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7,600 | mmp2/megaman | megaman/datasets/datasets.py | generate_megaman_data | def generate_megaman_data(sampling=2):
"""Generate 2D point data of the megaman image"""
data = get_megaman_image()
x = np.arange(sampling * data.shape[1]) / float(sampling)
y = np.arange(sampling * data.shape[0]) / float(sampling)
X, Y = map(np.ravel, np.meshgrid(x, y))
C = data[np.floor(Y.max(... | python | def generate_megaman_data(sampling=2):
"""Generate 2D point data of the megaman image"""
data = get_megaman_image()
x = np.arange(sampling * data.shape[1]) / float(sampling)
y = np.arange(sampling * data.shape[0]) / float(sampling)
X, Y = map(np.ravel, np.meshgrid(x, y))
C = data[np.floor(Y.max(... | [
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7,601 | mmp2/megaman | megaman/datasets/datasets.py | _make_S_curve | def _make_S_curve(x, range=(-0.75, 0.75)):
"""Make a 2D S-curve from a 1D vector"""
assert x.ndim == 1
x = x - x.min()
theta = 2 * np.pi * (range[0] + (range[1] - range[0]) * x / x.max())
X = np.empty((x.shape[0], 2), dtype=float)
X[:, 0] = np.sign(theta) * (1 - np.cos(theta))
X[:, 1] = np.s... | python | def _make_S_curve(x, range=(-0.75, 0.75)):
"""Make a 2D S-curve from a 1D vector"""
assert x.ndim == 1
x = x - x.min()
theta = 2 * np.pi * (range[0] + (range[1] - range[0]) * x / x.max())
X = np.empty((x.shape[0], 2), dtype=float)
X[:, 0] = np.sign(theta) * (1 - np.cos(theta))
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7,602 | mmp2/megaman | megaman/datasets/datasets.py | generate_megaman_manifold | def generate_megaman_manifold(sampling=2, nfolds=2,
rotate=True, random_state=None):
"""Generate a manifold of the megaman data"""
X, c = generate_megaman_data(sampling)
for i in range(nfolds):
X = np.hstack([_make_S_curve(x) for x in X.T])
if rotate:
rand ... | python | def generate_megaman_manifold(sampling=2, nfolds=2,
rotate=True, random_state=None):
"""Generate a manifold of the megaman data"""
X, c = generate_megaman_data(sampling)
for i in range(nfolds):
X = np.hstack([_make_S_curve(x) for x in X.T])
if rotate:
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7,603 | presslabs/z3 | z3/ssh_sync.py | snapshots_to_send | def snapshots_to_send(source_snaps, dest_snaps):
"""return pair of snapshots"""
if len(source_snaps) == 0:
raise AssertionError("No snapshots exist locally!")
if len(dest_snaps) == 0:
# nothing on the remote side, send everything
return None, source_snaps[-1]
last_remote = dest_s... | python | def snapshots_to_send(source_snaps, dest_snaps):
"""return pair of snapshots"""
if len(source_snaps) == 0:
raise AssertionError("No snapshots exist locally!")
if len(dest_snaps) == 0:
# nothing on the remote side, send everything
return None, source_snaps[-1]
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7,604 | presslabs/z3 | z3/pput.py | StreamHandler.get_chunk | def get_chunk(self):
"""Return complete chunks or None if EOF reached"""
while not self._eof_reached:
read = self.input_stream.read(self.chunk_size - len(self._partial_chunk))
if len(read) == 0:
self._eof_reached = True
self._partial_chunk += read
... | python | def get_chunk(self):
"""Return complete chunks or None if EOF reached"""
while not self._eof_reached:
read = self.input_stream.read(self.chunk_size - len(self._partial_chunk))
if len(read) == 0:
self._eof_reached = True
self._partial_chunk += read
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7,605 | presslabs/z3 | z3/pput.py | UploadSupervisor._handle_result | def _handle_result(self):
"""Process one result. Block untill one is available
"""
result = self.inbox.get()
if result.success:
if self._verbosity >= VERB_PROGRESS:
sys.stderr.write("\nuploaded chunk {} \n".format(result.index))
self.results.append... | python | def _handle_result(self):
"""Process one result. Block untill one is available
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result = self.inbox.get()
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sys.stderr.write("\nuploaded chunk {} \n".format(result.index))
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7,606 | presslabs/z3 | z3/pput.py | UploadSupervisor._send_chunk | def _send_chunk(self, index, chunk):
"""Send the current chunk to the workers for processing.
Called when the _partial_chunk is complete.
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"""
self._pending_chunks += 1
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7,607 | presslabs/z3 | z3/config.py | OnionDict._get | def _get(self, key, section=None, default=_onion_dict_guard):
"""Try to get the key from each dict in turn.
If you specify the optional section it looks there first.
"""
if section is not None:
section_dict = self.__sections.get(section, {})
if key in section_dict... | python | def _get(self, key, section=None, default=_onion_dict_guard):
"""Try to get the key from each dict in turn.
If you specify the optional section it looks there first.
"""
if section is not None:
section_dict = self.__sections.get(section, {})
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7,608 | presslabs/z3 | z3/snap.py | ZFSSnapshotManager._parse_snapshots | def _parse_snapshots(self):
"""Returns all snapshots grouped by filesystem, a dict of OrderedDict's
The order of snapshots matters when determining parents for incremental send,
so it's preserved.
Data is indexed by filesystem then for each filesystem we have an OrderedDict
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"""Returns all snapshots grouped by filesystem, a dict of OrderedDict's
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7,609 | presslabs/z3 | z3/snap.py | PairManager._compress | def _compress(self, cmd):
"""Adds the appropriate command to compress the zfs stream"""
compressor = COMPRESSORS.get(self.compressor)
if compressor is None:
return cmd
compress_cmd = compressor['compress']
return "{} | {}".format(compress_cmd, cmd) | python | def _compress(self, cmd):
"""Adds the appropriate command to compress the zfs stream"""
compressor = COMPRESSORS.get(self.compressor)
if compressor is None:
return cmd
compress_cmd = compressor['compress']
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7,610 | presslabs/z3 | z3/snap.py | PairManager._decompress | def _decompress(self, cmd, s3_snap):
"""Adds the appropriate command to decompress the zfs stream
This is determined from the metadata of the s3_snap.
"""
compressor = COMPRESSORS.get(s3_snap.compressor)
if compressor is None:
return cmd
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compressor = COMPRESSORS.get(s3_snap.compressor)
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7,611 | presslabs/z3 | z3/snap.py | PairManager.backup_full | def backup_full(self, snap_name=None, dry_run=False):
"""Do a full backup of a snapshot. By default latest local snapshot"""
z_snap = self._snapshot_to_backup(snap_name)
estimated_size = self._parse_estimated_size(
self._cmd.shell(
"zfs send -nvP '{}'".format(z_snap.n... | python | def backup_full(self, snap_name=None, dry_run=False):
"""Do a full backup of a snapshot. By default latest local snapshot"""
z_snap = self._snapshot_to_backup(snap_name)
estimated_size = self._parse_estimated_size(
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7,612 | presslabs/z3 | z3/snap.py | PairManager.backup_incremental | def backup_incremental(self, snap_name=None, dry_run=False):
"""Uploads named snapshot or latest, along with any other snapshots
required for an incremental backup.
