<filename>ph_plotter/points_sf_plotter.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import (absolute_import, division,
                        print_function, unicode_literals)
import numpy as np
from matplotlib.ticker import AutoMinorLocator
from matplotlib.backends.backend_pdf import PdfPages
from ph_plotter.sf_plotter import SFPlotter


__author__ = "<NAME>"


class PointsSFPlotter(SFPlotter):
    def configure(self, ax):
        variables = self._variables

        freq_label = "Frequency ({})".format(variables["freq_unit"])
        d_freq = variables["d_freq"]
        f_min = variables["f_min"]
        f_max = variables["f_max"]
        n_freq = int(round((f_max - f_min) / d_freq)) + 1

        sf_label = self._create_sf_label()
        sf_min = variables["sf_min"]
        sf_max = variables["sf_max"]
        d_sf = variables["d_sf"]
        nticks_sf = int(round((sf_max - sf_min) / d_sf)) + 1

        mlx = AutoMinorLocator(2)
        ax.xaxis.set_minor_locator(mlx)
        mly = AutoMinorLocator(2)
        ax.yaxis.set_minor_locator(mly)

        # zero axis
        ax.axvline(0, color="#b0b0b0", linewidth=0.8)
        ax.axhline(0, color="#b0b0b0", linewidth=0.8)

        if self._is_horizontal:

            ax.set_xticks(np.linspace(f_min, f_max, n_freq))
            ax.set_xlabel(freq_label)
            ax.set_xlim(f_min, f_max)

            ax.set_yticks(np.linspace(sf_min, sf_max, nticks_sf))
            ax.set_ylabel(sf_label)
            ax.set_ylim(sf_min, sf_max)

        else:

            ax.set_yticks(np.linspace(f_min, f_max, n_freq))
            ax.set_ylabel(freq_label)
            ax.set_ylim(f_min, f_max)

            ax.set_xticks(np.linspace(sf_min, sf_max, nticks_sf))
            ax.set_xlabel(sf_label)
            ax.set_xlim(sf_min, sf_max)

    def create_figure(self):
        fig, ax = self.prepare_figure()
        figure_name = self.create_figure_name()

        if self._variables['points'] is not None:
            indices = self._variables['points']
        else:
            indices = range(len(self._xs))

        with PdfPages(figure_name) as pdf:
            for iq in indices:
                print(iq, self._data_points[iq]['pointgroup_symbol'])
                self.configure(ax)
                self.plot_q(ax, iq)
                ax.legend()
                pdf.savefig(dpi=288, transparent=True)
                ax.clear()
                self._reset_prop_cycle(ax)

        self.close()

    def plot_q(self, ax, iq):
        raise NotImplementedError

    def plot_total_q(self, ax, iq):
        variables = self._variables

        sf = self._data_points[iq]['total_sf']

        if self._is_horizontal:
            xs = self._frequencies[iq] * variables["unit"]
            ys = sf
        else:
            xs = sf
            ys = self._frequencies[iq] * variables["unit"]

        lines_total = ax.plot(
            xs,
            ys,
            color=variables["linecolor"],
            dashes=variables["dashes"],
            linewidth=variables["linewidth"],
            label="Total",
        )

        return lines_total

    def _plot_curve(self, ax, iq, sf, label, **kwargs):
        variables = self._variables

        if self._is_horizontal:
            xs = self._frequencies[iq] * variables["unit"]
            ys = sf
        else:
            xs = sf
            ys = self._frequencies[iq] * variables["unit"]

        linewidth = self._variables["linewidth"]
        lines = ax.plot(
            xs,
            ys,
            linewidth=linewidth,
            label=label,
            **kwargs
        )
        if variables['is_filled']:
            # TODO(ikeda): So far this is only for the vertical plot.
            ax.fill_between(xs, ys, alpha=0.25, **kwargs)
        return lines

    def create_list_element_indices(self):
        from phonopy.interface.vasp import read_vasp
        filename = self._variables["poscar"]
        atoms = read_vasp(filename)

        symbols = atoms.get_chemical_symbols()
        reduced_symbols = sorted(set(symbols), key=symbols.index)
        list_element_indices = []
        for s in reduced_symbols:
            indices = [i for i, x in enumerate(symbols) if x == s]
            list_element_indices.append((s, indices))

        self._natoms = atoms.get_number_of_atoms()
        self._list_element_indices = list_element_indices

    def _expand_list_element_indices(self):
        list_element_indices = self._list_element_indices
        ndim = 3
        expanded_list_element_indices = []
        for element_indices in list_element_indices:
            s, indices = element_indices

            indices = np.repeat(indices, ndim)
            indices *= ndim
            for i in range(ndim):
                indices[i::ndim] += i

            expanded_list_element_indices.append((s, indices))

        self._list_element_indices = expanded_list_element_indices

    @staticmethod
    def _modify_dashes_by_linewidth(dashes, linewidth):
        return tuple(np.array(dashes) * linewidth)

    @staticmethod
    def _reset_prop_cycle(ax):
        # http://matplotlib.org/api/_as_gen/matplotlib.axes.Axes.set_prop_cycle.html#matplotlib.axes.Axes.set_prop_cycle
        ax.set_prop_cycle(None)

