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mabuchilab/QNET | src/qnet/algebra/core/abstract_algebra.py | Expression.bound_symbols | def bound_symbols(self):
"""Set of bound SymPy symbols in the expression"""
if self._bound_symbols is None:
res = set.union(
set([]), # dummy arg (union fails without arguments)
*[_bound_symbols(val) for val in self.kwargs.values()])
res.update(
... | python | def bound_symbols(self):
"""Set of bound SymPy symbols in the expression"""
if self._bound_symbols is None:
res = set.union(
set([]), # dummy arg (union fails without arguments)
*[_bound_symbols(val) for val in self.kwargs.values()])
res.update(
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daler/metaseq | metaseq/scripts/download_metaseq_example_data.py | download | def download(url, dest):
"""
Platform-agnostic downloader.
"""
u = urllib.FancyURLopener()
logger.info("Downloading %s..." % url)
u.retrieve(url, dest)
logger.info('Done, see %s' % dest)
return dest | python | def download(url, dest):
"""
Platform-agnostic downloader.
"""
u = urllib.FancyURLopener()
logger.info("Downloading %s..." % url)
u.retrieve(url, dest)
logger.info('Done, see %s' % dest)
return dest | [
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daler/metaseq | metaseq/scripts/download_metaseq_example_data.py | logged_command | def logged_command(cmds):
"helper function to log a command and then run it"
logger.info(' '.join(cmds))
os.system(' '.join(cmds)) | python | def logged_command(cmds):
"helper function to log a command and then run it"
logger.info(' '.join(cmds))
os.system(' '.join(cmds)) | [
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daler/metaseq | metaseq/scripts/download_metaseq_example_data.py | get_cufflinks | def get_cufflinks():
"Download cufflinks GTF files"
for size, md5, url in cufflinks:
cuff_gtf = os.path.join(args.data_dir, os.path.basename(url))
if not _up_to_date(md5, cuff_gtf):
download(url, cuff_gtf) | python | def get_cufflinks():
"Download cufflinks GTF files"
for size, md5, url in cufflinks:
cuff_gtf = os.path.join(args.data_dir, os.path.basename(url))
if not _up_to_date(md5, cuff_gtf):
download(url, cuff_gtf) | [
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daler/metaseq | metaseq/scripts/download_metaseq_example_data.py | get_bams | def get_bams():
"""
Download BAM files if needed, extract only chr17 reads, and regenerate .bai
"""
for size, md5, url in bams:
bam = os.path.join(
args.data_dir,
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if not _up_to_date(md5, bam):
l... | python | def get_bams():
"""
Download BAM files if needed, extract only chr17 reads, and regenerate .bai
"""
for size, md5, url in bams:
bam = os.path.join(
args.data_dir,
os.path.basename(url).replace('.bam', '_%s.bam' % CHROM))
if not _up_to_date(md5, bam):
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daler/metaseq | metaseq/scripts/download_metaseq_example_data.py | get_gtf | def get_gtf():
"""
Download GTF file from Ensembl, only keeping the chr17 entries.
"""
size, md5, url = GTF
full_gtf = os.path.join(args.data_dir, os.path.basename(url))
subset_gtf = os.path.join(
args.data_dir,
os.path.basename(url).replace('.gtf.gz', '_%s.gtf' % CHROM))
if... | python | def get_gtf():
"""
Download GTF file from Ensembl, only keeping the chr17 entries.
"""
size, md5, url = GTF
full_gtf = os.path.join(args.data_dir, os.path.basename(url))
subset_gtf = os.path.join(
args.data_dir,
os.path.basename(url).replace('.gtf.gz', '_%s.gtf' % CHROM))
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daler/metaseq | metaseq/scripts/download_metaseq_example_data.py | make_db | def make_db():
"""
Create gffutils database
"""
size, md5, fn = DB
if not _up_to_date(md5, fn):
gffutils.create_db(fn.replace('.db', ''), fn, verbose=True, force=True) | python | def make_db():
"""
Create gffutils database
"""
size, md5, fn = DB
if not _up_to_date(md5, fn):
gffutils.create_db(fn.replace('.db', ''), fn, verbose=True, force=True) | [
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daler/metaseq | metaseq/scripts/download_metaseq_example_data.py | cufflinks_conversion | def cufflinks_conversion():
"""
convert Cufflinks output GTF files into tables of score and FPKM.
"""
for size, md5, fn in cufflinks_tables:
fn = os.path.join(args.data_dir, fn)
table = fn.replace('.gtf.gz', '.table')
if not _up_to_date(md5, table):
logger.info("Conve... | python | def cufflinks_conversion():
"""
convert Cufflinks output GTF files into tables of score and FPKM.
"""
for size, md5, fn in cufflinks_tables:
fn = os.path.join(args.data_dir, fn)
table = fn.replace('.gtf.gz', '.table')
if not _up_to_date(md5, table):
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daler/metaseq | metaseq/minibrowser.py | BaseMiniBrowser.plot | def plot(self, feature):
"""
Spawns a new figure showing data for `feature`.
:param feature: A `pybedtools.Interval` object
Using the pybedtools.Interval `feature`, creates figure specified in
:meth:`BaseMiniBrowser.make_fig` and plots data on panels according to
`self.... | python | def plot(self, feature):
"""
Spawns a new figure showing data for `feature`.
:param feature: A `pybedtools.Interval` object
Using the pybedtools.Interval `feature`, creates figure specified in
:meth:`BaseMiniBrowser.make_fig` and plots data on panels according to
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daler/metaseq | metaseq/minibrowser.py | BaseMiniBrowser.example_panel | def example_panel(self, ax, feature):
"""
A example panel that just prints the text of the feature.
"""
txt = '%s:%s-%s' % (feature.chrom, feature.start, feature.stop)
ax.text(0.5, 0.5, txt, transform=ax.transAxes)
return feature | python | def example_panel(self, ax, feature):
"""
A example panel that just prints the text of the feature.
