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jrief/djangocms-cascade | cmsplugin_cascade/mixins.py | CascadePluginMixin.get_html_tag_attributes | def get_html_tag_attributes(cls, instance):
"""
Returns a dictionary of attributes, which shall be added to the current HTML tag.
This method normally is called by the models's property method ``html_tag_ attributes``,
which enriches the HTML tag with those attributes converted to a list... | python | def get_html_tag_attributes(cls, instance):
"""
Returns a dictionary of attributes, which shall be added to the current HTML tag.
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jrief/djangocms-cascade | cmsplugin_cascade/widgets.py | CascadingSizeWidgetMixin.compile_validation_pattern | def compile_validation_pattern(self, units=None):
"""
Assure that passed in units are valid size units, or if missing, use all possible units.
Return a tuple with a regular expression to be used for validating and an error message
in case this validation failed.
"""
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"""
Assure that passed in units are valid size units, or if missing, use all possible units.
Return a tuple with a regular expression to be used for validating and an error message
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jrief/djangocms-cascade | cmsplugin_cascade/sphinx/cms_menus.py | DocumentationMenu.get_nodes | def get_nodes(self, request):
"""
This method is used to build the menu tree.
"""
nodes = []
docsmap_file = os.path.join(settings.SPHINX_DOCS_ROOT, 'docsmap.json')
if not os.path.exists(docsmap_file):
return nodes
with io.open(docsmap_file) as fh:
... | python | def get_nodes(self, request):
"""
This method is used to build the menu tree.
"""
nodes = []
docsmap_file = os.path.join(settings.SPHINX_DOCS_ROOT, 'docsmap.json')
if not os.path.exists(docsmap_file):
return nodes
with io.open(docsmap_file) as fh:
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jrief/djangocms-cascade | cmsplugin_cascade/link/forms.py | LinkForm.unset_required_for | def unset_required_for(cls, sharable_fields):
"""
Fields borrowed by `SharedGlossaryAdmin` to build its temporary change form, only are
required if they are declared in `sharable_fields`. Otherwise just deactivate them.
"""
if 'link_content' in cls.base_fields and 'link_content' ... | python | def unset_required_for(cls, sharable_fields):
"""
Fields borrowed by `SharedGlossaryAdmin` to build its temporary change form, only are
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"""
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jrief/djangocms-cascade | cmsplugin_cascade/models.py | CascadePage.assure_relation | def assure_relation(cls, cms_page):
"""
Assure that we have a foreign key relation, pointing from CascadePage onto CMSPage.
"""
try:
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except cls.DoesNotExist:
cls.objects.create(extended_object=cms_page) | python | def assure_relation(cls, cms_page):
"""
Assure that we have a foreign key relation, pointing from CascadePage onto CMSPage.
"""
try:
cms_page.cascadepage
except cls.DoesNotExist:
cls.objects.create(extended_object=cms_page) | [
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jrief/djangocms-cascade | cmsplugin_cascade/bootstrap3/utils.py | reduce_breakpoints | def reduce_breakpoints(plugin, field_name, request=None, obj=None):
"""
Narrow down the number of breakpoints in the widget of the named glossary_field. This is useful
in case the container was defined with a subset of these breakpoints: xs, sm, md, lg.
"""
if not isinstance(plugin, CascadePluginBas... | python | def reduce_breakpoints(plugin, field_name, request=None, obj=None):
"""
Narrow down the number of breakpoints in the widget of the named glossary_field. This is useful
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jrief/djangocms-cascade | cmsplugin_cascade/bootstrap3/utils.py | compute_media_queries | def compute_media_queries(element):
"""
For e given Cascade element, compute the current media queries for each breakpoint,
even for nested containers, rows and columns.
"""
parent_glossary = element.get_parent_glossary()
# compute the max width and the required media queries for each chosen bre... | python | def compute_media_queries(element):
"""
For e given Cascade element, compute the current media queries for each breakpoint,
even for nested containers, rows and columns.
"""
parent_glossary = element.get_parent_glossary()
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jrief/djangocms-cascade | cmsplugin_cascade/bootstrap3/utils.py | get_image_tags | def get_image_tags(context, instance, options):
"""
Create a context returning the tags to render an <img ...> element:
``sizes``, ``srcset``, a fallback ``src`` and if required inline styles.
"""
if hasattr(instance, 'image') and hasattr(instance.image, 'exif'):
aspect_ratio = compute_aspec... | python | def get_image_tags(context, instance, options):
"""
Create a context returning the tags to render an <img ...> element:
``sizes``, ``srcset``, a fallback ``src`` and if required inline styles.
"""
if hasattr(instance, 'image') and hasattr(instance.image, 'exif'):
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jrief/djangocms-cascade | cmsplugin_cascade/bootstrap3/utils.py | get_picture_elements | def get_picture_elements(context, instance):
"""
Create a context, used to render a <picture> together with all its ``<source>`` elements:
It returns a list of HTML elements, each containing the information to render a ``<source>``
element.
