/usr/lib/python2.7/dist-packages/pyFAI/peakPicker.py is in pyfai 0.3.5-1.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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# -*- coding: utf8 -*-
#
# Project: Azimuthal integration
# https://forge.epn-campus.eu/projects/azimuthal
#
# File: "$Id$"
#
# Copyright (C) European Synchrotron Radiation Facility, Grenoble, France
#
# Principal author: Jérôme Kieffer (Jerome.Kieffer@ESRF.eu)
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
#
__author__ = "Jérôme Kieffer"
__contact__ = "Jerome.Kieffer@ESRF.eu"
__license__ = "GPLv3+"
__copyright__ = "European Synchrotron Radiation Facility, Grenoble, France"
__date__ = "23/12/2011"
__status__ = "development"
import os, sys, threading, logging, gc
from math import ceil, sqrt, pi
import numpy
from scipy.optimize import fmin
from scipy.ndimage.filters import median_filter
from scipy.ndimage import label#, binary_closing, binary_opening, binary_erosion #,binary_propagation
#import matplotlib
import pylab
import fabio
from utils import relabel, gaussian_filter, binning, unBinning
from bilinear import bilinear
logger = logging.getLogger("pyFAI.peakPicker")
if os.name != "nt":
WindowsError = RuntimeError
TARGET_SIZE = 1024
################################################################################
# PeakPicker
################################################################################
class PeakPicker(object):
def __init__(self, strFilename):
"""
@param: input image filename
"""
self.strFilename = strFilename
self.data = fabio.open(strFilename).data.astype("float32")
self.shape = self.data.shape
self.points = ControlPoints()
self.lstPoints = []
self.fig = None
self.fig2 = None
self.fig2sp = None
self.ax = None
self.ct = None
self.msp = None
self.massif = Massif(self.data)
self._sem = threading.Semaphore()
self._semGui = threading.Semaphore()
self.defaultNbPoints = 100
def gui(self, log=False):
"""
@param log: show z in log scale
"""
if self.fig is None:
self.fig = pylab.plt.figure()
self.ax = self.fig.add_subplot(111);
if log:
self.ax.imshow(numpy.log(1.0 + self.data - self.data.min()));
else:
self.ax.imshow(self.data);
self.fig.show()
self.fig.canvas.mpl_connect('button_press_event', self.onclick)
def load(self, filename):
"""
load a filename and plot data on the screen (if GUI)
"""
self.points.load(filename)
if self.ax is not None:
for idx, points in enumerate(self.points._points):
if len(points) > 0:
pt0x = points[0][1]
pt0y = points[0][0]
self.ax.annotate("%i" % (idx), xy=(pt0x, pt0y), xytext=(pt0x + 10, pt0y + 10),
color="white", arrowprops=dict(facecolor='white', edgecolor='white'))
npl = numpy.array(points)
self.ax.plot(npl[:, 1], npl[:, 0], "o", scalex=False, scaley=False)
def onclick(self, event):
def annontate(x, x0=None, idx=None):
"""
Call back method to annotate the figure while calculation are going on ...
@param x: coordinates
@param x0: coordinates of the starting point
"""
if x0 is None:
self.ax.annotate(".", xy=(x[1], x[0]), color="black")
else:
self.ax.annotate("%i" % (len(self.points)), xy=(x[1], x[0]), xytext=(x0[1], x0[0]), color="white",
arrowprops=dict(facecolor='white', edgecolor='white'),)
self.fig.canvas.draw()
self._sem.acquire()
if event.button == 3: #right click
x0 = event.xdata
y0 = event.ydata
listpeak = self.massif.find_peaks([y0, x0], self.defaultNbPoints, annontate, self.massif_contour)
if len(listpeak) == 0:
logging.warning("No peak found !!!")