"""
txt = '%s:%s-%s' % (feature.chrom, feature.start, feature.stop)
ax.text(0.5, 0.5, txt, transform=ax.transAxes)
return feature | [
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daler/metaseq | metaseq/minibrowser.py | SignalMiniBrowser.signal_panel | def signal_panel(self, ax, feature):
"""
Plots each genomic signal as a line using the corresponding
plotting_kwargs
"""
for gs, kwargs in zip(self.genomic_signal_objs, self.plotting_kwargs):
x, y = gs.local_coverage(feature, **self.local_coverage_kwargs)
... | python | def signal_panel(self, ax, feature):
"""
Plots each genomic signal as a line using the corresponding
plotting_kwargs
"""
for gs, kwargs in zip(self.genomic_signal_objs, self.plotting_kwargs):
x, y = gs.local_coverage(feature, **self.local_coverage_kwargs)
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daler/metaseq | metaseq/minibrowser.py | GeneModelMiniBrowser.panels | def panels(self):
"""
Add 2 panels to the figure, top for signal and bottom for gene models
"""
ax1 = self.fig.add_subplot(211)
ax2 = self.fig.add_subplot(212, sharex=ax1)
return (ax2, self.gene_panel), (ax1, self.signal_panel) | python | def panels(self):
"""
Add 2 panels to the figure, top for signal and bottom for gene models
"""
ax1 = self.fig.add_subplot(211)
ax2 = self.fig.add_subplot(212, sharex=ax1)
return (ax2, self.gene_panel), (ax1, self.signal_panel) | [
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hfaran/progressive | progressive/examples.py | simple | def simple():
"""Simple example using just the Bar class
This example is intended to show usage of the Bar class at the lowest
level.
"""
MAX_VALUE = 100
# Create our test progress bar
bar = Bar(max_value=MAX_VALUE, fallback=True)
bar.cursor.clear_lines(2)
# Before beginning to d... | python | def simple():
"""Simple example using just the Bar class
This example is intended to show usage of the Bar class at the lowest
level.
"""
MAX_VALUE = 100
# Create our test progress bar
bar = Bar(max_value=MAX_VALUE, fallback=True)
bar.cursor.clear_lines(2)
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hfaran/progressive | progressive/examples.py | tree | def tree():
"""Example showing tree progress view"""
#############
# Test data #
#############
# For this example, we're obviously going to be feeding fictitious data
# to ProgressTree, so here it is
leaf_values = [Value(0) for i in range(6)]
bd_defaults = dict(type=Bar, kwargs=dict(... | python | def tree():
"""Example showing tree progress view"""
#############
# Test data #
#############
# For this example, we're obviously going to be feeding fictitious data
# to ProgressTree, so here it is
leaf_values = [Value(0) for i in range(6)]
bd_defaults = dict(type=Bar, kwargs=dict(... | [
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daler/metaseq | metaseq/plotutils.py | ci_plot | def ci_plot(x, arr, conf=0.95, ax=None, line_kwargs=None, fill_kwargs=None):
"""
Plots the mean and 95% ci for the given array on the given axes
Parameters
----------
x : 1-D array-like
x values for the plot
arr : 2-D array-like
The array to calculate mean and std for
conf... | python | def ci_plot(x, arr, conf=0.95, ax=None, line_kwargs=None, fill_kwargs=None):
"""
Plots the mean and 95% ci for the given array on the given axes
Parameters
----------
x : 1-D array-like
x values for the plot
arr : 2-D array-like
The array to calculate mean and std for
conf... | [
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The array to calculate mean and std for
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Confidence interval to use
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daler/metaseq | metaseq/plotutils.py | add_labels_to_subsets | def add_labels_to_subsets(ax, subset_by, subset_order, text_kwargs=None,
add_hlines=True, hline_kwargs=None):
"""
Helper function for adding labels to subsets within a heatmap.
Assumes that imshow() was called with `subsets` and `subset_order`.
Parameters
----------
a... | python | def add_labels_to_subsets(ax, subset_by, subset_order, text_kwargs=None,
add_hlines=True, hline_kwargs=None):
"""
Helper function for adding labels to subsets within a heatmap.
Assumes that imshow() was called with `subsets` and `subset_order`.
Parameters
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daler/metaseq | metaseq/plotutils.py | calculate_limits | def calculate_limits(array_dict, method='global', percentiles=None, limit=()):
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"""
Calculate limits for a group of arrays in a flexible manner.
Returns a dictionary of calculated (vmin, vmax), with the same keys as
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daler/metaseq | metaseq/plotutils.py | ci | def ci(arr, conf=0.95):
"""
Column-wise confidence interval.
Parameters
----------
arr : array-like
conf : float
Confidence interval
Returns
-------
m : array
column-wise mean
lower : array
lower column-wise confidence bound
upper : array
up... | python | def ci(arr, conf=0.95):
"""
Column-wise confidence interval.
Parameters
----------
arr : array-like
conf : float
Confidence interval
Returns
-------
m : array
column-wise mean
lower : array
lower column-wise confidence bound
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daler/metaseq | metaseq/plotutils.py | nice_log | def nice_log(x):
"""
Uses a log scale but with negative numbers.
:param x: NumPy array
"""
neg = x < 0
xi = np.log2(np.abs(x) + 1)
xi[neg] = -xi[neg]
return xi | python | def nice_log(x):
"""
Uses a log scale but with negative numbers.
:param x: NumPy array
"""
neg = x < 0
xi = np.log2(np.abs(x) + 1)
xi[neg] = -xi[neg]
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daler/metaseq | metaseq/plotutils.py | tip_fdr | def tip_fdr(a, alpha=0.05):
"""
Returns adjusted TIP p-values for a particular `alpha`.
(see :func:`tip_zscores` for more info)
:param a: NumPy array, where each row is the signal for a feature
:param alpha: False discovery rate
"""
zscores = tip_zscores(a)
pvals = stats.norm.pdf(zsco... | python | def tip_fdr(a, alpha=0.05):
"""
Returns adjusted TIP p-values for a particular `alpha`.