The purpose of this HTML entity is to display images with a... | python | def get_picture_elements(context, instance):
"""
Create a context, used to render a <picture> together with all its ``<source>`` elements:
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jrief/djangocms-cascade | cmsplugin_cascade/bootstrap4/card.py | BootstrapCardPlugin.get_child_classes | def get_child_classes(cls, slot, page, instance=None):
"""Restrict child classes of Card to one of each: Header, Body and Footer"""
child_classes = super(BootstrapCardPlugin, cls).get_child_classes(slot, page, instance)
# allow only one child of type Header, Body, Footer
for child in ins... | python | def get_child_classes(cls, slot, page, instance=None):
"""Restrict child classes of Card to one of each: Header, Body and Footer"""
child_classes = super(BootstrapCardPlugin, cls).get_child_classes(slot, page, instance)
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jrief/djangocms-cascade | cmsplugin_cascade/extra_fields/admin.py | PluginExtraFieldsAdmin.get_form | def get_form(self, request, obj=None, **kwargs):
"""
Build the form used for changing the model.
"""
kwargs.update(widgets={
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"""
Build the form used for changing the model.
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jrief/djangocms-cascade | cmsplugin_cascade/fields.py | GlossaryField.get_element_ids | def get_element_ids(self, prefix_id):
"""
Returns a single or a list of element ids, one for each input widget of this field
"""
if isinstance(self.widget, widgets.MultiWidget):
ids = ['{0}_{1}_{2}'.format(prefix_id, self.name, field_name) for field_name in self.widget]
... | python | def get_element_ids(self, prefix_id):
"""
Returns a single or a list of element ids, one for each input widget of this field
"""
if isinstance(self.widget, widgets.MultiWidget):
ids = ['{0}_{1}_{2}'.format(prefix_id, self.name, field_name) for field_name in self.widget]
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jrief/djangocms-cascade | examples/bs4demo/utils.py | find_django_migrations_module | def find_django_migrations_module(module_name):
""" Tries to locate <module_name>.migrations_django (without actually importing it).
Appends either ".migrations_django" or ".migrations" to module_name.
For details why:
https://docs.djangoproject.com/en/1.7/topics/migrations/#libraries-third-party-apps... | python | def find_django_migrations_module(module_name):
""" Tries to locate <module_name>.migrations_django (without actually importing it).
Appends either ".migrations_django" or ".migrations" to module_name.
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jrief/djangocms-cascade | cmsplugin_cascade/segmentation/mixins.py | EmulateUserModelMixin.get_context_override | def get_context_override(self, request):
"""
Override the request object with an emulated user.
"""
context_override = super(EmulateUserModelMixin, self).get_context_override(request)
try:
if request.user.is_staff:
user = self.UserModel.objects.get(pk=... | python | def get_context_override(self, request):
"""
Override the request object with an emulated user.
"""
context_override = super(EmulateUserModelMixin, self).get_context_override(request)
try:
if request.user.is_staff:
user = self.UserModel.objects.get(pk=... | [
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jrief/djangocms-cascade | cmsplugin_cascade/segmentation/mixins.py | EmulateUserAdminMixin.emulate_users | def emulate_users(self, request):
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def display_as_link(self, obj):
try:
identifier = getattr(user_model_admin, list_display_link)(obj)
except AttributeError:
identifier = admin.utils.lookup_field(list_display_li... | python | def emulate_users(self, request):
"""
The list view
"""
def display_as_link(self, obj):
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"""
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try:
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"""
Create the default permissions for the just added proxy model
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try:
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jrief/djangocms-cascade | cmsplugin_cascade/apps.py | CascadeConfig.revoke_permissions | def revoke_permissions(self, ctype):
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adamreeve/npTDMS | nptdms/writer.py | to_file | def to_file(file, array):
"""Wrapper around ndarray.tofile to support any file-like object"""
try:
array.tofile(file)
except (TypeError, IOError, UnsupportedOperation):
# tostring actually returns bytes
file.write(array.tostring()) | python | def to_file(file, array):
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""" Write a segment of data to a TDMS file
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segment = TdmsSegment(objects)
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adamreeve/npTDMS | nptdms/tdms.py | fromfile | def fromfile(file, dtype, count, *args, **kwargs):
"""Wrapper around np.fromfile to support any file-like object"""
try:
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except (TypeError, IOError, UnsupportedOperation):
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file.read(count *... | python | def fromfile(file, dtype, count, *args, **kwargs):
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prop_data_type = types.tds_data_types[types.Uint32.read(f, endianness)]
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""" Read a property from a segment's metadata """
prop_name = types.String.read(f, endianness)
prop_data_type = types.tds_data_types[types.Uint32.read(f, endianness)]
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adamreeve/npTDMS | nptdms/tdms.py | path_components | def path_components(path):
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def yield_components(path):
# Iterate over each character and the next character
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try:
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adamreeve/npTDMS | nptdms/tdms.py | TdmsFile.object | def object(self, *path):
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adamreeve/npTDMS | nptdms/tdms.py | TdmsFile.groups | def groups(self):
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adamreeve/npTDMS | nptdms/tdms.py | TdmsFile.group_channels | def group_channels(self, group):
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adamreeve/npTDMS | nptdms/tdms.py | TdmsFile.as_dataframe | def as_dataframe(self, time_index=False, absolute_time=False):