"""
z_snap = self._snapshot_to_backup(snap_name)
to_upload = []
current = z_snap
uploaded_meta = []... | python | def backup_incremental(self, snap_name=None, dry_run=False):
"""Uploads named snapshot or latest, along with any other snapshots
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z_snap = self._snapshot_to_backup(snap_name)
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7,613 | pyannote/pyannote-metrics | pyannote/metrics/utils.py | UEMSupportMixin.extrude | def extrude(self, uem, reference, collar=0.0, skip_overlap=False):
"""Extrude reference boundary collars from uem
reference |----| |--------------| |-------------|
uem |---------------------| |-------------------------------|
extruded |--| |--| |---| |-----| |... | python | def extrude(self, uem, reference, collar=0.0, skip_overlap=False):
"""Extrude reference boundary collars from uem
reference |----| |--------------| |-------------|
uem |---------------------| |-------------------------------|
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7,614 | pyannote/pyannote-metrics | pyannote/metrics/utils.py | UEMSupportMixin.common_timeline | def common_timeline(self, reference, hypothesis):
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"""Return timeline common to both reference and hypothesis
reference |--------| |------------| |---------| |----|
hypothesis |--------------| |------| |----------------|
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hypothesis |--------------| |------| |----------------|
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7,615 | pyannote/pyannote-metrics | pyannote/metrics/utils.py | UEMSupportMixin.project | def project(self, annotation, timeline):
"""Project annotation onto timeline segments
reference |__A__| |__B__|
|____C____|
timeline |---|---|---| |---|
projection |_A_|_A_|_C_| |_B_|
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Parameters
---... | python | def project(self, annotation, timeline):
"""Project annotation onto timeline segments
reference |__A__| |__B__|
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projection |_A_|_A_|_C_| |_B_|
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7,616 | pyannote/pyannote-metrics | pyannote/metrics/utils.py | UEMSupportMixin.uemify | def uemify(self, reference, hypothesis, uem=None, collar=0.,
skip_overlap=False, returns_uem=False, returns_timeline=False):
"""Crop 'reference' and 'hypothesis' to 'uem' support
Parameters
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reference, hypothesis : Annotation
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7,617 | pyannote/pyannote-metrics | scripts/pyannote-metrics.py | get_hypothesis | def get_hypothesis(hypotheses, current_file):
"""Get hypothesis for given file
Parameters
----------
hypotheses : `dict`
Speaker diarization hypothesis provided by `load_rttm`.
current_file : `dict`
File description as given by pyannote.database protocols.
Returns
-------
... | python | def get_hypothesis(hypotheses, current_file):
"""Get hypothesis for given file
Parameters
----------
hypotheses : `dict`
Speaker diarization hypothesis provided by `load_rttm`.
current_file : `dict`
File description as given by pyannote.database protocols.
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7,618 | pyannote/pyannote-metrics | scripts/pyannote-metrics.py | reindex | def reindex(report):
"""Reindex report so that 'TOTAL' is the last row"""
index = list(report.index)
i = index.index('TOTAL')
return report.reindex(index[:i] + index[i+1:] + ['TOTAL']) | python | def reindex(report):
"""Reindex report so that 'TOTAL' is the last row"""
index = list(report.index)
i = index.index('TOTAL')
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7,619 | pyannote/pyannote-metrics | pyannote/metrics/binary_classification.py | precision_recall_curve | def precision_recall_curve(y_true, scores, distances=False):
"""Precision-recall curve
Parameters
----------
y_true : (n_samples, ) array-like
Boolean reference.
scores : (n_samples, ) array-like
Predicted score.
distances : boolean, optional
When True, indicate that `sc... | python | def precision_recall_curve(y_true, scores, distances=False):
"""Precision-recall curve
Parameters
----------
y_true : (n_samples, ) array-like
Boolean reference.
scores : (n_samples, ) array-like
Predicted score.
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7,620 | pyannote/pyannote-metrics | pyannote/metrics/errors/identification.py | IdentificationErrorAnalysis.difference | def difference(self, reference, hypothesis, uem=None, uemified=False):
"""Get error analysis as `Annotation`
Labels are (status, reference_label, hypothesis_label) tuples.
`status` is either 'correct', 'confusion', 'missed detection' or
'false alarm'.
`reference_label` is None i... | python | def difference(self, reference, hypothesis, uem=None, uemified=False):
"""Get error analysis as `Annotation`
Labels are (status, reference_label, hypothesis_label) tuples.
`status` is either 'correct', 'confusion', 'missed detection' or
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7,621 | pyannote/pyannote-metrics | pyannote/metrics/base.py | BaseMetric.reset | def reset(self):
"""Reset accumulated components and metric values"""
if self.parallel:
from pyannote.metrics import manager_
self.accumulated_ = manager_.dict()
self.results_ = manager_.list()
self.uris_ = manager_.dict()
else:
self.ac... | python | def reset(self):
"""Reset accumulated components and metric values"""
if self.parallel:
from pyannote.metrics import manager_
self.accumulated_ = manager_.dict()
self.results_ = manager_.list()
self.uris_ = manager_.dict()
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7,622 | pyannote/pyannote-metrics | pyannote/metrics/base.py | BaseMetric.confidence_interval | def confidence_interval(self, alpha=0.9):
"""Compute confidence interval on accumulated metric values
Parameters
----------
alpha : float, optional
Probability that the returned confidence interval contains
the true metric value.
Returns
-------
... | python | def confidence_interval(self, alpha=0.9):
"""Compute confidence interval on accumulated metric values
Parameters
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alpha : float, optional
Probability that the returned confidence interval contains
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7,623 | pyannote/pyannote-metrics | pyannote/metrics/base.py | Precision.compute_metric | def compute_metric(self, components):
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"""Compute precision from `components`"""
numerator = components[PRECISION_RELEVANT_RETRIEVED]
denominator = components[PRECISION_RETRIEVED]
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7,624 | pyannote/pyannote-metrics | pyannote/metrics/base.py | Recall.compute_metric | def compute_metric(self, components):
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numerator = components[RECALL_RELEVANT_RETRIEVED]
denominator = components[RECALL_RELEVANT]
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7,625 | pyannote/pyannote-metrics | pyannote/metrics/diarization.py | DiarizationErrorRate.optimal_mapping | def optimal_mapping(self, reference, hypothesis, uem=None):
"""Optimal label mapping
Parameters
----------
reference : Annotation
hypothesis : Annotation
Reference and hypothesis diarization
uem : Timeline
Evaluation map
Returns
-... | python | def optimal_mapping(self, reference, hypothesis, uem=None):
"""Optimal label mapping
Parameters
----------
reference : Annotation
hypothesis : Annotation
Reference and hypothesis diarization
uem : Timeline
Evaluation map
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7,626 | pyannote/pyannote-metrics | pyannote/metrics/diarization.py | GreedyDiarizationErrorRate.greedy_mapping | def greedy_mapping(self, reference, hypothesis, uem=None):
"""Greedy label mapping
Parameters
----------
reference : Annotation
hypothesis : Annotation
Reference and hypothesis diarization
uem : Timeline
Evaluation map
Returns
---... | python | def greedy_mapping(self, reference, hypothesis, uem=None):
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hypothesis : Annotation
Reference and hypothesis diarization
uem : Timeline
Evaluation map
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7,627 | brian-rose/climlab | climlab/radiation/radiation.py | default_absorbers | def default_absorbers(Tatm,
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All values are volumetric mixing ratios.
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All values are volumetric mixing ratios.