(see :func:`tip_zscores` for more info)
:param a: NumPy array, where each row is the signal for a feature
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daler/metaseq | metaseq/plotutils.py | prepare_logged | def prepare_logged(x, y):
"""
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a particu... | python | def prepare_logged(x, y):
"""
Transform `x` and `y` to a log scale while dealing with zeros.
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daler/metaseq | metaseq/plotutils.py | _updatecopy | def _updatecopy(orig, update_with, keys=None, override=False):
"""
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with those keys.
"""
d = orig.copy()
if keys is None:
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if k in... | python | def _updatecopy(orig, update_with, keys=None, override=False):
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daler/metaseq | metaseq/plotutils.py | MarginalHistScatter.append | def append(self, x, y, scatter_kwargs, hist_kwargs=None, xhist_kwargs=None,
yhist_kwargs=None, num_ticks=3, labels=None, hist_share=False,
marginal_histograms=True):
"""
Adds a new scatter to self.scatter_ax as well as marginal histograms
for the same data, borrowin... | python | def append(self, x, y, scatter_kwargs, hist_kwargs=None, xhist_kwargs=None,
yhist_kwargs=None, num_ticks=3, labels=None, hist_share=False,
marginal_histograms=True):
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daler/metaseq | metaseq/plotutils.py | MarginalHistScatter.add_legends | def add_legends(self, xhists=True, yhists=False, scatter=True, **kwargs):
"""
Add legends to axes.
"""
axs = []
if xhists:
axs.extend(self.hxs)
if yhists:
axs.extend(self.hys)
if scatter:
axs.extend(self.ax)
for ax in a... | python | def add_legends(self, xhists=True, yhists=False, scatter=True, **kwargs):
"""
Add legends to axes.
"""
axs = []
if xhists:
axs.extend(self.hxs)
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axs.extend(self.hys)
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daler/metaseq | metaseq/_genomic_signal.py | genomic_signal | def genomic_signal(fn, kind):
"""
Factory function that makes the right class for the file format.
Typically you'll only need this function to create a new genomic signal
object.
:param fn: Filename
:param kind:
String. Format of the file; see
metaseq.genomic_signal._registry.... | python | def genomic_signal(fn, kind):
"""
Factory function that makes the right class for the file format.
Typically you'll only need this function to create a new genomic signal
object.
:param fn: Filename
:param kind:
String. Format of the file; see
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daler/metaseq | metaseq/_genomic_signal.py | BamSignal.genome | def genome(self):
"""
"genome" dictionary ready for pybedtools, based on the BAM header.
"""
# This gets the underlying pysam Samfile object
f = self.adapter.fileobj
d = {}
for ref, length in zip(f.references, f.lengths):
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r... | python | def genome(self):
"""
"genome" dictionary ready for pybedtools, based on the BAM header.
"""
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daler/metaseq | metaseq/_genomic_signal.py | BamSignal.mapped_read_count | def mapped_read_count(self, force=False):
"""
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that file that doesn't start with a "#". If such a file doesn't exist,
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"""
Counts total reads in a BAM file.
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daler/metaseq | metaseq/tableprinter.py | print_2x2_table | def print_2x2_table(table, row_labels, col_labels, fmt="%d"):
"""
Prints a table used for Fisher's exact test. Adds row, column, and grand
totals.
:param table: The four cells of a 2x2 table: [r1c1, r1c2, r2c1, r2c2]
:param row_labels: A length-2 list of row names
:param col_labels: A length-2 ... | python | def print_2x2_table(table, row_labels, col_labels, fmt="%d"):
"""
Prints a table used for Fisher's exact test. Adds row, column, and grand
totals.
:param table: The four cells of a 2x2 table: [r1c1, r1c2, r2c1, r2c2]
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daler/metaseq | metaseq/tableprinter.py | print_row_perc_table | def print_row_perc_table(table, row_labels, col_labels):
"""
given a table, print the percentages rather than the totals
"""
r1c1, r1c2, r2c1, r2c2 = map(float, table)
row1 = r1c1 + r1c2
row2 = r2c1 + r2c2
blocks = [
(r1c1, row1),
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(r2c1, row2),
... | python | def print_row_perc_table(table, row_labels, col_labels):
"""
given a table, print the percentages rather than the totals
"""
r1c1, r1c2, r2c1, r2c2 = map(float, table)
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daler/metaseq | metaseq/tableprinter.py | print_col_perc_table | def print_col_perc_table(table, row_labels, col_labels):
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given a table, print the cols as percentages
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"""
given a table, print the cols as percentages
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hfaran/progressive | progressive/tree.py | ProgressTree.draw | def draw(self, tree, bar_desc=None, save_cursor=True, flush=True):
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hfaran/progressive | progressive/tree.py | ProgressTree.make_room | def make_room(self, tree):
"""Clear lines in terminal below current cursor position as required
This is important to do before drawing to ensure sufficient
room at the bottom of your terminal.
:type tree: dict
:param tree: tree as described in ``BarDescriptor``
"""
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"""Clear lines in terminal below current cursor position as required
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:type tree: dict
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hfaran/progressive | progressive/tree.py | ProgressTree.lines_required | def lines_required(self, tree, count=0):
"""Calculate number of lines required to draw ``tree``"""
if all([
isinstance(tree, dict),
type(tree) != BarDescriptor
]):
return sum(self.lines_required(v, count=count)
for v in tree.values()) + ... | python | def lines_required(self, tree, count=0):
"""Calculate number of lines required to draw ``tree``"""
if all([
isinstance(tree, dict),
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]):
return sum(self.lines_required(v, count=count)
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hfaran/progressive | progressive/tree.py | ProgressTree._calculate_values | def _calculate_values(self, tree, bar_d):
"""Calculate values for drawing bars of non-leafs in ``tree``
Recurses through ``tree``, replaces ``dict``s with
``(BarDescriptor, dict)`` so ``ProgressTree._draw`` can use
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"""
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"""Calculate values for drawing bars of non-leafs in ``tree``
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hfaran/progressive | progressive/tree.py | ProgressTree._draw | def _draw(self, tree, indent=0):
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]):
for k, v in sorted(tree.items()):
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"""Recurse through ``tree`` and draw all nodes"""
if all([
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]):
for k, v in sorted(tree.items()):
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daler/metaseq | metaseq/persistence.py | load_features_and_arrays | def load_features_and_arrays(prefix, mmap_mode='r'):
"""
Returns the features and NumPy arrays that were saved with
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Parameters
----------
prefix : str
Path to where data are saved
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Mode in which to memory-ma... | python | def load_features_and_arrays(prefix, mmap_mode='r'):
"""
Returns the features and NumPy arrays that were saved with
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----------
prefix : str
Path to where data are saved
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daler/metaseq | metaseq/persistence.py | save_features_and_arrays | def save_features_and_arrays(features, arrays, prefix, compressed=False,
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"""
Saves NumPy arrays of processed data, along with the features that
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hthiery/python-fritzhome | pyfritzhome/cli.py | list_all | def list_all(fritz, args):
"""Command that prints all device information."""