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adamreeve/npTDMS | nptdms/tdms.py | TdmsFile.as_hdf | def as_hdf(self, filepath, mode='w', group='/'):
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adamreeve/npTDMS | nptdms/tdms.py | _TdmsSegment.read_metadata | def read_metadata(self, f, objects, previous_segment=None):
"""Read segment metadata section and update object information"""
if not self.toc["kTocMetaData"]:
try:
self.ordered_objects = previous_segment.ordered_objects
except AttributeError:
rais... | python | def read_metadata(self, f, objects, previous_segment=None):
"""Read segment metadata section and update object information"""
if not self.toc["kTocMetaData"]:
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adamreeve/npTDMS | nptdms/tdms.py | _TdmsSegment.read_raw_data | def read_raw_data(self, f):
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adamreeve/npTDMS | nptdms/tdms.py | _TdmsSegment._read_interleaved_numpy | def _read_interleaved_numpy(self, f, data_objects):
"""Read interleaved data where all channels have a numpy type"""
log.debug("Reading interleaved data all at once")
# Read all data into 1 byte unsigned ints first
all_channel_bytes = data_objects[0].raw_data_width
if all_channe... | python | def _read_interleaved_numpy(self, f, data_objects):
"""Read interleaved data where all channels have a numpy type"""
log.debug("Reading interleaved data all at once")
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adamreeve/npTDMS | nptdms/tdms.py | _TdmsSegment._read_interleaved | def _read_interleaved(self, f, data_objects):
"""Read interleaved data that doesn't have a numpy type"""
log.debug("Reading interleaved data point by point")
object_data = {}
points_added = {}
for obj in data_objects:
object_data[obj.path] = obj._new_segment_data()
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adamreeve/npTDMS | nptdms/tdms.py | TdmsObject.time_track | def time_track(self, absolute_time=False, accuracy='ns'):
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adamreeve/npTDMS | nptdms/tdms.py | TdmsObject._initialise_data | def _initialise_data(self, memmap_dir=None):
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adamreeve/npTDMS | nptdms/tdms.py | TdmsObject._update_data | def _update_data(self, new_data):
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log.debug("Adding %d data points to data for %s" %
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if self._data is None:
self._data = new_data
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adamreeve/npTDMS | nptdms/tdms.py | TdmsObject.as_dataframe | def as_dataframe(self, absolute_time=False):
"""
Converts the TDMS object to a DataFrame
:param absolute_time: Whether times should be absolute rather than
relative to the start time.
:return: The TDMS object data.
:rtype: pandas.DataFrame
"""
import... | python | def as_dataframe(self, absolute_time=False):
"""
Converts the TDMS object to a DataFrame
:param absolute_time: Whether times should be absolute rather than
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:return: The TDMS object data.
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adamreeve/npTDMS | nptdms/tdms.py | TdmsObject.data | def data(self):
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NumPy array containing data if there is data for this object,
otherwise None.
"""
if self._data is None:
# self._data is None if data segment is empty
return np.empty((0, 1))
if self._data_scaled is None:
scale = sca... | python | def data(self):
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NumPy array containing data if there is data for this object,
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"""
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adamreeve/npTDMS | nptdms/tdms.py | _TdmsmxDAQMetadata._read_metadata | def _read_metadata(self, f, endianness):
"""
Read the metadata for a DAQmx raw segment. This is the raw
DAQmx-specific portion of the raw data index.
"""
self.data_type = types.tds_data_types[0xFFFFFFFF]
self.dimension = types.Uint32.read(f, endianness)
# In TDMS... | python | def _read_metadata(self, f, endianness):
"""
Read the metadata for a DAQmx raw segment. This is the raw
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"""
self.data_type = types.tds_data_types[0xFFFFFFFF]
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adamreeve/npTDMS | nptdms/tdms.py | _TdmsSegmentObject._read_metadata | def _read_metadata(self, f):
"""Read object metadata and update object information"""
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log.debug("Reading metadata for object %s", self.tdms_object.path)
# Object has no data in this segment
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"""Read object metadata and update object information"""
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adamreeve/npTDMS | nptdms/tdms.py | _TdmsSegmentObject._read_value | def _read_value(self, file):
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adamreeve/npTDMS | nptdms/tdms.py | _TdmsSegmentObject._read_values | def _read_values(self, file, number_values):
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adamreeve/npTDMS | nptdms/tdms.py | _TdmsSegmentObject._new_segment_data | def _new_segment_data(self):
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apriha/lineage | src/lineage/snps.py | detect_build | def detect_build(snps):
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Notes
-----
rs3094315 : plus strand in 36, 37, and 38
rs11928389 : plus strand in 36, minus strand in 37 and 38
rs2500347 : plu... | python | def detect_build(snps):
""" Detect build of SNPs.
Use the coordinates of common SNPs to identify the build / assembly of a genotype file
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rs11928389 : plus strand in 36, minus strand in 37 and 38
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Use the coordinates of common SNPs to identify the build / assembly of a genotype file
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Notes
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rs3094315 : plus strand in 36, 37, and 38
rs11928389 : plus strand in 36, minus strand in 37 and 38
rs2500347 : plus strand in 36 and 37, minus str... | [
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apriha/lineage | src/lineage/snps.py | get_chromosomes | def get_chromosomes(snps):
""" Get the chromosomes of SNPs.
