def getBox(self):
offset = np.array([self.offset_y.get(), self.offset_x.get()])
box = fph.get_box(self.proj, self.width.get(), offset)
return box
file, long, raw_input, reduce, reload,
unicode, xrange, StandardError)
__metaclass__ = type #New style classes in Python 2.x
import forgi.threedee.model.coarse_grain as ftmc
import forgi.projection.projection2d as fpp
import forgi.projection.hausdorff as fph
import sys, random
import numpy as np
import scipy.misc
import scipy.ndimage
WIDTH=350
if __name__=="__main__":
for filename in sys.argv[1:]:
cg=ftmc.CoarseGrainRNA(filename)
try:
proj=fpp.Projection2D(cg, project_virtual_atoms=True)
except ValueError:
a=random.random()
b=random.random()
c=random.random()
proj=fpp.Projection2D(cg, project_virtual_atoms=True, proj_direction=[a,b,c])
rot=random.randrange(0,3600)/10
proj.rotate(rot)
box=fph.get_box(proj, WIDTH)
img, _= proj.rasterize(70, box)
scipy.misc.imsave(filename+".rot{}.width{}.png".format(rot, WIDTH), img)
def getBox(self):
offset = np.array([self.offset_y.get(), self.offset_x.get()])
box = fph.get_box(self.proj, self.width.get(), offset)
return box
else:
res_nums = []
for filename in args.cgfiles:
for n in range(args.n):
cg = ftmc.CoarseGrainRNA(filename)
try:
proj = fpp.Projection2D(cg,
project_virtual_atoms=True,
project_virtual_residues=res_nums)
except ValueError:
a = random.random()
b = random.random()
c = random.random()
print("Projecting from {}, {}, {}".format(a, b, c))
proj = fpp.Projection2D(cg,
project_virtual_atoms=True,
proj_direction=[a, b, c],
project_virtual_residues=res_nums)
if args.rotate == 99999999999:
rot = random.randrange(0, 3600) / 10
else:
rot = args.rotate
proj.rotate(rot)
box = fph.get_box(proj, args.width)
img, _ = proj.rasterize(args.dpi, box)
outname = filename + ".dpi{}.width{}.{}.png".format(
args.dpi, args.width, n)
scipy.misc.imsave(outname, img, "png")
print("File {} written".format(outname))
s=args.scale/2
ref_box=-s/2, s/2, -s/2, s/2
else:
parser.error("--scale is required if the reference is a png image")
if args.show:
fig, ax=plt.subplots()
ax.imshow(ref_img, interpolation="none", cmap='gray')
plt.show()
else:
ref_cg=ftmc.CoarseGrainRNA(args.reference)
try:
ref_proj=ftmp.Projection2D(ref_cg, project_virtual_atoms=True)
except ValueError:
parser.error('The reference *.cg file needs a "project" line.')
if args.scale:
ref_box=fph.get_box(ref_proj, args.scale)
else:
ref_box=ref_proj.get_bounding_square(margin=50)
args.scale=ref_box[1]-ref_box[0]
if args.dpi:
ref_img, _=ref_proj.rasterize(args.dpi, bounding_square=ref_box)
else:
parser.error("If the reference is not a png image, --dpi is required")
ref_img=(ref_img>np.zeros_like(ref_img)) #Make it a boolean array
for f in args.files:
cg=ftmc.CoarseGrainRNA(f)
if args.global_search or cg.project_from is None:
distance, img, params = fph.globally_minimal_distance(ref_img, args.scale, cg)
fname = os.path.basename(f)
print ("{}:\t{} distance (projected from {}, rotated by {}, offset {}. Globally optimized)".format(fname, distance, params[0], params[1], params[2] ))
else:
args = parser.parse_args()
if args.res_nums:
res_nums = list(map(int, args.res_nums.split(",")))
else:
res_nums = []
for filename in args.cgfiles:
for n in range(args.n):
cg = ftmc.CoarseGrainRNA(filename)
try:
proj = fpp.Projection2D(cg, project_virtual_atoms=True,
project_virtual_residues=res_nums)
except ValueError:
a = random.random()
b = random.random()
c = random.random()
print("Projecting from {}, {}, {}".format(a, b, c))
proj = fpp.Projection2D(cg, project_virtual_atoms=True, proj_direction=[a, b, c],
project_virtual_residues=res_nums)
if args.rotate == 99999999999:
rot = random.randrange(0, 3600) / 10
else:
rot = args.rotate
proj.rotate(rot)
box = fph.get_box(proj, args.width)
img, _ = proj.rasterize(args.dpi, box)
outname = filename + \
".dpi{}.width{}.{}.png".format(args.dpi, args.width, n)
scipy.misc.imsave(outname, img, "png")
print("File {} written".format(outname))
s=args.scale/2
ref_box=-s/2, s/2, -s/2, s/2
else:
parser.error("--scale is required if the reference is a png image")
if args.show:
fig, ax=plt.subplots()
ax.imshow(ref_img, interpolation="none", cmap='gray')
plt.show()
else:
ref_cg=ftmc.CoarseGrainRNA(args.reference)
try:
ref_proj=ftmp.Projection2D(ref_cg, project_virtual_atoms=True)
except ValueError:
parser.error('The reference *.cg file needs a "project" line.')
if args.scale:
ref_box=fph.get_box(ref_proj, args.scale)
else:
ref_box=ref_proj.get_bounding_square(margin=50)
args.scale=ref_box[1]-ref_box[0]
if args.dpi:
ref_img, _=ref_proj.rasterize(args.dpi, bounding_square=ref_box)
else:
parser.error("If the reference is not a png image, --dpi is required")
ref_img=(ref_img>np.zeros_like(ref_img)) #Make it a boolean array
for f in args.files:
cg=ftmc.CoarseGrainRNA(f)
if args.global_search or cg.project_from is None:
distance, img, params = fph.globally_minimal_distance(ref_img, args.scale, cg)
fname = os.path.basename(f)
print ("{}:\t{} distance (projected from {}, rotated by {}, offset {}. Globally optimized)".format(fname, distance, params[0], params[1], params[2] ))
else: