text_prompt stringlengths 157 13.1k | code_prompt stringlengths 7 19.8k ⌀ |
|---|---|
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
| def _make_immutable(self):
'''
Prevents any future changes to the object
'''
self._bytes = bytes(self._bytes)
self.__immutable = True |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
| def find(self, substring):
'''
byte-like -> int
Finds the index of substring
'''
if isinstance(substring, ByteData):
substring = substring.to_bytes()
return self._bytes.find(substring) |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
| def from_bytes(VarInt, byte_string):
'''
byte-like -> VarInt
accepts arbitrary length input, gets a VarInt off the front
'''
num = byte_string
if num[0] <= 0xfc:
num = num[0:1]
non_compact = False
elif num[0] == 0xfd:
num = num[... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
| def copy(self, tx_ins=None, tx_outs=None, lock_time=None,
expiry_height=None, value_balance=None, tx_shielded_spends=None,
tx_shielded_outputs=None, tx_joinsplits=None,
joinsplit_pubkey=None, joinsplit_sig=None, binding_sig=None):
'''
SaplingTx, ... -> SaplingTx
... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def encode(data, checksum=True):
"""Convert binary to base58 using BASE58_ALPHABET.""" |
if checksum:
data = data + utils.hash256(data)[:4]
v, prefix = to_long(256, lambda x: x, iter(data))
data = from_long(v, prefix, BASE58_BASE, lambda v: BASE58_ALPHABET[v])
return data.decode("utf8") |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
| def make_pkh_output_script(pubkey, witness=False):
'''
bytearray -> bytearray
'''
if witness and not riemann.network.SEGWIT:
raise ValueError(
'Network {} does not support witness scripts.'
.format(riemann.get_current_network_name()))
output_script = bytearray()
... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
| def _make_output(value, output_script, version=None):
'''
byte-like, byte-like -> TxOut
'''
if 'decred' in riemann.get_current_network_name():
return tx.DecredTxOut(
value=value,
version=version,
output_script=output_script)
return tx.TxOut(value=value, ou... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
| def make_sh_output(value, output_script, witness=False):
'''
int, str -> TxOut
'''
return _make_output(
value=utils.i2le_padded(value, 8),
output_script=make_sh_output_script(output_script, witness)) |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
| def make_pkh_output(value, pubkey, witness=False):
'''
int, bytearray -> TxOut
'''
return _make_output(
value=utils.i2le_padded(value, 8),
output_script=make_pkh_output_script(pubkey, witness)) |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
| def make_outpoint(tx_id_le, index, tree=None):
'''
byte-like, int, int -> Outpoint
'''
if 'decred' in riemann.get_current_network_name():
return tx.DecredOutpoint(tx_id=tx_id_le,
index=utils.i2le_padded(index, 4),
tree=utils.i2le_... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
| def make_script_sig(stack_script, redeem_script):
'''
str, str -> bytearray
'''
stack_script += ' {}'.format(
serialization.hex_serialize(redeem_script))
return serialization.serialize(stack_script) |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
| def make_legacy_input(outpoint, stack_script, redeem_script, sequence):
'''
Outpoint, byte-like, byte-like, int -> TxIn
'''
if 'decred' in riemann.get_current_network_name():
return tx.DecredTxIn(
outpoint=outpoint,
sequence=utils.i2le_padded(sequence, 4))
return tx.T... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
| def make_witness_input(outpoint, sequence):
'''
Outpoint, int -> TxIn
'''
if 'decred' in riemann.get_current_network_name():
return tx.DecredTxIn(
outpoint=outpoint,
sequence=utils.i2le_padded(sequence, 4))
return tx.TxIn(outpoint=outpoint,
stack_sc... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
| def length_prepend(byte_string):
'''
bytes -> bytes
'''
length = tx.VarInt(len(byte_string))
return length.to_bytes() + byte_string |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
| def _hash_to_sh_address(script_hash, witness=False, cashaddr=True):
'''
bytes, bool, bool -> str
cashaddrs are preferred where possible
but cashaddr is ignored in most cases
is there a better way to structure this?
'''
addr_bytes = bytearray()
if riemann.network.CASHADDR_P2SH is not None... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
| def _ser_script_to_sh_address(script_bytes, witness=False, cashaddr=True):
'''
makes an p2sh address from a serialized script
'''
if witness:
script_hash = utils.sha256(script_bytes)
else:
script_hash = utils.hash160(script_bytes)
return _hash_to_sh_address(
script_hash=s... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
| def make_sh_address(script_string, witness=False, cashaddr=True):
'''
str, bool, bool -> str
'''
script_bytes = script_ser.serialize(script_string)
return _ser_script_to_sh_address(
script_bytes=script_bytes,
witness=witness,
cashaddr=cashaddr) |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
| def to_output_script(address):
'''
str -> bytes
There's probably a better way to do this
'''
parsed = parse(address)
parsed_hash = b''
try:
if (parsed.find(riemann.network.P2WPKH_PREFIX) == 0
and len(parsed) == 22):
return parsed
except TypeError:
... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
| def parse_hash(address):
'''
str -> bytes
There's probably a better way to do this.