devices = fritz.get_devices()
for device in devices:
print('#' * 30)
print('name=%s' % device.name)
print(' ain=%s' % device.ain)
print(' id=%s' % device.identifier)
print(' productname=%... | python | def list_all(fritz, args):
"""Command that prints all device information."""
devices = fritz.get_devices()
for device in devices:
print('#' * 30)
print('name=%s' % device.name)
print(' ain=%s' % device.ain)
print(' id=%s' % device.identifier)
print(' productname=%... | [
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hthiery/python-fritzhome | pyfritzhome/cli.py | device_statistics | def device_statistics(fritz, args):
"""Command that prints the device statistics."""
stats = fritz.get_device_statistics(args.ain)
print(stats) | python | def device_statistics(fritz, args):
"""Command that prints the device statistics."""
stats = fritz.get_device_statistics(args.ain)
print(stats) | [
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daler/metaseq | metaseq/helpers.py | chunker | def chunker(f, n):
"""
Utility function to split iterable `f` into `n` chunks
"""
f = iter(f)
x = []
while 1:
if len(x) < n:
try:
x.append(f.next())
except StopIteration:
if len(x) > 0:
yield tuple(x)
... | python | def chunker(f, n):
"""
Utility function to split iterable `f` into `n` chunks
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f = iter(f)
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daler/metaseq | metaseq/helpers.py | split_feature | def split_feature(f, n):
"""
Split an interval into `n` roughly equal portions
"""
if not isinstance(n, int):
raise ValueError('n must be an integer')
orig_feature = copy(f)
step = (f.stop - f.start) / n
for i in range(f.start, f.stop, step):
f = copy(orig_feature)
st... | python | def split_feature(f, n):
"""
Split an interval into `n` roughly equal portions
"""
if not isinstance(n, int):
raise ValueError('n must be an integer')
orig_feature = copy(f)
step = (f.stop - f.start) / n
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daler/metaseq | metaseq/helpers.py | tointerval | def tointerval(s):
"""
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"""
if isinstance(s, basestring):
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"""
If string, then convert to an interval; otherwise just return the input
"""
if isinstance(s, basestring):
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hfaran/progressive | progressive/bar.py | Bar.max_width | def max_width(self):
"""Get maximum width of progress bar
:rtype: int
:returns: Maximum column width of progress bar
"""
value, unit = float(self._width_str[:-1]), self._width_str[-1]
ensure(unit in ["c", "%"], ValueError,
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"""Get maximum width of progress bar
:rtype: int
:returns: Maximum column width of progress bar
"""
value, unit = float(self._width_str[:-1]), self._width_str[-1]
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hfaran/progressive | progressive/bar.py | Bar.full_line_width | def full_line_width(self):
"""Find actual length of bar_str
e.g., Progress [ | ] 10/10
"""
bar_str_len = sum([
self._indent,
((len(self.title) + 1) if self._title_pos in ["left", "right"]
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len(self.start... | python | def full_line_width(self):
"""Find actual length of bar_str
e.g., Progress [ | ] 10/10
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hfaran/progressive | progressive/bar.py | Bar._supports_colors | def _supports_colors(term, raise_err, colors):
"""Check if ``term`` supports ``colors``
:raises ColorUnsupportedError: This is raised if ``raise_err``
is ``False`` and a color in ``colors`` is unsupported by ``term``
:type raise_err: bool
:param raise_err: Set to ``False`` t... | python | def _supports_colors(term, raise_err, colors):
"""Check if ``term`` supports ``colors``
:raises ColorUnsupportedError: This is raised if ``raise_err``
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hfaran/progressive | progressive/bar.py | Bar._get_format_callable | def _get_format_callable(term, color, back_color):
"""Get string-coloring callable
Get callable for string output using ``color`` on ``back_color``
on ``term``
:param term: blessings.Terminal instance
:param color: Color that callable will color the string it's passed
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"""Get string-coloring callable
Get callable for string output using ``color`` on ``back_color``
on ``term``
:param term: blessings.Terminal instance
:param color: Color that callable will color the string it's passed
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hfaran/progressive | progressive/bar.py | Bar.draw | def draw(self, value, newline=True, flush=True):
"""Draw the progress bar
:type value: int
:param value: Progress value relative to ``self.max_value``
:type newline: bool
:param newline: If this is set, a newline will be written after drawing
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"""Draw the progress bar
:type value: int
:param value: Progress value relative to ``self.max_value``
:type newline: bool
:param newline: If this is set, a newline will be written after drawing
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hthiery/python-fritzhome | pyfritzhome/fritzhome.py | get_text | def get_text(nodelist):
"""Get the value from a text node."""
value = []
for node in nodelist:
if node.nodeType == node.TEXT_NODE:
value.append(node.data)
return ''.join(value) | python | def get_text(nodelist):
"""Get the value from a text node."""
value = []
for node in nodelist:
if node.nodeType == node.TEXT_NODE:
value.append(node.data)
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hthiery/python-fritzhome | pyfritzhome/fritzhome.py | Fritzhome._request | def _request(self, url, params=None, timeout=10):
"""Send a request with parameters."""
