def __init__(self):
"""Initializes the :class:`clusterking.scan.Scanner` class."""
super().__init__()
# todo: move
self.log = get_logger("Scanner")
#: Points in wilson space
#: Use self.spoints to access this
self._spoints = None # type: Optional[np.ndarray]
#: Instance of SpointCalculator to perform the claculations of
#: the wilson space points.
self._spoint_calculator = SpointCalculator()
# todo: move
self.md = nested_dict()
self.md["git"] = version_info(self.log)
self.md["time"] = time.strftime("%a %d %b %Y %H:%M", time.gmtime())
# todo: shouldn't that be in metadata?
#: Names of the parameters
self._coeffs = [] # type: List[str]
self._no_workers = None # type: Optional[int]
self._progress_bar = True
self._tqdm_kwargs = {}
self.set_imaginary_prefix("im_")
def __init__(self):
""" """
super().__init__()
self.bpoints = None
self.md = nested_dict()
self.log = get_logger("Benchmark")
self.set_cluster_column()
def __init__(self, data):
"""
Args:
data: :py:class:`~clusterking.data.data.Data` object
"""
#: logging.Logger object
self.log = get_logger("BundlePlot", sh_level=logging.WARNING)
#: pandas dataframe
self.data = data
#: Name of the column holding the cluster number
self.cluster_column = "cluster"
self.bpoint_column = "bpoint"
#: Color scheme
# fixme: this will be problematic if I reinitialize this
if self._has_clusters:
self.color_scheme = ColorScheme(self._clusters)
else:
self.color_scheme = ColorScheme([0])
#: Draw legend?
self.draw_legend = True
#: Override default titles with this title. If None, the default title
#: is used.
self.title = None
#: Instance of matplotlib.axes.Axes
self.ax = None
def __init__(self):
super().__init__()
self._noise_kwargs = {}
self._noise_args = []
self._repeat = 10
self._cache_data = True
self.set_repeat()
self.log = get_logger("NoisySample")
def __init__(
self,
path: Optional[Union[str, PurePath]] = None,
log: Optional[Union[str, logging.Logger]] = None,
):
"""
Initialize a DFMD object.
Args:
path: Optional: load from this file (specified as string or
:class:`pathlib.PurePath`)
log: Optional: instance of :py:class:`logging.Logger` or name of
logger to be created
"""
# These are the three attributes of this class
#: This will hold all the configuration that we will write out
self.md = None
#: :py:class:`pandas.DataFrame` to hold all of the results
self.df = None # type: Optional[pd.DataFrame]
#: Instance of :py:class:`logging.Logger`
self.log = None
# todo: remember path?
if not path:
# Initialize blank
self.md = nested_dict()
self.df = pd.DataFrame()
self.log = None
else:
self._load(path)
# Overwrite log if user wants that.
if isinstance(log, logging.Logger):
self.log = log
elif isinstance(log, str):
self.log = get_logger(log)
elif log is None:
if not self.log:
self.log = get_logger("DFMD")
else:
raise ValueError(
"Unsupported type '{}' for 'log' argument.".format(type(log)))
def __init__(self, data: Data):
""" Initializer of the object.
.. note::
The :class:`~clusterking.result.Result` is not meant to be
initialized by the user. Rather it is a return object of the
:meth:`clusterking.worker.Worker.run` method.
"""
super().__init__()
self._data = data # type: Data
self.log = get_logger(str(type(self)))
def import_matplotlib():
""" Tries to import matplotlib, printing help message if it fails. """
try:
import matplotlib
except ImportError:
from clusterking.util.log import get_logger
log = get_logger()
msg = (
"Could not import matplotlib. Perhaps you didn't install "
"ClusterKinG with the 'plotting' option? Please install matplotlib "
"to use ClusterKinG's plotting funcionality. ")
log.critical(msg)
raise ImportError(msg)
def __init__(self):
"""
Args:
data: :py:class:`~clusterking.data.Data` object
"""
super().__init__()
self.log = get_logger("Scanner")
self.clusters = None
# self.bpoints = None
#: Metadata
self.md = nested_dict()
self.md["git"] = version_info(self.log)
self.md["time"] = time.strftime("%a %d %b %Y %H:%M", time.gmtime())
def __init__(
self,
clusters: Optional[List[int]] = None,
colors: Optional[List[str]] = None,
):
""" Initialize `ColorScheme` object.
Args:
clusters: List of cluster names
colors: List of colors
"""
self.log = get_logger("Colors", sh_level=logging.WARNING)
self._cluster_colors = None
# todo: perhaps use this: https://personal.sron.nl/~pault/
self.cluster_colors = [
"xkcd:light red",
"xkcd:apple green",
"xkcd:bright blue",
"xkcd:charcoal grey",
"xkcd:orange",
"xkcd:purple",
"xkcd:brick red",
"xkcd:hunter green",
"xkcd:marigold",
"xkcd:darkish blue",
"xkcd:dirt brown",
"xkcd:vivid green",
"xkcd:periwinkle",
]
if colors:
self.cluster_colors = colors
if not clusters:
self.clusters = range(len(self.cluster_colors))
else:
self.clusters = list(clusters)
if len(self.clusters) > len(self.cluster_colors):
self.log.warning(
"Not enough colors for all clusters. Some clusters might end up"
" with identical colors.")
def __init__(self, data):
"""
Args:
data: :py:class:`~clusterking.data.data.Data` object
"""
#: logging.Logger object
self.log = get_logger("ClusterPlot", sh_level=logging.WARNING)
#: Instance of pandas.DataFrame
self.data = data
# (Advanced) config values
# Documented in docstring of this class
#: Color scheme
self.color_scheme = None
#: List of markers of the get_clusters (scatter plot only).
self.markers = None
if not self.markers:
self.markers = ["o", "v", "^", "v", "<", ">"]
#: Maximal number of subplots
self.max_subplots = 16
#: Maximal number of columns of the subplot grid
self.max_cols = 4
#: Formatting of key-value pairs in title of plots
self.kv_formatter = "{}={:.2f}"
#: figure size of each subplot
self.fig_base_size = 4
#: Ratio of height/width. None: Automatically inferred
self.aspect_ratio = None
#: The name of the column that holds the cluster index
self.cluster_column = "cluster"
#: The name of the column that holds the benchmark yes/no information
self.bpoint_column = "bpoint"
#: Default marker size
self.default_marker_size = (1 / 2 *
matplotlib.rcParams["lines.markersize"]**2)
#: Marker size of benchmark points
self.bpoint_marker_size = 6 * self.default_marker_size
#: If true, a legend is drawn
self.draw_legend = True
# Internal values: Do not modify
# ----------------------------------------------------------------------
# Names of the columns to be on the axes of
# the plot.
self._axis_columns = None
self._clusters = None
self._df_dofs = None
self._fig = None
self._axs = None
#!/usr/bin/env python3
# std
import sys
# ours
import clusterking.cluster
import clusterking.data
import clusterking.maths
import clusterking.scan
import clusterking.util
from clusterking.data import Data, DataWithErrors
from clusterking.benchmark.benchmark import Benchmark
from clusterking.util.metadata import get_version as _get_version
from clusterking.util.log import get_logger
version = _get_version()
if sys.version_info < (3, 6):
get_logger().warning("The newer versions of ClusterKinG will require "
"python >= 3.6. Anything below that has reached"
" its end of life. Please consider upgrading.")