'''
raw = parse(address)
# Cash addresses
try:
if address.find(riemann.network.CASHADDR_PREFIX) == 0:
if raw.find(riemann.network.CASHADDR_P2SH) == 0:
return raw[len(riem... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
| def guess_version(redeem_script):
'''
str -> int
Bitcoin uses tx version 2 for nSequence signaling.
Zcash uses tx version 2 for joinsplits.
We want to signal nSequence if we're using OP_CSV.
Unless we're in zcash.
'''
n = riemann.get_current_network_name()
if 'sprout' in n:
... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
| def guess_sequence(redeem_script):
'''
str -> int
If OP_CSV is used, guess an appropriate sequence
Otherwise, disable RBF, but leave lock_time on.
Fails if there's not a constant before OP_CSV
'''
try:
script_array = redeem_script.split()
loc = script_array.index('OP_CHECKSEQ... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
| def output(value, address):
'''
int, str -> TxOut
accepts base58 or bech32 addresses
'''
script = addr.to_output_script(address)
value = utils.i2le_padded(value, 8)
return tb._make_output(value, script) |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
| def outpoint(tx_id, index, tree=None):
'''
hex_str, int, int -> Outpoint
accepts block explorer txid string
'''
tx_id_le = bytes.fromhex(tx_id)[::-1]
return tb.make_outpoint(tx_id_le, index, tree) |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
| def unsigned_input(outpoint, redeem_script=None, sequence=None):
'''
Outpoint, byte-like, int -> TxIn
'''
if redeem_script is not None and sequence is None:
sequence = guess_sequence(redeem_script)
if sequence is None:
sequence = 0xFFFFFFFE
return tb.make_legacy_input(
ou... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
| def p2pkh_input(outpoint, sig, pubkey, sequence=0xFFFFFFFE):
'''
OutPoint, hex_string, hex_string, int -> TxIn
Create a signed legacy TxIn from a p2pkh prevout
'''
stack_script = '{sig} {pk}'.format(sig=sig, pk=pubkey)
stack_script = script_ser.serialize(stack_script)
return tb.make_legacy_i... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
| def p2sh_input(outpoint, stack_script, redeem_script, sequence=None):
'''
OutPoint, str, str, int -> TxIn
Create a signed legacy TxIn from a p2pkh prevout
'''
if sequence is None:
sequence = guess_sequence(redeem_script)
stack_script = script_ser.serialize(stack_script)
redeem_scrip... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
| def copy(self, tx_ins=None, tx_outs=None, lock_time=None,
expiry_height=None, tx_joinsplits=None, joinsplit_pubkey=None,
joinsplit_sig=None):
'''
OverwinterTx, ... -> OverwinterTx
Makes a copy. Allows over-writing specific pieces.
'''
return OverwinterT... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
| def from_bytes(OverwinterTx, byte_string):
'''
byte-like -> OverwinterTx
'''
header = byte_string[0:4]
group_id = byte_string[4:8]
if header != b'\x03\x00\x00\x80' or group_id != b'\x70\x82\xc4\x03':
raise ValueError(
'Bad header or group ID. ... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def cli(ctx):
"""Initializes the CLI environment.""" |
dir_path = os.path.join(os.path.expanduser('~'), '.keep')
if os.path.exists(dir_path):
if click.confirm('[CRITICAL] Remove everything inside ~/.keep ?', abort=True):
shutil.rmtree(dir_path)
utils.first_time_use(ctx) |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def cli(ctx, pattern, arguments, safe):
"""Executes a saved command.""" |
matches = utils.grep_commands(pattern)
if matches:
selected = utils.select_command(matches)
if selected >= 0:
cmd, desc = matches[selected]
pcmd = utils.create_pcmd(cmd)
raw_params, params, defaults = utils.get_params_in_pcmd(pcmd)
arguments = l... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def cli(ctx):
"""Saves a new command""" |
cmd = click.prompt('Command')
desc = click.prompt('Description ')
alias = click.prompt('Alias (optional)', default='')
utils.save_command(cmd, desc, alias)
utils.log(ctx, 'Saved the new command - {} - with the description - {}.'.format(cmd, desc)) |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def log(self, msg, *args):
"""Logs a message to stderr.""" |
if args:
msg %= args
click.echo(msg, file=sys.stderr) |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def vlog(self, msg, *args):
"""Logs a message to stderr only if verbose is enabled.""" |
if self.verbose:
self.log(msg, *args) |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def cli(ctx):
"""Check for an update of Keep.""" |
utils.check_update(ctx, forced=True)
click.secho("Keep is at its latest version v{}".format(about.__version__), fg='green') |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def cli(ctx, pattern):
"""Searches for a saved command.""" |
matches = utils.grep_commands(pattern)
if matches:
for cmd, desc in matches:
click.secho("$ {} :: {}".format(cmd, desc), fg='green')
elif matches == []:
click.echo('No saved commands matches the pattern {}'.format(pattern))
else:
click.echo('No commands to show. Add ... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def cli(ctx):
"""Shows the saved commands.""" |
json_path = os.path.join(os.path.expanduser('~'), '.keep', 'commands.json')
if not os.path.exists(json_path):
click.echo('No commands to show. Add one by `keep new`.')