rsp = self._session.get(url, params=params, timeout=timeout)
rsp.raise_for_status()
return rsp.text.strip() | python | def _request(self, url, params=None, timeout=10):
"""Send a request with parameters."""
rsp = self._session.get(url, params=params, timeout=timeout)
rsp.raise_for_status()
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hthiery/python-fritzhome | pyfritzhome/fritzhome.py | Fritzhome._login_request | def _login_request(self, username=None, secret=None):
"""Send a login request with paramerters."""
url = 'http://' + self._host + '/login_sid.lua'
params = {}
if username:
params['username'] = username
if secret:
params['response'] = secret
plain ... | python | def _login_request(self, username=None, secret=None):
"""Send a login request with paramerters."""
url = 'http://' + self._host + '/login_sid.lua'
params = {}
if username:
params['username'] = username
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params['response'] = secret
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hthiery/python-fritzhome | pyfritzhome/fritzhome.py | Fritzhome._logout_request | def _logout_request(self):
"""Send a logout request."""
_LOGGER.debug('logout')
url = 'http://' + self._host + '/login_sid.lua'
params = {
'security:command/logout': '1',
'sid': self._sid
}
self._request(url, params) | python | def _logout_request(self):
"""Send a logout request."""
_LOGGER.debug('logout')
url = 'http://' + self._host + '/login_sid.lua'
params = {
'security:command/logout': '1',
'sid': self._sid
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hthiery/python-fritzhome | pyfritzhome/fritzhome.py | Fritzhome._create_login_secret | def _create_login_secret(challenge, password):
"""Create a login secret."""
to_hash = (challenge + '-' + password).encode('UTF-16LE')
hashed = hashlib.md5(to_hash).hexdigest()
return '{0}-{1}'.format(challenge, hashed) | python | def _create_login_secret(challenge, password):
"""Create a login secret."""
to_hash = (challenge + '-' + password).encode('UTF-16LE')
hashed = hashlib.md5(to_hash).hexdigest()
return '{0}-{1}'.format(challenge, hashed) | [
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hthiery/python-fritzhome | pyfritzhome/fritzhome.py | Fritzhome._aha_request | def _aha_request(self, cmd, ain=None, param=None, rf=str):
"""Send an AHA request."""
url = 'http://' + self._host + '/webservices/homeautoswitch.lua'
params = {
'switchcmd': cmd,
'sid': self._sid
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params['param'] = param
if ... | python | def _aha_request(self, cmd, ain=None, param=None, rf=str):
"""Send an AHA request."""
url = 'http://' + self._host + '/webservices/homeautoswitch.lua'
params = {
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hthiery/python-fritzhome | pyfritzhome/fritzhome.py | Fritzhome.login | def login(self):
"""Login and get a valid session ID."""
try:
(sid, challenge) = self._login_request()
if sid == '0000000000000000':
secret = self._create_login_secret(challenge, self._password)
(sid2, challenge) = self._login_request(username=self... | python | def login(self):
"""Login and get a valid session ID."""
try:
(sid, challenge) = self._login_request()
if sid == '0000000000000000':
secret = self._create_login_secret(challenge, self._password)
(sid2, challenge) = self._login_request(username=self... | [
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hthiery/python-fritzhome | pyfritzhome/fritzhome.py | Fritzhome.get_device_elements | def get_device_elements(self):
"""Get the DOM elements for the device list."""
plain = self._aha_request('getdevicelistinfos')
dom = xml.dom.minidom.parseString(plain)
_LOGGER.debug(dom)
return dom.getElementsByTagName("device") | python | def get_device_elements(self):
"""Get the DOM elements for the device list."""
plain = self._aha_request('getdevicelistinfos')
dom = xml.dom.minidom.parseString(plain)
_LOGGER.debug(dom)
return dom.getElementsByTagName("device") | [
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hthiery/python-fritzhome | pyfritzhome/fritzhome.py | Fritzhome.get_device_element | def get_device_element(self, ain):
"""Get the DOM element for the specified device."""
elements = self.get_device_elements()
for element in elements:
if element.getAttribute('identifier') == ain:
return element
return None | python | def get_device_element(self, ain):
"""Get the DOM element for the specified device."""
elements = self.get_device_elements()
for element in elements:
if element.getAttribute('identifier') == ain:
return element
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hthiery/python-fritzhome | pyfritzhome/fritzhome.py | Fritzhome.get_devices | def get_devices(self):
"""Get the list of all known devices."""
devices = []
for element in self.get_device_elements():
device = FritzhomeDevice(self, node=element)
devices.append(device)
return devices | python | def get_devices(self):
"""Get the list of all known devices."""
devices = []
for element in self.get_device_elements():
device = FritzhomeDevice(self, node=element)
devices.append(device)
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hthiery/python-fritzhome | pyfritzhome/fritzhome.py | Fritzhome.get_device_by_ain | def get_device_by_ain(self, ain):
"""Returns a device specified by the AIN."""
devices = self.get_devices()
for device in devices:
if device.ain == ain:
return device | python | def get_device_by_ain(self, ain):
"""Returns a device specified by the AIN."""
devices = self.get_devices()
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if device.ain == ain:
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hthiery/python-fritzhome | pyfritzhome/fritzhome.py | Fritzhome.set_target_temperature | def set_target_temperature(self, ain, temperature):
"""Set the thermostate target temperature."""
param = 16 + ((float(temperature) - 8) * 2)
if param < min(range(16, 56)):
param = 253
elif param > max(range(16, 56)):
param = 254
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"""Set the thermostate target temperature."""
param = 16 + ((float(temperature) - 8) * 2)
if param < min(range(16, 56)):
param = 253
elif param > max(range(16, 56)):
param = 254
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hthiery/python-fritzhome | pyfritzhome/fritzhome.py | FritzhomeDevice.update | def update(self):
"""Update the device values."""
node = self._fritz.get_device_element(self.ain)
self._update_from_node(node) | python | def update(self):
"""Update the device values."""
node = self._fritz.get_device_element(self.ain)
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hthiery/python-fritzhome | pyfritzhome/fritzhome.py | FritzhomeDevice.get_hkr_state | def get_hkr_state(self):
"""Get the thermostate state."""
self.update()
try:
return {
126.5: 'off',
127.0: 'on',
self.eco_temperature: 'eco',
self.comfort_temperature: 'comfort'
}[self.target_temperature]
... | python | def get_hkr_state(self):
"""Get the thermostate state."""
self.update()
try:
return {
126.5: 'off',
127.0: 'on',
self.eco_temperature: 'eco',
self.comfort_temperature: 'comfort'
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hthiery/python-fritzhome | pyfritzhome/fritzhome.py | FritzhomeDevice.set_hkr_state | def set_hkr_state(self, state):
"""Set the state of the thermostat.
