def plot(data, headers=None, pconfig=None):
""" Return HTML for a MultiQC table.
:param data: 2D dict, first keys as sample names, then x:y data pairs
:param headers: list of optional dicts with column config in key:value pairs.
:return: HTML ready to be inserted into the page
"""
if headers is None:
headers = []
if pconfig is None:
pconfig = {}
# Make a datatable object
dt = table_object.datatable(data, headers, pconfig)
# Collect unique sample names
s_names = set()
for d in dt.data:
for s_name in d.keys():
s_names.add(s_name)
# Make a beeswarm plot if we have lots of samples
if len(s_names) >= config.max_table_rows and pconfig.get(
'no_beeswarm') is not True:
logger.debug('Plotting beeswarm instead of table, {} samples'.format(
len(s_names)))
warning = '<p class="text-muted"><span class="glyphicon glyphicon-exclamation-sign" ' \
'title="A beeswarm plot has been generated instead because of the large number of samples. '\
'See http://multiqc.info/docs/#tables--beeswarm-plots"'\
' data-toggle="tooltip"></span> Showing {} samples.</p>'.format(len(s_names))
return warning + beeswarm.make_plot(dt)
else:
return make_table(dt)
def plot (data, headers=[], pconfig={}):
""" Return HTML for a MultiQC table.
:param data: 2D dict, first keys as sample names, then x:y data pairs
:param headers: list of optional dicts with column config in key:value pairs.
:return: HTML ready to be inserted into the page
"""
# Make a datatable object
dt = table_object.datatable(data, headers, pconfig)
# Collect unique sample names
s_names = set()
for d in dt.data:
for s_name in d.keys():
s_names.add(s_name)
# Make a beeswarm plot if we have lots of samples
if len(s_names) >= config.max_table_rows and pconfig.get('no_beeswarm') is not True:
logger.debug('Plotting beeswarm instead of table, {} samples'.format(len(s_names)))
warning = """<p>This report is very large.
A beeswarm plot has been generated instead of a table to aid usability.
To disable this, set <code>max_table_rows</code> to a very high number
in your MultiQC config file.</p>"""
return warning + beeswarm.make_plot( dt )
else:
return make_table ( dt )
def plot (data, headers=[], pconfig={}):
""" Return HTML for a MultiQC table.
:param data: 2D dict, first keys as sample names, then x:y data pairs
:param headers: list of optional dicts with column config in key:value pairs.
:return: HTML ready to be inserted into the page
"""
# Make a datatable object
dt = table_object.datatable(data, headers, pconfig)
# Collect unique sample names
s_names = set()
for d in dt.data:
for s_name in d.keys():
s_names.add(s_name)
# Make a beeswarm plot if we have lots of samples
if len(s_names) >= config.max_table_rows and pconfig.get('no_beeswarm') is not True:
logger.debug('Plotting beeswarm instead of table, {} samples'.format(len(s_names)))
warning = '<p class="text-muted"><span class="glyphicon glyphicon-exclamation-sign" ' \
'title="A beeswarm plot has been generated instead because of the large number of samples. '\
'See http://multiqc.info/docs/#tables--beeswarm-plots"'\
' data-toggle="tooltip"></span> Showing {} samples.</p>'.format(len(s_names))
return warning + beeswarm.make_plot( dt )
else:
return make_table ( dt )
def plot (data, headers=[], pconfig={}):
""" Helper HTML for a beeswarm plot.
:param data: A list of data dicts
:param headers: A list of Dicts / OrderedDicts with information
for the series, such as colour scales, min and
max values etc.
:return: HTML string
"""
# Make a datatable object
dt = table_object.datatable(data, headers, pconfig)
return make_plot( dt )
def plot(data, headers=[], pconfig={}):
""" Helper HTML for a beeswarm plot.
:param data: A list of data dicts
:param headers: A list of Dicts / OrderedDicts with information
for the series, such as colour scales, min and
max values etc.
:return: HTML string
"""
# Make a datatable object
dt = table_object.datatable(data, headers, pconfig)
return make_plot(dt)
def plot(data, headers=None, pconfig=None):
""" Return HTML for a MultiQC table.
:param data: 2D dict, first keys as sample names, then x:y data pairs
:param headers: list of optional dicts with column config in key:value pairs.
:return: HTML ready to be inserted into the page
"""
if headers is None:
headers = []
if pconfig is None:
pconfig = {}
# Make a datatable object
dt = table_object.datatable(data, headers, pconfig)
# Collect unique sample names
s_names = set()
for d in dt.data:
for s_name in d.keys():
s_names.add(s_name)
return make_table(dt)
def plot (data, headers=None, pconfig=None):
""" Helper HTML for a beeswarm plot.
:param data: A list of data dicts
:param headers: A list of Dicts / OrderedDicts with information
for the series, such as colour scales, min and
max values etc.
:return: HTML string
"""
if headers is None:
headers = []
if pconfig is None:
pconfig = {}
# Allow user to overwrite any given config for this plot
if 'id' in pconfig and pconfig['id'] and pconfig['id'] in config.custom_plot_config:
for k, v in config.custom_plot_config[pconfig['id']].items():
pconfig[k] = v
# Make a datatable object
dt = table_object.datatable(data, headers, pconfig)
return make_plot( dt )