self._sem.release()
return
npl = numpy.array(listpeak)
self.ax.plot(npl[:, 1], npl[:, 0], "o", scalex=False, scaley=False)
logging.info("Added %3i points to group #%i" % (len(listpeak), len(self.points)))
self.points.append(listpeak)
self.fig.show()
sys.stdout.flush()
elif event.button == 2: #center click
a = self.points.pop()
# for i in a:
if len(self.ax.texts) > 0:
self.ax.texts.pop()
if len(self.ax.lines) > 0:
self.ax.lines.pop()
self.fig.show()
logging.info("Removing point group #%i (%5.1f %5.1f) containing %i subpoints" % (len(self.points), a[0][0], a[0][1], len(a)))
sys.stdout.flush()
self._sem.release()
def readFloatFromKeyboard(self, text, dictVar):
"""
Read float from the keyboard ....
@param text: string to be displayed
@param dictVar: dict of this type: {1: [set_dist_min],3: [set_dist_min, set_dist_guess, set_dist_max]}
"""
fromkb = raw_input(text).strip()
try:
vals = [float(i) for i in fromkb.split()]
except:
logging.error("Error in parsing values")
else:
found = False
for i in dictVar:
if len(vals) == i:
found = True
for j in range(i):
dictVar[i][j](vals[j])
if not found:
logging.error("You should provide the good number of floats")
def finish(self, filename=None):
"""
Ask the 2theta values for the given points
"""
logging.info("Please use the GUI and Right-click on the peaks to mark them")
raw_input("Please press enter when you are happy; to fill in 2theta values" + os.linesep)
self.points.readAngleFromKeyboard()
if filename is not None:
self.points.save(filename)
self.lstPoints = self.points.getList()
return self.lstPoints
def contour(self, data):
if self.fig is None:
logging.warning("No diffraction image available => not showing the contour")
else:
if self.msp is not None:
if len(self.msp.images) > 1:
self.msp.images.pop()
self.msp = None
if self.ct is None:
self.ct = self.fig.add_subplot(111)
else:
while len(self.ct.images) > 1:
self.ct.images.pop()
while len(self.ct.collections) > 0:
self.ct.collections.pop()
try:
self.ct.contour(data)
except MemoryError:
logging.error("Sorry but your computer does NOT have enough memory to display the 2-theta contour plot")
self.fig.show()
def massif_contour(self, data):
if self.fig is None:
logging.error("No diffraction image available => not showing the contour")
else:
tmp = 100 * (1 - data.astype("uint8"))
mask = numpy.zeros((data.shape[0], data.shape[1], 4), dtype="uint8")
mask[:, :, 0] = tmp
mask[:, :, 1] = tmp
mask[:, :, 2] = tmp
mask[:, :, 3] = tmp
if self.msp is None:
self.msp = self.fig.add_subplot(111)
else:
if len(self.msp.images) > 1:
self.msp.images.pop()
try:
self.msp.imshow(mask, cmap="gray")
except MemoryError:
logging.error("Sorry but your computer does NOT have enough memory to display the massif plot")
#self.fig.show()
self.fig.canvas.draw()
def closeGUI(self):
if self.fig is not None:
self.fig.clear()
self.fig = None
gc.collect()
################################################################################
# ControlPoints
################################################################################
class ControlPoints(object):
"""
This class contains a set of control points with (optionaly) their diffrection 2Theta angle
"""
def __init__(self, filename=None):
if filename is not None:
self.load(filename)
self._angles = [] #angles are enforced in radians, conversion from degrees or q-space nm-1 are done on the fly
self._points = []
self._sem = threading.Semaphore()
self._wavelength = None
def __repr__(self):
self.check()
lstOut = ["ControlPoints instance containing %i group of point:" % len(self)]
if self._wavelength is not None:
lstOut = "wavelength: %s" % self._wavelength
for angle, points in zip(self._angles, self._points):
lstOut.append("%s: %s" % (angle, points))
return os.linesep.join(lstOut)
def __len__(self):
return len(self._angles)
def check(self):
"""
check internal consistency of the class
"""
if len(self._angles) != len(self._points):
logger.error("in ControlPoints: length of the two arrays are not consistent!!! angle: %i points: %s ",
len(self._angles), len(self._points))
def reset(self):
"""
remove all stored values and resets them to default
"""
with self._sem:
self._wavelength = None
self._angles = [] #angles are enforced in radians, conversion from degrees or q-space nm-1 are done on the fly
self._points = []
def append(self, points, angle=None):
"""
@param point: list of points
@param angle: 2-theta angle in radians
"""
with self._sem:
self._angles.append(angle)
self._points.append(points)
append_2theta_deg = append
def append_2theta_deg(self, points, angle=None):
"""
@param point: list of points
@param angle: 2-theta angle in degrees
"""
with self._sem:
self._angles.append(pi * angle / 180.)