Parameters
----------
snps : pandas.DataFrame
Returns
-------
list
list of str chromosomes (e.g., ['1', '2', '3', 'MT'], empty list if no chromosomes
"""
if isinstance(snps, pd.DataFrame):
return list(pd.u... | python | def get_chromosomes(snps):
""" Get the chromosomes of SNPs.
Parameters
----------
snps : pandas.DataFrame
Returns
-------
list
list of str chromosomes (e.g., ['1', '2', '3', 'MT'], empty list if no chromosomes
"""
if isinstance(snps, pd.DataFrame):
return list(pd.u... | [
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apriha/lineage | src/lineage/snps.py | get_chromosomes_summary | def get_chromosomes_summary(snps):
""" Summary of the chromosomes of SNPs.
Parameters
----------
snps : pandas.DataFrame
Returns
-------
str
human-readable listing of chromosomes (e.g., '1-3, MT'), empty str if no chromosomes
"""
if isinstance(snps, pd.DataFrame):
... | python | def get_chromosomes_summary(snps):
""" Summary of the chromosomes of SNPs.
Parameters
----------
snps : pandas.DataFrame
Returns
-------
str
human-readable listing of chromosomes (e.g., '1-3, MT'), empty str if no chromosomes
"""
if isinstance(snps, pd.DataFrame):
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apriha/lineage | src/lineage/snps.py | determine_sex | def determine_sex(
snps, y_snps_not_null_threshold=0.1, heterozygous_x_snps_threshold=0.01
):
""" Determine sex from SNPs using thresholds.
Parameters
----------
snps : pandas.DataFrame
y_snps_not_null_threshold : float
percentage Y SNPs that are not null; above this threshold, Male is ... | python | def determine_sex(
snps, y_snps_not_null_threshold=0.1, heterozygous_x_snps_threshold=0.01
):
""" Determine sex from SNPs using thresholds.
Parameters
----------
snps : pandas.DataFrame
y_snps_not_null_threshold : float
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apriha/lineage | src/lineage/snps.py | sort_snps | def sort_snps(snps):
""" Sort SNPs based on ordered chromosome list and position. """
sorted_list = sorted(snps["chrom"].unique(), key=_natural_sort_key)
# move PAR and MT to the end of the dataframe
if "PAR" in sorted_list:
sorted_list.remove("PAR")
sorted_list.append("PAR")
if "... | python | def sort_snps(snps):
""" Sort SNPs based on ordered chromosome list and position. """
sorted_list = sorted(snps["chrom"].unique(), key=_natural_sort_key)
# move PAR and MT to the end of the dataframe
if "PAR" in sorted_list:
sorted_list.remove("PAR")
sorted_list.append("PAR")
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apriha/lineage | src/lineage/snps.py | SNPs.get_summary | def get_summary(self):
""" Get summary of ``SNPs``.
Returns
-------
dict
summary info, else None if ``SNPs`` is not valid
"""
if not self.is_valid():
return None
else:
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"source": self.source,
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""" Get summary of ``SNPs``.
Returns
-------
dict
summary info, else None if ``SNPs`` is not valid
"""
if not self.is_valid():
return None
else:
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apriha/lineage | src/lineage/snps.py | SNPs._read_23andme | def _read_23andme(file):
""" Read and parse 23andMe file.
https://www.23andme.com
Parameters
----------
file : str
path to file
Returns
-------
pandas.DataFrame
individual's genetic data normalized for use with `lineage`
... | python | def _read_23andme(file):
""" Read and parse 23andMe file.
https://www.23andme.com
Parameters
----------
file : str
path to file
Returns
-------
pandas.DataFrame
individual's genetic data normalized for use with `lineage`
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apriha/lineage | src/lineage/snps.py | SNPs._read_ftdna | def _read_ftdna(file):
""" Read and parse Family Tree DNA (FTDNA) file.
https://www.familytreedna.com
Parameters
----------
file : str
path to file
Returns
-------
pandas.DataFrame
individual's genetic data normalized for use wit... | python | def _read_ftdna(file):
""" Read and parse Family Tree DNA (FTDNA) file.
https://www.familytreedna.com
Parameters
----------
file : str
path to file
Returns
-------
pandas.DataFrame
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apriha/lineage | src/lineage/snps.py | SNPs._read_ftdna_famfinder | def _read_ftdna_famfinder(file):
""" Read and parse Family Tree DNA (FTDNA) "famfinder" file.
https://www.familytreedna.com
Parameters
----------
file : str
path to file
Returns
-------
pandas.DataFrame
individual's genetic data ... | python | def _read_ftdna_famfinder(file):
""" Read and parse Family Tree DNA (FTDNA) "famfinder" file.
https://www.familytreedna.com
Parameters
----------
file : str
path to file
Returns
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pandas.DataFrame
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apriha/lineage | src/lineage/snps.py | SNPs._read_ancestry | def _read_ancestry(file):
""" Read and parse Ancestry.com file.
http://www.ancestry.com
Parameters
----------
file : str
path to file
Returns
-------
pandas.DataFrame
individual's genetic data normalized for use with `lineage`
... | python | def _read_ancestry(file):
""" Read and parse Ancestry.com file.
http://www.ancestry.com
Parameters
----------
file : str
path to file
Returns
-------
pandas.DataFrame
individual's genetic data normalized for use with `lineage`
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apriha/lineage | src/lineage/snps.py | SNPs._read_lineage_csv | def _read_lineage_csv(file, comments):
""" Read and parse CSV file generated by lineage.
