How to use the refinem.plots.base_plot.BasePlot function in refinem

#                                                                             #
#    You should have received a copy of the GNU General Public License        #
#    along with this program. If not, see .     #
#                                                                             #
###############################################################################

import mpld3

from scipy.stats import pearsonr
import numpy as np

from refinem.plots.base_plot import BasePlot
from refinem.plots.mpld3_plugins import Tooltip


class CovCorrPlots(BasePlot):
    """Histogram and scatterplot showing coverage profile correlation of scaffolds."""

    def __init__(self, options):
        """Initialize."""
        BasePlot.__init__(self, options)
        
    def _correlation(self, genome_scaffold_stats, mean_coverage):
        """Calculate percent deviant of coverage profiles for each scaffold."""
        
        correlations = []
        for stats in genome_scaffold_stats.values():
            corr_r = 1.0
            if len(mean_coverage) >= 1:
                corr_r, _corr_p = pearsonr(mean_coverage, stats.coverage)
                if np.isnan(corr_r):
                    # both coverage profiles contain identical values,

#    along with this program. If not, see .     #
#                                                                             #
###############################################################################

import matplotlib
import mpld3

import numpy as np

from refinem.plots.base_plot import BasePlot
from refinem.plots.mpld3_plugins import LinkedBrush, Tooltip

from biolib.pca import PCA


class TetraPcaPlot(BasePlot):
    """Create a scatterplot of the first 2 tetranucleotide principal components."""

    def __init__(self, options):
        """Initialize."""
        BasePlot.__init__(self, options)

        self.pca_computed = False
        self.pc = None
        self.variance = None
        
    def data_pts(self, genome_scaffold_stats, pc_xaxis, pc_yaxis):
        """Get data points to plot.

        Parameters
        ----------
        genome_scaffold_stats : d[scaffold_id] -> namedtuple of scaffold stats

#    along with this program. If not, see .     #
#                                                                             #
###############################################################################

import numpy as np

import mpld3

from biolib.common import find_nearest
from biolib.genomic_signature import GenomicSignature

from refinem.plots.base_plot import BasePlot
from refinem.plots.mpld3_plugins import Tooltip


class TdPlots(BasePlot):
    """Create histogram and scatterplot showing tetranucleotide distribution (TD) of scaffolds."""

    def __init__(self, options):
        """Initialize."""
        BasePlot.__init__(self, options)
        
    def data_pts(self, genome_scaffold_stats, mean_signature):
        """Get data points to plot.

        Parameters
        ----------
        genome_scaffold_stats : d[scaffold_id] -> namedtuple of scaffold stats
          Statistics for scaffolds in genome.
          
        Returns
        -------

#    GNU General Public License for more details.                             #
#                                                                             #
#    You should have received a copy of the GNU General Public License        #
#    along with this program. If not, see .     #
#                                                                             #
###############################################################################

import mpld3

import numpy as np

from refinem.plots.base_plot import BasePlot
from refinem.plots.mpld3_plugins import Tooltip


class CovPercPlots(BasePlot):
    """Histogram and scatterplot showing mean percent difference of coverage profiles of scaffolds."""

    def __init__(self, options):
        """Initialize."""
        BasePlot.__init__(self, options)
        
    def _mean_perc_diffs(self, genome_scaffold_stats, mean_coverage):
        """Calculate percent difference of coverage profiles for each scaffold."""
        
        mean_perc_diffs = []
        for stats in genome_scaffold_stats.values():
            mean_perc_diff = []
            for cov_genome, cov_scaffold in zip(mean_coverage, stats.coverage):
                if cov_genome == 0:
                    mean_perc_diff.append(0)
                elif len(mean_coverage) >= 2:

#    along with this program. If not, see .     #
#                                                                             #
###############################################################################

import numpy as np

import matplotlib
import mpld3

from biolib.common import find_nearest

from refinem.plots.base_plot import BasePlot
from refinem.plots.mpld3_plugins import Tooltip


class GcPlots(BasePlot):
    """Create histogram and scatterplot showing GC distribution of scaffolds."""

    def __init__(self, options):
        """Initialize."""
        BasePlot.__init__(self, options)
        
    def data_pts(self, genome_scaffold_stats, mean_gc):
        """Get data points to plot.

        Parameters
        ----------
        genome_scaffold_stats : d[scaffold_id] -> namedtuple of scaffold stats
          Statistics for scaffolds in genome.
          
        Returns
        -------