else:
utils.list_commands(ctx) |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def cli(ctx, overwrite):
"""Updates the local database with remote.""" |
credentials_path = os.path.join(os.path.expanduser('~'), '.keep', '.credentials')
if not os.path.exists(credentials_path):
click.echo('You are not registered.')
utils.register()
else:
utils.pull(ctx, overwrite) |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def cli(ctx):
"""Register user over server.""" |
dir_path = os.path.join(os.path.expanduser('~'), '.keep', '.credentials')
if os.path.exists(dir_path):
if click.confirm('[CRITICAL] Reset credentials saved in ~/.keep/.credentials ?', abort=True):
os.remove(dir_path)
utils.register() |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def check_update(ctx, forced=False):
""" Check for update on pypi. Limit to 1 check per day if not forced """ |
try:
if ctx.update_checked and not forced:
return
except AttributeError:
update_check_file = os.path.join(dir_path, 'update_check.txt')
today = datetime.date.today().strftime("%m/%d/%Y")
if os.path.exists(update_check_file):
date = open(update_check_file,... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def cli(ctx, editor):
"""Edit saved commands.""" |
commands = utils.read_commands()
if commands is []:
click.echo("No commands to edit, Add one by 'keep new'. ")
else:
edit_header = "# Unchanged file will abort the operation\n"
new_commands = utils.edit_commands(commands, editor, edit_header)
if new_commands and new_command... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def cli(ctx, pattern):
"""Deletes a saved command.""" |
matches = utils.grep_commands(pattern)
if matches:
selected = utils.select_command(matches)
if selected >= 0:
cmd, desc = matches[selected]
command = "$ {} :: {}".format(cmd, desc)
if click.confirm("Remove\n\t{}\n\n?".format(command), default=True):
... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def show_mesh(mesh):
r""" Visualizes the mesh of a region as obtained by ``get_mesh`` function in the ``metrics`` submodule. Parameters mesh : tuple A mesh retur... |
lim_max = sp.amax(mesh.verts, axis=0)
lim_min = sp.amin(mesh.verts, axis=0)
# Display resulting triangular mesh using Matplotlib.
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
# Fancy indexing: `verts[faces]` to generate a collection of triangles
mesh = Poly3DCollection(me... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def representative_elementary_volume(im, npoints=1000):
r""" Calculates the porosity of the image as a function subdomain size. This function extracts a specifie... |
im_temp = sp.zeros_like(im)
crds = sp.array(sp.rand(npoints, im.ndim)*im.shape, dtype=int)
pads = sp.array(sp.rand(npoints)*sp.amin(im.shape)/2+10, dtype=int)
im_temp[tuple(crds.T)] = True
labels, N = spim.label(input=im_temp)
slices = spim.find_objects(input=labels)
porosity = sp.zeros(sha... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def porosity_profile(im, axis):
r""" Returns a porosity profile along the specified axis Parameters im : ND-array The volumetric image for which to calculate the... |
if axis >= im.ndim:
raise Exception('axis out of range')
im = np.atleast_3d(im)
a = set(range(im.ndim)).difference(set([axis]))
a1, a2 = a
prof = np.sum(np.sum(im, axis=a2), axis=a1)/(im.shape[a2]*im.shape[a1])
return prof*100 |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def porosity(im):
r""" Calculates the porosity of an image assuming 1's are void space and 0's are solid phase. All other values are ignored, so this can also re... |
im = sp.array(im, dtype=int)
Vp = sp.sum(im == 1)
Vs = sp.sum(im == 0)
e = Vp/(Vs + Vp)
return e |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def _radial_profile(autocorr, r_max, nbins=100):
r""" Helper functions to calculate the radial profile of the autocorrelation Masks the image in radial segments ... |
if len(autocorr.shape) == 2:
adj = sp.reshape(autocorr.shape, [2, 1, 1])
inds = sp.indices(autocorr.shape) - adj/2
dt = sp.sqrt(inds[0]**2 + inds[1]**2)
elif len(autocorr.shape) == 3:
adj = sp.reshape(autocorr.shape, [3, 1, 1, 1])
inds = sp.indices(autocorr.shape) - adj/... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def two_point_correlation_fft(im):
r""" Calculates the two-point correlation function using fourier transforms Parameters im : ND-array The image of the void spa... |
# Calculate half lengths of the image
hls = (np.ceil(np.shape(im))/2).astype(int)
# Fourier Transform and shift image
F = sp_ft.ifftshift(sp_ft.fftn(sp_ft.fftshift(im)))
# Compute Power Spectrum
P = sp.absolute(F**2)
# Auto-correlation is inverse of Power Spectrum
autoc = sp.absolute(sp... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def pore_size_distribution(im, bins=10, log=True, voxel_size=1):
r""" Calculate a pore-size distribution based on the image produced by the ``porosimetry`` or ``... |