Possible values for state are: 'on', 'off', 'comfort', 'eco'.
"""
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"""Set the state of the thermostat.
Possible values for state are: 'on', 'off', 'comfort', 'eco'.
"""
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hfaran/progressive | progressive/cursor.py | Cursor.write | def write(self, s):
"""Writes ``s`` to the terminal output stream
Writes can be disabled by setting the environment variable
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"""
should_write_s = os.getenv('PROGRESSIVE_NOWRITE') != "True"
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self._stream.... | python | def write(self, s):
"""Writes ``s`` to the terminal output stream
Writes can be disabled by setting the environment variable
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"""
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hfaran/progressive | progressive/cursor.py | Cursor.save | def save(self):
"""Saves current cursor position, so that it can be restored later"""
self.write(self.term.save)
self._saved = True | python | def save(self):
"""Saves current cursor position, so that it can be restored later"""
self.write(self.term.save)
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hfaran/progressive | progressive/cursor.py | Cursor.newline | def newline(self):
"""Effects a newline by moving the cursor down and clearing"""
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daler/metaseq | metaseq/results_table.py | ResultsTable.attach_db | def attach_db(self, db):
"""
Attach a gffutils.FeatureDB for access to features.
Useful if you want to attach a db after this instance has already been
created.
Parameters
----------
db : gffutils.FeatureDB
"""
if db is not None:
if i... | python | def attach_db(self, db):
"""
Attach a gffutils.FeatureDB for access to features.
Useful if you want to attach a db after this instance has already been
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Parameters
----------
db : gffutils.FeatureDB
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daler/metaseq | metaseq/results_table.py | ResultsTable.features | def features(self, ignore_unknown=False):
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Generator of features.
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daler/metaseq | metaseq/results_table.py | ResultsTable.reindex_to | def reindex_to(self, x, attribute="Name"):
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----------
x : str or pybedtools.BedTool
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"""
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daler/metaseq | metaseq/results_table.py | ResultsTable.align_with | def align_with(self, other):
"""
Align the dataframe's index with another.
"""
return self.__class__(self.data.reindex_like(other), **self._kwargs) | python | def align_with(self, other):
"""
Align the dataframe's index with another.
"""
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daler/metaseq | metaseq/results_table.py | ResultsTable.radviz | def radviz(self, column_names, transforms=dict(), **kwargs):
"""
Radviz plot.
Useful for exploratory visualization, a radviz plot can show
multivariate data in 2D. Conceptually, the variables (here, specified
in `column_names`) are distributed evenly around the unit circle. Th... | python | def radviz(self, column_names, transforms=dict(), **kwargs):
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daler/metaseq | metaseq/results_table.py | ResultsTable.strip_unknown_features | def strip_unknown_features(self):
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useful if the database was created from a different one than was used
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"""
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"""
Remove features not found in the `gffutils.FeatureDB`. This will
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useful if the database was created from a different one than was used
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daler/metaseq | metaseq/results_table.py | ResultsTable.genes_with_peak | def genes_with_peak(self, peaks, transform_func=None, split=False,
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Returns a boolean index of genes that have a peak nearby.
Parameters
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daler/metaseq | metaseq/results_table.py | DifferentialExpressionResults.enriched | def enriched(self, thresh=0.05, idx=True):
"""
Enriched features.
{threshdoc}
"""
return self.upregulated(thresh=thresh, idx=idx) | python | def enriched(self, thresh=0.05, idx=True):
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Enriched features.
{threshdoc}
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daler/metaseq | metaseq/results_table.py | DifferentialExpressionResults.upregulated | def upregulated(self, thresh=0.05, idx=True):
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"""
Upregulated features.
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daler/metaseq | metaseq/results_table.py | DifferentialExpressionResults.disenriched | def disenriched(self, thresh=0.05, idx=True):
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Disenriched features.
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daler/metaseq | metaseq/results_table.py | DESeqResults.colormapped_bedfile | def colormapped_bedfile(self, genome, cmap=None):
"""
Create a BED file with padj encoded as color
Features will be colored according to adjusted pval (phred
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Parameters
----------
cmap : matplotlib col... | python | def colormapped_bedfile(self, genome, cmap=None):
"""
Create a BED file with padj encoded as color
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daler/metaseq | metaseq/array_helpers.py | _array_parallel | def _array_parallel(fn, cls, genelist, chunksize=250, processes=1, **kwargs):
"""
Returns an array of genes in `genelist`, using `bins` bins.
`genelist` is a list of pybedtools.Interval objects
Splits `genelist` into pieces of size `chunksize`, creating an array
for each chunk and merging ret
... | python | def _array_parallel(fn, cls, genelist, chunksize=250, processes=1, **kwargs):
"""
Returns an array of genes in `genelist`, using `bins` bins.
`genelist` is a list of pybedtools.Interval objects
Splits `genelist` into pieces of size `chunksize`, creating an array
for each chunk and merging ret
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daler/metaseq | metaseq/array_helpers.py | _array_star | def _array_star(args):
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"""
fn, cls, genelist, kwargs = args
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"""
Unpacks the tuple `args` and calls _array. Needed to pass multiple args to
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fn, cls, genelist, kwargs = args
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daler/metaseq | metaseq/arrayify.py | Binner.to_npz | def to_npz(self, bigwig, metric='mean0', outdir=None):
"""
Bin data for bigwig and save to disk.
