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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | CMAAdaptSigmaBase._update_ps | def _update_ps(self, es):
"""update the isotropic evolution path
:type es: CMAEvolutionStrategy
"""
if not self.is_initialized_base:
self.initialize_base(es)
if self._ps_updated_iteration == es.countiter:
return
if es.countiter <= es.itereigenupda... | python | def _update_ps(self, es):
"""update the isotropic evolution path
:type es: CMAEvolutionStrategy
"""
if not self.is_initialized_base:
self.initialize_base(es)
if self._ps_updated_iteration == es.countiter:
return
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | CMAEvolutionStrategy.stop | def stop(self, check=True):
"""return a dictionary with the termination status.
With ``check==False``, the termination conditions are not checked
and the status might not reflect the current situation.
"""
if (check and self.countiter > 0 and self.opts['termination_callback'] an... | python | def stop(self, check=True):
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With ``check==False``, the termination conditions are not checked
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | CMAEvolutionStrategy.random_rescale_to_mahalanobis | def random_rescale_to_mahalanobis(self, x):
"""change `x` like for injection, all on genotypic level"""
x -= self.mean
if any(x):
x *= sum(self.randn(len(x))**2)**0.5 / self.mahalanobis_norm(x)
x += self.mean
return x | python | def random_rescale_to_mahalanobis(self, x):
"""change `x` like for injection, all on genotypic level"""
x -= self.mean
if any(x):
x *= sum(self.randn(len(x))**2)**0.5 / self.mahalanobis_norm(x)
x += self.mean
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | CMAEvolutionStrategy.prepare_injection_directions | def prepare_injection_directions(self):
"""provide genotypic directions for TPA and selective mirroring,
with no specific length normalization, to be used in the
coming iteration.
Details:
This method is called in the end of `tell`. The result is
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"""provide genotypic directions for TPA and selective mirroring,
with no specific length normalization, to be used in the
coming iteration.
Details:
This method is called in the end of `tell`. The result is
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | CMAEvolutionStrategy.inject | def inject(self, solutions):
"""inject a genotypic solution. The solution is used as direction
relative to the distribution mean to compute a new candidate
solution returned in method `ask_geno` which in turn is used in
method `ask`.
>>> import cma
>>> es = cma.CMAEvolut... | python | def inject(self, solutions):
"""inject a genotypic solution. The solution is used as direction
relative to the distribution mean to compute a new candidate
solution returned in method `ask_geno` which in turn is used in
method `ask`.
>>> import cma
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | CMAEvolutionStrategy.result_pretty | def result_pretty(self, number_of_runs=0, time_str=None,
fbestever=None):
"""pretty print result.
Returns ``self.result()``
"""
if fbestever is None:
fbestever = self.best.f
s = (' after %i restart' + ('s' if number_of_runs > 1 else '')) \
... | python | def result_pretty(self, number_of_runs=0, time_str=None,
fbestever=None):
"""pretty print result.
Returns ``self.result()``
"""
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fbestever = self.best.f
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | CMAEvolutionStrategy.clip_or_fit_solutions | def clip_or_fit_solutions(self, pop, idx):
"""make sure that solutions fit to sample distribution, this interface will probably change.
In particular the frequency of long vectors appearing in pop[idx] - self.mean is limited.
"""
for k in idx:
self.repair_genotype(pop[k]) | python | def clip_or_fit_solutions(self, pop, idx):
"""make sure that solutions fit to sample distribution, this interface will probably change.
In particular the frequency of long vectors appearing in pop[idx] - self.mean is limited.
"""
for k in idx:
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | CMAEvolutionStrategy.repair_genotype | def repair_genotype(self, x, copy_if_changed=False):
"""make sure that solutions fit to the sample distribution, this interface will probably change.
In particular the frequency of x - self.mean being long is limited.
"""
x = array(x, copy=False)
mold = array(self.mean, copy=Fa... | python | def repair_genotype(self, x, copy_if_changed=False):
"""make sure that solutions fit to the sample distribution, this interface will probably change.
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"""
x = array(x, copy=False)
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | CMAEvolutionStrategy.decompose_C | def decompose_C(self):
"""eigen-decompose self.C and update self.dC, self.C, self.B.
Known bugs: this might give a runtime error with
CMA_diagonal / separable option on.
"""
if self.opts['CMA_diagonal']:
_print_warning("this might fail with CMA_diagonal option on",
... | python | def decompose_C(self):
"""eigen-decompose self.C and update self.dC, self.C, self.B.
Known bugs: this might give a runtime error with
CMA_diagonal / separable option on.
"""
if self.opts['CMA_diagonal']:
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | CMAEvolutionStrategy.feedForResume | def feedForResume(self, X, function_values):
"""Given all "previous" candidate solutions and their respective
function values, the state of a `CMAEvolutionStrategy` object
can be reconstructed from this history. This is the purpose of
function `feedForResume`.
Arguments
... | python | def feedForResume(self, X, function_values):
"""Given all "previous" candidate solutions and their respective
function values, the state of a `CMAEvolutionStrategy` object
can be reconstructed from this history. This is the purpose of
function `feedForResume`.
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | CMAOptions.defaults | def defaults():
"""return a dictionary with default option values and description"""
return dict((str(k), str(v)) for k, v in cma_default_options.items()) | python | def defaults():
"""return a dictionary with default option values and description"""
return dict((str(k), str(v)) for k, v in cma_default_options.items()) | [
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | CMAOptions.check | def check(self, options=None):
"""check for ambiguous keys and move attributes into dict"""
self.check_values(options)
self.check_attributes(options)
self.check_values(options)
return self | python | def check(self, options=None):
"""check for ambiguous keys and move attributes into dict"""
self.check_values(options)
self.check_attributes(options)
self.check_values(options)
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | CMAOptions.init | def init(self, dict_or_str, val=None, warn=True):
"""initialize one or several options.