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7,628 | brian-rose/climlab | climlab/radiation/radiation.py | init_interface | def init_interface(field):
'''Return a Field object defined at the vertical interfaces of the input Field object.'''
interface_shape = np.array(field.shape); interface_shape[-1] += 1
interfaces = np.tile(False,len(interface_shape)); interfaces[-1] = True
interface_zero = Field(np.zeros(interface_shape),... | python | def init_interface(field):
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interface_shape = np.array(field.shape); interface_shape[-1] += 1
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7,629 | brian-rose/climlab | climlab/convection/akmaev_adjustment.py | convective_adjustment_direct | def convective_adjustment_direct(p, T, c, lapserate=6.5):
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Input argument lapserate gives the lapse rate expressed in degrees K per km
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Default lapse rate is 6.5 K / km.
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Returns the adjusted Column temperature.
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p is pressure in hPa
T is tempe... | [
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7,630 | brian-rose/climlab | climlab/convection/akmaev_adjustment.py | Akmaev_adjustment | def Akmaev_adjustment(theta, q, beta, n_k, theta_k, s_k, t_k):
'''Single column only.'''
L = q.size # number of vertical levels
# Akmaev step 1
k = 1
n_k[k-1] = 1
theta_k[k-1] = theta[k-1]
l = 2
while True:
# Akmaev step 2
n = 1
thistheta = theta[l-1]
whi... | python | def Akmaev_adjustment(theta, q, beta, n_k, theta_k, s_k, t_k):
'''Single column only.'''
L = q.size # number of vertical levels
# Akmaev step 1
k = 1
n_k[k-1] = 1
theta_k[k-1] = theta[k-1]
l = 2
while True:
# Akmaev step 2
n = 1
thistheta = theta[l-1]
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7,631 | brian-rose/climlab | climlab/model/column.py | GreyRadiationModel.do_diagnostics | def do_diagnostics(self):
'''Set all the diagnostics from long and shortwave radiation.'''
self.OLR = self.subprocess['LW'].flux_to_space
self.LW_down_sfc = self.subprocess['LW'].flux_to_sfc
self.LW_up_sfc = self.subprocess['LW'].flux_from_sfc
self.LW_absorbed_sfc = self.LW_down_... | python | def do_diagnostics(self):
'''Set all the diagnostics from long and shortwave radiation.'''
self.OLR = self.subprocess['LW'].flux_to_space
self.LW_down_sfc = self.subprocess['LW'].flux_to_sfc
self.LW_up_sfc = self.subprocess['LW'].flux_from_sfc
self.LW_absorbed_sfc = self.LW_down_... | [
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7,632 | brian-rose/climlab | climlab/utils/thermo.py | clausius_clapeyron | def clausius_clapeyron(T):
"""Compute saturation vapor pressure as function of temperature T.
Input: T is temperature in Kelvin
Output: saturation vapor pressure in mb or hPa
Formula from Rogers and Yau "A Short Course in Cloud Physics" (Pergammon Press), p. 16
claimed to be accurate to within 0.1... | python | def clausius_clapeyron(T):
"""Compute saturation vapor pressure as function of temperature T.
Input: T is temperature in Kelvin
Output: saturation vapor pressure in mb or hPa
Formula from Rogers and Yau "A Short Course in Cloud Physics" (Pergammon Press), p. 16
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claimed to be accurate to within 0.1% between -30degC and 35 degC
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7,633 | brian-rose/climlab | climlab/utils/thermo.py | qsat | def qsat(T,p):
"""Compute saturation specific humidity as function of temperature and pressure.
Input: T is temperature in Kelvin
p is pressure in hPa or mb
Output: saturation specific humidity (dimensionless).
"""
es = clausius_clapeyron(T)
q = eps * es / (p - (1 - eps) * es )
... | python | def qsat(T,p):
"""Compute saturation specific humidity as function of temperature and pressure.
Input: T is temperature in Kelvin
p is pressure in hPa or mb
Output: saturation specific humidity (dimensionless).
"""
es = clausius_clapeyron(T)
q = eps * es / (p - (1 - eps) * es )
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7,634 | brian-rose/climlab | climlab/utils/thermo.py | pseudoadiabat | def pseudoadiabat(T,p):
"""Compute the local slope of the pseudoadiabat at given temperature and pressure
Inputs: p is pressure in hPa or mb
T is local temperature in Kelvin
Output: dT/dp, the rate of temperature change for pseudoadiabatic ascent
in units of K / hPa
T... | python | def pseudoadiabat(T,p):
"""Compute the local slope of the pseudoadiabat at given temperature and pressure
Inputs: p is pressure in hPa or mb
T is local temperature in Kelvin
Output: dT/dp, the rate of temperature change for pseudoadiabatic ascent
in units of K / hPa
T... | [
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7,635 | brian-rose/climlab | climlab/dynamics/diffusion.py | _solve_implicit_banded | def _solve_implicit_banded(current, banded_matrix):
"""Uses a banded solver for matrix inversion of a tridiagonal matrix.
Converts the complete listed tridiagonal matrix *(nxn)* into a three row
matrix *(3xn)* and calls :py:func:`scipy.linalg.solve_banded()`.
:param array current: the curren... | python | def _solve_implicit_banded(current, banded_matrix):
"""Uses a banded solver for matrix inversion of a tridiagonal matrix.
Converts the complete listed tridiagonal matrix *(nxn)* into a three row
matrix *(3xn)* and calls :py:func:`scipy.linalg.solve_banded()`.
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7,636 | brian-rose/climlab | climlab/dynamics/diffusion.py | _guess_diffusion_axis | def _guess_diffusion_axis(process_or_domain):
"""Scans given process, domain or dictionary of domains for a diffusion axis
and returns appropriate name.
In case only one axis with length > 1 in the process or set of domains
exists, the name of that axis is returned. Otherwise an error is raised.
:... | python | def _guess_diffusion_axis(process_or_domain):
"""Scans given process, domain or dictionary of domains for a diffusion axis
and returns appropriate name.
In case only one axis with length > 1 in the process or set of domains
exists, the name of that axis is returned. Otherwise an error is raised.
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7,637 | brian-rose/climlab | climlab/dynamics/diffusion.py | Diffusion._implicit_solver | def _implicit_solver(self):
"""Invertes and solves the matrix problem for diffusion matrix
and temperature T.
The method is called by the
:func:`~climlab.process.implicit.ImplicitProcess._compute()` function
of the :class:`~climlab.process.implicit.ImplicitProcess` class and
... | python | def _implicit_solver(self):
"""Invertes and solves the matrix problem for diffusion matrix
and temperature T.
The method is called by the
:func:`~climlab.process.implicit.ImplicitProcess._compute()` function
of the :class:`~climlab.process.implicit.ImplicitProcess` class and
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7,638 | brian-rose/climlab | climlab/surface/albedo.py | P2Albedo._compute_fixed | def _compute_fixed(self):
'''Recompute any fixed quantities after a change in parameters'''
try:
lon, lat = np.meshgrid(self.lon, self.lat)
except:
lat = self.lat
phi = np.deg2rad(lat)
try:
albedo = self.a0 + self.a2 * P2(np.sin(phi))
e... | python | def _compute_fixed(self):
'''Recompute any fixed quantities after a change in parameters'''
try:
lon, lat = np.meshgrid(self.lon, self.lat)
except:
lat = self.lat
phi = np.deg2rad(lat)
try:
albedo = self.a0 + self.a2 * P2(np.sin(phi))
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7,639 | brian-rose/climlab | climlab/surface/albedo.py | Iceline.find_icelines | def find_icelines(self):
"""Finds iceline according to the surface temperature.