im = im.flatten()
vals = im[im > 0]*voxel_size
if log:
vals = sp.log10(vals)
h = _parse_histogram(sp.histogram(vals, bins=bins, density=True))
psd = namedtuple('pore_size_distribution',
(log*'log' + 'R', 'pdf', 'cdf', 'satn',
'bin_centers', 'bin_ed... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def chord_counts(im):
r""" Finds the length of each chord in the supplied image and returns a list of their individual sizes Parameters im : ND-array An image co... |
labels, N = spim.label(im > 0)
props = regionprops(labels, coordinates='xy')
chord_lens = sp.array([i.filled_area for i in props])
return chord_lens |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def chord_length_distribution(im, bins=None, log=False, voxel_size=1, normalization='count'):
r""" Determines the distribution of chord lengths in an image conta... |
x = chord_counts(im)
if bins is None:
bins = sp.array(range(0, x.max()+2))*voxel_size
x = x*voxel_size
if log:
x = sp.log10(x)
if normalization == 'length':
h = list(sp.histogram(x, bins=bins, density=False))
h[0] = h[0]*(h[1][1:]+h[1][:-1])/2 # Scale bin heigths by... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def region_interface_areas(regions, areas, voxel_size=1, strel=None):
r""" Calculates the interfacial area between all pairs of adjecent regions Parameters regio... |
print('_'*60)
print('Finding interfacial areas between each region')
from skimage.morphology import disk, square, ball, cube
im = regions.copy()
if im.ndim != im.squeeze().ndim:
warnings.warn('Input image conains a singleton axis:' + str(im.shape) +
' Reduce dimensiona... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def region_surface_areas(regions, voxel_size=1, strel=None):
r""" Extracts the surface area of each region in a labeled image. Optionally, it can also find the t... |
print('_'*60)
print('Finding surface area of each region')
im = regions.copy()
# Get 'slices' into im for each pore region
slices = spim.find_objects(im)
# Initialize arrays
Ps = sp.arange(1, sp.amax(im)+1)
sa = sp.zeros_like(Ps, dtype=float)
# Start extracting marching cube area fr... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def mesh_surface_area(mesh=None, verts=None, faces=None):
r""" Calculates the surface area of a meshed region Parameters mesh : tuple The tuple returned from the... |
if mesh:
verts = mesh.verts
faces = mesh.faces
else:
if (verts is None) or (faces is None):
raise Exception('Either mesh or verts and faces must be given')
surface_area = measure.mesh_surface_area(verts, faces)
return surface_area |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def show_planes(im):
r""" Create a quick montage showing a 3D image in all three directions Parameters im : ND-array A 3D image of the porous material Returns --... |
if sp.squeeze(im.ndim) < 3:
raise Exception('This view is only necessary for 3D images')
x, y, z = (sp.array(im.shape)/2).astype(int)
im_xy = im[:, :, z]
im_xz = im[:, y, :]
im_yz = sp.rot90(im[x, :, :])
new_x = im_xy.shape[0] + im_yz.shape[0] + 10
new_y = im_xy.shape[1] + im_xz.s... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def sem(im, direction='X'):
r""" Simulates an SEM photograph looking into the porous material in the specified direction. Features are colored according to their... |
im = sp.array(~im, dtype=int)
if direction in ['Y', 'y']:
im = sp.transpose(im, axes=[1, 0, 2])
if direction in ['Z', 'z']:
im = sp.transpose(im, axes=[2, 1, 0])
t = im.shape[0]
depth = sp.reshape(sp.arange(0, t), [t, 1, 1])
im = im*depth
im = sp.amax(im, axis=0)
return ... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def xray(im, direction='X'):
r""" Simulates an X-ray radiograph looking through the porouls material in the specfied direction. The resulting image is colored ac... |
im = sp.array(~im, dtype=int)
if direction in ['Y', 'y']:
im = sp.transpose(im, axes=[1, 0, 2])
if direction in ['Z', 'z']:
im = sp.transpose(im, axes=[2, 1, 0])
im = sp.sum(im, axis=0)
return im |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def props_to_DataFrame(regionprops):
r""" Returns a Pandas DataFrame containing all the scalar metrics for each region, such as volume, sphericity, and so on, ca... |
# Parse the regionprops list and pull out all props with scalar values
metrics = []
reg = regionprops[0]
for item in reg.__dir__():
if not item.startswith('_'):
try:
if sp.shape(getattr(reg, item)) == ():
metrics.append(item)
except (T... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def props_to_image(regionprops, shape, prop):
r""" Creates an image with each region colored according the specified ``prop``, as obtained by ``regionprops_3d``.... |
im = sp.zeros(shape=shape)
for r in regionprops:
if prop == 'convex':
mask = r.convex_image
else:
mask = r.image
temp = mask * r[prop]
