diff --git a/cfelgeom.py b/cfelgeom.py
index 63582d7c9102a5b3c1b53637744f867e2a8f92b7..ba7849d25a92acf091fe641596c213b7834456b4 100644
--- a/cfelgeom.py
+++ b/cfelgeom.py
@@ -23,8 +23,140 @@ files.
import numpy
+def apply_geometry_from_file(data_as_slab, geometry_filename):
+ """Parse a geometry file and applies the geometry to detector data in 'slab' format.
+ Turns a 2d array of pixel values into an array containing a representation of the
+ physical layout of the detector, keeping the origin of the reference system at the
+ beam interaction point.
+
+ Args:
+
+ data_as_slab (numpy.ndarray): the pixel values to which geometry is to be applied.
+
+ geometry_filename (str): geometry filename.
+
+ Returns:
+
+ im_out (numpy.ndarray data_as_slab.dtype): Array containing a representation of the
+ physical layout of the detector, with the origin of the reference system at the
+ beam interaction point.
+ """
+
+ yx, slab_shape, img_shape = pixel_maps_for_image_view(geometry_filename)
+ im_out = numpy.zeros(img_shape, dtype=data_as_slab.dtype)
+
+ im_out[yx[0], yx[1]] = data_as_slab.ravel()
+ return im_out
+
+
+def apply_geometry_from_pixel_maps(data_as_slab, yx, im_out=None):
+ """Applies geometry, in the form of pixel maps, to detector data in 'slab' format.
+ Turns a 2d array of pixel values into an array containing a representation of the
+ physical layout of the detector, keeping the origin of the reference system at the
+ beam interaction point.
+
+ Args:
+
+ data_as_slab (numpy.ndarray): the pixel values to which geometry is to be applied.
+
+ yx (tuple): the yx pixel maps describing the geometry of the detector.
+ Each map is a numpy.ndarray
+
+ im_out (numpy.ndarray) optional: array to hold the output. If not provided,
+ one will be generated automatically.
+
+
+ Returns:
+
+ im_out (numpy.ndarray data_as_slab.dtype): Array containing a representation of the
+ physical layout of the detector, with the origin of the reference system at the
+ beam interaction point.
+ """
+ if im_out is None:
+ im_out = numpy.zeros(data_as_slab.shape, dtype=data_as_slab.dtype)
+
+ im_out[yx[0], yx[1]] = data_as_slab.ravel()
+ return im_out
+
+
+def pixel_maps_for_image_view(geometry_filename):
+ """Parse the geometry file and pixel maps for an array in 'slab' format
+ containing pixel values. The pixel maps can be used to create a representation
+ of the physical layout of the detector in a pyqtgraph ImageView widget (i.e.
+ they apply the detector geometry setting the origin of the reference
+ system is in the top left corner of the output array).
+
+ Args:
+
+ geometry_filename (str): geometry filename.
+
+ Returns:
+
+ (y, x) (numpy.ndarray int, numpy.ndarray int): pixel maps
+
+ slab_shape tuple (int, int): shape of the original geometry uncorrected array
+ (the pixel values in "slab" format).
+
+ img_shape tuple (int, int): shape of the array needed to contain the
+ representation of the physical layout of the detector.
+ """
+ pixm = pixel_maps_from_geometry_file(geometry_filename)
+ x, y = pixm[0], pixm[1]
+ slab_shape = x.shape
+
+ # find the smallest size of cspad_geom that contains all
+ # xy values but is symmetric about the origin
+ n = 2 * int(max(abs(y.max()), abs(y.min()))) + 2
+ m = 2 * int(max(abs(x.max()), abs(x.min()))) + 2
+
+ # convert y x values to i j values
+ i = numpy.array(y, dtype=numpy.int) + n/2 - 1
+ j = numpy.array(x, dtype=numpy.int) + m/2 - 1
+
+ yx = (i.flatten(), j.flatten())
+ img_shape = (n, m)
+ return yx, slab_shape, img_shape
+
+
+def parse_xy(string):
+ """Parse the x, y values from strings that have the format:
+ '1x + 2.0y'.
+
+ Args:
+
+ string (str): the string to be parsed.
+
+ Returns:
+
+ [x, y] [float, float]:
+ len two list of floats, e.g.:
+ 1x + 2.y --> [1., 2.]
+ 1x --> [1., 0.]
+ x --> [1., 0.]
+ """
+ x = y = 0
+
+ if string.find('x') is not -1:
+ xs = string.split('x')[0].split(' ')[-1]
+ if len(xs) > 0:
+ x = float(xs)
+ else:
+ x = 1.
+
+ if string.find('y') is not -1:
+ ys = string.split('y')[0].split(' ')[-1]
+ if len(ys) > 0:
+ y = float(ys)
+ else:
+ y = 1.
+ return [x, y]
+
+
def pixel_maps_from_geometry_file(fnam):
- """Extracts pixel maps from a CrystFEL-style geometry file.