This method is called by the private function
:func:`~climlab.surface.albedo.Iceline._compute`
and updates following attributes according to the freezing temperature
``self.param['Tf']`` and the surf... | python | def find_icelines(self):
"""Finds iceline according to the surface temperature.
This method is called by the private function
:func:`~climlab.surface.albedo.Iceline._compute`
and updates following attributes according to the freezing temperature
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7,640 | brian-rose/climlab | climlab/surface/albedo.py | StepFunctionAlbedo._get_current_albedo | def _get_current_albedo(self):
'''Simple step-function albedo based on ice line at temperature Tf.'''
ice = self.subprocess['iceline'].ice
# noice = self.subprocess['iceline'].diagnostics['noice']
cold_albedo = self.subprocess['cold_albedo'].albedo
warm_albedo = self.subprocess['... | python | def _get_current_albedo(self):
'''Simple step-function albedo based on ice line at temperature Tf.'''
ice = self.subprocess['iceline'].ice
# noice = self.subprocess['iceline'].diagnostics['noice']
cold_albedo = self.subprocess['cold_albedo'].albedo
warm_albedo = self.subprocess['... | [
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7,641 | brian-rose/climlab | climlab/process/process.py | process_like | def process_like(proc):
"""Make an exact clone of a process, including state and all subprocesses.
The creation date is updated.
:param proc: process
:type proc: :class:`~climlab.process.process.Process`
:return: new process identical to the given process
:rtype: :class:`... | python | def process_like(proc):
"""Make an exact clone of a process, including state and all subprocesses.
The creation date is updated.
:param proc: process
:type proc: :class:`~climlab.process.process.Process`
:return: new process identical to the given process
:rtype: :class:`... | [
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7,642 | brian-rose/climlab | climlab/process/process.py | get_axes | def get_axes(process_or_domain):
"""Returns a dictionary of all Axis in a domain or dictionary of domains.
:param process_or_domain: a process or a domain object
:type process_or_domain: :class:`~climlab.process.process.Process` or
:class:`~climlab.domain.domain._Domain... | python | def get_axes(process_or_domain):
"""Returns a dictionary of all Axis in a domain or dictionary of domains.
:param process_or_domain: a process or a domain object
:type process_or_domain: :class:`~climlab.process.process.Process` or
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7,643 | brian-rose/climlab | climlab/process/process.py | Process.add_subprocesses | def add_subprocesses(self, procdict):
"""Adds a dictionary of subproceses to this process.
Calls :func:`add_subprocess` for every process given in the
input-dictionary. It can also pass a single process, which will
be given the name *default*.
:param procdict: a dictionary w... | python | def add_subprocesses(self, procdict):
"""Adds a dictionary of subproceses to this process.
Calls :func:`add_subprocess` for every process given in the
input-dictionary. It can also pass a single process, which will
be given the name *default*.
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7,644 | brian-rose/climlab | climlab/process/process.py | Process.add_subprocess | def add_subprocess(self, name, proc):
"""Adds a single subprocess to this process.
:param string name: name of the subprocess
:param proc: a Process object
:type proc: :class:`~climlab.process.process.Process`
:raises: :exc:`ValueError`
... | python | def add_subprocess(self, name, proc):
"""Adds a single subprocess to this process.
:param string name: name of the subprocess
:param proc: a Process object
:type proc: :class:`~climlab.process.process.Process`
:raises: :exc:`ValueError`
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7,645 | brian-rose/climlab | climlab/process/process.py | Process.remove_subprocess | def remove_subprocess(self, name, verbose=True):
"""Removes a single subprocess from this process.
:param string name: name of the subprocess
:param bool verbose: information whether warning message
should be printed [default: True]
:Example:
... | python | def remove_subprocess(self, name, verbose=True):
"""Removes a single subprocess from this process.
:param string name: name of the subprocess
:param bool verbose: information whether warning message
should be printed [default: True]
:Example:
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7,646 | brian-rose/climlab | climlab/process/process.py | Process.set_state | def set_state(self, name, value):
"""Sets the variable ``name`` to a new state ``value``.
:param string name: name of the state
:param value: state variable
:type value: :class:`~climlab.domain.field.Field` or *array*
:raises: :exc:`ValueError`
... | python | def set_state(self, name, value):
"""Sets the variable ``name`` to a new state ``value``.
:param string name: name of the state
:param value: state variable
:type value: :class:`~climlab.domain.field.Field` or *array*
:raises: :exc:`ValueError`
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7,647 | brian-rose/climlab | climlab/process/process.py | Process._add_field | def _add_field(self, field_type, name, value):
"""Adds a new field to a specified dictionary. The field is also added
as a process attribute. field_type can be 'input', 'diagnostics' """
try:
self.__getattribute__(field_type).update({name: value})
except:
raise Va... | python | def _add_field(self, field_type, name, value):
"""Adds a new field to a specified dictionary. The field is also added
as a process attribute. field_type can be 'input', 'diagnostics' """
try:
self.__getattribute__(field_type).update({name: value})
except:
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7,648 | brian-rose/climlab | climlab/process/process.py | Process.add_diagnostic | def add_diagnostic(self, name, value=None):
"""Create a new diagnostic variable called ``name`` for this process
and initialize it with the given ``value``.
Quantity is accessible in two ways:
* as a process attribute, i.e. ``proc.name``
* as a member of the diagnostics... | python | def add_diagnostic(self, name, value=None):
"""Create a new diagnostic variable called ``name`` for this process
and initialize it with the given ``value``.
Quantity is accessible in two ways:
* as a process attribute, i.e. ``proc.name``
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7,649 | brian-rose/climlab | climlab/process/process.py | Process.add_input | def add_input(self, name, value=None):
'''Create a new input variable called ``name`` for this process
and initialize it with the given ``value``.
Quantity is accessible in two ways:
* as a process attribute, i.e. ``proc.name``
* as a member of the input dictionary,
... | python | def add_input(self, name, value=None):
'''Create a new input variable called ``name`` for this process
and initialize it with the given ``value``.
Quantity is accessible in two ways:
* as a process attribute, i.e. ``proc.name``
* as a member of the input dictionary,
... | [
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7,650 | brian-rose/climlab | climlab/process/process.py | Process.remove_diagnostic | def remove_diagnostic(self, name):
""" Removes a diagnostic from the ``process.diagnostic`` dictionary
and also delete the associated process attribute.
:param str name: name of diagnostic quantity to be removed
:Example:
Remove diagnostic variable 'icelat' from energy ... | python | def remove_diagnostic(self, name):
""" Removes a diagnostic from the ``process.diagnostic`` dictionary
and also delete the associated process attribute.
:param str name: name of diagnostic quantity to be removed
:Example:
Remove diagnostic variable 'icelat' from energy ... | [
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7,651 | brian-rose/climlab | climlab/process/process.py | Process.to_xarray | def to_xarray(self, diagnostics=False):
""" Convert process variables to ``xarray.Dataset`` format.
With ``diagnostics=True``, both state and diagnostic variables are included.
Otherwise just the state variables are included.
Returns an ``xarray.Dataset`` object with all spatial axes,... | python | def to_xarray(self, diagnostics=False):
""" Convert process variables to ``xarray.Dataset`` format.