The .npz file will have the pattern
{outdir}/{bigwig}.{chrom}.{windowsize}.{metric}.npz and will have two
arrays, x (genomic coordinates of midpoints of each window) and
y (m... | python | def to_npz(self, bigwig, metric='mean0', outdir=None):
"""
Bin data for bigwig and save to disk.
The .npz file will have the pattern
{outdir}/{bigwig}.{chrom}.{windowsize}.{metric}.npz and will have two
arrays, x (genomic coordinates of midpoints of each window) and
y (m... | [
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daler/metaseq | metaseq/integration/signal_comparison.py | compare | def compare(signal1, signal2, features, outfn, comparefunc=np.subtract,
batchsize=5000, array_kwargs=None, verbose=False):
"""
Compares two genomic signal objects and outputs results as a bedGraph file.
Can be used for entire genome-wide comparisons due to its parallel nature.
Typical usage wou... | python | def compare(signal1, signal2, features, outfn, comparefunc=np.subtract,
batchsize=5000, array_kwargs=None, verbose=False):
"""
Compares two genomic signal objects and outputs results as a bedGraph file.
Can be used for entire genome-wide comparisons due to its parallel nature.
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moble/h5py_cache | __init__.py | _find_next_prime | def _find_next_prime(N):
"""Find next prime >= N"""
def is_prime(n):
if n % 2 == 0:
return False
i = 3
while i * i <= n:
if n % i:
i += 2
else:
return False
return True
if N < 3:
return 2
if N % 2... | python | def _find_next_prime(N):
"""Find next prime >= N"""
def is_prime(n):
if n % 2 == 0:
return False
i = 3
while i * i <= n:
if n % i:
i += 2
else:
return False
return True
if N < 3:
return 2
if N % 2... | [
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moble/h5py_cache | __init__.py | File | def File(name, mode='a', chunk_cache_mem_size=1024**2, w0=0.75, n_cache_chunks=None, **kwds):
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This function is basically just a wrapper around the usual h5py.File constructor,
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Parameters
----------
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"""Create h5py File object with cache specification
This function is basically just a wrapper around the usual h5py.File constructor,
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daler/metaseq | metaseq/integration/chipseq.py | save | def save(c, prefix, relative_paths=True):
"""
Save data from a Chipseq object.
Parameters
----------
c : Chipseq object
Chipseq object, most likely after calling the `diffed_array` method
prefix : str
Prefix, including any leading directory paths, to save the data.
relati... | python | def save(c, prefix, relative_paths=True):
"""
Save data from a Chipseq object.
Parameters
----------
c : Chipseq object
Chipseq object, most likely after calling the `diffed_array` method
prefix : str
Prefix, including any leading directory paths, to save the data.
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daler/metaseq | metaseq/integration/chipseq.py | xcorr | def xcorr(x, y, maxlags):
"""
Streamlined version of matplotlib's `xcorr`, without the plots.
:param x, y: NumPy arrays to cross-correlate
:param maxlags: Max number of lags; result will be `2*maxlags+1` in length
"""
xlen = len(x)
ylen = len(y)
assert xlen == ylen
c = np.correlate... | python | def xcorr(x, y, maxlags):
"""
Streamlined version of matplotlib's `xcorr`, without the plots.
:param x, y: NumPy arrays to cross-correlate
:param maxlags: Max number of lags; result will be `2*maxlags+1` in length
"""
xlen = len(x)
ylen = len(y)
assert xlen == ylen
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daler/metaseq | metaseq/integration/chipseq.py | Chipseq.plot | def plot(self, x, row_order=None, imshow_kwargs=None, strip=True):
"""
Plot the scaled ChIP-seq data.
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"""
Plot the scaled ChIP-seq data.
:param x: X-axis to use (e.g, for TSS +/- 1kb with 100 bins, this would
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daler/metaseq | metaseq/integration/chipseq.py | Chipseq.callback | def callback(self, event):
"""
Callback function to spawn a mini-browser when a feature is clicked.
"""
artist = event.artist
ind = artist.ind
limit = 5
browser = True
if len(event.ind) > limit:
print "more than %s genes selected; not spawning ... | python | def callback(self, event):
"""
Callback function to spawn a mini-browser when a feature is clicked.
"""
artist = event.artist
ind = artist.ind
limit = 5
browser = True
if len(event.ind) > limit:
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h2non/paco | paco/observer.py | Observer.remove | def remove(self, event=None):
"""
Remove all the registered observers for the given event name.
Arguments:
event (str): event name to remove.
"""
observers = self._pool.get(event)
if observers:
self._pool[event] = [] | python | def remove(self, event=None):
"""
Remove all the registered observers for the given event name.
Arguments:
event (str): event name to remove.
"""
observers = self._pool.get(event)
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h2non/paco | paco/observer.py | Observer.trigger | def trigger(self, event, *args, **kw):
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# If no observers registered for the event, do no-op
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Triggers event observers for the given event name,
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h2non/paco | paco/until.py | until | def until(coro, coro_test, assert_coro=None, *args, **kw):
"""
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This function is the inverse of `paco.whilst()`.
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coro (coroutinefunction): coroutine function to execute.
... | python | def until(coro, coro_test, assert_coro=None, *args, **kw):
"""
Repeatedly call `coro` coroutine function until `coro_test` returns `True`.
This function is the inverse of `paco.whilst()`.
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coro (coroutinefunction): coroutine function to execute.
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h2non/paco | paco/curry.py | curry | def curry(arity_or_fn=None, ignore_kwargs=False, evaluator=None, *args, **kw):
"""
Creates a function that accepts one or more arguments of a function and
either invokes func returning its result if at least arity number of
arguments have been provided, or returns a function that accepts the
remaini... | python | def curry(arity_or_fn=None, ignore_kwargs=False, evaluator=None, *args, **kw):
"""
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h2non/paco | paco/compose.py | compose | def compose(*coros):
"""
Creates a coroutine function based on the composition of the passed
coroutine functions.
Each function consumes the yielded result of the coroutine that follows.