s = bbox_to_slices(r.bbox)
im[s] += temp
return im |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def regionprops_3D(im):
r""" Calculates various metrics for each labeled region in a 3D image. The ``regionsprops`` method in **skimage** is very thorough for 2D... |
print('_'*60)
print('Calculating regionprops')
results = regionprops(im, coordinates='xy')
for i in tqdm(range(len(results))):
mask = results[i].image
mask_padded = sp.pad(mask, pad_width=1, mode='constant')
temp = spim.distance_transform_edt(mask_padded)
dt = extract_s... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def snow_n(im, voxel_size=1, boundary_faces=['top', 'bottom', 'left', 'right', 'front', 'back'], marching_cubes_area=False, alias=None):
r""" Analyzes an image t... |
# -------------------------------------------------------------------------
# Get alias if provided by user
al = _create_alias_map(im, alias=alias)
# -------------------------------------------------------------------------
# Perform snow on each phase and merge all segmentation and dt together
... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def dict_to_vtk(data, path='./dictvtk', voxel_size=1, origin=(0, 0, 0)):
r""" Accepts multiple images as a dictionary and compiles them into a vtk file Parameter... |
vs = voxel_size
for entry in data:
if data[entry].dtype == bool:
data[entry] = data[entry].astype(np.int8)
if data[entry].flags['C_CONTIGUOUS']:
data[entry] = np.ascontiguousarray(data[entry])
imageToVTK(path, cellData=data, spacing=(vs, vs, vs), origin=origin) |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def to_openpnm(net, filename):
r""" Save the result of the `snow` network extraction function in a format suitable for opening in OpenPNM. Parameters net : dict ... |
from openpnm.network import GenericNetwork
# Convert net dict to an openpnm Network
pn = GenericNetwork()
pn.update(net)
pn.project.save_project(filename)
ws = pn.project.workspace
ws.close_project(pn.project) |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def to_vtk(im, path='./voxvtk', divide=False, downsample=False, voxel_size=1, vox=False):
r""" Converts an array to a vtk file. Parameters im : 3D image The imag... |
if len(im.shape) == 2:
im = im[:, :, np.newaxis]
if im.dtype == bool:
vox = True
if vox:
im = im.astype(np.int8)
vs = voxel_size
if divide:
split = np.round(im.shape[2]/2).astype(np.int)
im1 = im[:, :, 0:split]
im2 = im[:, :, split:]
imageToVT... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def to_palabos(im, filename, solid=0):
r""" Converts an ND-array image to a text file that Palabos can read in as a geometry for Lattice Boltzmann simulations. U... |
# Create binary image for fluid and solid phases
bin_im = im == solid
# Transform to integer for distance transform
bin_im = bin_im.astype(int)
# Distance Transform computes Euclidean distance in lattice units to
# Nearest fluid for every solid voxel
dt = nd.distance_transform_edt(bin_im)
... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def distance_transform_lin(im, axis=0, mode='both'):
r""" Replaces each void voxel with the linear distance to the nearest solid voxel along the specified axis. ... |
if im.ndim != im.squeeze().ndim:
warnings.warn('Input image conains a singleton axis:' + str(im.shape) +
' Reduce dimensionality with np.squeeze(im) to avoid' +
' unexpected behavior.')
if mode in ['backward', 'reverse']:
im = sp.flip(im, axis)
... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def snow_partitioning(im, dt=None, r_max=4, sigma=0.4, return_all=False, mask=True, randomize=True):
r""" Partitions the void space into pore regions using a mar... |
tup = namedtuple('results', field_names=['im', 'dt', 'peaks', 'regions'])
print('_'*60)
print("Beginning SNOW Algorithm")
im_shape = sp.array(im.shape)
if im.dtype is not bool:
print('Converting supplied image (im) to boolean')
im = im > 0
if dt is None:
print('Peforming... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def snow_partitioning_n(im, r_max=4, sigma=0.4, return_all=True, mask=True, randomize=False, alias=None):
r""" This function partitions an imaging oontain an arb... |
# Get alias if provided by user
al = _create_alias_map(im=im, alias=alias)
# Perform snow on each phase and merge all segmentation and dt together
phases_num = sp.unique(im * 1)
phases_num = sp.trim_zeros(phases_num)
combined_dt = 0
combined_region = 0
num = [0]
for i in phases_num:... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def find_peaks(dt, r_max=4, footprint=None):
r""" Returns all local maxima in the distance transform Parameters dt : ND-array The distance transform of the pore ... |
im = dt > 0
if im.ndim != im.squeeze().ndim:
warnings.warn('Input image conains a singleton axis:' + str(im.shape) +
' Reduce dimensionality with np.squeeze(im) to avoid' +
' unexpected behavior.')