Parameters
----------
file : str
path to file
comments : str
comments at beginning of file
Returns
-------
pandas.DataFrame
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""" Read and parse CSV file generated by lineage.
Parameters
----------
file : str
path to file
comments : str
comments at beginning of file
Returns
-------
pandas.DataFrame
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apriha/lineage | src/lineage/snps.py | SNPs._read_generic_csv | def _read_generic_csv(file):
""" Read and parse generic CSV file.
Notes
-----
Assumes columns are 'rsid', 'chrom' / 'chromosome', 'pos' / 'position', and 'genotype';
values are comma separated; unreported genotypes are indicated by '--'; and one header row
precedes data.... | python | def _read_generic_csv(file):
""" Read and parse generic CSV file.
Notes
-----
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values are comma separated; unreported genotypes are indicated by '--'; and one header row
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apriha/lineage | src/lineage/snps.py | SNPs._assign_par_snps | def _assign_par_snps(self):
""" Assign PAR SNPs to the X or Y chromosome using SNP position.
References
-----
..[1] National Center for Biotechnology Information, Variation Services, RefSNP,
https://api.ncbi.nlm.nih.gov/variation/v0/
..[2] Yates et. al. (doi:10.1093/bi... | python | def _assign_par_snps(self):
""" Assign PAR SNPs to the X or Y chromosome using SNP position.
References
-----
..[1] National Center for Biotechnology Information, Variation Services, RefSNP,
https://api.ncbi.nlm.nih.gov/variation/v0/
..[2] Yates et. al. (doi:10.1093/bi... | [
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apriha/lineage | src/lineage/visualization.py | plot_chromosomes | def plot_chromosomes(one_chrom_match, two_chrom_match, cytobands, path, title, build):
""" Plots chromosomes with designated markers.
Parameters
----------
one_chrom_match : list of dicts
segments to highlight on the chromosomes representing one shared chromosome
two_chrom_match : list of d... | python | def plot_chromosomes(one_chrom_match, two_chrom_match, cytobands, path, title, build):
""" Plots chromosomes with designated markers.
Parameters
----------
one_chrom_match : list of dicts
segments to highlight on the chromosomes representing one shared chromosome
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apriha/lineage | src/lineage/visualization.py | _patch_chromosomal_features | def _patch_chromosomal_features(cytobands, one_chrom_match, two_chrom_match):
""" Highlight positions for each chromosome segment / feature.
Parameters
----------
cytobands : pandas.DataFrame
cytoband table from UCSC
one_chrom_match : list of dicts
segments to highlight on the chrom... | python | def _patch_chromosomal_features(cytobands, one_chrom_match, two_chrom_match):
""" Highlight positions for each chromosome segment / feature.
Parameters
----------
cytobands : pandas.DataFrame
cytoband table from UCSC
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apriha/lineage | src/lineage/__init__.py | create_dir | def create_dir(path):
""" Create directory specified by `path` if it doesn't already exist.
Parameters
----------
path : str
path to directory
Returns
-------
bool
True if `path` exists
"""
# https://stackoverflow.com/a/5032238
try:
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""" Create directory specified by `path` if it doesn't already exist.
Parameters
----------
path : str
path to directory
Returns
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bool
True if `path` exists
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apriha/lineage | src/lineage/__init__.py | save_df_as_csv | def save_df_as_csv(df, path, filename, comment=None, **kwargs):
""" Save dataframe to a CSV file.
Parameters
----------
df : pandas.DataFrame
dataframe to save
path : str
path to directory where to save CSV file
filename : str
filename of CSV file
comment : str
... | python | def save_df_as_csv(df, path, filename, comment=None, **kwargs):
""" Save dataframe to a CSV file.
Parameters
----------
df : pandas.DataFrame
dataframe to save
path : str
path to directory where to save CSV file
filename : str
filename of CSV file
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apriha/lineage | src/lineage/__init__.py | Lineage.remap_snps | def remap_snps(self, individual, target_assembly, complement_bases=True):
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apriha/lineage | src/lineage/__init__.py | Lineage.find_discordant_snps | def find_discordant_snps(
self, individual1, individual2, individual3=None, save_output=False
):
""" Find discordant SNPs between two or three individuals.
Parameters
----------
individual1 : Individual
reference individual (child if `individual2` and `individual... | python | def find_discordant_snps(
self, individual1, individual2, individual3=None, save_output=False
):
""" Find discordant SNPs between two or three individuals.
Parameters
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individual1 : Individual
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apriha/lineage | src/lineage/__init__.py | Lineage.find_shared_dna | def find_shared_dna(
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shared_genes=False,
save_output=True,
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""" Find the shared DNA between two individuals.
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self,
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cM_threshold=0.75,
snp_threshold=1100,
shared_genes=False,
save_output=True,
):
""" Find the shared DNA between two individuals.
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apriha/lineage | src/lineage/resources.py | Resources.get_genetic_map_HapMapII_GRCh37 | def get_genetic_map_HapMapII_GRCh37(self):
""" Get International HapMap Consortium HapMap Phase II genetic map for Build 37.