<filename>ph_plotter/points_sf_plotter.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import (absolute_import, division,
                        print_function, unicode_literals)
import numpy as np
from matplotlib.ticker import AutoMinorLocator
from matplotlib.backends.backend_pdf import PdfPages
from ph_plotter.sf_plotter import SFPlotter


__author__ = "<NAME>"


class PointsSFPlotter(SFPlotter):
    def configure(self, ax):
        variables = self._variables

        freq_label = "Frequency ({})".format(variables["freq_unit"])
        d_freq = variables["d_freq"]
        f_min = variables["f_min"]
        f_max = variables["f_max"]
        n_freq = int(round((f_max - f_min) / d_freq)) + 1

        sf_label = self._create_sf_label()
        sf_min = variables["sf_min"]
        sf_max = variables["sf_max"]
        d_sf = variables["d_sf"]
        nticks_sf = int(round((sf_max - sf_min) / d_sf)) + 1

        mlx = AutoMinorLocator(2)
        ax.xaxis.set_minor_locator(mlx)
        mly = AutoMinorLocator(2)
        ax.yaxis.set_minor_locator(mly)

        # zero axis
        ax.axvline(0, color="#b0b0b0", linewidth=0.8)
        ax.axhline(0, color="#b0b0b0", linewidth=0.8)

        if self._is_horizontal:

            ax.set_xticks(np.linspace(f_min, f_max, n_freq))
            ax.set_xlabel(freq_label)
            ax.set_xlim(f_min, f_max)

            ax.set_yticks(np.linspace(sf_min, sf_max, nticks_sf))
            ax.set_ylabel(sf_label)
            ax.set_ylim(sf_min, sf_max)

        else:

            ax.set_yticks(np.linspace(f_min, f_max, n_freq))
            ax.set_ylabel(freq_label)
            ax.set_ylim(f_min, f_max)

            ax.set_xticks(np.linspace(sf_min, sf_max, nticks_sf))
            ax.set_xlabel(sf_label)
            ax.set_xlim(sf_min, sf_max)

    def create_figure(self):
        fig, ax = self.prepare_figure()
        figure_name = self.create_figure_name()

        if self._variables['points'] is not None:
            indices = self._variables['points']
        else:
            indices = range(len(self._xs))

        with PdfPages(figure_name) as pdf:
            for iq in indices:
                print(iq, self._data_points[iq]['pointgroup_symbol'])
                self.configure(ax)
                self.plot_q(ax, iq)
                ax.legend()
                pdf.savefig(dpi=288, transparent=True)
                ax.clear()
                self._reset_prop_cycle(ax)

        self.close()

    def plot_q(self, ax, iq):
        raise NotImplementedError

    def plot_total_q(self, ax, iq):
        variables = self._variables

        sf = self._data_points[iq]['total_sf']

        if self._is_horizontal:
            xs = self._frequencies[iq] * variables["unit"]
            ys = sf
        else:
            xs = sf
            ys = self._frequencies[iq] * variables["unit"]

        lines_total = ax.plot(
            xs,
            ys,
            color=variables["linecolor"],
            dashes=variables["dashes"],
            linewidth=variables["linewidth"],
            label="Total",
        )

        return lines_total

    def _plot_curve(self, ax, iq, sf, label, **kwargs):
        variables = self._variables

        if self._is_horizontal:
            xs = self._frequencies[iq] * variables["unit"]
            ys = sf
        else:
            xs = sf
            ys = self._frequencies[iq] * variables["unit"]

        linewidth = self._variables["linewidth"]
        lines = ax.plot(
            xs,
            ys,
            linewidth=linewidth,
            label=label,
            **kwargs
        )
        if variables['is_filled']:
            # TODO(ikeda): So far this is only for the vertical plot.
            ax.fill_between(xs, ys, alpha=0.25, **kwargs)
        return lines

    def create_list_element_indices(self):
        from phonopy.interface.vasp import read_vasp
        filename = self._variables["poscar"]
        atoms = read_vasp(filename)

        symbols = atoms.get_chemical_symbols()
        reduced_symbols = sorted(set(symbols), key=symbols.index)
        list_element_indices = []
        for s in reduced_symbols:
            indices = [i for i, x in enumerate(symbols) if x == s]
            list_element_indices.append((s, indices))

        self._natoms = atoms.get_number_of_atoms()
        self._list_element_indices = list_element_indices

    def _expand_list_element_indices(self):
        list_element_indices = self._list_element_indices
        ndim = 3
        expanded_list_element_indices = []
        for element_indices in list_element_indices:
            s, indices = element_indices

            indices = np.repeat(indices, ndim)
            indices *= ndim
            for i in range(ndim):
                indices[i::ndim] += i

            expanded_list_element_indices.append((s, indices))

        self._list_element_indices = expanded_list_element_indices

    @staticmethod
    def _modify_dashes_by_linewidth(dashes, linewidth):
        return tuple(np.array(dashes) * linewidth)

    @staticmethod
    def _reset_prop_cycle(ax):
        # http://matplotlib.org/api/_as_gen/matplotlib.axes.Axes.set_prop_cycle.html#matplotlib.axes.Axes.set_prop_cycle
        ax.set_prop_cycle(None)

#!/usr/bin/env python # -*- coding: utf-8 -*- # zero axis # TODO(ikeda): So far this is only for the vertical plot. # http://matplotlib.org/api/_as_gen/matplotlib.axes.Axes.set_prop_cycle.html#matplotlib.axes.Axes.set_prop_cycle