With ``diagnostics=True``, both state and diagnostic variables are included.
Otherwise just the state variables are included.
Returns an ``xarray.Dataset`` object with all spatial axes,... | [
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7,652 | brian-rose/climlab | climlab/process/process.py | Process.diagnostics | def diagnostics(self):
"""Dictionary access to all diagnostic variables
:type: dict
"""
diag_dict = {}
for key in self._diag_vars:
try:
#diag_dict[key] = getattr(self,key)
# using self.__dict__ doesn't count diagnostics defined ... | python | def diagnostics(self):
"""Dictionary access to all diagnostic variables
:type: dict
"""
diag_dict = {}
for key in self._diag_vars:
try:
#diag_dict[key] = getattr(self,key)
# using self.__dict__ doesn't count diagnostics defined ... | [
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7,653 | brian-rose/climlab | climlab/process/process.py | Process.input | def input(self):
"""Dictionary access to all input variables
That can be boundary conditions and other gridded quantities
independent of the `process`
:type: dict
"""
input_dict = {}
for key in self._input_vars:
try:
input_dict[... | python | def input(self):
"""Dictionary access to all input variables
That can be boundary conditions and other gridded quantities
independent of the `process`
:type: dict
"""
input_dict = {}
for key in self._input_vars:
try:
input_dict[... | [
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7,654 | brian-rose/climlab | climlab/solar/orbital/table.py | _get_Berger_data | def _get_Berger_data(verbose=True):
'''Read in the Berger and Loutre orbital table as a pandas dataframe, convert to xarray
'''
# The first column of the data file is used as the row index, and represents kyr from present
orbit91_pd, path = load_data_source(local_path = local_path,
r... | python | def _get_Berger_data(verbose=True):
'''Read in the Berger and Loutre orbital table as a pandas dataframe, convert to xarray
'''
# The first column of the data file is used as the row index, and represents kyr from present
orbit91_pd, path = load_data_source(local_path = local_path,
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7,655 | brian-rose/climlab | climlab/utils/data_source.py | load_data_source | def load_data_source(local_path,
remote_source_list,
open_method,
open_method_kwargs=dict(),
remote_kwargs=dict(),
verbose=True):
'''Flexible data retreiver to download and cache the data files locally.
Usage example (this makes a local... | python | def load_data_source(local_path,
remote_source_list,
open_method,
open_method_kwargs=dict(),
remote_kwargs=dict(),
verbose=True):
'''Flexible data retreiver to download and cache the data files locally.
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7,656 | brian-rose/climlab | climlab/radiation/transmissivity.py | tril | def tril(array, k=0):
'''Lower triangle of an array.
Return a copy of an array with elements above the k-th diagonal zeroed.
Need a multi-dimensional version here because numpy.tril does not
broadcast for numpy verison < 1.9.'''
try:
tril_array = np.tril(array, k=k)
except:
# hav... | python | def tril(array, k=0):
'''Lower triangle of an array.
Return a copy of an array with elements above the k-th diagonal zeroed.
Need a multi-dimensional version here because numpy.tril does not
broadcast for numpy verison < 1.9.'''
try:
tril_array = np.tril(array, k=k)
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7,657 | brian-rose/climlab | climlab/radiation/transmissivity.py | Transmissivity.flux_up | def flux_up(self, fluxUpBottom, emission=None):
'''Compute downwelling radiative flux at interfaces between layers.
Inputs:
* fluxDownTop: flux down at top
* emission: emission from atmospheric levels (N)
defaults to zero if not given
Returns:
... | python | def flux_up(self, fluxUpBottom, emission=None):
'''Compute downwelling radiative flux at interfaces between layers.
Inputs:
* fluxDownTop: flux down at top
* emission: emission from atmospheric levels (N)
defaults to zero if not given
Returns:
... | [
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* emission: emission from atmospheric levels (N)
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7,658 | brian-rose/climlab | climlab/radiation/transmissivity.py | Transmissivity.flux_down | def flux_down(self, fluxDownTop, emission=None):
'''Compute upwelling radiative flux at interfaces between layers.
Inputs:
* fluxUpBottom: flux up from bottom
* emission: emission from atmospheric levels (N)
defaults to zero if not given
Returns:
... | python | def flux_down(self, fluxDownTop, emission=None):
'''Compute upwelling radiative flux at interfaces between layers.
Inputs:
* fluxUpBottom: flux up from bottom
* emission: emission from atmospheric levels (N)
defaults to zero if not given
Returns:
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7,659 | brian-rose/climlab | climlab/radiation/rrtm/rrtmg_lw.py | RRTMG_LW._compute_heating_rates | def _compute_heating_rates(self):
'''Prepare arguments and call the RRTGM_LW driver to calculate
radiative fluxes and heating rates'''
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... | python | def _compute_heating_rates(self):
'''Prepare arguments and call the RRTGM_LW driver to calculate
radiative fluxes and heating rates'''
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7,660 | brian-rose/climlab | climlab/radiation/rrtm/utils.py | _prepare_general_arguments | def _prepare_general_arguments(RRTMGobject):
'''Prepare arguments needed for both RRTMG_SW and RRTMG_LW with correct dimensions.'''
tlay = _climlab_to_rrtm(RRTMGobject.Tatm)
tlev = _climlab_to_rrtm(interface_temperature(**RRTMGobject.state))
play = _climlab_to_rrtm(RRTMGobject.lev * np.ones_like(tlay))
... | python | def _prepare_general_arguments(RRTMGobject):
'''Prepare arguments needed for both RRTMG_SW and RRTMG_LW with correct dimensions.'''
tlay = _climlab_to_rrtm(RRTMGobject.Tatm)
tlev = _climlab_to_rrtm(interface_temperature(**RRTMGobject.state))
play = _climlab_to_rrtm(RRTMGobject.lev * np.ones_like(tlay))
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7,661 | brian-rose/climlab | climlab/radiation/rrtm/utils.py | interface_temperature | def interface_temperature(Ts, Tatm, **kwargs):
'''Compute temperature at model layer interfaces.'''
# Actually it's not clear to me how the RRTM code uses these values
lev = Tatm.domain.axes['lev'].points
lev_bounds = Tatm.domain.axes['lev'].bounds
# Interpolate to layer interfaces
f = interp1... | python | def interface_temperature(Ts, Tatm, **kwargs):
'''Compute temperature at model layer interfaces.'''
# Actually it's not clear to me how the RRTM code uses these values
lev = Tatm.domain.axes['lev'].points
lev_bounds = Tatm.domain.axes['lev'].bounds
# Interpolate to layer interfaces
f = interp1... | [
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7,662 | brian-rose/climlab | climlab/dynamics/meridional_moist_diffusion.py | moist_amplification_factor | def moist_amplification_factor(Tkelvin, relative_humidity=0.8):
'''Compute the moisture amplification factor for the moist diffusivity
given relative humidity and reference temperature profile.'''
deltaT = 0.01
# slope of saturation specific humidity at 1000 hPa
dqsdTs = (qsat(Tkelvin+deltaT/2, 100... | python | def moist_amplification_factor(Tkelvin, relative_humidity=0.8):
'''Compute the moisture amplification factor for the moist diffusivity
given relative humidity and reference temperature profile.'''
deltaT = 0.01
# slope of saturation specific humidity at 1000 hPa
dqsdTs = (qsat(Tkelvin+deltaT/2, 100... | [
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7,663 | brian-rose/climlab | climlab/solar/insolation.py | daily_insolation | def daily_insolation(lat, day, orb=const.orb_present, S0=const.S0, day_type=1):
"""Compute daily average insolation given latitude, time of year and orbital parameters.