Returns
-------
dict
dict of pandas.DataFrame HapMapII genetic maps if loading was successful, else None
"""
if self._genetic_map_HapM... | python | def get_genetic_map_HapMapII_GRCh37(self):
""" Get International HapMap Consortium HapMap Phase II genetic map for Build 37.
Returns
-------
dict
dict of pandas.DataFrame HapMapII genetic maps if loading was successful, else None
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apriha/lineage | src/lineage/resources.py | Resources.get_cytoBand_hg19 | def get_cytoBand_hg19(self):
""" Get UCSC cytoBand table for Build 37.
Returns
-------
pandas.DataFrame
cytoBand table if loading was successful, else None
"""
if self._cytoBand_hg19 is None:
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""" Get UCSC cytoBand table for Build 37.
Returns
-------
pandas.DataFrame
cytoBand table if loading was successful, else None
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apriha/lineage | src/lineage/resources.py | Resources.get_knownGene_hg19 | def get_knownGene_hg19(self):
""" Get UCSC knownGene table for Build 37.
Returns
-------
pandas.DataFrame
knownGene table if loading was successful, else None
"""
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""" Get UCSC knownGene table for Build 37.
Returns
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pandas.DataFrame
knownGene table if loading was successful, else None
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apriha/lineage | src/lineage/resources.py | Resources.get_kgXref_hg19 | def get_kgXref_hg19(self):
""" Get UCSC kgXref table for Build 37.
Returns
-------
pandas.DataFrame
kgXref table if loading was successful, else None
"""
if self._kgXref_hg19 is None:
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""" Get UCSC kgXref table for Build 37.
Returns
-------
pandas.DataFrame
kgXref table if loading was successful, else None
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apriha/lineage | src/lineage/resources.py | Resources.get_assembly_mapping_data | def get_assembly_mapping_data(self, source_assembly, target_assembly):
""" Get assembly mapping data.
Parameters
----------
source_assembly : {'NCBI36', 'GRCh37', 'GRCh38'}
assembly to remap from
target_assembly : {'NCBI36', 'GRCh37', 'GRCh38'}
assembly t... | python | def get_assembly_mapping_data(self, source_assembly, target_assembly):
""" Get assembly mapping data.
Parameters
----------
source_assembly : {'NCBI36', 'GRCh37', 'GRCh38'}
assembly to remap from
target_assembly : {'NCBI36', 'GRCh37', 'GRCh38'}
assembly t... | [
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apriha/lineage | src/lineage/resources.py | Resources.download_example_datasets | def download_example_datasets(self):
""" Download example datasets from `openSNP <https://opensnp.org>`_.
Per openSNP, "the data is donated into the public domain using `CC0 1.0
<http://creativecommons.org/publicdomain/zero/1.0/>`_."
Returns
-------
paths : list of str ... | python | def download_example_datasets(self):
""" Download example datasets from `openSNP <https://opensnp.org>`_.
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apriha/lineage | src/lineage/resources.py | Resources.get_all_resources | def get_all_resources(self):
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Returns
-------
dict
dict of resources
"""
resources = {}
resources[
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""" Get / download all resources used throughout `lineage`.
Returns
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dict
dict of resources
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resources[
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apriha/lineage | src/lineage/resources.py | Resources._load_genetic_map | def _load_genetic_map(filename):
""" Load genetic map (e.g. HapMapII).
Parameters
----------
filename : str
path to compressed archive with genetic map data
Returns
-------
genetic_map : dict
dict of pandas.DataFrame genetic maps if loadi... | python | def _load_genetic_map(filename):
""" Load genetic map (e.g. HapMapII).
Parameters
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filename : str
path to compressed archive with genetic map data
Returns
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apriha/lineage | src/lineage/resources.py | Resources._load_assembly_mapping_data | def _load_assembly_mapping_data(filename):
""" Load assembly mapping data.
Parameters
----------
filename : str
path to compressed archive with assembly mapping data
Returns
-------
assembly_mapping_data : dict
dict of assembly maps if lo... | python | def _load_assembly_mapping_data(filename):
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filename : str
path to compressed archive with assembly mapping data
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apriha/lineage | src/lineage/resources.py | Resources._load_cytoBand | def _load_cytoBand(filename):
""" Load UCSC cytoBand table.
Parameters
----------
filename : str
path to cytoBand file
Returns
-------
df : pandas.DataFrame
cytoBand table if loading was successful, else None
References
-... | python | def _load_cytoBand(filename):
""" Load UCSC cytoBand table.
Parameters
----------
filename : str
path to cytoBand file
Returns
-------
df : pandas.DataFrame
cytoBand table if loading was successful, else None
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apriha/lineage | src/lineage/resources.py | Resources._load_knownGene | def _load_knownGene(filename):
""" Load UCSC knownGene table.
Parameters
----------
filename : str
path to knownGene file
Returns
-------
df : pandas.DataFrame
knownGene table if loading was successful, else None
"""
try:
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Parameters
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filename : str
path to knownGene file
Returns
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df : pandas.DataFrame
knownGene table if loading was successful, else None
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apriha/lineage | src/lineage/resources.py | Resources._load_kgXref | def _load_kgXref(filename):
""" Load UCSC kgXref table.
Parameters
----------
filename : str
path to kgXref file
Returns
-------
df : pandas.DataFrame
kgXref table if loading was successful, else None
"""
try:
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""" Load UCSC kgXref table.