self._points.append(points)
def pop(self, idx=None):
"""
Remove the set of points at given index (by default the last)
@param idx: poistion of the point to remove
"""
out = None
if idx is None:
with self._sem:
self._angles.pop()
out = self._points.pop()
else:
with self._sem:
self._angles.pop(idx)
out = self._points.pop(idx)
return out
def save(self, filename):
"""
Save a set of control points to a file
@param filename: name of the file
@return: None
"""
self.check()
with self._sem:
lstOut = ["# set of control point used by pyFAI to calibrate the geometry of a scattering experiment",
"#angles are in radians, wavelength in meter and positions in pixels"]
if self._wavelength is not None:
lstOut = "wavelength: %s" % self._wavelength
for idx, angle, points in zip(range(self.__len__()), self._angles, self._points):
lstOut.append("")
lstOut.append("New group of points: %i" % idx)
lstOut.append("2theta: %s" % angle)
for point in points:
lstOut.append("point: x=%s y=%s" % (point[1], point[0]))
with open(filename, "w") as f:
f.write(os.linesep.join(lstOut))
def load(self, filename):
"""
load all control points from a file
"""
if not os.path.isfile(filename):
logger.error("ControlPoint.load: No such file %s", filename)
return
self.reset()
tth = None
points = []
for line in open(filename, "r"):
if line.startswith("#"):
continue
elif ":" in line:
key, value = line.split(":", 1)
value = value.strip()
key = key.strip().lower()
if key == "wavelength":
try:
self._wavelength = float(value)
except:
logger.error("ControlPoints.load: unable to convert to float %s (wavelength)", value)
elif key == "2theta":
if value.lower() == "none":
tth = None
else:
try:
tth = float(value)
except:
logger.error("ControlPoints.load: unable to convert to float %s (2theta)", value)
elif key == "point":
vx = None
vy = None
if "x=" in value:
vx = value[value.index("x=") + 2:].split()[0]
if "y=" in value:
vy = value[value.index("y=") + 2:].split()[0]
if (vx is not None) and (vy is not None):
try:
x = float(vx)
y = float(vy)
except:
logger.error("ControlPoints.load: unable to convert to float %s (point)", value)
else:
points.append([y, x])
elif key.startswith("new"):
if len(points) > 0:
with self._sem:
self._angles.append(tth)
self._points.append(points)
tth = None
points = []
else:
logger.error("Unknown key: %s", key)
if len(points) > 0:
self._angles.append(tth)
self._points.append(points)
def getList(self):
"""
Retrieve the list of control points suitable for geometry refinement
"""
lstOut = []
for tth, points in zip(self._angles, self._points):
lstOut += [[pt[0], pt[1], tth] for pt in points]
return lstOut
def readAngleFromKeyboard(self):
"""
Ask the 2theta values for the given points
"""
last2Theta = None
for idx, tth, point in zip(range(self.__len__()), self._angles, self._points):
bOk = False
while not bOk:
if tth is not None:
last2Theta = numpy.rad2deg(tth)
res = raw_input("Point group #%2i (%i points)\t (%6.1f,%6.1f) \t [default=%s] 2Theta= " % (idx, len(point), point[0][1], point[0][0], last2Theta)).strip()
if res == "":
res = last2Theta
try:
tth = float(res)
except (ValueError, TypeError):
logging.error("I did not understand your 2theta value")
else:
if tth > 0:
last2Theta = tth
self._angles[idx] = numpy.deg2rad(tth)
bOk = True
def setWavelength(self, value=None):
with self._sem:
if self._wavelength is None:
self._wavelength = value
else:
logger.warning("Forbidden to change the wavelength once it is fixed !!!!")