Arguments
---------
`dict_or_str`
a dictionary if ``val is None``, otherwise a key.
If `val` is provided `dict_or_str` must be a valid key.
`val`
... | python | def init(self, dict_or_str, val=None, warn=True):
"""initialize one or several options.
Arguments
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`dict_or_str`
a dictionary if ``val is None``, otherwise a key.
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | CMAOptions.complement | def complement(self):
"""add all missing options with their default values"""
# add meta-parameters, given options have priority
self.check()
for key in CMAOptions.defaults():
if key not in self:
self[key] = CMAOptions.defaults()[key]
return self | python | def complement(self):
"""add all missing options with their default values"""
# add meta-parameters, given options have priority
self.check()
for key in CMAOptions.defaults():
if key not in self:
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | CMAOptions.settable | def settable(self):
"""return the subset of those options that are settable at any
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Settable options are in `versatile_options()`, but the
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"""
return CMAOptions([i for i in list(self.items())
if i[0] in CMAO... | python | def settable(self):
"""return the subset of those options that are settable at any
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | CMAOptions.eval | def eval(self, key, default=None, loc=None, correct_key=True):
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environment `loc`. Many options need ``N`` to be defined in
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | CMAOptions.evalall | def evalall(self, loc=None, defaults=None):
"""Evaluates all option values in environment `loc`.
:See: `eval()`
"""
self.check()
if defaults is None:
defaults = cma_default_options
# TODO: this needs rather the parameter N instead of loc
if 'N' in lo... | python | def evalall(self, loc=None, defaults=None):
"""Evaluates all option values in environment `loc`.
:See: `eval()`
"""
self.check()
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defaults = cma_default_options
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | CMAOptions.match | def match(self, s=''):
"""return all options that match, in the name or the description,
with string `s`, case is disregarded.
Example: ``cma.CMAOptions().match('verb')`` returns the verbosity
options.
"""
match = s.lower()
res = {}
for k in sorted(self)... | python | def match(self, s=''):
"""return all options that match, in the name or the description,
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"""
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | CMADataLogger.data | def data(self):
"""return dictionary with data.
If data entries are None or incomplete, consider calling
``.load().data()`` to (re-)load the data from files first.
"""
d = {}
for name in self.key_names:
d[name] = self.__dict__.get(name, None)
return ... | python | def data(self):
"""return dictionary with data.
If data entries are None or incomplete, consider calling
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"""
d = {}
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | CMADataLogger.register | def register(self, es, append=None, modulo=None):
"""register a `CMAEvolutionStrategy` instance for logging,
``append=True`` appends to previous data logged under the same name,
by default previous data are overwritten.
"""
if not isinstance(es, CMAEvolutionStrategy):
... | python | def register(self, es, append=None, modulo=None):
"""register a `CMAEvolutionStrategy` instance for logging,
``append=True`` appends to previous data logged under the same name,
by default previous data are overwritten.
"""
if not isinstance(es, CMAEvolutionStrategy):
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | CMADataLogger.save_to | def save_to(self, nameprefix, switch=False):
"""saves logger data to a different set of files, for
``switch=True`` also the loggers name prefix is switched to
the new value
"""
if not nameprefix or not isinstance(nameprefix, basestring):
raise _Error('filename prefix... | python | def save_to(self, nameprefix, switch=False):
"""saves logger data to a different set of files, for
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if not nameprefix or not isinstance(nameprefix, basestring):
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | CMADataLogger.select_data | def select_data(self, iteration_indices):
"""keep only data of `iteration_indices`"""
dat = self
iteridx = iteration_indices
dat.f = dat.f[np.where([x in iteridx for x in dat.f[:, 0]])[0], :]
dat.D = dat.D[np.where([x in iteridx for x in dat.D[:, 0]])[0], :]
try:
... | python | def select_data(self, iteration_indices):
"""keep only data of `iteration_indices`"""
dat = self
iteridx = iteration_indices
dat.f = dat.f[np.where([x in iteridx for x in dat.f[:, 0]])[0], :]
dat.D = dat.D[np.where([x in iteridx for x in dat.D[:, 0]])[0], :]
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | CMADataLogger.plot_correlations | def plot_correlations(self, iabscissa=1):
"""spectrum of correlation matrix and largest correlation"""
if not hasattr(self, 'corrspec'):
self.load()
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return self
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y = self.corrspec[:, 6:] # principl... | python | def plot_correlations(self, iabscissa=1):
"""spectrum of correlation matrix and largest correlation"""
if not hasattr(self, 'corrspec'):
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return self
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | CMADataLogger._enter_plotting | def _enter_plotting(self, fontsize=9):
"""assumes that a figure is open """
# interactive_status = matplotlib.is_interactive()
self.original_fontsize = pyplot.rcParams['font.size']
pyplot.rcParams['font.size'] = fontsize
pyplot.hold(False) # opens a figure window, if non exists
... | python | def _enter_plotting(self, fontsize=9):
"""assumes that a figure is open """
# interactive_status = matplotlib.is_interactive()
self.original_fontsize = pyplot.rcParams['font.size']
pyplot.rcParams['font.size'] = fontsize
pyplot.hold(False) # opens a figure window, if non exists
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | CMADataLogger.downsampling | def downsampling(self, factor=10, first=3, switch=True, verbose=True):
"""
rude downsampling of a `CMADataLogger` data file by `factor`,
keeping also the first `first` entries. This function is a
stump and subject to future changes. Return self.
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---------
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"""
rude downsampling of a `CMADataLogger` data file by `factor`,
keeping also the first `first` entries. This function is a
stump and subject to future changes. Return self.
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | NoiseHandler.update_measure | def update_measure(self):
"""updated noise level measure using two fitness lists ``self.fit`` and
``self.fitre``, return ``self.noiseS, all_individual_measures``.
