plot.py 20.5 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
from . import dobj
from .domains.gl_space import GLSpace
from .domains.hp_space import HPSpace
Philipp Arras's avatar
Philipp Arras committed
25
from .domains.log_rg_space import LogRGSpace
Martin Reinecke's avatar
fix  
Martin Reinecke committed
26 27 28
from .domains.power_space import PowerSpace
from .domains.rg_space import RGSpace
from .field import Field
29

Martin Reinecke's avatar
Martin Reinecke committed
30 31 32 33 34 35 36 37
# 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
38
# - labels
Martin Reinecke's avatar
Martin Reinecke committed
39

Martin Reinecke's avatar
PEP8  
Martin Reinecke committed
40

Martin Reinecke's avatar
Martin Reinecke committed
41 42 43
def _mollweide_helper(xsize):
    xsize = int(xsize)
    ysize = xsize//2
Martin Reinecke's avatar
Martin Reinecke committed
44
    res = np.full(shape=(ysize, xsize), fill_value=np.nan, dtype=np.float64)
Martin Reinecke's avatar
Martin Reinecke committed
45
    xc, yc = (xsize-1)*0.5, (ysize-1)*0.5
Martin Reinecke's avatar
Martin Reinecke committed
46
    u, v = np.meshgrid(np.arange(xsize), np.arange(ysize))
Martin Reinecke's avatar
Martin Reinecke committed
47
    u, v = 2*(u-xc)/(xc/1.02), (v-yc)/(yc/1.02)
Martin Reinecke's avatar
Martin Reinecke committed
48 49 50 51 52 53 54 55 56

    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
57

58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170
def _rgb_data(spectral_cube):
    _xyz = np.array(
          [[0.000160, 0.000662, 0.002362, 0.007242, 0.019110,
            0.043400, 0.084736, 0.140638, 0.204492, 0.264737,
            0.314679, 0.357719, 0.383734, 0.386726, 0.370702,
            0.342957, 0.302273, 0.254085, 0.195618, 0.132349,
            0.080507, 0.041072, 0.016172, 0.005132, 0.003816,
            0.015444, 0.037465, 0.071358, 0.117749, 0.172953,
            0.236491, 0.304213, 0.376772, 0.451584, 0.529826,
            0.616053, 0.705224, 0.793832, 0.878655, 0.951162,
            1.014160, 1.074300, 1.118520, 1.134300, 1.123990,
            1.089100, 1.030480, 0.950740, 0.856297, 0.754930,
            0.647467, 0.535110, 0.431567, 0.343690, 0.268329,
            0.204300, 0.152568, 0.112210, 0.081261, 0.057930,
            0.040851, 0.028623, 0.019941, 0.013842, 0.009577,
            0.006605, 0.004553, 0.003145, 0.002175, 0.001506,
            0.001045, 0.000727, 0.000508, 0.000356, 0.000251,
            0.000178, 0.000126, 0.000090, 0.000065, 0.000046,
            0.000033],
           [0.000017, 0.000072, 0.000253, 0.000769, 0.002004,
            0.004509, 0.008756, 0.014456, 0.021391, 0.029497,
            0.038676, 0.049602, 0.062077, 0.074704, 0.089456,
            0.106256, 0.128201, 0.152761, 0.185190, 0.219940,
            0.253589, 0.297665, 0.339133, 0.395379, 0.460777,
            0.531360, 0.606741, 0.685660, 0.761757, 0.823330,
            0.875211, 0.923810, 0.961988, 0.982200, 0.991761,
            0.999110, 0.997340, 0.982380, 0.955552, 0.915175,
            0.868934, 0.825623, 0.777405, 0.720353, 0.658341,
            0.593878, 0.527963, 0.461834, 0.398057, 0.339554,
            0.283493, 0.228254, 0.179828, 0.140211, 0.107633,
            0.081187, 0.060281, 0.044096, 0.031800, 0.022602,
            0.015905, 0.011130, 0.007749, 0.005375, 0.003718,
            0.002565, 0.001768, 0.001222, 0.000846, 0.000586,
            0.000407, 0.000284, 0.000199, 0.000140, 0.000098,
            0.000070, 0.000050, 0.000036, 0.000025, 0.000018,
            0.000013],
           [0.000705, 0.002928, 0.010482, 0.032344, 0.086011,
            0.197120, 0.389366, 0.656760, 0.972542, 1.282500,
            1.553480, 1.798500, 1.967280, 2.027300, 1.994800,
            1.900700, 1.745370, 1.554900, 1.317560, 1.030200,
            0.772125, 0.570060, 0.415254, 0.302356, 0.218502,
            0.159249, 0.112044, 0.082248, 0.060709, 0.043050,
            0.030451, 0.020584, 0.013676, 0.007918, 0.003988,
            0.001091, 0.000000, 0.000000, 0.000000, 0.000000,
            0.000000, 0.000000, 0.000000, 0.000000, 0.000000,
            0.000000, 0.000000, 0.000000, 0.000000, 0.000000,
            0.000000, 0.000000, 0.000000, 0.000000, 0.000000,
            0.000000, 0.000000, 0.000000, 0.000000, 0.000000,
            0.000000, 0.000000, 0.000000, 0.000000, 0.000000,
            0.000000, 0.000000, 0.000000, 0.000000, 0.000000,
            0.000000, 0.000000, 0.000000, 0.000000, 0.000000,
            0.000000, 0.000000, 0.000000, 0.000000, 0.000000,
            0.000000]])