def getWavelength(self): return self._wavelength
wavelength = property(getWavelength, setWavelength)
################################################################################
# Massif
################################################################################
class Massif(object):
"""
A massif is defined as an area around a peak, it is used to find neighbouring peaks
"""
def __init__(self, data=None):
"""
"""
if isinstance(data, (str, unicode)) and os.path.isfile(data):
self.data = fabio.open(data).data.astype("float32")
elif isinstance(data, fabio.fabioimage.fabioimage):
self.data = data.data.astype("float32")
else:
try:
self.data = data.astype("float32")
except Exception as error:
logger.error("Unable to understand this type of data %s: %s", data, error)
self._bilin = bilinear(self.data)
self._blured_data = None
self._median_data = None
self._labeled_massif = None
self._number_massif = None
self._valley_size = None
self._binned_data = None
self.binning = None #Binning is 2-list usually
self._sem = threading.Semaphore()
self._sem_label = threading.Semaphore()
self._sem_binning = threading.Semaphore()
self._sem_median = threading.Semaphore()
def nearest_peak(self, x):
"""
@returns the coordinates of the nearest peak
"""
x = numpy.array(x, dtype="float32")
out = fmin(self._bilin.f_cy, x, disp=0).round().astype(numpy.int)
if isinstance(out, numpy.ndarray):
res = [int(i) for idx, i in enumerate(out) if 0 <= i < self.data.shape[idx] ]
else:
print out
res = [int(i) for idx, i in enumerate(out) if 0 <= i < self.data.shape[idx] ]
if len(res) == 2:
return res
def calculate_massif(self, x):
"""
defines a map of the massif around x and returns the mask
"""
labeled = self.getLabeledMassif()
if labeled[x[0], x[1]] != labeled.max():
return (labeled == labeled[x[0], x[1]])
def find_peaks(self, x, nmax=200, annotate=None, massif_contour=None, stdout=sys.stdout):
"""
All in one function that finds a maximum from the given seed (x)
then calculates the region extension and extract position of the neighboring peaks.
@param x: seed for the calculation, input coordinates
@param nmax: maximum number of peak per region
@param annotate: call back method taking number of points + coordinate as input.
@param massif_contour: callback to show the contour of a massif with the given index.
@param stdout: this is the file where output is written by default.
@return: list of peaks
"""
listpeaks = []
region = self.calculate_massif(x)
if region is None:
logger.error("You picked a background point at %s", x)
return listpeaks
xinit = self.nearest_peak(x)
if xinit is None:
logger.error("Unable to find peak in the vinicy of %s", x)
return listpeaks
else:
if not region[xinit[0], xinit[1]]:
logger.error("Nearest peak %s is not in the same region %s", xinit, x)
return listpeaks
if annotate is not None:
try:
annotate(xinit, x)
except Exception as error:
logger.error("Error in annotate %i: %i %i. %s" , len(listpeaks), xinit[0], xinit[1], error)
listpeaks.append(xinit)
idx = numpy.arange(region.size)
idx.shape = region.shape
regionIdx = idx[region]
numpy.random.shuffle(regionIdx)
nmax = min(nmax, int(ceil(sqrt(region.sum()))))
if massif_contour is not None:
try:
massif_contour(region)
except (WindowsError, MemoryError) as error:
logger.error("Error in plotting region: %s", error)
nbFailure = 0
dim1 = region.shape[1]
for idx in regionIdx:
x0 = idx // dim1
x1 = idx % dim1
if not region[x0, x1]:
logger.warning("Input point (%s,%s) not in region !!!! " % (x0, x1))
xopt = self.nearest_peak([x0, x1])
if xopt is None:
nbFailure += 1
continue
if (region[xopt[0], xopt[1]]) and not (xopt in listpeaks):
stdout.write("[ %4i, %4i ] --> [ %4i, %4i ] after %3i iterations %s" % (x0, x1, xopt[0], xopt[1], nbFailure, os.linesep))
listpeaks.append(xopt)
nbFailure = 0
else:
nbFailure += 1
if (len(listpeaks) > nmax) or (nbFailure > 2 * nmax):
break
return listpeaks
def initValleySize(self):
if self._valley_size is None:
self.valley_size = max(5., max(self.data.shape) / 50.)