+ """Extracts pixel maps from a CrystFEL-style geometry file. The pixel maps
+ can be used to create a representation of the physical layout of the
+ detector, keeping the origin of the reference system at the beam interaction
+ point.
Args:
@@ -35,7 +167,6 @@ def pixel_maps_from_geometry_file(fnam):
x,y,r (numpy.ndarray float, numpy.ndarray float, numpy.ndarray float):
slab-like pixel maps with respectively x, y coordinates of the pixel
and distance of the pixel from the center of the reference system
- (usually the beam position).
"""
f = open(fnam, 'r')
@@ -46,7 +177,9 @@ def pixel_maps_from_geometry_file(fnam):
detector_dict = {}
- panel_lines = [x for x in f_lines if '/' in x and len(x.split('/')) == 2 and x.split('/')[1].split('=')[0].strip() in keyword_list]
+ panel_lines = [x for x in f_lines if '/' in x and
+ len(x.split('/')) == 2 and x.split('/')[1].split('=')[0].strip() in keyword_list and
+ 'bad_' not in x.split('/')[0].strip()]
for pline in panel_lines:
items = pline.split('=')[0].split('/')
@@ -67,12 +200,8 @@ def pixel_maps_from_geometry_file(fnam):
parsed_detector_dict[p]['max_fs'] = int(detector_dict[p]['max_fs'])
parsed_detector_dict[p]['min_ss'] = int(detector_dict[p]['min_ss'])
parsed_detector_dict[p]['max_ss'] = int(detector_dict[p]['max_ss'])
- parsed_detector_dict[p]['fs'] = []
- parsed_detector_dict[p]['fs'].append(float(detector_dict[p]['fs'].split('x')[0]))
- parsed_detector_dict[p]['fs'].append(float(detector_dict[p]['fs'].split('x')[1].split('y')[0]))
- parsed_detector_dict[p]['ss'] = []
- parsed_detector_dict[p]['ss'].append(float(detector_dict[p]['ss'].split('x')[0]))
- parsed_detector_dict[p]['ss'].append(float(detector_dict[p]['ss'].split('x')[1].split('y')[0] ) )
+ parsed_detector_dict[p]['fs'] = parse_xy(detector_dict[p]['fs'])
+ parsed_detector_dict[p]['ss'] = parse_xy(detector_dict[p]['ss'])
parsed_detector_dict[p]['corner_x'] = float(detector_dict[p]['corner_x'])
parsed_detector_dict[p]['corner_y'] = float(detector_dict[p]['corner_y'])
@@ -85,7 +214,8 @@ def pixel_maps_from_geometry_file(fnam):
for p in parsed_detector_dict.keys():
# get the pixel coords for this asic
i, j = numpy.meshgrid(numpy.arange(parsed_detector_dict[p]['max_ss'] - parsed_detector_dict[p]['min_ss'] + 1),
- numpy.arange(parsed_detector_dict[p]['max_fs'] - parsed_detector_dict[p]['min_fs'] + 1), indexing='ij')
+ numpy.arange(parsed_detector_dict[p]['max_fs'] - parsed_detector_dict[p]['min_fs'] + 1),
+ indexing='ij')
#
# make the y-x ( ss, fs ) vectors, using complex notation
@@ -95,8 +225,11 @@ def pixel_maps_from_geometry_file(fnam):
#
r = i * dy + j * dx + r_0
#
- y[parsed_detector_dict[p]['min_ss']: parsed_detector_dict[p]['max_ss'] + 1, parsed_detector_dict[p]['min_fs']: parsed_detector_dict[p]['max_fs'] + 1] = r.real
- x[parsed_detector_dict[p]['min_ss']: parsed_detector_dict[p]['max_ss'] + 1, parsed_detector_dict[p]['min_fs']: parsed_detector_dict[p]['max_fs'] + 1] = r.imag
+ y[parsed_detector_dict[p]['min_ss']: parsed_detector_dict[p]['max_ss'] + 1,
+ parsed_detector_dict[p]['min_fs']: parsed_detector_dict[p]['max_fs'] + 1] = r.real
+
+ x[parsed_detector_dict[p]['min_ss']: parsed_detector_dict[p]['max_ss'] + 1,
+ parsed_detector_dict[p]['min_fs']: parsed_detector_dict[p]['max_fs'] + 1] = r.imag
r = numpy.sqrt(numpy.square(x) + numpy.square(y))
@@ -123,7 +256,7 @@ def coffset_from_geometry_file(fnam):
for line in f_lines:
if line.startswith('coffset'):
- coffset = float(line.split('=')[1].split('#')[0])
+ coffset = float(line.split('=')[1].split(';')[0])
return coffset
@@ -148,6 +281,6 @@ def res_from_geometry_file(fnam):
for line in f_lines:
if line.startswith('res'):
- res = float(line.split('=')[1].split('#')[0])
+ res = float(line.split('=')[1].split(';')[0])
return res