Composing coroutine functions f(), g(), and h() would produce
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Arguments:
... | python | def compose(*coros):
"""
Creates a coroutine function based on the composition of the passed
coroutine functions.
Each function consumes the yielded result of the coroutine that follows.
Composing coroutine functions f(), g(), and h() would produce
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Arguments:
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kalbhor/MusicNow | musicnow/command_line.py | add_config | def add_config():
"""
Prompts user for API keys, adds them in an .ini file stored in the same
location as that of the script
"""
genius_key = input('Enter Genius key : ')
bing_key = input('Enter Bing key : ')
CONFIG['keys']['bing_key'] = bing_key
CONFIG['keys']['genius_key'] = genius_k... | python | def add_config():
"""
Prompts user for API keys, adds them in an .ini file stored in the same
location as that of the script
"""
genius_key = input('Enter Genius key : ')
bing_key = input('Enter Bing key : ')
CONFIG['keys']['bing_key'] = bing_key
CONFIG['keys']['genius_key'] = genius_k... | [
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kalbhor/MusicNow | musicnow/command_line.py | get_tracks_from_album | def get_tracks_from_album(album_name):
'''
Gets tracks from an album using Spotify's API
'''
spotify = spotipy.Spotify()
album = spotify.search(q='album:' + album_name, limit=1)
album_id = album['tracks']['items'][0]['album']['id']
results = spotify.album_tracks(album_id=str(album_id))
... | python | def get_tracks_from_album(album_name):
'''
Gets tracks from an album using Spotify's API
'''
spotify = spotipy.Spotify()
album = spotify.search(q='album:' + album_name, limit=1)
album_id = album['tracks']['items'][0]['album']['id']
results = spotify.album_tracks(album_id=str(album_id))
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kalbhor/MusicNow | musicnow/command_line.py | get_url | def get_url(song_input, auto):
'''
Provides user with a list of songs to choose from
returns the url of chosen song.
'''
youtube_list = OrderedDict()
num = 0 # List of songs index
html = requests.get("https://www.youtube.com/results",
params={'search_query': song_in... | python | def get_url(song_input, auto):
'''
Provides user with a list of songs to choose from
returns the url of chosen song.
'''
youtube_list = OrderedDict()
num = 0 # List of songs index
html = requests.get("https://www.youtube.com/results",
params={'search_query': song_in... | [
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kalbhor/MusicNow | musicnow/command_line.py | prompt | def prompt(youtube_list):
'''
Prompts for song number from list of songs
'''
option = int(input('\nEnter song number > '))
try:
song_url = list(youtube_list.values())[option - 1]
song_title = list(youtube_list.keys())[option - 1]
except IndexError:
log.log_error('Invalid... | python | def prompt(youtube_list):
'''
Prompts for song number from list of songs
'''
option = int(input('\nEnter song number > '))
try:
song_url = list(youtube_list.values())[option - 1]
song_title = list(youtube_list.keys())[option - 1]
except IndexError:
log.log_error('Invalid... | [
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kalbhor/MusicNow | musicnow/command_line.py | main | def main():
'''
Starts here, handles arguments
'''
system('clear') # Must be system('cls') for windows
setup()
parser = argparse.ArgumentParser(
description='Download songs with album art and metadata!')
parser.add_argument('-c', '--config', action='store_true',
... | python | def main():
'''
Starts here, handles arguments
'''
system('clear') # Must be system('cls') for windows
setup()
parser = argparse.ArgumentParser(
description='Download songs with album art and metadata!')
parser.add_argument('-c', '--config', action='store_true',
... | [
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vpelletier/python-hidraw | hidraw/__init__.py | HIDRaw.getRawReportDescriptor | def getRawReportDescriptor(self):
"""
Return a binary string containing the raw HID report descriptor.
"""
descriptor = _hidraw_report_descriptor()
size = ctypes.c_uint()
self._ioctl(_HIDIOCGRDESCSIZE, size, True)
descriptor.size = size
self._ioctl(_HIDIOC... | python | def getRawReportDescriptor(self):
"""
Return a binary string containing the raw HID report descriptor.
"""
descriptor = _hidraw_report_descriptor()
size = ctypes.c_uint()
self._ioctl(_HIDIOCGRDESCSIZE, size, True)
descriptor.size = size
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vpelletier/python-hidraw | hidraw/__init__.py | HIDRaw.getName | def getName(self, length=512):
"""
Returns device name as an unicode object.
"""
name = ctypes.create_string_buffer(length)
self._ioctl(_HIDIOCGRAWNAME(length), name, True)
return name.value.decode('UTF-8') | python | def getName(self, length=512):
"""
Returns device name as an unicode object.
"""
name = ctypes.create_string_buffer(length)
self._ioctl(_HIDIOCGRAWNAME(length), name, True)
return name.value.decode('UTF-8') | [
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vpelletier/python-hidraw | hidraw/__init__.py | HIDRaw.getPhysicalAddress | def getPhysicalAddress(self, length=512):
"""
Returns device physical address as a string.
See hidraw documentation for value signification, as it depends on
device's bus type.
"""
name = ctypes.create_string_buffer(length)
self._ioctl(_HIDIOCGRAWPHYS(length), nam... | python | def getPhysicalAddress(self, length=512):
"""
Returns device physical address as a string.
See hidraw documentation for value signification, as it depends on
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"""
name = ctypes.create_string_buffer(length)
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vpelletier/python-hidraw | hidraw/__init__.py | HIDRaw.sendFeatureReport | def sendFeatureReport(self, report, report_num=0):
"""
Send a feature report.
"""
length = len(report) + 1
buf = bytearray(length)
buf[0] = report_num
buf[1:] = report
self._ioctl(
_HIDIOCSFEATURE(length),
(ctypes.c_char * length).f... | python | def sendFeatureReport(self, report, report_num=0):
"""
Send a feature report.
"""
length = len(report) + 1
buf = bytearray(length)
buf[0] = report_num
buf[1:] = report
self._ioctl(
_HIDIOCSFEATURE(length),
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