Assumes that `self.idx` contains the indices where the fitness
lists differ
"""
lam = len(self.fit)
... | python | def update_measure(self):
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lam = len(self.fit)
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | NoiseHandler.indices | def indices(self, fit):
"""return the set of indices to be reevaluated for noise
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Given the first values are the earliest, this is a useful policy also
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## meta_parameters.noise_reeval_multiplier == 1.0
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | Sections.plot | def plot(self, plot_cmd=None, tf=lambda y: y):
"""plot the data we have, return ``self``"""
if not plot_cmd:
plot_cmd = self.plot_cmd
colors = 'bgrcmyk'
pyplot.hold(False)
res = self.res
flatx, flatf = self.flattened()
minf = np.inf
for i in f... | python | def plot(self, plot_cmd=None, tf=lambda y: y):
"""plot the data we have, return ``self``"""
if not plot_cmd:
plot_cmd = self.plot_cmd
colors = 'bgrcmyk'
pyplot.hold(False)
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | Sections.save | def save(self, name=None):
"""save to file"""
import pickle
name = name if name else self.name
fun = self.func
del self.func # instance method produces error
pickle.dump(self, open(name + '.pkl', "wb"))
self.func = fun
return self | python | def save(self, name=None):
"""save to file"""
import pickle
name = name if name else self.name
fun = self.func
del self.func # instance method produces error
pickle.dump(self, open(name + '.pkl', "wb"))
self.func = fun
return self | [
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | Sections.load | def load(self, name=None):
"""load from file"""
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name = name if name else self.name
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | Misc.loglikelihood | def loglikelihood(self, x, previous=False):
"""return log-likelihood of `x` regarding the current sample distribution"""
# testing of original fct: MC integrate must be one: mean(p(x_i)) * volume(where x_i are uniformely sampled)
# for i in xrange(3): print mean([cma.likelihood(20*r-10, dim * [0... | python | def loglikelihood(self, x, previous=False):
"""return log-likelihood of `x` regarding the current sample distribution"""
# testing of original fct: MC integrate must be one: mean(p(x_i)) * volume(where x_i are uniformely sampled)
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | FitnessFunctions.noisysphere | def noisysphere(self, x, noise=2.10e-9, cond=1.0, noise_offset=0.10):
"""noise=10 does not work with default popsize, noise handling does not help """
return self.elli(x, cond=cond) * (1 + noise * np.random.randn() / len(x)) + noise_offset * np.random.rand() | python | def noisysphere(self, x, noise=2.10e-9, cond=1.0, noise_offset=0.10):
"""noise=10 does not work with default popsize, noise handling does not help """
return self.elli(x, cond=cond) * (1 + noise * np.random.randn() / len(x)) + noise_offset * np.random.rand() | [
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | FitnessFunctions.cigar | def cigar(self, x, rot=0, cond=1e6, noise=0):
"""Cigar test objective function"""
if rot:
x = rotate(x)
x = [x] if isscalar(x[0]) else x # scalar into list
f = [(x[0]**2 + cond * sum(x[1:]**2)) * np.exp(noise * np.random.randn(1)[0] / len(x)) for x in x]
return f if ... | python | def cigar(self, x, rot=0, cond=1e6, noise=0):
"""Cigar test objective function"""
if rot:
x = rotate(x)
x = [x] if isscalar(x[0]) else x # scalar into list
f = [(x[0]**2 + cond * sum(x[1:]**2)) * np.exp(noise * np.random.randn(1)[0] / len(x)) for x in x]
return f if ... | [
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | FitnessFunctions.tablet | def tablet(self, x, rot=0):
"""Tablet test objective function"""
if rot and rot is not fcts.tablet:
x = rotate(x)
x = [x] if isscalar(x[0]) else x # scalar into list
f = [1e6 * x[0]**2 + sum(x[1:]**2) for x in x]
return f if len(f) > 1 else f[0] # 1-element-list int... | python | def tablet(self, x, rot=0):
"""Tablet test objective function"""
if rot and rot is not fcts.tablet:
x = rotate(x)
x = [x] if isscalar(x[0]) else x # scalar into list
f = [1e6 * x[0]**2 + sum(x[1:]**2) for x in x]
return f if len(f) > 1 else f[0] # 1-element-list int... | [
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | FitnessFunctions.elli | def elli(self, x, rot=0, xoffset=0, cond=1e6, actuator_noise=0.0, both=False):
"""Ellipsoid test objective function"""
if not isscalar(x[0]): # parallel evaluation
return [self.elli(xi, rot) for xi in x] # could save 20% overall
if rot:
x = rotate(x)
N = len(x)
... | python | def elli(self, x, rot=0, xoffset=0, cond=1e6, actuator_noise=0.0, both=False):
"""Ellipsoid test objective function"""
if not isscalar(x[0]): # parallel evaluation
return [self.elli(xi, rot) for xi in x] # could save 20% overall
if rot:
x = rotate(x)
N = len(x)
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | FitnessFunctions.elliconstraint | def elliconstraint(self, x, cfac=1e8, tough=True, cond=1e6):
"""ellipsoid test objective function with "constraints" """
N = len(x)
f = sum(cond**(np.arange(N)[-1::-1] / (N - 1)) * x**2)
cvals = (x[0] + 1,
x[0] + 1 + 100 * x[1],
x[0] + 1 - 100 * x[1])
... | python | def elliconstraint(self, x, cfac=1e8, tough=True, cond=1e6):
"""ellipsoid test objective function with "constraints" """
N = len(x)
f = sum(cond**(np.arange(N)[-1::-1] / (N - 1)) * x**2)
cvals = (x[0] + 1,
x[0] + 1 + 100 * x[1],
x[0] + 1 - 100 * x[1])
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | FitnessFunctions.rosen | def rosen(self, x, alpha=1e2):
"""Rosenbrock test objective function"""