Orbital parameters can be interpolated to any time in the last 5 Myears with
``climlab.solar.orbital.OrbitalTable`` (see example above).
... | python | def daily_insolation(lat, day, orb=const.orb_present, S0=const.S0, day_type=1):
"""Compute daily average insolation given latitude, time of year and orbital parameters.
Orbital parameters can be interpolated to any time in the last 5 Myears with
``climlab.solar.orbital.OrbitalTable`` (see example above).
... | [
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7,664 | brian-rose/climlab | climlab/solar/insolation.py | solar_longitude | def solar_longitude( day, orb=const.orb_present, days_per_year = None ):
"""Estimates solar longitude from calendar day.
Method is using an approximation from :cite:`Berger_1978` section 3
(lambda = 0 at spring equinox).
**Function-call arguments** \n
:param array day: Indicator of time... | python | def solar_longitude( day, orb=const.orb_present, days_per_year = None ):
"""Estimates solar longitude from calendar day.
Method is using an approximation from :cite:`Berger_1978` section 3
(lambda = 0 at spring equinox).
**Function-call arguments** \n
:param array day: Indicator of time... | [
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7,665 | brian-rose/climlab | climlab/domain/domain.py | single_column | def single_column(num_lev=30, water_depth=1., lev=None, **kwargs):
"""Creates domains for a single column of atmosphere overlying a slab of water.
Can also pass a pressure array or pressure level axis object specified in ``lev``.
If argument ``lev`` is not ``None`` then function tries to build a level axi... | python | def single_column(num_lev=30, water_depth=1., lev=None, **kwargs):
"""Creates domains for a single column of atmosphere overlying a slab of water.
Can also pass a pressure array or pressure level axis object specified in ``lev``.
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7,666 | brian-rose/climlab | climlab/domain/domain.py | zonal_mean_surface | def zonal_mean_surface(num_lat=90, water_depth=10., lat=None, **kwargs):
"""Creates a 1D slab ocean Domain in latitude with uniform water depth.
Domain has a single heat capacity according to the specified water depth.
**Function-call argument** \n
:param int num_lat: number of latitude point... | python | def zonal_mean_surface(num_lat=90, water_depth=10., lat=None, **kwargs):
"""Creates a 1D slab ocean Domain in latitude with uniform water depth.
Domain has a single heat capacity according to the specified water depth.
**Function-call argument** \n
:param int num_lat: number of latitude point... | [
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7,667 | brian-rose/climlab | climlab/domain/domain.py | surface_2D | def surface_2D(num_lat=90, num_lon=180, water_depth=10., lon=None,
lat=None, **kwargs):
"""Creates a 2D slab ocean Domain in latitude and longitude with uniform water depth.
Domain has a single heat capacity according to the specified water depth.
**Function-call argument** \n
:param i... | python | def surface_2D(num_lat=90, num_lon=180, water_depth=10., lon=None,
lat=None, **kwargs):
"""Creates a 2D slab ocean Domain in latitude and longitude with uniform water depth.
Domain has a single heat capacity according to the specified water depth.
**Function-call argument** \n
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7,668 | brian-rose/climlab | climlab/domain/domain.py | _Domain._make_axes_dict | def _make_axes_dict(self, axes):
"""Makes an axes dictionary.
.. note::
In case the input is ``None``, the dictionary :code:`{'empty': None}`
is returned.
**Function-call argument** \n
:param axes: axes input
:type axes: dict or single instance ... | python | def _make_axes_dict(self, axes):
"""Makes an axes dictionary.
.. note::
In case the input is ``None``, the dictionary :code:`{'empty': None}`
is returned.
**Function-call argument** \n
:param axes: axes input
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7,669 | brian-rose/climlab | climlab/process/implicit.py | ImplicitProcess._compute | def _compute(self):
"""Computes the state variable tendencies in time for implicit processes.
To calculate the new state the :func:`_implicit_solver()` method is
called for daughter classes. This however returns the new state of the
variables, not just the tendencies. Therefore, the adj... | python | def _compute(self):
"""Computes the state variable tendencies in time for implicit processes.
To calculate the new state the :func:`_implicit_solver()` method is
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7,670 | brian-rose/climlab | climlab/utils/walk.py | walk_processes | def walk_processes(top, topname='top', topdown=True, ignoreFlag=False):
"""Generator for recursive tree of climlab processes
Starts walking from climlab process ``top`` and generates a complete
list of all processes and sub-processes that are managed from ``top`` process.
``level`` indicades the rank o... | python | def walk_processes(top, topname='top', topdown=True, ignoreFlag=False):
"""Generator for recursive tree of climlab processes
Starts walking from climlab process ``top`` and generates a complete
list of all processes and sub-processes that are managed from ``top`` process.
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7,671 | brian-rose/climlab | climlab/utils/walk.py | process_tree | def process_tree(top, name='top'):
"""Creates a string representation of the process tree for process top.
This method uses the :func:`walk_processes` method to create the process tree.
:param top: top process for which process tree string should be
created
:typ... | python | def process_tree(top, name='top'):
"""Creates a string representation of the process tree for process top.
This method uses the :func:`walk_processes` method to create the process tree.
:param top: top process for which process tree string should be
created
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7,672 | brian-rose/climlab | climlab/radiation/greygas.py | GreyGas._compute_fluxes | def _compute_fluxes(self):
''' All fluxes are band by band'''
self.emission = self._compute_emission()
self.emission_sfc = self._compute_emission_sfc()
fromspace = self._from_space()
self.flux_down = self.trans.flux_down(fromspace, self.emission)
self.flux_reflected_up = ... | python | def _compute_fluxes(self):
''' All fluxes are band by band'''
self.emission = self._compute_emission()
self.emission_sfc = self._compute_emission_sfc()
fromspace = self._from_space()
self.flux_down = self.trans.flux_down(fromspace, self.emission)
self.flux_reflected_up = ... | [
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7,673 | brian-rose/climlab | climlab/radiation/greygas.py | GreyGas.flux_components_top | def flux_components_top(self):
'''Compute the contributions to the outgoing flux to space due to
emissions from each level and the surface.'''
N = self.lev.size
flux_up_bottom = self.flux_from_sfc
emission = np.zeros_like(self.emission)
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'''Compute the contributions to the outgoing flux to space due to
emissions from each level and the surface.'''
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7,674 | brian-rose/climlab | climlab/radiation/greygas.py | GreyGas.flux_components_bottom | def flux_components_bottom(self):
'''Compute the contributions to the downwelling flux to surface due to
emissions from each level.'''
N = self.lev.size
atmComponents = np.zeros_like(self.Tatm)
flux_down_top = np.zeros_like(self.Ts)
# same comment as above... would be ni... | python | def flux_components_bottom(self):
'''Compute the contributions to the downwelling flux to surface due to
emissions from each level.'''
