plot.py 12.8 KB
Newer Older
1 2 3 4 5 6 7 8 9 10 11 12 13
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# 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 <http://www.gnu.org/licenses/>.
#
14
# Copyright(C) 2013-2019 Max-Planck-Society
15
#
16
# NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik.
17

Martin Reinecke's avatar
Martin Reinecke committed
18 19
import os

20 21
import numpy as np

Martin Reinecke's avatar
fix  
Martin Reinecke committed
22 23 24 25 26 27
from . import dobj
from .domains.gl_space import GLSpace
from .domains.hp_space import HPSpace
from .domains.power_space import PowerSpace
from .domains.rg_space import RGSpace
from .field import Field
28

Martin Reinecke's avatar
Martin Reinecke committed
29 30 31 32 33 34 35 36
# relevant properties:
# - x/y size
# - x/y/z log
# - x/y/z min/max
# - colorbar/colormap
# - axis on/off
# - title
# - axis labels
Martin Reinecke's avatar
Martin Reinecke committed
37
# - labels
Martin Reinecke's avatar
Martin Reinecke committed
38

Martin Reinecke's avatar
PEP8  
Martin Reinecke committed
39

Martin Reinecke's avatar
Martin Reinecke committed
40 41 42
def _mollweide_helper(xsize):
    xsize = int(xsize)
    ysize = xsize//2
Martin Reinecke's avatar
Martin Reinecke committed
43
    res = np.full(shape=(ysize, xsize), fill_value=np.nan, dtype=np.float64)
Martin Reinecke's avatar
Martin Reinecke committed
44
    xc, yc = (xsize-1)*0.5, (ysize-1)*0.5
Martin Reinecke's avatar
Martin Reinecke committed
45
    u, v = np.meshgrid(np.arange(xsize), np.arange(ysize))
Martin Reinecke's avatar
Martin Reinecke committed
46
    u, v = 2*(u-xc)/(xc/1.02), (v-yc)/(yc/1.02)
Martin Reinecke's avatar
Martin Reinecke committed
47 48 49 50 51 52 53 54 55

    mask = np.where((u*u*0.25 + v*v) <= 1.)
    t1 = v[mask]
    theta = 0.5*np.pi-(
        np.arcsin(2/np.pi*(np.arcsin(t1) + t1*np.sqrt((1.-t1)*(1+t1)))))
    phi = -0.5*np.pi*u[mask]/np.maximum(np.sqrt((1-t1)*(1+t1)), 1e-6)
    phi = np.where(phi < 0, phi+2*np.pi, phi)
    return res, mask, theta, phi

Martin Reinecke's avatar
PEP8  
Martin Reinecke committed
56

Martin Reinecke's avatar
Martin Reinecke committed
57 58
def _find_closest(A, target):
    # A must be sorted
Martin Reinecke's avatar
Martin Reinecke committed
59 60
    idx = np.clip(A.searchsorted(target), 1, len(A)-1)
    idx -= target - A[idx-1] < A[idx] - target
Martin Reinecke's avatar
Martin Reinecke committed
61 62
    return idx

Martin Reinecke's avatar
PEP8  
Martin Reinecke committed
63

Martin Reinecke's avatar
Martin Reinecke committed
64
def _makeplot(name):
65
    import matplotlib.pyplot as plt
Martin Reinecke's avatar
Martin Reinecke committed
66
    if dobj.rank != 0:
67
        plt.close()
Martin Reinecke's avatar
tweaks  
Martin Reinecke committed
68
        return
Martin Reinecke's avatar
Martin Reinecke committed
69 70
    if name is None:
        plt.show()
71
        plt.close()
Martin Reinecke's avatar
Martin Reinecke committed
72 73
        return
    extension = os.path.splitext(name)[1]
74
    if extension in (".pdf", ".png", ".svg"):
Martin Reinecke's avatar
Martin Reinecke committed
75 76 77 78 79
        plt.savefig(name)
        plt.close()
    else:
        raise ValueError("file format not understood")