x = [x] if isscalar(x[0]) else x # scalar into list
f = [sum(alpha * (x[:-1]**2 - x[1:])**2 + (1. - x[:-1])**2) for x in x]
return f if len(f) > 1 else f[0] # 1-element-list into scalar | python | def rosen(self, x, alpha=1e2):
"""Rosenbrock test objective function"""
x = [x] if isscalar(x[0]) else x # scalar into list
f = [sum(alpha * (x[:-1]**2 - x[1:])**2 + (1. - x[:-1])**2) for x in x]
return f if len(f) > 1 else f[0] # 1-element-list into scalar | [
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | FitnessFunctions.diffpow | def diffpow(self, x, rot=0):
"""Diffpow test objective function"""
N = len(x)
if rot:
x = rotate(x)
return sum(np.abs(x)**(2. + 4.*np.arange(N) / (N - 1.)))**0.5 | python | def diffpow(self, x, rot=0):
"""Diffpow test objective function"""
N = len(x)
if rot:
x = rotate(x)
return sum(np.abs(x)**(2. + 4.*np.arange(N) / (N - 1.)))**0.5 | [
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | FitnessFunctions.ridgecircle | def ridgecircle(self, x, expo=0.5):
"""happy cat by HG Beyer"""
a = len(x)
s = sum(x**2)
return ((s - a)**2)**(expo / 2) + s / a + sum(x) / a | python | def ridgecircle(self, x, expo=0.5):
"""happy cat by HG Beyer"""
a = len(x)
s = sum(x**2)
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | FitnessFunctions.rastrigin | def rastrigin(self, x):
"""Rastrigin test objective function"""
if not isscalar(x[0]):
N = len(x[0])
return [10 * N + sum(xi**2 - 10 * np.cos(2 * np.pi * xi)) for xi in x]
# return 10*N + sum(x**2 - 10*np.cos(2*np.pi*x), axis=1)
N = len(x)
return 10 * ... | python | def rastrigin(self, x):
"""Rastrigin test objective function"""
if not isscalar(x[0]):
N = len(x[0])
return [10 * N + sum(xi**2 - 10 * np.cos(2 * np.pi * xi)) for xi in x]
# return 10*N + sum(x**2 - 10*np.cos(2*np.pi*x), axis=1)
N = len(x)
return 10 * ... | [
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | FitnessFunctions.schwefelmult | def schwefelmult(self, x, pen_fac=1e4):
"""multimodal Schwefel function with domain -500..500"""
y = [x] if isscalar(x[0]) else x
N = len(y[0])
f = array([418.9829 * N - 1.27275661e-5 * N - sum(x * np.sin(np.abs(x)**0.5))
+ pen_fac * sum((abs(x) > 500) * (abs(x) - 500)**2... | python | def schwefelmult(self, x, pen_fac=1e4):
"""multimodal Schwefel function with domain -500..500"""
y = [x] if isscalar(x[0]) else x
N = len(y[0])
f = array([418.9829 * N - 1.27275661e-5 * N - sum(x * np.sin(np.abs(x)**0.5))
+ pen_fac * sum((abs(x) > 500) * (abs(x) - 500)**2... | [
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | FitnessFunctions.lincon | def lincon(self, x, theta=0.01):
"""ridge like linear function with one linear constraint"""
if x[0] < 0:
return np.NaN
return theta * x[1] + x[0] | python | def lincon(self, x, theta=0.01):
"""ridge like linear function with one linear constraint"""
if x[0] < 0:
return np.NaN
return theta * x[1] + x[0] | [
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | FitnessFunctions.rosen_nesterov | def rosen_nesterov(self, x, rho=100):
"""needs exponential number of steps in a non-increasing f-sequence.
x_0 = (-1,1,...,1)
See Jarre (2011) "On Nesterov's Smooth Chebyshev-Rosenbrock Function"
"""
f = 0.25 * (x[0] - 1)**2
f += rho * sum((x[1:] - 2 * x[:-1]**2 + 1)**2... | python | def rosen_nesterov(self, x, rho=100):
"""needs exponential number of steps in a non-increasing f-sequence.
x_0 = (-1,1,...,1)
See Jarre (2011) "On Nesterov's Smooth Chebyshev-Rosenbrock Function"
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f = 0.25 * (x[0] - 1)**2
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flowersteam/explauto | explauto/sensorimotor_model/inverse/cma.py | FitnessFunctions.bukin | def bukin(self, x):
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http://en.wikipedia.org/wiki/Test_functions_for_optimization"""
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flowersteam/explauto | explauto/models/pydmps/dmp.py | DMPs.reset_state | def reset_state(self):
"""Reset the system state"""
self.y = self.y0.copy()
self.dy = np.zeros(self.dmps)
self.ddy = np.zeros(self.dmps)
self.cs.reset_state() | python | def reset_state(self):
"""Reset the system state"""
self.y = self.y0.copy()
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self.ddy = np.zeros(self.dmps)
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flowersteam/explauto | explauto/models/pydmps/dmp.py | DMPs.step | def step(self, tau=1.0, state_fb=None):
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tau float: scales the timestep
increase tau to make the system execute faster
state_fb np.array: optional system feedback
"""
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tau float: scales the timestep
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flowersteam/explauto | explauto/environment/npendulum/simulation.py | step | def step(weights, duration):
""" This function creates a sum of boxcar functions.
:param numpy.array weight: height of each boxcar function.
:param float duration: duration of the generated trajectory.
"""
dt = duration / len(weights)
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""" This function creates a sum of boxcar functions.
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flowersteam/explauto | explauto/environment/npendulum/simulation.py | cartesian | def cartesian(n, states):
""" This function computes cartesians coordinates from the states returned by the simulate function.
:param int n: number of particules suspended to the top one
:param numpy.array states: list of the positions and speeds at a certain time.
"""
length = 1. / n # arm_length... | python | def cartesian(n, states):
""" This function computes cartesians coordinates from the states returned by the simulate function.
