th_dim_index>
E.g.: data.h5::/data_5D#1#1
""",
)
args = parser.parse_args(args=sys.argv[1:])
# Start GUI
app = qt.QApplication([])
# Create the viewer main window
window = ScalarFieldView()
# Create a parameter tree for the scalar field view
treeView = SFViewParamTree.TreeView(window)
treeView.setSfView(window) # Attach the parameter tree to the view
# Add the parameter tree to the main window in a dock widget
dock = qt.QDockWidget()
dock.setWindowTitle("Parameters")
dock.setWidget(treeView)
window.addDockWidget(qt.Qt.RightDockWidgetArea, dock)
# Load data from file
if args.filename is not None:
data = load(args.filename)
_logger.info(
"Data:\n\tShape: %s\n\tRange: [%f, %f]", str(data.shape), data.min(), data.max()
)
else:
# Create dummy data
_logger.warning("Not data file provided, creating dummy data")
coords = numpy.linspace(-10, 10, 64)
z = coords.reshape(-1, 1, 1)
y = coords.reshape(1, -1, 1)
x = coords.reshape(1, 1, -1)
data = numpy.sin(x * y * z) / (x * y * z)
# Set ScalarFieldView data
window.setData(data)
# Set scale of the data
window.setScale(args.xscale, args.yscale, args.zscale)
# Set offset of the data
window.setTranslation(args.xoffset, args.yoffset, args.zoffset)
# Set axes labels
window.setAxesLabels("X", "Y", "Z")
# Add an iso-surface
if not numpy.isnan(args.level):
# Add an iso-surface at the given iso-level
window.addIsosurface(args.level, "#FF0000FF")
else:
# Add an iso-surface from a function
window.addIsosurface(default_isolevel, "#FF0000FF")
window.show()
app.exec()
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