Parameters
----------
filename : str
path to kgXref file
Returns
-------
df : pandas.DataFrame
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apriha/lineage | src/lineage/resources.py | Resources._get_path_assembly_mapping_data | def _get_path_assembly_mapping_data(
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source_assembly : {'NCBI36', 'GRCh37', 'GRCh38'}
assembly to remap from
... | python | def _get_path_assembly_mapping_data(
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""" Get local path to assembly mapping data, downloading if necessary.
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apriha/lineage | src/lineage/resources.py | Resources._download_file | def _download_file(self, url, filename, compress=False, timeout=30):
""" Download a file to the resources folder.
Download data from `url`, save as `filename`, and optionally compress with gzip.
Parameters
----------
url : str
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apriha/lineage | src/lineage/individual.py | Individual.discrepant_snps | def discrepant_snps(self):
""" SNPs with discrepant positions and / or genotypes discovered while loading SNPs.
Returns
-------
pandas.DataFrame
"""
df = self._discrepant_positions.append(self._discrepant_genotypes)
if len(df) > 1:
df = df.drop_duplic... | python | def discrepant_snps(self):
""" SNPs with discrepant positions and / or genotypes discovered while loading SNPs.
Returns
-------
pandas.DataFrame
"""
df = self._discrepant_positions.append(self._discrepant_genotypes)
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apriha/lineage | src/lineage/individual.py | Individual.load_snps | def load_snps(
self,
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discrepant_genotypes_threshold=500,
save_output=False,
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save_output=False,
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apriha/lineage | src/lineage/individual.py | Individual.save_snps | def save_snps(self, filename=None):
""" Save SNPs to file.
Parameters
----------
filename : str
filename for file to save
Returns
-------
str
path to file in output directory if SNPs were saved, else empty str
"""
comment ... | python | def save_snps(self, filename=None):
""" Save SNPs to file.
Parameters
----------
filename : str
filename for file to save
Returns
-------
str
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apriha/lineage | src/lineage/individual.py | Individual.remap_snps | def remap_snps(self, target_assembly, complement_bases=True):
""" Remap the SNP coordinates of this ``Individual`` from one assembly to another.
This method is a wrapper for `remap_snps` in the ``Lineage`` class.
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apriha/lineage | src/lineage/individual.py | Individual._set_snps | def _set_snps(self, snps, build=37):
""" Set `_snps` and `_build` properties of this ``Individual``.
Notes
-----
Intended to be used internally to `lineage`.
Parameters
----------
snps : pandas.DataFrame
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apriha/lineage | src/lineage/individual.py | Individual._add_snps | def _add_snps(
self,
snps,
discrepant_snp_positions_threshold,
discrepant_genotypes_threshold,
save_output,
):
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Parameters
----------
snps : SNPs
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discrepant_snp_positions_threshol... | python | def _add_snps(
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save_output,
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apriha/lineage | src/lineage/individual.py | Individual._double_single_alleles | def _double_single_alleles(df, chrom):
""" Double any single alleles in the specified chromosome.
Parameters
----------
df : pandas.DataFrame
SNPs
chrom : str
chromosome of alleles to double
Returns
-------
df : pandas.DataFrame
... | python | def _double_single_alleles(df, chrom):
""" Double any single alleles in the specified chromosome.
Parameters
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df : pandas.DataFrame
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chrom : str
chromosome of alleles to double
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df : pandas.DataFrame
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tBuLi/symfit | symfit/core/support.py | seperate_symbols | def seperate_symbols(func):
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Seperate the symbols in symbolic function func. Return them in alphabetical
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:param func: scipy symbolic function.
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:raises TypeError: only symfit V... | python | def seperate_symbols(func):
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tBuLi/symfit | symfit/core/support.py | sympy_to_py | def sympy_to_py(func, args):
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tBuLi/symfit | symfit/core/support.py | sympy_to_scipy | def sympy_to_scipy(func, vars, params):
"""
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"""
... | python | def sympy_to_scipy(func, vars, params):
"""
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tBuLi/symfit | symfit/core/support.py | variables | def variables(names, **kwargs):
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:param names: string of variable names.
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"""
Convenience function for the creation of multiple variables. For more
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tBuLi/symfit | symfit/core/support.py | parameters | def parameters(names, **kwargs):
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tBuLi/symfit | symfit/core/support.py | jacobian | def jacobian(expr, symbols):
"""
Derive a symbolic expr w.r.t. each symbol in symbols. This returns a symbolic jacobian vector.
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f... | python | def jacobian(expr, symbols):
"""
Derive a symbolic expr w.r.t. each symbol in symbols. This returns a symbolic jacobian vector.
:param expr: A sympy Expr.
:param symbols: The symbols w.r.t. which to derive.
"""
jac = []
for symbol in symbols:
# Differentiate to every param
f... | [
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tBuLi/symfit | symfit/core/support.py | key2str | def key2str(target):
"""
In ``symfit`` there are many dicts with symbol: value pairs.
These can not be used immediately as \*\*kwargs, even though this would make
a lot of sense from the context.
This function wraps such dict to make them usable as \*\*kwargs immediately.
:param target: `Mappin... | python | def key2str(target):
"""
In ``symfit`` there are many dicts with symbol: value pairs.