:param int n: number of particules suspended to the top one
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aamalev/aiohttp_apiset | aiohttp_apiset/swagger/route.py | SwaggerRoute.build_swagger_data | def build_swagger_data(self, loader):
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:param swagger_schema: loaded schema
"""
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self.is_built = True
self._required = []
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aamalev/aiohttp_apiset | aiohttp_apiset/swagger/route.py | SwaggerRoute.validate | async def validate(self, request: web.Request):
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:param request: Request
:return: tuple of parameters and errors
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parameters = {}
files = {}
errors = self.errors_factory()
body = None
... | python | async def validate(self, request: web.Request):
""" Returns parameters extract from request and multidict errors
:param request: Request
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parameters = {}
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aamalev/aiohttp_apiset | aiohttp_apiset/swagger/router.py | SwaggerRouter.include | def include(self, spec, *,
basePath=None,
operationId_mapping=None,
name=None):
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:param spec: path to specification
:param basePath: override base path specify in specification
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basePath=None,
operationId_mapping=None,
name=None):
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aamalev/aiohttp_apiset | aiohttp_apiset/swagger/router.py | SwaggerRouter.setup | def setup(self, app: web.Application):
""" Installation routes to app.router
:param app: instance of aiohttp.web.Application
"""
if self.app is app:
raise ValueError('The router is already configured '
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self.app = a... | python | def setup(self, app: web.Application):
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aamalev/aiohttp_apiset | aiohttp_apiset/jinja2.py | template | def template(template_name, *, app_key=APP_KEY, encoding='utf-8', status=200):
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Decorator compatible with aiohttp_apiset router
"""
def wrapper(func):
@functools.wraps(func)
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"""
Decorator compatible with aiohttp_apiset router
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aamalev/aiohttp_apiset | aiohttp_apiset/swagger/validate.py | get_collection | def get_collection(source, name, collection_format, default):
"""get collection named `name` from the given `source` that
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"""
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separator = COLLECTION_SEP[collection_format]
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aamalev/aiohttp_apiset | aiohttp_apiset/compat.py | CompatRouter.add_get | def add_get(self, *args, **kwargs):
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Shortcut for add_route with method GET
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Shortcut for add_route with method GET
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aamalev/aiohttp_apiset | aiohttp_apiset/swagger/operations.py | OperationIdMapping.add | def add(self, *args, **kwargs):
""" Add new mapping from args and kwargs
>>> om = OperationIdMapping()
>>> om.add(
... OperationIdMapping(),
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""" Add new mapping from args and kwargs
>>> om = OperationIdMapping()
>>> om.add(
... OperationIdMapping(),
... 'aiohttp_apiset.swagger.operations', # any module
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mila/pyoo | pyoo.py | str_repr | def str_repr(klass):
"""
Implements string conversion methods for the given class.
The given class must implement the __str__ method. This decorat
will add __repr__ and __unicode__ (for Python 2).
"""
if PY2:
klass.__unicode__ = klass.__str__
klass.__str__ = lambda self: self._... | python | def str_repr(klass):
"""
Implements string conversion methods for the given class.
The given class must implement the __str__ method. This decorat
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"""
if PY2:
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mila/pyoo | pyoo.py | _clean_slice | def _clean_slice(key, length):
"""
Validates and normalizes a cell range slice.
>>> _clean_slice(slice(None, None), 10)
(0, 10)
>>> _clean_slice(slice(-10, 10), 10)
(0, 10)
>>> _clean_slice(slice(-11, 11), 10)
(0, 10)
>>> _clean_slice(slice('x', 'y'), 10)
Traceback (most recent ... | python | def _clean_slice(key, length):
"""
Validates and normalizes a cell range slice.
>>> _clean_slice(slice(None, None), 10)
(0, 10)
>>> _clean_slice(slice(-10, 10), 10)
(0, 10)
>>> _clean_slice(slice(-11, 11), 10)
(0, 10)
>>> _clean_slice(slice('x', 'y'), 10)
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mila/pyoo | pyoo.py | _clean_index | def _clean_index(key, length):
"""
Validates and normalizes a cell range index.
>>> _clean_index(0, 10)
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>>> _clean_index(-10, 10)
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>>> _clean_index(10, 10)
Traceback (most recent call last):
...
IndexError: Cell index out of range.
>>> _clean_index(-11, 10)
Traceback ... | python | def _clean_index(key, length):
"""
Validates and normalizes a cell range index.
>>> _clean_index(0, 10)
0
>>> _clean_index(-10, 10)
0
>>> _clean_index(10, 10)
Traceback (most recent call last):
...
IndexError: Cell index out of range.
>>> _clean_index(-11, 10)
Traceback ... | [
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mila/pyoo | pyoo.py | _col_name | def _col_name(index):
"""
Converts a column index to a column name.
>>> _col_name(0)
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>>> _col_name(26)
'AA'
"""
for exp in itertools.count(1):
limit = 26 ** exp
if index < limit:
return ''.join(chr(ord('A') + index // (26 ** i) % 26) for i in range(exp-1... | python | def _col_name(index):
"""
Converts a column index to a column name.
>>> _col_name(0)
'A'
>>> _col_name(26)
'AA'
"""
for exp in itertools.count(1):
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mila/pyoo | pyoo.py | Axis.__set_title | def __set_title(self, value):
"""
Sets title of this axis.
"""
# OpenOffice on Debian "squeeze" ignore value of target.XAxis.String
# unless target.HasXAxisTitle is set to True first. (Despite the
# fact that target.HasXAxisTitle is reported to be False until
# ta... | python | def __set_title(self, value):
"""
Sets title of this axis.
"""
# OpenOffice on Debian "squeeze" ignore value of target.XAxis.String
# unless target.HasXAxisTitle is set to True first. (Despite the
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mila/pyoo | pyoo.py | Chart.ranges | def ranges(self):
"""
Returns a list of addresses with source data.
