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[FIX] removes memory leak issue by removing c code and using numpy/sc…
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…ipy functions (#9)

* remove c-extension: minimal gain and memory leaks
* add regression tests for siemens_B to check that numpy legendre are equivalent
* fix tests by replacing the custom n-d meshgrid with numpy one
* rewriting parser for robustness/readability
---------
Co-authored-by: Chris Markiewicz <[email protected]>
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@bpinsard
bpinsard authored Jan 19, 2024
1 parent 6c9df6f commit 4af3c75
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167 changes: 55 additions & 112 deletions gradunwarp/core/coeffs.py
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Original file line number Diff line number Diff line change
Expand Up @@ -46,7 +46,7 @@ def coef_file_parse(cfile, txt_var_map):
'''
# parse .coef file. Strip unneeded characters. a valid line in that file is
# broken into validline_list
coef_re = re.compile('^[^\#]') # regex for first character not a '#'
coef_re = re.compile(r'^[^\#]') # regex for first character not a '#'
coef_file = open(cfile, 'r')
for line in coef_file.readlines():
if coef_re.match(line):
Expand Down Expand Up @@ -78,137 +78,80 @@ def get_siemens_coef(cfile):
# allegra is slightly different
if cfile.startswith('allegra'):
coef_array_sz = 15
ax = np.zeros((coef_array_sz, coef_array_sz))
ay = np.zeros((coef_array_sz, coef_array_sz))
az = np.zeros((coef_array_sz, coef_array_sz))
bx = np.zeros((coef_array_sz, coef_array_sz))
by = np.zeros((coef_array_sz, coef_array_sz))
bz = np.zeros((coef_array_sz, coef_array_sz))
txt_var_map = {'Alpha_x': ax,
'Alpha_y': ay,
'Alpha_z': az,
'Beta_x': bx,
'Beta_y': by,
'Beta_z': bz}

txt_var_map = create_txt_var_map(coef_array_sz)

coef_file_parse(cfile, txt_var_map)

return Coeffs(ax, ay, az, bx, by, bz, R0_m)
return Coeffs(
txt_var_map['alpha_y'],
txt_var_map['alpha_z'],
txt_var_map['alpha_x'],
txt_var_map['beta_y'],
txt_var_map['beta_x'],
txt_var_map['beta_z'],
R0_m)


def get_ge_coef(cfile):
''' Parse the GE .coef file.
'''
ax = np.zeros((ge_cas, ge_cas))
ay = np.zeros((ge_cas, ge_cas))
az = np.zeros((ge_cas, ge_cas))
bx = np.zeros((ge_cas, ge_cas))
by = np.zeros((ge_cas, ge_cas))
bz = np.zeros((ge_cas, ge_cas))
txt_var_map = {'Alpha_x': ax,
'Alpha_y': ay,
'Alpha_z': az,
'Beta_x': bx,
'Beta_y': by,
'Beta_z': bz}
txt_var_map = create_txt_var_map(coef_array_sz)

coef_file_parse(cfile, txt_var_map)

return Coeffs(ax, ay, az, bx, by, bz, R0_m)
return Coeffs(
txt_var_map['alpha_y'],
txt_var_map['alpha_z'],
txt_var_map['alpha_x'],
txt_var_map['beta_y'],
txt_var_map['beta_x'],
txt_var_map['beta_z'],
R0_m)

def grad_file_parse(gfile, txt_var_map):
''' a separate function because GE and Siemens .coef files
have similar structure
modifies txt_var_map in place
'''
gf = open(gfile, 'r')
line = next(gf)
# skip the comments
while not line.startswith('#*] END:'):
line = next(gf)