Martin Reinecke's avatar
PEP8  
Martin Reinecke committed
80

Martin Reinecke's avatar
Martin Reinecke committed
81
def _limit_xy(**kwargs):
Martin Reinecke's avatar
Martin Reinecke committed
82
    import matplotlib.pyplot as plt
Martin Reinecke's avatar
PEP8  
Martin Reinecke committed
83
    x1, x2, y1, y2 = plt.axis()
clienhar's avatar
clienhar committed
84 85 86 87
    x1 = kwargs.pop("xmin", x1)
    x2 = kwargs.pop("xmax", x2)
    y1 = kwargs.pop("ymin", y1)
    y2 = kwargs.pop("ymax", y2)
Martin Reinecke's avatar
PEP8  
Martin Reinecke committed
88 89
    plt.axis((x1, x2, y1, y2))

Martin Reinecke's avatar
Martin Reinecke committed
90

Martin Reinecke's avatar
Martin Reinecke committed
91 92 93 94 95 96 97 98 99
def _register_cmaps():
    try:
        if _register_cmaps._cmaps_registered:
            return
    except AttributeError:
        _register_cmaps._cmaps_registered = True

    from matplotlib.colors import LinearSegmentedColormap
    import matplotlib.pyplot as plt
Martin Reinecke's avatar
Martin Reinecke committed
100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145
    planckcmap = {'red':   ((0., 0., 0.), (.4, 0., 0.), (.5, 1., 1.),
                            (.7, 1., 1.), (.8, .83, .83), (.9, .67, .67),
                            (1., .5, .5)),
                  'green': ((0., 0., 0.), (.2, 0., 0.), (.3, .3, .3),
                            (.4, .7, .7), (.5, 1., 1.), (.6, .7, .7),
                            (.7, .3, .3), (.8, 0., 0.), (1., 0., 0.)),
                  'blue':  ((0., .5, .5), (.1, .67, .67), (.2, .83, .83),
                            (.3, 1., 1.), (.5, 1., 1.), (.6, 0., 0.),
                            (1., 0., 0.))}
    he_cmap = {'red':   ((0., 0., 0.), (.167, 0., 0.), (.333, .5, .5),
                         (.5, 1., 1.), (1., 1., 1.)),
               'green': ((0., 0., 0.), (.5, 0., 0.), (.667, .5, .5),
                         (.833, 1., 1.), (1., 1., 1.)),
               'blue':  ((0., 0., 0.), (.167, 1., 1.), (.333, .5, .5),
                         (.5, 0., 0.), (1., 1., 1.))}
    fd_cmap = {'red':   ((0., .35, .35), (.1, .4, .4), (.2, .25, .25),
                         (.41, .47, .47), (.5, .8, .8), (.56, .96, .96),
                         (.59, 1., 1.), (.74, .8, .8), (.8, .8, .8),
                         (.9, .5, .5), (1., .4, .4)),
               'green': ((0., 0., 0.), (.2, 0., 0.), (.362, .88, .88),
                         (.5, 1., 1.), (.638, .88, .88), (.8, .25, .25),
                         (.9, .3, .3), (1., .2, .2)),
               'blue':  ((0., .35, .35), (.1, .4, .4), (.2, .8, .8),
                         (.26, .8, .8), (.41, 1., 1.), (.44, .96, .96),
                         (.5, .8, .8), (.59, .47, .47), (.8, 0., 0.),
                         (1., 0., 0.))}
    fdu_cmap = {'red':   ((0., 1., 1.), (0.1, .8, .8), (.2, .65, .65),
                          (.41, .6, .6), (.5, .7, .7), (.56, .96, .96),
                          (.59, 1., 1.), (.74, .8, .8), (.8, .8, .8),
                          (.9, .5, .5), (1., .4, .4)),
                'green': ((0., .9, .9), (.362, .95, .95), (.5, 1., 1.),
                          (.638, .88, .88), (.8, .25, .25), (.9, .3, .3),
                          (1., .2, .2)),
                'blue':  ((0., 1., 1.), (.1, .8, .8), (.2, 1., 1.),
                          (.41, 1., 1.), (.44, .96, .96), (.5, .7, .7),
                          (.59, .42, .42), (.8, 0., 0.), (1., 0., 0.))}
    pm_cmap = {'red':   ((0., 1., 1.), (.1, .96, .96), (.2, .84, .84),
                         (.3, .64, .64), (.4, .36, .36), (.5, 0., 0.),
                         (1., 0., 0.)),
               'green': ((0., .5, .5), (.1, .32, .32), (.2, .18, .18),
                         (.3, .8, .8),  (.4, .2, .2), (.5, 0., 0.),
                         (.6, .2, .2), (.7, .8, .8), (.8, .18, .18),
                         (.9, .32, .32), (1., .5, .5)),
               'blue':  ((0., 0., 0.), (.5, 0., 0.), (.6, .36, .36),
                         (.7, .64, .64), (.8, .84, .84), (.9, .96, .96),
                         (1., 1., 1.))}
Martin Reinecke's avatar
Martin Reinecke committed
146 147 148