"""
ranges = self._target.getRanges()
return map(SheetAddress._from_uno, ranges) | python | def ranges(self):
"""
Returns a list of addresses with source data.
"""
ranges = self._target.getRanges()
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mila/pyoo | pyoo.py | Chart.diagram | def diagram(self):
"""
Diagram - inner content of this chart.
The diagram can be replaced by another type using change_type method.
"""
target = self._embedded.getDiagram()
target_type = target.getDiagramType()
cls = _DIAGRAM_TYPES.get(target_type, Diagram)
... | python | def diagram(self):
"""
Diagram - inner content of this chart.
The diagram can be replaced by another type using change_type method.
"""
target = self._embedded.getDiagram()
target_type = target.getDiagramType()
cls = _DIAGRAM_TYPES.get(target_type, Diagram)
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mila/pyoo | pyoo.py | Chart.change_type | def change_type(self, cls):
"""
Change type of diagram in this chart.
Accepts one of classes which extend Diagram.
"""
target_type = cls._type
target = self._embedded.createInstance(target_type)
self._embedded.setDiagram(target)
return cls(target) | python | def change_type(self, cls):
"""
Change type of diagram in this chart.
Accepts one of classes which extend Diagram.
"""
target_type = cls._type
target = self._embedded.createInstance(target_type)
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mila/pyoo | pyoo.py | ChartCollection.create | def create(self, name, position, ranges=(), col_header=False, row_header=False):
"""
Creates and inserts a new chart.
"""
rect = self._uno_rect(position)
ranges = self._uno_ranges(ranges)
self._create(name, rect, ranges, col_header, row_header)
return self[name] | python | def create(self, name, position, ranges=(), col_header=False, row_header=False):
"""
Creates and inserts a new chart.
"""
rect = self._uno_rect(position)
ranges = self._uno_ranges(ranges)
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mila/pyoo | pyoo.py | SheetCursor.get_target | def get_target(self, row, col, row_count, col_count):
"""
Moves cursor to the specified position and returns in.
"""
# This method is called for almost any operation so it should
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#
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"""
Moves cursor to the specified position and returns in.
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# This method is called for almost any operation so it should
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mila/pyoo | pyoo.py | Cell.__set_value | def __set_value(self, value):
"""
Sets cell value to a string or number based on the given value.
"""
array = ((self._clean_value(value),),)
return self._get_target().setDataArray(array) | python | def __set_value(self, value):
"""
Sets cell value to a string or number based on the given value.
"""
array = ((self._clean_value(value),),)
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mila/pyoo | pyoo.py | Cell.__set_formula | def __set_formula(self, formula):
"""
Sets a formula in this cell.
Any cell value can be set using this method. Actual formulas must
start with an equal sign.
"""
array = ((self._clean_formula(formula),),)
return self._get_target().setFormulaArray(array) | python | def __set_formula(self, formula):
"""
Sets a formula in this cell.
Any cell value can be set using this method. Actual formulas must
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"""
array = ((self._clean_formula(formula),),)
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mila/pyoo | pyoo.py | TabularCellRange.__set_values | def __set_values(self, values):
"""
Sets values in this cell range from an iterable of iterables.
"""
# Tuple of tuples is required
array = tuple(tuple(self._clean_value(col) for col in row) for row in values)
self._get_target().setDataArray(array) | python | def __set_values(self, values):
"""
Sets values in this cell range from an iterable of iterables.
"""
# Tuple of tuples is required
array = tuple(tuple(self._clean_value(col) for col in row) for row in values)
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mila/pyoo | pyoo.py | TabularCellRange.__set_formulas | def __set_formulas(self, formulas):
"""
Sets formulas in this cell range from an iterable of iterables.
Any cell values can be set using this method. Actual formulas must
start with an equal sign.
"""
# Tuple of tuples is required
array = tuple(tuple(self._clean_... | python | def __set_formulas(self, formulas):
"""
Sets formulas in this cell range from an iterable of iterables.
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"""
# Tuple of tuples is required
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mila/pyoo | pyoo.py | VerticalCellRange.__get_values | def __get_values(self):
"""
Gets values in this cell range as a tuple.
This is much more effective than reading cell values one by one.
"""
array = self._get_target().getDataArray()
return tuple(itertools.chain.from_iterable(array)) | python | def __get_values(self):
"""
Gets values in this cell range as a tuple.
This is much more effective than reading cell values one by one.
"""
array = self._get_target().getDataArray()
return tuple(itertools.chain.from_iterable(array)) | [
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mila/pyoo | pyoo.py | VerticalCellRange.__set_values | def __set_values(self, values):
"""
Sets values in this cell range from an iterable.
This is much more effective than writing cell values one by one.
"""
array = tuple((self._clean_value(v),) for v in values)
self._get_target().setDataArray(array) | python | def __set_values(self, values):
"""
Sets values in this cell range from an iterable.
This is much more effective than writing cell values one by one.
"""
array = tuple((self._clean_value(v),) for v in values)
self._get_target().setDataArray(array) | [
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mila/pyoo | pyoo.py | VerticalCellRange.__get_formulas | def __get_formulas(self):
"""
Gets formulas in this cell range as a tuple.
If cells contain actual formulas then the returned values start
with an equal sign but all values are returned.
"""
array = self._get_target().getFormulaArray()
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"""
Gets formulas in this cell range as a tuple.
If cells contain actual formulas then the returned values start
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mila/pyoo | pyoo.py | VerticalCellRange.__set_formulas | def __set_formulas(self, formulas):
"""
Sets formulas in this cell range from an iterable.
Any cell values can be set using this method. Actual formulas must
start with an equal sign.
"""
array = tuple((self._clean_formula(v),) for v in formulas)
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"""
Sets formulas in this cell range from an iterable.
