Improved geometry parsing and added functions to apply the geometry. Mostly Andrew's work

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