    plt.register_cmap(cmap=LinearSegmentedColormap("Planck-like", planckcmap))
    plt.register_cmap(cmap=LinearSegmentedColormap("High Energy", he_cmap))
Martin Reinecke's avatar
Martin Reinecke committed
149
    plt.register_cmap(cmap=LinearSegmentedColormap("Faraday Map", fd_cmap))
Martin Reinecke's avatar
Martin Reinecke committed
150 151
    plt.register_cmap(cmap=LinearSegmentedColormap("Faraday Uncertainty",
                                                   fdu_cmap))
Martin Reinecke's avatar
Martin Reinecke committed
152
    plt.register_cmap(cmap=LinearSegmentedColormap("Plus Minus", pm_cmap))
Martin Reinecke's avatar
Martin Reinecke committed
153

Martin Reinecke's avatar
Martin Reinecke committed
154

Martin Reinecke's avatar
Martin Reinecke committed
155
def _plot(f, ax, **kwargs):
156
    import matplotlib.pyplot as plt
Martin Reinecke's avatar
Martin Reinecke committed
157
    _register_cmaps()
158 159 160
    if isinstance(f, Field):
        f = [f]
    if not isinstance(f, list):
Martin Reinecke's avatar
Martin Reinecke committed
161
        raise TypeError("incorrect data type")
162 163 164 165 166 167 168 169 170 171 172
    for i, fld in enumerate(f):
        if not isinstance(fld, Field):
            raise TypeError("incorrect data type")
        if i == 0:
            dom = fld.domain
            if len(dom) != 1:
                raise ValueError("input field must have exactly one domain")
        else:
            if fld.domain != dom:
                raise ValueError("domain mismatch")
            if not (isinstance(dom[0], PowerSpace) or
173
                    (isinstance(dom[0], RGSpace) and len(dom[0].shape) == 1)):
174
                raise ValueError("PowerSpace or 1D RGSpace required")
Martin Reinecke's avatar
Martin Reinecke committed
175

clienhar's avatar
clienhar committed
176
    label = kwargs.pop("label", None)
177
    if not isinstance(label, list):
Martin Reinecke's avatar
Martin Reinecke committed
178
        label = [label] * len(f)
Martin Reinecke's avatar
Martin Reinecke committed
179

Martin Reinecke's avatar
Martin Reinecke committed
180
    linewidth = kwargs.pop("linewidth", 1.)
Philipp Arras's avatar
Philipp Arras committed
181
    if not isinstance(linewidth, list):
Martin Reinecke's avatar
Martin Reinecke committed
182
        linewidth = [linewidth] * len(f)
Philipp Arras's avatar
Philipp Arras committed
183

clienhar's avatar
clienhar committed
184
    alpha = kwargs.pop("alpha", None)
Philipp Arras's avatar
Philipp Arras committed
185
    if not isinstance(alpha, list):
Martin Reinecke's avatar
Martin Reinecke committed
186
        alpha = [alpha] * len(f)
Philipp Arras's avatar
Philipp Arras committed
187

Philipp Arras's avatar
Philipp Arras committed
188 189
    foo = kwargs.pop("norm", None)
    norm = {} if foo is None else {'norm': foo}
190