Any cell values can be set using this method. Actual formulas must
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"""
array = tuple((self._clean_formula(v),) for v in formulas)
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mila/pyoo | pyoo.py | SpreadsheetCollection.create | def create(self, name, index=None):
"""
Creates a new sheet with the given name.
If an optional index argument is not provided then the created
sheet is appended at the end. Returns the new sheet.
"""
if index is None:
index = len(self)
self._create(n... | python | def create(self, name, index=None):
"""
Creates a new sheet with the given name.
If an optional index argument is not provided then the created
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"""
if index is None:
index = len(self)
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mila/pyoo | pyoo.py | SpreadsheetCollection.copy | def copy(self, old_name, new_name, index=None):
"""
Copies an old sheet with the old_name to a new sheet with new_name.
If an optional index argument is not provided then the created
sheet is appended at the end. Returns the new sheet.
"""
if index is None:
i... | python | def copy(self, old_name, new_name, index=None):
"""
Copies an old sheet with the old_name to a new sheet with new_name.
If an optional index argument is not provided then the created
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mila/pyoo | pyoo.py | SpreadsheetDocument.save | def save(self, path=None, filter_name=None):
"""
Saves this document to a local file system.
The optional first argument defaults to the document's path.
Accept optional second argument which defines type of
the saved file. Use one of FILTER_* constants or see list of
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"""
Saves this document to a local file system.
The optional first argument defaults to the document's path.
Accept optional second argument which defines type of
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mila/pyoo | pyoo.py | SpreadsheetDocument.get_locale | def get_locale(self, language=None, country=None, variant=None):
"""
Returns locale which can be used for access to number formats.
"""
# http://www.openoffice.org/api/docs/common/ref/com/sun/star/lang/Locale.html
locale = uno.createUnoStruct('com.sun.star.lang.Locale')
i... | python | def get_locale(self, language=None, country=None, variant=None):
"""
Returns locale which can be used for access to number formats.
"""
# http://www.openoffice.org/api/docs/common/ref/com/sun/star/lang/Locale.html
locale = uno.createUnoStruct('com.sun.star.lang.Locale')
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mila/pyoo | pyoo.py | SpreadsheetDocument.sheets | def sheets(self):
"""
Collection of sheets in this document.
"""
# http://www.openoffice.org/api/docs/common/ref/com/sun/star/sheet/XSpreadsheetDocument.html#getSheets
try:
return self._sheets
except AttributeError:
target = self._target.getSheets(... | python | def sheets(self):
"""
Collection of sheets in this document.
"""
# http://www.openoffice.org/api/docs/common/ref/com/sun/star/sheet/XSpreadsheetDocument.html#getSheets
try:
return self._sheets
except AttributeError:
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mila/pyoo | pyoo.py | SpreadsheetDocument.date_from_number | def date_from_number(self, value):
"""
Converts a float value to corresponding datetime instance.
"""
if not isinstance(value, numbers.Real):
return None
delta = datetime.timedelta(days=value)
return self._null_date + delta | python | def date_from_number(self, value):
"""
Converts a float value to corresponding datetime instance.
"""
if not isinstance(value, numbers.Real):
return None
delta = datetime.timedelta(days=value)
return self._null_date + delta | [
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mila/pyoo | pyoo.py | SpreadsheetDocument.date_to_number | def date_to_number(self, date):
"""
Converts a date or datetime instance to a corresponding float value.
"""
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"""
Converts a date or datetime instance to a corresponding float value.
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mila/pyoo | pyoo.py | SpreadsheetDocument.time_from_number | def time_from_number(self, value):
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Converts a float value to corresponding time instance.
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minutes, second = divmod(delta.seconds, 60)
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Converts a float value to corresponding time instance.
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mila/pyoo | pyoo.py | SpreadsheetDocument.time_to_number | def time_to_number(self, time):
"""
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"""
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raise TypeError(time)
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mila/pyoo | pyoo.py | SpreadsheetDocument._null_date | def _null_date(self):
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mila/pyoo | pyoo.py | LazyDesktop.create_spreadsheet | def create_spreadsheet(self):
"""
Creates a new spreadsheet document.
"""
desktop = self.cls(self.hostname, self.port, self.pipe)
return desktop.create_spreadsheet() | python | def create_spreadsheet(self):
"""
Creates a new spreadsheet document.
"""
desktop = self.cls(self.hostname, self.port, self.pipe)
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mbakker7/timml | timml/util.py | PlotTim.vcontoursf1D | def vcontoursf1D(self, x1, x2, nx, levels, labels=False, decimals=0, color=None,
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"""
Vertical contour for 1D model
"""
naq = self.aq.naq
xflow = np.linspace(x1 + nudge, x2 - nudge, nx)
Qx ... | python | def vcontoursf1D(self, x1, x2, nx, levels, labels=False, decimals=0, color=None,
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Vertical contour for 1D model
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naq = self.aq.naq
xflow = np.linspace(x1 + nudge, x2 - nudge, nx)
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mbakker7/timml | timml/linesink1d.py | LineSink1DBase.discharge | def discharge(self):
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Q = np.zeros(self.aq.naq)
Q[self.layers] = self.parameters[:, 0]
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"""Discharge per unit length"""
Q = np.zeros(self.aq.naq)
Q[self.layers] = self.parameters[:, 0]
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mbakker7/timml | timml/linesink.py | LineSinkStringBase2.discharge | def discharge(self):
"""Discharge of the element in each layer
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rv = np.zeros(self.aq[0].naq)
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Qls.shape = (self.nls, self.nlayers, self.order + 1)
Qls = np.sum(Qls, 2)
for i, q in enumerate(Qls):
... | python | def discharge(self):
"""Discharge of the element in each layer
"""
rv = np.zeros(self.aq[0].naq)
Qls = self.parameters[:, 0] * self.dischargeinf()
Qls.shape = (self.nls, self.nlayers, self.order + 1)
Qls = np.sum(Qls, 2)
for i, q in enumerate(Qls):
... | [
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mbakker7/timml | timml/aquifer.py | AquiferData.findlayer | def findlayer(self, z):
'''
Returns layer-number, layer-type and model-layer-number'''
if z > self.z[0]:
modellayer, ltype = -1, 'above'
layernumber = None
elif z < self.z[-1]:
modellayer, ltype = len(self.layernumber), 'below'
layernumber ... | python | def findlayer(self, z):
'''
Returns layer-number, layer-type and model-layer-number'''
if z > self.z[0]:
modellayer, ltype = -1, 'above'
layernumber = None
elif z < self.z[-1]:
modellayer, ltype = len(self.layernumber), 'below'
layernumber ... | [
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mbakker7/timml | timml/model.py | Model.remove_element | def remove_element(self, e):
"""Remove element `e` from model
"""
if e.label is not None: self.elementdict.pop(e.label)
self.elementlist.remove(e) | python | def remove_element(self, e):
"""Remove element `e` from model
"""
if e.label is not None: self.elementdict.pop(e.label)
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limix/pandas-plink | pandas_plink/_read.py | read_plink | def read_plink(file_prefix, verbose=True):
r"""Read PLINK files into Pandas data frames.