if footprint is None:
if im.ndim == 2:
... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def reduce_peaks(peaks):
r""" Any peaks that are broad or elongated are replaced with a single voxel that is located at the center of mass of the original voxels... |
if peaks.ndim == 2:
strel = square
else:
strel = cube
markers, N = spim.label(input=peaks, structure=strel(3))
inds = spim.measurements.center_of_mass(input=peaks,
labels=markers,
index=sp.arange(1, ... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def trim_saddle_points(peaks, dt, max_iters=10):
r""" Removes peaks that were mistakenly identified because they lied on a saddle or ridge in the distance transf... |
peaks = sp.copy(peaks)
if dt.ndim == 2:
from skimage.morphology import square as cube
else:
from skimage.morphology import cube
labels, N = spim.label(peaks)
slices = spim.find_objects(labels)
for i in range(N):
s = extend_slice(s=slices[i], shape=peaks.shape, pad=10)
... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def trim_nearby_peaks(peaks, dt):
r""" Finds pairs of peaks that are nearer to each other than to the solid phase, and removes the peak that is closer to the sol... |
peaks = sp.copy(peaks)
if dt.ndim == 2:
from skimage.morphology import square as cube
else:
from skimage.morphology import cube
peaks, N = spim.label(peaks, structure=cube(3))
crds = spim.measurements.center_of_mass(peaks, labels=peaks,
in... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def fill_blind_pores(im):
r""" Fills all pores that are not connected to the edges of the image. Parameters im : ND-array The image of the porous material Return... |
im = sp.copy(im)
holes = find_disconnected_voxels(im)
im[holes] = False
return im |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def trim_floating_solid(im):
r""" Removes all solid that that is not attached to the edges of the image. Parameters im : ND-array The image of the porous materia... |
im = sp.copy(im)
holes = find_disconnected_voxels(~im)
im[holes] = True
return im |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def trim_nonpercolating_paths(im, inlet_axis=0, outlet_axis=0):
r""" Removes all nonpercolating paths between specified edges This function is essential when per... |
if im.ndim != im.squeeze().ndim:
warnings.warn('Input image conains a singleton axis:' + str(im.shape) +
' Reduce dimensionality with np.squeeze(im) to avoid' +
' unexpected behavior.')
im = trim_floating_solid(~im)
labels = spim.label(~im)[0]
inlet =... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def trim_extrema(im, h, mode='maxima'):
r""" Trims local extrema in greyscale values by a specified amount. This essentially decapitates peaks and/or floods vall... |
result = im
if mode in ['maxima', 'extrema']:
result = reconstruction(seed=im - h, mask=im, method='dilation')
elif mode in ['minima', 'extrema']:
result = reconstruction(seed=im + h, mask=im, method='erosion')
return result |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def find_dt_artifacts(dt):
r""" Finds points in a distance transform that are closer to wall than solid. These points could *potentially* be erroneously high sin... |
temp = sp.ones(shape=dt.shape)*sp.inf
for ax in range(dt.ndim):
dt_lin = distance_transform_lin(sp.ones_like(temp, dtype=bool),
axis=ax, mode='both')
temp = sp.minimum(temp, dt_lin)
result = sp.clip(dt - temp, a_min=0, a_max=sp.inf)
return result |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def region_size(im):
r""" Replace each voxel with size of region to which it belongs Parameters im : ND-array Either a boolean image wtih ``True`` indicating the... |
if im.dtype == bool:
im = spim.label(im)[0]
counts = sp.bincount(im.flatten())
counts[0] = 0
chords = counts[im]
return chords |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def apply_chords(im, spacing=1, axis=0, trim_edges=True, label=False):
r""" Adds chords to the void space in the specified direction. The chords are separated by... |
if im.ndim != im.squeeze().ndim:
warnings.warn('Input image conains a singleton axis:' + str(im.shape) +
' Reduce dimensionality with np.squeeze(im) to avoid' +
' unexpected behavior.')
if spacing < 0:
raise Exception('Spacing cannot be less than 0')
... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def apply_chords_3D(im, spacing=0, trim_edges=True):
r""" Adds chords to the void space in all three principle directions. The chords are seprated by 1 voxel plu... |
if im.ndim != im.squeeze().ndim:
warnings.warn('Input image conains a singleton axis:' + str(im.shape) +
' Reduce dimensionality with np.squeeze(im) to avoid' +
' unexpected behavior.')