191
    dom = dom[0]
clienhar's avatar
clienhar committed
192 193 194 195
    ax.set_title(kwargs.pop("title", ""))
    ax.set_xlabel(kwargs.pop("xlabel", ""))
    ax.set_ylabel(kwargs.pop("ylabel", ""))
    cmap = kwargs.pop("colormap", plt.rcParams['image.cmap'])
Martin Reinecke's avatar
Martin Reinecke committed
196
    if isinstance(dom, RGSpace):
Martin Reinecke's avatar
PEP8  
Martin Reinecke committed
197
        if len(dom.shape) == 1:
Martin Reinecke's avatar
Martin Reinecke committed
198 199
            npoints = dom.shape[0]
            dist = dom.distances[0]
Martin Reinecke's avatar
PEP8  
Martin Reinecke committed
200
            xcoord = np.arange(npoints, dtype=np.float64)*dist
Martin Reinecke's avatar
Martin Reinecke committed
201
            for i, fld in enumerate(f):
Martin Reinecke's avatar
tweaks  
Martin Reinecke committed
202
                ycoord = fld.to_global_data()
Martin Reinecke's avatar
Martin Reinecke committed
203 204
                plt.plot(xcoord, ycoord, label=label[i],
                         linewidth=linewidth[i], alpha=alpha[i])
Martin Reinecke's avatar
Martin Reinecke committed
205
            _limit_xy(**kwargs)
206 207
            if label != ([None]*len(f)):
                plt.legend()
Martin Reinecke's avatar
Martin Reinecke committed
208
            return
Martin Reinecke's avatar
PEP8  
Martin Reinecke committed
209
        elif len(dom.shape) == 2:
Martin Reinecke's avatar
Martin Reinecke committed
210 211
            nx, ny = dom.shape
            dx, dy = dom.distances
Martin Reinecke's avatar
Martin Reinecke committed
212 213 214 215
            im = ax.imshow(
                f[0].to_global_data().T, extent=[0, nx*dx, 0, ny*dy],
                vmin=kwargs.get("zmin"), vmax=kwargs.get("zmax"),
                cmap=cmap, origin="lower", **norm)
Martin Reinecke's avatar
PEP8  
Martin Reinecke committed
216 217 218 219
            # from mpl_toolkits.axes_grid1 import make_axes_locatable
            # divider = make_axes_locatable(ax)
            # cax = divider.append_axes("right", size="5%", pad=0.05)
            # plt.colorbar(im,cax=cax)
Martin Reinecke's avatar
Martin Reinecke committed
220
            plt.colorbar(im)
Martin Reinecke's avatar
Martin Reinecke committed
221
            _limit_xy(**kwargs)
Martin Reinecke's avatar
Martin Reinecke committed
222 223 224 225
            return
    elif isinstance(dom, PowerSpace):
        plt.xscale('log')
        plt.yscale('log')
Philipp Arras's avatar
Philipp Arras committed
226
        xcoord = dom.k_lengths
Martin Reinecke's avatar
Martin Reinecke committed
227
        for i, fld in enumerate(f):
Martin Reinecke's avatar
tweaks  
Martin Reinecke committed
228
            ycoord = fld.to_global_data()
Martin Reinecke's avatar
Martin Reinecke committed
229 230
            plt.plot(xcoord, ycoord, label=label[i],
                     linewidth=linewidth[i], alpha=alpha[i])
Martin Reinecke's avatar
Martin Reinecke committed
231
        _limit_xy(**kwargs)
232 233
        if label != ([None]*len(f)):
            plt.legend()
Martin Reinecke's avatar
Martin Reinecke committed
234
        return
Martin Reinecke's avatar
Martin Reinecke committed
235
    elif isinstance(dom, (HPSpace, GLSpace)):
Martin Reinecke's avatar
Martin Reinecke committed
236 237 238
        import pyHealpix
        xsize = 800
        res, mask, theta, phi = _mollweide_helper(xsize)
Martin Reinecke's avatar
Martin Reinecke committed
239 240 241 242 243 244 245 246 247 248 249 250 251
        if isinstance(dom, HPSpace):
            ptg = np.empty((phi.size, 2), dtype=np.float64)
            ptg[:, 0] = theta
            ptg[:, 1] = phi
            base = pyHealpix.Healpix_Base(int(np.sqrt(f[0].size//12)), "RING")
            res[mask] = f[0].to_global_data()[base.ang2pix(ptg)]
        else:
            ra = np.linspace(0, 2*np.pi, dom.nlon+1)
            dec = pyHealpix.GL_thetas(dom.nlat)
            ilat = _find_closest(dec, theta)
            ilon = _find_closest(ra, phi)
            ilon = np.where(ilon == dom.nlon, 0, ilon)
            res[mask] = f[0].to_global_data()[ilat*dom.nlon + ilon]
Martin Reinecke's avatar
Martin Reinecke committed
252
        plt.axis('off')
Martin Reinecke's avatar
PEP8  
Martin Reinecke committed
253
        plt.imshow(res, vmin=kwargs.get("zmin"), vmax=kwargs.get("zmax"),
Martin Reinecke's avatar
Martin Reinecke committed
254
                   cmap=cmap, origin="lower")
Martin Reinecke's avatar
Martin Reinecke committed
255
        plt.colorbar(orientation="horizontal")
Martin Reinecke's avatar
Martin Reinecke committed
256 257 258
        return