Parameters
----------
file_prefix : str
Path prefix to the set of PLINK files. It supports loading many BED
files at once using globstrings wildcard.
verbose : bool
``True`` for progress... | python | def read_plink(file_prefix, verbose=True):
r"""Read PLINK files into Pandas data frames.
Parameters
----------
file_prefix : str
Path prefix to the set of PLINK files. It supports loading many BED
files at once using globstrings wildcard.
verbose : bool
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Path prefix to the set of PLINK files. It supports loading many BED
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moremoban/moban | setup.py | read_files | def read_files(*files):
"""Read files into setup"""
text = ""
for single_file in files:
content = read(single_file)
text = text + content + "\n"
return text | python | def read_files(*files):
"""Read files into setup"""
text = ""
for single_file in files:
content = read(single_file)
text = text + content + "\n"
return text | [
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moremoban/moban | setup.py | read | def read(afile):
"""Read a file into setup"""
the_relative_file = os.path.join(HERE, afile)
with codecs.open(the_relative_file, 'r', 'utf-8') as opened_file:
content = filter_out_test_code(opened_file)
content = "".join(list(content))
return content | python | def read(afile):
"""Read a file into setup"""
the_relative_file = os.path.join(HERE, afile)
with codecs.open(the_relative_file, 'r', 'utf-8') as opened_file:
content = filter_out_test_code(opened_file)
content = "".join(list(content))
return content | [
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moremoban/moban | moban/main.py | main | def main():
"""
program entry point
"""
parser = create_parser()
options = vars(parser.parse_args())
HASH_STORE.IGNORE_CACHE_FILE = options[constants.LABEL_FORCE]
moban_file = options[constants.LABEL_MOBANFILE]
load_engine_factory_and_engines() # Error: jinja2 if removed
if moban_fi... | python | def main():
"""
program entry point
"""
parser = create_parser()
options = vars(parser.parse_args())
HASH_STORE.IGNORE_CACHE_FILE = options[constants.LABEL_FORCE]
moban_file = options[constants.LABEL_MOBANFILE]
load_engine_factory_and_engines() # Error: jinja2 if removed
if moban_fi... | [
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moremoban/moban | moban/main.py | create_parser | def create_parser():
"""
construct the program options
"""
parser = argparse.ArgumentParser(
prog=constants.PROGRAM_NAME, description=constants.PROGRAM_DESCRIPTION
)
parser.add_argument(
"-cd",
"--%s" % constants.LABEL_CONFIG_DIR,
help="the directory for configura... | python | def create_parser():
"""
construct the program options
"""
parser = argparse.ArgumentParser(
prog=constants.PROGRAM_NAME, description=constants.PROGRAM_DESCRIPTION
)
parser.add_argument(
"-cd",
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moremoban/moban | moban/main.py | handle_moban_file | def handle_moban_file(moban_file, options):
"""
act upon default moban file
"""
moban_file_configurations = load_data(None, moban_file)
if moban_file_configurations is None:
raise exceptions.MobanfileGrammarException(
constants.ERROR_INVALID_MOBAN_FILE % moban_file
)
... | python | def handle_moban_file(moban_file, options):
"""
act upon default moban file
"""
moban_file_configurations = load_data(None, moban_file)
if moban_file_configurations is None:
raise exceptions.MobanfileGrammarException(
constants.ERROR_INVALID_MOBAN_FILE % moban_file
)
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moremoban/moban | moban/main.py | handle_command_line | def handle_command_line(options):
"""
act upon command options
"""
options = merge(options, constants.DEFAULT_OPTIONS)
engine = plugins.ENGINES.get_engine(
options[constants.LABEL_TEMPLATE_TYPE],
options[constants.LABEL_TMPL_DIRS],
options[constants.LABEL_CONFIG_DIR],
)
... | python | def handle_command_line(options):
"""
act upon command options
"""
options = merge(options, constants.DEFAULT_OPTIONS)
engine = plugins.ENGINES.get_engine(
options[constants.LABEL_TEMPLATE_TYPE],
options[constants.LABEL_TMPL_DIRS],
options[constants.LABEL_CONFIG_DIR],
)
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tammoippen/iso4217parse | iso4217parse/__init__.py | by_symbol | def by_symbol(symbol, country_code=None):
"""Get list of possible currencies for symbol; filter by country_code
Look for all currencies that use the `symbol`. If there are currencies used
in the country of `country_code`, return only those; otherwise return all
found currencies.
Parameters:
... | python | def by_symbol(symbol, country_code=None):
"""Get list of possible currencies for symbol; filter by country_code
Look for all currencies that use the `symbol`. If there are currencies used
in the country of `country_code`, return only those; otherwise return all
found currencies.
Parameters:
... | [
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