if im.ndim < 3:
raise Exception('Must be a 3D image to use this f... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def porosimetry(im, sizes=25, inlets=None, access_limited=True, mode='hybrid'):
r""" Performs a porosimetry simulution on the image Parameters im : ND-array An N... |
if im.ndim != im.squeeze().ndim:
warnings.warn('Input image conains a singleton axis:' + str(im.shape) +
' Reduce dimensionality with np.squeeze(im) to avoid' +
' unexpected behavior.')
dt = spim.distance_transform_edt(im > 0)
if inlets is None:
... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def trim_disconnected_blobs(im, inlets):
r""" Removes foreground voxels not connected to specified inlets Parameters im : ND-array The array to be trimmed inlets... |
temp = sp.zeros_like(im)
temp[inlets] = True
labels, N = spim.label(im + temp)
im = im ^ (clear_border(labels=labels) > 0)
return im |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
| def _make_stack(im, include_diagonals=False):
r'''
Creates a stack of images with one extra dimension to the input image
with length equal to the number of borders to search + 1.
Image is rolled along the axial shifts so that the border pixel is
overlapping the original pixel. First image in stack i... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def map_to_regions(regions, values):
r""" Maps pore values from a network onto the image from which it was extracted This function assumes that the pore numberin... |
values = sp.array(values).flatten()
if sp.size(values) != regions.max() + 1:
raise Exception('Number of values does not match number of regions')
im = sp.zeros_like(regions)
im = values[regions]
return im |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def label_boundary_cells(network=None, boundary_faces=None):
r""" Takes 2D or 3D network and assign labels to boundary pores Parameters network : dictionary A di... |
f = boundary_faces
if f is not None:
coords = network['pore.coords']
condition = coords[~network['pore.boundary']]
dic = {'left': 0, 'right': 0, 'front': 1, 'back': 1,
'top': 2, 'bottom': 2}
if all(coords[:, 2] == 0):
dic['top'] = 1
dic['bo... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def insert_shape(im, element, center=None, corner=None, value=1, mode='overwrite'):
r""" Inserts sub-image into a larger image at the specified location. If the ... |
im = im.copy()
if im.ndim != element.ndim:
raise Exception('Image shape ' + str(im.shape)
+ ' and element shape ' + str(element.shape)
+ ' do not match')
s_im = []
s_el = []
if (center is not None) and (corner is None):
for dim in rang... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def bundle_of_tubes(shape: List[int], spacing: int):
r""" Create a 3D image of a bundle of tubes, in the form of a rectangular plate with randomly sized holes th... |
shape = sp.array(shape)
if sp.size(shape) == 1:
shape = sp.full((3, ), int(shape))
if sp.size(shape) == 2:
shape = sp.hstack((shape, [1]))
temp = sp.zeros(shape=shape[:2])
Xi = sp.ceil(sp.linspace(spacing/2,
shape[0]-(spacing/2)-1,
... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def polydisperse_spheres(shape: List[int], porosity: float, dist, nbins: int = 5, r_min: int = 5):
r""" Create an image of randomly place, overlapping spheres wi... |
shape = sp.array(shape)
if sp.size(shape) == 1:
shape = sp.full((3, ), int(shape))
Rs = dist.interval(sp.linspace(0.05, 0.95, nbins))
Rs = sp.vstack(Rs).T
Rs = (Rs[:-1] + Rs[1:])/2
Rs = sp.clip(Rs.flatten(), a_min=r_min, a_max=None)
phi_desired = 1 - (1 - porosity)/(len(Rs))
im ... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def _get_Voronoi_edges(vor):
r""" Given a Voronoi object as produced by the scipy.spatial.Voronoi class, this function calculates the start and end points of eea... |
edges = [[], []]
for facet in vor.ridge_vertices:
# Create a closed cycle of vertices that define the facet
edges[0].extend(facet[:-1]+[facet[-1]])
edges[1].extend(facet[1:]+[facet[0]])
edges = sp.vstack(edges).T # Convert to scipy-friendly format
mask = sp.any(edges == -1, axi... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def overlapping_spheres(shape: List[int], radius: int, porosity: float, iter_max: int = 10, tol: float = 0.01):
r""" Generate a packing of overlapping mono-dispe... |
shape = sp.array(shape)
if sp.size(shape) == 1:
shape = sp.full((3, ), int(shape))
ndim = (shape != 1).sum()
s_vol = ps_disk(radius).sum() if ndim == 2 else ps_ball(radius).sum()
bulk_vol = sp.prod(shape)
N = int(sp.ceil((1 - porosity)*bulk_vol/s_vol))
im = sp.random.random(size=sh... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def generate_noise(shape: List[int], porosity=None, octaves: int = 3, frequency: int = 32, mode: str = 'simplex'):
r""" Generate a field of spatially correlated ... |
try:
import noise