    raise ValueError("Field type not(yet) supported")
Martin Reinecke's avatar
Martin Reinecke committed
259

Martin Reinecke's avatar
tweaks  
Martin Reinecke committed
260

261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276
class Plot(object):
    def __init__(self):
        self._plots = []
        self._kwargs = []

    def add(self, f, **kwargs):
        """Add a figure to the current list of plots.

        Notes
        -----
        After doing one or more calls `plot()`, one also needs to call
        `plot_finish()` to output the result.

        Parameters
        ----------
        f: Field, or list of Field objects
Philipp Arras's avatar
Philipp Arras committed
277
            If `f` is a single Field, it must be defined on a single `RGSpace`,
Martin Reinecke's avatar
typo  
Martin Reinecke committed
278
            `PowerSpace`, `HPSpace`, `GLSpace`.
Philipp Arras's avatar
Philipp Arras committed
279
            If it is a list, all list members must be Fields defined over the
280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336
            same one-dimensional `RGSpace` or `PowerSpace`.
        title: string
            title of the plot
        xlabel: string
            label for the x axis
        ylabel: string
            label for the y axis
        [xyz]min, [xyz]max: float
            limits for the values to plot
        colormap: string
            color map to use for the plot (if it is a 2D plot)
        linewidth: float or list of floats
            line width
        label: string of list of strings
            annotation string
        alpha: float or list of floats
            transparency value
        """
        self._plots.append(f)
        self._kwargs.append(kwargs)

    def output(self, **kwargs):
        """Plot the accumulated list of figures.

        Parameters
        ----------
        title: string
            title of the full plot
        nx, ny: integer (default: square root of the numer of plots, rounded up)
            number of subplots to use in x- and y-direction
        xsize, ysize: float (default: 6)
            dimensions of the full plot in inches
        name: string (default: "")
            if left empty, the plot will be shown on the screen,
            otherwise it will be written to a file with the given name.
            Supported extensions: .png and .pdf
        """
        import matplotlib.pyplot as plt
        nplot = len(self._plots)
        fig = plt.figure()
        if "title" in kwargs:
            plt.suptitle(kwargs.pop("title"))
        nx = kwargs.pop("nx", int(np.ceil(np.sqrt(nplot))))
        ny = kwargs.pop("ny", int(np.ceil(np.sqrt(nplot))))
        if nx*ny < nplot:
            raise ValueError(
                'Figure dimensions not sufficient for number of plots. '
                'Available plot slots: {}, number of plots: {}'
                .format(nx*ny, nplot))
        xsize = kwargs.pop("xsize", 6)
        ysize = kwargs.pop("ysize", 6)
        fig.set_size_inches(xsize, ysize)
        for i in range(nplot):
            ax = fig.add_subplot(ny, nx, i+1)
            _plot(self._plots[i], ax, **self._kwargs[i])
        fig.tight_layout()
        _makeplot(kwargs.pop("name", None))