def getValleySize(self):
if self._valley_size is None:
self.initValleySize()
return self._valley_size
def setValleySize(self, size):
self._valley_size = size
t = threading.Thread(target=self.getLabeledMassif)
t.start()
def delValleySize(self):
self._valley_size = None
self._blured_data = None
valley_size = property(getValleySize, setValleySize, delValleySize, "Defines the minimum distance between two massifs")
def getBinnedData(self):
"""
@return binned data
"""
if self._binned_data is None:
with self._sem_binning:
if self._binned_data is None:
logger.info("Image size is %s", self.data.shape)
self.binning = []
for i in self.data.shape:
if i % TARGET_SIZE == 0:
self.binning.append(max(1, i // TARGET_SIZE))
else:
for j in range(i // TARGET_SIZE - 1, 0, -1):
if i % j == 0:
self.binning.append(max(1, j))
break
else:
self.binning.append(1)
# self.binning = max([max(1, i // TARGET_SIZE) for i in self.data.shape])
logger.info("Binning size is %s", self.binning)
self._binned_data = binning(self.data, self.binning)
return self._binned_data
def getMedianData(self):
if self._median_data is None:
with self._sem_median:
if self._median_data is None:
self._median_data = median_filter(self.data, 3)
if logger.getEffectiveLevel() == logging.DEBUG:
fabio.edfimage.edfimage(data=self._median_data).write("median_data.edf")
return self._median_data
def getBluredData(self):
if self._blured_data is None:
with self._sem:
if self._blured_data is None:
logger.debug("Blurring image with kernel size: %s" , self.valley_size)
self._blured_data = gaussian_filter(self.getBinnedData(), [self.valley_size / i for i in self.binning], mode="reflect")
if logger.getEffectiveLevel() == logging.DEBUG:
fabio.edfimage.edfimage(data=self._blured_data).write("blured_data.edf")
return self._blured_data
def getLabeledMassif(self, pattern=None):
if self._labeled_massif is None:
with self._sem_label:
if self._labeled_massif is None:
if pattern is None:
pattern = [[1] * 3] * 3#[[0, 1, 0], [1, 1, 1], [0, 1, 0]]#[[1] * 3] * 3
logger.debug("Labeling all massifs. This takes some time !!!")
labeled_massif, self._number_massif = label((self.getBinnedData() > self.getBluredData()), pattern)
logger.info("Labeling found %s massifs." % self._number_massif)
if logger.getEffectiveLevel() == logging.DEBUG:
fabio.edfimage.edfimage(data=labeled_massif).write("labeled_massif_small.edf")
relabeled = relabel(labeled_massif, self.getBinnedData(), self.getBluredData())
if logger.getEffectiveLevel() == logging.DEBUG:
fabio.edfimage.edfimage(data=relabeled).write("relabeled_massif_small.edf")
self._labeled_massif = unBinning(relabeled, self.binning)
if logger.getEffectiveLevel() == logging.DEBUG:
fabio.edfimage.edfimage(data=self._labeled_massif).write("labeled_massif.edf")
logger.info("Labeling found %s massifs." % self._number_massif)
return self._labeled_massif
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