These can not be used immediately as \*\*kwargs, even though this would make
a lot of sense from the context.
This function wraps such dict to make them usable as \*\*kwargs immediately.
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:param target: `Mapping` to be made save
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tBuLi/symfit | symfit/core/support.py | name | def name(self):
"""
Save name which can be used for alphabetic sorting and can be turned
into a kwarg.
"""
base_str = 'd{}{}_'.format(self.derivative_count if
self.derivative_count > 1 else '', self.expr)
for var, count in self.variable_count:
base_str += '... | python | def name(self):
"""
Save name which can be used for alphabetic sorting and can be turned
into a kwarg.
"""
base_str = 'd{}{}_'.format(self.derivative_count if
self.derivative_count > 1 else '', self.expr)
for var, count in self.variable_count:
base_str += '... | [
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tBuLi/symfit | symfit/core/minimizers.py | BaseMinimizer._baseobjective_from_callable | def _baseobjective_from_callable(self, func, objective_type=MinimizeModel):
"""
symfit works with BaseObjective subclasses internally. If a custom
objective is provided, we wrap it into a BaseObjective, MinimizeModel by
default.
:param func: Callable. If already an instance of B... | python | def _baseobjective_from_callable(self, func, objective_type=MinimizeModel):
"""
symfit works with BaseObjective subclasses internally. If a custom
objective is provided, we wrap it into a BaseObjective, MinimizeModel by
default.
:param func: Callable. If already an instance of B... | [
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tBuLi/symfit | symfit/core/minimizers.py | GradientMinimizer.resize_jac | def resize_jac(self, func):
"""
Removes values with identical indices to fixed parameters from the
output of func. func has to return the jacobian of a scalar function.
:param func: Jacobian function to be wrapped. Is assumed to be the
jacobian of a scalar function.
... | python | def resize_jac(self, func):
"""
Removes values with identical indices to fixed parameters from the
output of func. func has to return the jacobian of a scalar function.
:param func: Jacobian function to be wrapped. Is assumed to be the
jacobian of a scalar function.
... | [
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tBuLi/symfit | symfit/core/minimizers.py | HessianMinimizer.resize_hess | def resize_hess(self, func):
"""
Removes values with identical indices to fixed parameters from the
output of func. func has to return the Hessian of a scalar function.
:param func: Hessian function to be wrapped. Is assumed to be the
Hessian of a scalar function.
:r... | python | def resize_hess(self, func):
"""
Removes values with identical indices to fixed parameters from the
output of func. func has to return the Hessian of a scalar function.
:param func: Hessian function to be wrapped. Is assumed to be the
Hessian of a scalar function.
:r... | [
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] | train | https://github.com/tBuLi/symfit/blob/759dd3d1d4270510d651f40b23dd26b1b10eee83/symfit/core/minimizers.py#L179-L197 |
tBuLi/symfit | symfit/core/minimizers.py | ChainedMinimizer.execute | def execute(self, **minimizer_kwargs):
"""
Execute the chained-minimization. In order to pass options to the
seperate minimizers, they can be passed by using the
names of the minimizers as keywords. For example::
fit = Fit(self.model, self.xx, self.yy, self.ydata,
... | python | def execute(self, **minimizer_kwargs):
"""
Execute the chained-minimization. In order to pass options to the
seperate minimizers, they can be passed by using the
names of the minimizers as keywords. For example::
fit = Fit(self.model, self.xx, self.yy, self.ydata,
... | [
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fit = Fit(self.model, self.xx, self.yy, self.ydata,
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tBuLi/symfit | symfit/core/minimizers.py | ChainedMinimizer._make_signature | def _make_signature(self):
"""
Create a signature for `execute` based on the minimizers this
`ChainedMinimizer` was initiated with. For the format, see the docstring
of :meth:`ChainedMinimizer.execute`.
:return: :class:`inspect.Signature` instance.
"""
# Create K... | python | def _make_signature(self):
"""
Create a signature for `execute` based on the minimizers this
`ChainedMinimizer` was initiated with. For the format, see the docstring
of :meth:`ChainedMinimizer.execute`.
:return: :class:`inspect.Signature` instance.
"""
# Create K... | [
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tBuLi/symfit | symfit/core/minimizers.py | ScipyMinimize.execute | def execute(self, bounds=None, jacobian=None, hessian=None, constraints=None, **minimize_options):
"""
Calls the wrapped algorithm.
:param bounds: The bounds for the parameters. Usually filled by
:class:`~symfit.core.minimizers.BoundedMinimizer`.
:param jacobian: The Jacobia... | python | def execute(self, bounds=None, jacobian=None, hessian=None, constraints=None, **minimize_options):
"""
Calls the wrapped algorithm.
:param bounds: The bounds for the parameters. Usually filled by
:class:`~symfit.core.minimizers.BoundedMinimizer`.
:param jacobian: The Jacobia... | [
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:param bounds: The bounds for the parameters. Usually filled by
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:param jacobian: The Jacobian. Usually filled by
:class:`~symfit.core.minimizers.ScipyGradientMinimize`.
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] | train | https://github.com/tBuLi/symfit/blob/759dd3d1d4270510d651f40b23dd26b1b10eee83/symfit/core/minimizers.py#L331-L353 |
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