N = self.lev.size
atmComponents = np.zeros_like(self.Tatm)
flux_down_top = np.zeros_like(self.Ts)
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7,675 | brian-rose/climlab | climlab/surface/turbulent.py | LatentHeatFlux._compute | def _compute(self):
'''Overides the _compute method of EnergyBudget'''
tendencies = self._temperature_tendencies()
if 'q' in self.state:
# in a model with active water vapor, this flux should affect
# water vapor tendency, NOT air temperature tendency!
tenden... | python | def _compute(self):
'''Overides the _compute method of EnergyBudget'''
tendencies = self._temperature_tendencies()
if 'q' in self.state:
# in a model with active water vapor, this flux should affect
# water vapor tendency, NOT air temperature tendency!
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7,676 | brian-rose/climlab | climlab/utils/legendre.py | Pn | def Pn(x):
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:param float x: argument to calculate Legendre polynomials
:return Pn: dictionary which contains order of Legendre polynomials
(from 0 to 28) as keys and the corresponding ... | python | def Pn(x):
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7,677 | brian-rose/climlab | climlab/utils/legendre.py | Pnprime | def Pnprime(x):
"""Calculates first derivatives of Legendre polynomials and returns them
in a dictionary ``Pnprime``.
:param float x: argument to calculate first derivate of Legendre polynomials
:return Pn: dictionary which contains order of Legendre polynomials
(fro... | python | def Pnprime(x):
"""Calculates first derivatives of Legendre polynomials and returns them
in a dictionary ``Pnprime``.
:param float x: argument to calculate first derivate of Legendre polynomials
:return Pn: dictionary which contains order of Legendre polynomials
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7,678 | brian-rose/climlab | climlab/model/ebm.py | EBM.inferred_heat_transport | def inferred_heat_transport(self):
"""Calculates the inferred heat transport by integrating the TOA
energy imbalance from pole to pole.
The method is calculating
.. math::
H(\\varphi) = 2 \pi R^2 \int_{-\pi/2}^{\\varphi} cos\phi \ R_{TOA} d\phi
where :math:`R_{TOA... | python | def inferred_heat_transport(self):
"""Calculates the inferred heat transport by integrating the TOA
energy imbalance from pole to pole.
The method is calculating
.. math::
H(\\varphi) = 2 \pi R^2 \int_{-\pi/2}^{\\varphi} cos\phi \ R_{TOA} d\phi
where :math:`R_{TOA... | [
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7,679 | brian-rose/climlab | climlab/radiation/rrtm/_rrtmg_lw/setup.py | rrtmg_lw_gen_source | def rrtmg_lw_gen_source(ext, build_dir):
'''Add RRTMG_LW fortran source if Fortran 90 compiler available,
if no compiler is found do not try to build the extension.'''
thispath = config.local_path
module_src = []
for item in modules:
fullname = join(thispath,'rrtmg_lw_v4.85','gcm_model','mod... | python | def rrtmg_lw_gen_source(ext, build_dir):
'''Add RRTMG_LW fortran source if Fortran 90 compiler available,
if no compiler is found do not try to build the extension.'''
thispath = config.local_path
module_src = []
for item in modules:
fullname = join(thispath,'rrtmg_lw_v4.85','gcm_model','mod... | [
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7,680 | brian-rose/climlab | climlab/process/time_dependent_process.py | TimeDependentProcess.compute | def compute(self):
"""Computes the tendencies for all state variables given current state
and specified input.
The function first computes all diagnostic processes. They don't produce
any tendencies directly but they may affect the other processes (such as
change in solar distri... | python | def compute(self):
"""Computes the tendencies for all state variables given current state
and specified input.
The function first computes all diagnostic processes. They don't produce
any tendencies directly but they may affect the other processes (such as
change in solar distri... | [
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7,681 | brian-rose/climlab | climlab/process/time_dependent_process.py | TimeDependentProcess._compute_type | def _compute_type(self, proctype):
"""Computes tendencies due to all subprocesses of given type
``'proctype'``. Also pass all diagnostics up to parent process."""
tendencies = {}
for varname in self.state:
tendencies[varname] = 0. * self.state[varname]
for proc in sel... | python | def _compute_type(self, proctype):
"""Computes tendencies due to all subprocesses of given type
``'proctype'``. Also pass all diagnostics up to parent process."""
tendencies = {}
for varname in self.state:
tendencies[varname] = 0. * self.state[varname]
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7,682 | brian-rose/climlab | climlab/process/time_dependent_process.py | TimeDependentProcess._compute | def _compute(self):
"""Where the tendencies are actually computed...
Needs to be implemented for each daughter class
Returns a dictionary with same keys as self.state"""
tendencies = {}
for name, value in self.state.items():
tendencies[name] = value * 0.
ret... | python | def _compute(self):
"""Where the tendencies are actually computed...
Needs to be implemented for each daughter class
Returns a dictionary with same keys as self.state"""
tendencies = {}
for name, value in self.state.items():
tendencies[name] = value * 0.
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7,683 | brian-rose/climlab | climlab/process/time_dependent_process.py | TimeDependentProcess._build_process_type_list | def _build_process_type_list(self):
"""Generates lists of processes organized by process type.
Following object attributes are generated or updated:
:ivar dict process_types: a dictionary with entries:
``'diagnostic'``, ``'explicit'``,
... | python | def _build_process_type_list(self):
"""Generates lists of processes organized by process type.
Following object attributes are generated or updated:
:ivar dict process_types: a dictionary with entries:
``'diagnostic'``, ``'explicit'``,
... | [
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7,684 | brian-rose/climlab | climlab/process/time_dependent_process.py | TimeDependentProcess.step_forward | def step_forward(self):
"""Updates state variables with computed tendencies.
Calls the :func:`compute` method to get current tendencies for all
process states. Multiplied with the timestep and added up to the state
variables is updating all model states.
:Example:
... | python | def step_forward(self):
"""Updates state variables with computed tendencies.
Calls the :func:`compute` method to get current tendencies for all
process states. Multiplied with the timestep and added up to the state
variables is updating all model states.
:Example:
... | [
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7,685 | brian-rose/climlab | climlab/process/time_dependent_process.py | TimeDependentProcess._update_time | def _update_time(self):
"""Increments the timestep counter by one.
Furthermore ``self.time['days_elapsed']`` and
``self.time['num_steps_per_year']`` are updated.
The function is called by the time stepping methods.
"""
self.time['steps'] += 1
# time in days sin... | python | def _update_time(self):
"""Increments the timestep counter by one.
Furthermore ``self.time['days_elapsed']`` and
``self.time['num_steps_per_year']`` are updated.
The function is called by the time stepping methods.
"""
self.time['steps'] += 1
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The function is called by the time stepping methods. | [
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7,686 | brian-rose/climlab | climlab/process/time_dependent_process.py | TimeDependentProcess.integrate_years | def integrate_years(self, years=1.0, verbose=True):
"""Integrates the model by a given number of years.
:param float years: integration time for the model in years
[default: 1.0]
:param bool verbose: information whether model time details
... | python | def integrate_years(self, years=1.0, verbose=True):
"""Integrates the model by a given number of years.
:param float years: integration time for the model in years
[default: 1.0]
:param bool verbose: information whether model time details
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7,687 | brian-rose/climlab | climlab/process/time_dependent_process.py | TimeDependentProcess.integrate_days | def integrate_days(self, days=1.0, verbose=True):
"""Integrates the model forward for a specified number of days.
It convertes the given number of days into years and calls
:func:`integrate_years`.
:param float days: integration time for the model in days
... | python | def integrate_days(self, days=1.0, verbose=True):
"""Integrates the model forward for a specified number of days.
It convertes the given number of days into years and calls
:func:`integrate_years`.