# get R0
line = next(gf)
line = next(gf)
line = next(gf)
R0_m = float(line.strip().split()[0])

# go to the data
line = next(gf)
line = next(gf)
line = next(gf)
line = next(gf)
line = next(gf)
line = next(gf)
line = next(gf)

xmax = 0
ymax = 0

while 1:
lindex = line.find('(')
rindex = line.find(')')
if lindex == -1 and rindex == -1:
break
arrindex = line[lindex+1:rindex]
xs, ys = arrindex.split(',')
x = int(xs)
y = int(ys)
if x > xmax:
xmax = x
if y > ymax:
ymax = y
if line.find('A') != -1 and line.find('x') != -1:
txt_var_map['Alpha_x'][x,y] = float(line.split()[-2])
if line.find('A') != -1 and line.find('y') != -1:
txt_var_map['Alpha_y'][x,y] = float(line.split()[-2])
if line.find('A') != -1 and line.find('z') != -1:
txt_var_map['Alpha_z'][x,y] = float(line.split()[-2])
if line.find('B') != -1 and line.find('x') != -1:
txt_var_map['Beta_x'][x,y] = float(line.split()[-2])
if line.find('B') != -1 and line.find('y') != -1:
txt_var_map['Beta_y'][x,y] = float(line.split()[-2])
if line.find('B') != -1 and line.find('z') != -1:
txt_var_map['Beta_z'][x,y] = float(line.split()[-2])
try:
line = next(gf)
except StopIteration:
break

# just return R0_m but also txt_var_map is returned
with open(gfile, 'r') as gf:
for line in gf:
re_search = re.search(r"(?P<no>\d+)[\s]+(?P<aorb>[AB])[\s]*\(\s*(?P<x>\d+),\s*(?P<y>\d+)\)\s+(?P<spectrum>[\-]?\d+\.\d+)\s+(?P<axis>[xyz])", line)
if re_search:
re_res = re_search.groupdict()
alphabeta = 'alpha' if re_res['aorb'] == 'A' else 'beta'
x, y = int(re_res['x']),int(re_res['y'])
field = "%s_%s"%(alphabeta, re_res['axis'])
txt_var_map[field][x, y] = float(re_res['spectrum'])
xmax, ymax = max(x, xmax), max(y, ymax)
else:
re_search = re.search(r"(?P<R0>\d+\.\d+) m = R0", line)
if re_search:
R0_m = float(re_search.group('R0'))
return R0_m, (xmax, ymax)

def create_txt_var_map(coef_array_sz):
txt_var_map = {}
for ab in ['alpha', 'beta']:
for axis in 'xyz':
txt_var_map['%s_%s'%(ab,axis)] = np.zeros((coef_array_sz,)*2)
return txt_var_map

def get_siemens_grad(gfile):
''' Parse the siemens .grad file
'''
coef_array_sz = siemens_cas
# allegra is slightly different
if gfile.startswith('coef_AC44'):
coef_array_sz = 15
ax = np.zeros((coef_array_sz, coef_array_sz))
ay = np.zeros((coef_array_sz, coef_array_sz))
az = np.zeros((coef_array_sz, coef_array_sz))
bx = np.zeros((coef_array_sz, coef_array_sz))
by = np.zeros((coef_array_sz, coef_array_sz))
bz = np.zeros((coef_array_sz, coef_array_sz))
txt_var_map = {'Alpha_x': ax,
'Alpha_y': ay,
'Alpha_z': az,
'Beta_x': bx,
'Beta_y': by,
'Beta_z': bz}
coef_array_sz = 15 if gfile.startswith('coef_AC44') else siemens_cas

R0_m, max_ind = grad_file_parse(gfile, txt_var_map)
ind = max(max_ind)

# pruned alphas and betas
ax = ax[:ind+1, :ind+1]
ay = ay[:ind+1, :ind+1]
az = az[:ind+1, :ind+1]
bx = bx[:ind+1, :ind+1]
by = by[:ind+1, :ind+1]
bz = bz[:ind+1, :ind+1]

return Coeffs(ax, ay, az, bx, by, bz, R0_m)
txt_var_map = create_txt_var_map(coef_array_sz)
print(txt_var_map)

R0_m, max_ind = grad_file_parse(gfile, txt_var_map)
ind = max(max_ind) + 1

return Coeffs(
txt_var_map['alpha_x'][:ind, :ind],
txt_var_map['alpha_y'][:ind, :ind],
txt_var_map['alpha_z'][:ind, :ind],
txt_var_map['beta_x'][:ind, :ind],
txt_var_map['beta_y'][:ind, :ind],
txt_var_map['beta_z'],
R0_m)
198 changes: 0 additions & 198 deletions gradunwarp/core/interp3_ext.c
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