except ModuleNotFoundError:
raise Exception("The noise package must be installed")
shape = sp.array(shape)
if sp.size(shape) == 1:
Lx, Ly, Lz = sp.full((3, ), int(shape))
elif len(shape) == 2:
Lx, Ly = shape
Lz = 1
elif len(shape) == 3:
... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def blobs(shape: List[int], porosity: float = 0.5, blobiness: int = 1):
""" Generates an image containing amorphous blobs Parameters shape : list The size of the... |
blobiness = sp.array(blobiness)
shape = sp.array(shape)
if sp.size(shape) == 1:
shape = sp.full((3, ), int(shape))
sigma = sp.mean(shape)/(40*blobiness)
im = sp.random.random(shape)
im = spim.gaussian_filter(im, sigma=sigma)
im = norm_to_uniform(im, scale=[0, 1])
if porosity:
... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def cylinders(shape: List[int], radius: int, ncylinders: int, phi_max: float = 0, theta_max: float = 90):
r""" Generates a binary image of overlapping cylinders.... |
shape = sp.array(shape)
if sp.size(shape) == 1:
shape = sp.full((3, ), int(shape))
elif sp.size(shape) == 2:
raise Exception("2D cylinders don't make sense")
R = sp.sqrt(sp.sum(sp.square(shape))).astype(int)
im = sp.zeros(shape)
# Adjust max angles to be between 0 and 90
if ... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def line_segment(X0, X1):
r""" Calculate the voxel coordinates of a straight line between the two given end points Parameters X0 and X1 : array_like The [x, y] o... |
X0 = sp.around(X0).astype(int)
X1 = sp.around(X1).astype(int)
if len(X0) == 3:
L = sp.amax(sp.absolute([[X1[0]-X0[0]], [X1[1]-X0[1]], [X1[2]-X0[2]]])) + 1
x = sp.rint(sp.linspace(X0[0], X1[0], L)).astype(int)
y = sp.rint(sp.linspace(X0[1], X1[1], L)).astype(int)
z = sp.rint(... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
| def _remove_edge(im, r):
r'''
Fill in the edges of the input image.
Used by RSA to ensure that no elements are placed too close to the edge.
'''
edge = sp.ones_like(im)
if len(im.shape) == 2:
sx, sy = im.shape
edge[r:sx-r, r:sy-r] = im[r:sx-r, r:sy-r]
else:
sx, sy, sz... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def align_image_with_openpnm(im):
r""" Rotates an image to agree with the coordinates used in OpenPNM. It is unclear why they are not in agreement to start with.... |
if im.ndim != im.squeeze().ndim:
warnings.warn('Input image conains a singleton axis:' + str(im.shape) +
' Reduce dimensionality with np.squeeze(im) to avoid' +
' unexpected behavior.')
im = sp.copy(im)
if im.ndim == 2:
im = (sp.swapaxes(im, 1, 0)... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def fftmorphology(im, strel, mode='opening'):
r""" Perform morphological operations on binary images using fft approach for improved performance Parameters im : ... |
def erode(im, strel):
t = fftconvolve(im, strel, mode='same') > (strel.sum() - 0.1)
return t
def dilate(im, strel):
t = fftconvolve(im, strel, mode='same') > 0.1
return t
if im.ndim != im.squeeze().ndim:
warnings.warn('Input image conains a singleton axis:' + str(... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def subdivide(im, divs=2):
r""" Returns slices into an image describing the specified number of sub-arrays. This function is useful for performing operations on ... |
# Expand scalar divs
if isinstance(divs, int):
divs = [divs for i in range(im.ndim)]
s = shape_split(im.shape, axis=divs)
return s |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def bbox_to_slices(bbox):
r""" Given a tuple containing bounding box coordinates, return a tuple of slice objects. A bounding box in the form of a straight list ... |
if len(bbox) == 4:
ret = (slice(bbox[0], bbox[2]),
slice(bbox[1], bbox[3]))
else:
ret = (slice(bbox[0], bbox[3]),
slice(bbox[1], bbox[4]),
slice(bbox[2], bbox[5]))
return ret |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def get_slice(im, center, size, pad=0):
r""" Given a ``center`` location and ``radius`` of a feature, returns the slice object into the ``im`` that bounds the fe... |
p = sp.ones(shape=im.ndim, dtype=int) * sp.array(pad)
s = sp.ones(shape=im.ndim, dtype=int) * sp.array(size)
slc = []
for dim in range(im.ndim):
lower_im = sp.amax((center[dim] - s[dim] - p[dim], 0))
upper_im = sp.amin((center[dim] + s[dim] + 1 + p[dim], im.shape[dim]))
slc.appe... |
<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
def find_outer_region(im, r=0):
r""" Finds regions of the image that are outside of the solid matrix. This function uses the rolling ball method to define where ... |
if r == 0:
dt = spim.distance_transform_edt(input=im)
r = int(sp.amax(dt)) * 2
im_padded = sp.pad(array=im, pad_width=r, mode='constant',
constant_values=True)
dt = spim.distance_transform_edt(input=im_padded)
seeds = (dt >= r) + get_border(shape=im_padded.shape)
... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.