:param float days: integration time for the model in days
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7,688 | brian-rose/climlab | climlab/process/time_dependent_process.py | TimeDependentProcess.integrate_converge | def integrate_converge(self, crit=1e-4, verbose=True):
"""Integrates the model until model states are converging.
:param crit: exit criteria for difference of iterated
solutions [default: 0.0001]
:type crit: float
:param bool verbos... | python | def integrate_converge(self, crit=1e-4, verbose=True):
"""Integrates the model until model states are converging.
:param crit: exit criteria for difference of iterated
solutions [default: 0.0001]
:type crit: float
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7,689 | brian-rose/climlab | climlab/radiation/cam3/setup.py | cam3_gen_source | def cam3_gen_source(ext, build_dir):
'''Add CAM3 fortran source if Fortran 90 compiler available,
if no compiler is found do not try to build the extension.'''
# Fortran 90 sources in order of compilation
fort90source = ['pmgrid.F90',
'prescribed_aerosols.F90',
'shr_kind... | python | def cam3_gen_source(ext, build_dir):
'''Add CAM3 fortran source if Fortran 90 compiler available,
if no compiler is found do not try to build the extension.'''
# Fortran 90 sources in order of compilation
fort90source = ['pmgrid.F90',
'prescribed_aerosols.F90',
'shr_kind... | [
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7,690 | brian-rose/climlab | climlab/domain/field.py | global_mean | def global_mean(field):
"""Calculates the latitude weighted global mean of a field
with latitude dependence.
:param Field field: input field
:raises: :exc:`ValueError` if input field has no latitude axis
:return: latitude weighted global mean of the field
:rtype: float
:Example:
i... | python | def global_mean(field):
"""Calculates the latitude weighted global mean of a field
with latitude dependence.
:param Field field: input field
:raises: :exc:`ValueError` if input field has no latitude axis
:return: latitude weighted global mean of the field
:rtype: float
:Example:
i... | [
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7,691 | brian-rose/climlab | climlab/domain/field.py | to_latlon | def to_latlon(array, domain, axis = 'lon'):
"""Broadcasts a 1D axis dependent array across another axis.
:param array input_array: the 1D array used for broadcasting
:param domain: the domain associated with that
array
:param axis: the axis ... | python | def to_latlon(array, domain, axis = 'lon'):
"""Broadcasts a 1D axis dependent array across another axis.
:param array input_array: the 1D array used for broadcasting
:param domain: the domain associated with that
array
:param axis: the axis ... | [
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7,692 | brian-rose/climlab | climlab/domain/xarray.py | Field_to_xarray | def Field_to_xarray(field):
'''Convert a climlab.Field object to xarray.DataArray'''
dom = field.domain
dims = []; dimlist = []; coords = {};
for axname in dom.axes:
dimlist.append(axname)
try:
assert field.interfaces[dom.axis_index[axname]]
bounds_name = axname +... | python | def Field_to_xarray(field):
'''Convert a climlab.Field object to xarray.DataArray'''
dom = field.domain
dims = []; dimlist = []; coords = {};
for axname in dom.axes:
dimlist.append(axname)
try:
assert field.interfaces[dom.axis_index[axname]]
bounds_name = axname +... | [
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7,693 | brian-rose/climlab | climlab/domain/xarray.py | state_to_xarray | def state_to_xarray(state):
'''Convert a dictionary of climlab.Field objects to xarray.Dataset
Input: dictionary of climlab.Field objects
(e.g. process.state or process.diagnostics dictionary)
Output: xarray.Dataset object with all spatial axes,
including 'bounds' axes indicating cell boundaries i... | python | def state_to_xarray(state):
'''Convert a dictionary of climlab.Field objects to xarray.Dataset
Input: dictionary of climlab.Field objects
(e.g. process.state or process.diagnostics dictionary)
Output: xarray.Dataset object with all spatial axes,
including 'bounds' axes indicating cell boundaries i... | [
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7,694 | brian-rose/climlab | climlab/domain/xarray.py | to_xarray | def to_xarray(input):
'''Convert climlab input to xarray format.
If input is a climlab.Field object, return xarray.DataArray
If input is a dictionary (e.g. process.state or process.diagnostics),
return xarray.Dataset object with all spatial axes,
including 'bounds' axes indicating cell boundaries ... | python | def to_xarray(input):
'''Convert climlab input to xarray format.
If input is a climlab.Field object, return xarray.DataArray
If input is a dictionary (e.g. process.state or process.diagnostics),
return xarray.Dataset object with all spatial axes,
including 'bounds' axes indicating cell boundaries ... | [
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7,695 | adamrehn/slidingwindow | slidingwindow/SlidingWindow.py | generate | def generate(data, dimOrder, maxWindowSize, overlapPercent, transforms = []):
"""
Generates a set of sliding windows for the specified dataset.
"""
# Determine the dimensions of the input data
width = data.shape[dimOrder.index('w')]
height = data.shape[dimOrder.index('h')]
# Generate the windows
return gene... | python | def generate(data, dimOrder, maxWindowSize, overlapPercent, transforms = []):
"""
Generates a set of sliding windows for the specified dataset.
"""
# Determine the dimensions of the input data
width = data.shape[dimOrder.index('w')]
height = data.shape[dimOrder.index('h')]
# Generate the windows
return gene... | [
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7,696 | adamrehn/slidingwindow | slidingwindow/SlidingWindow.py | generateForSize | def generateForSize(width, height, dimOrder, maxWindowSize, overlapPercent, transforms = []):
"""
Generates a set of sliding windows for a dataset with the specified dimensions and order.
"""
# If the input data is smaller than the specified window size,
# clip the window size to the input size on both dimension... | python | def generateForSize(width, height, dimOrder, maxWindowSize, overlapPercent, transforms = []):
"""
Generates a set of sliding windows for a dataset with the specified dimensions and order.
"""
# If the input data is smaller than the specified window size,
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7,697 | adamrehn/slidingwindow | slidingwindow/SlidingWindow.py | SlidingWindow.apply | def apply(self, matrix):
"""
Slices the supplied matrix and applies any transform bound to this window
"""
view = matrix[ self.indices() ]
return self.transform(view) if self.transform != None else view | python | def apply(self, matrix):
"""
Slices the supplied matrix and applies any transform bound to this window
"""
view = matrix[ self.indices() ]
return self.transform(view) if self.transform != None else view | [
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7,698 | adamrehn/slidingwindow | slidingwindow/SlidingWindow.py | SlidingWindow.indices | def indices(self, includeChannel=True):
"""
Retrieves the indices for this window as a tuple of slices
"""
if self.dimOrder == DimOrder.HeightWidthChannel:
# Equivalent to [self.y:self.y+self.h+1, self.x:self.x+self.w+1]
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... | python | def indices(self, includeChannel=True):
"""
Retrieves the indices for this window as a tuple of slices
"""
if self.dimOrder == DimOrder.HeightWidthChannel:
# Equivalent to [self.y:self.y+self.h+1, self.x:self.x+self.w+1]
return (
slice(self.y, self.y+self.h),
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7,699 | adamrehn/slidingwindow | slidingwindow/Batching.py | batchWindows | def batchWindows(windows, batchSize):
"""
Splits a list of windows into a series of batches.
"""
return np.array_split(np.array(windows), len(windows) // batchSize) | python | def batchWindows(windows, batchSize):
"""
Splits a list of windows into a series of batches.
"""
return np.array_split(np.array(windows), len(windows) // batchSize) | [
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