    MATRIX_SRGB_D65 = np.array(
            [[ 3.2404542, -1.5371385, -0.4985314],
             [-0.9692660,  1.8760108,  0.0415560],
             [ 0.0556434, -0.2040259,  1.0572252]])


    def _gammacorr(inp):
        mask = np.zeros(inp.shape, dtype=np.float64)
        mask[inp <= 0.0031308] = 1.
        r1 = 12.92*inp
        a = 0.055
        r2 = (1 + a) * (np.maximum(inp,0.0031308) ** (1/2.4)) - a
        return r1*mask + r2*(1.-mask)


    def lambda2rgb(lam):
        lammin=380.
        lammax=780.
        lam=np.asarray(lam, dtype=np.float64)
        lam = np.clip(lam, lammin, lammax)

        idx = (lam-lammin)/(lammax-lammin)*(_xyz.shape[1]-1)
        ii = np.maximum(0, np.minimum(79, int(idx)))
        w1 = 1.-(idx-ii)
        w2 = 1.-w1
        c = w1*_xyz[:,ii] + w2*_xyz[:,ii+1]
        c = _gammacorr(np.matmul(MATRIX_SRGB_D65, c))
        c = c.clip(0.,1.)
        return c

    def lambda2xyz(lam):
        lammin=380.
        lammax=780.
        lam=np.asarray(lam, dtype=np.float64)
        lam = np.clip(lam, lammin, lammax)

        idx = (lam-lammin)/(lammax-lammin)*(_xyz.shape[1]-1)
        ii = np.maximum(0, np.minimum(79, int(idx)))
        w1 = 1.-(idx-ii)
        w2 = 1.-w1
        c = w1*_xyz[:,ii] + w2*_xyz[:,ii+1]
        return c

    def getcol(n):
        E0, E1 = 1./700., 1./400.
        E = E0 + np.arange(n)*(E1-E0)/(n-1)
        res = np.zeros((3, n), dtype=np.float64)
        for i in range(n):
            res[:,i] = lambda2rgb(1./E[i])
        return res

    def getxyz(n):
        E0, E1 = 1./700., 1./400.
        E = E0 + np.arange(n)*(E1-E0)/(n-1)
        res = np.zeros((3, n), dtype=np.float64)
        for i in range(n):
            res[:,i] = lambda2xyz(1./E[i])
        return res

Martin Reinecke's avatar
tweaks  
Martin Reinecke committed
171 172 173 174 175 176 177 178 179
    def to_logscale(arr, lo, hi):
        res = arr.clip(lo, hi)
        res = np.log(res/hi)
        tmp = np.log(hi/lo)
        res += tmp
        res /= tmp
        return res

    spectral_cube = spectral_cube.reshape((-1, spectral_cube.shape[-1]))
180 181
    xyz = getxyz(spectral_cube.shape[-1])
    xyz_data = np.tensordot(spectral_cube, xyz, axes=[-1, -1])
Martin Reinecke's avatar
tweaks  
Martin Reinecke committed
182 183 184 185 186 187
#    vmax = max(xyz_data[:,0].max()/0.9505,
#               xyz_data[:,1].max(),
#               xyz_data[:,2].max()/1.0890)
    vmax = xyz_data.max()
    xyz_data /= vmax
    xyz_data = to_logscale(xyz_data, 1e-3, 1.)
188
    rgb_data = xyz_data.copy()
Martin Reinecke's avatar
tweaks  
Martin Reinecke committed
189 190 191 192 193
    it = np.nditer(xyz_data[:,0], flags=['multi_index'])
    for x in range(xyz_data.shape[0]):
        rgb_data[x] = _gammacorr(np.matmul(MATRIX_SRGB_D65, xyz_data[x]))
    rgb_data = rgb_data.clip(1e-13,1.)
    return rgb_data.reshape(spectral_cube.shape[:-1]+(-1,))
194 195


Martin Reinecke's avatar
Martin Reinecke committed
196 197
def _find_closest(A, target):
    # A must be sorted
Martin Reinecke's avatar
Martin Reinecke committed
198 199
    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
200 201
    return idx

Martin Reinecke's avatar
PEP8  
Martin Reinecke committed
202

Martin Reinecke's avatar
Martin Reinecke committed
203
def _makeplot(name):
204
    import matplotlib.pyplot as plt
Martin Reinecke's avatar
Martin Reinecke committed
205
    if dobj.rank != 0:
206
        plt.close()
Martin Reinecke's avatar
tweaks  
Martin Reinecke committed
207
        return
Martin Reinecke's avatar
Martin Reinecke committed
208 209
    if name is None:
        plt.show()
210
        plt.close()
Martin Reinecke's avatar
Martin Reinecke committed
211 212
        return
    extension = os.path.splitext(name)[1]
213
    if extension in (".pdf", ".png", ".svg"):
Martin Reinecke's avatar
Martin Reinecke committed
214 215 216 217 218
        plt.savefig(name)
        plt.close()
    else:
        raise ValueError("file format not understood")

Martin Reinecke's avatar
PEP8  
Martin Reinecke committed
219

Martin Reinecke's avatar
Martin Reinecke committed
220
def _limit_xy(**kwargs):
Martin Reinecke's avatar
Martin Reinecke committed
221
    import matplotlib.pyplot as plt
Martin Reinecke's avatar
PEP8  
Martin Reinecke committed
222
    x1, x2, y1, y2 = plt.axis()
clienhar's avatar
clienhar committed
223 224 225 226
    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
227 228
    plt.axis((x1, x2, y1, y2))

Martin Reinecke's avatar
Martin Reinecke committed
229

Martin Reinecke's avatar
Martin Reinecke committed
230 231 232 233 234 235 236 237 238
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
239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284
    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
285 286 287

    plt.register_cmap(cmap=LinearSegmentedColormap("Planck-like", planckcmap))
    plt.register_cmap(cmap=LinearSegmentedColormap("High Energy", he_cmap))
Martin Reinecke's avatar
Martin Reinecke committed
288
    plt.register_cmap(cmap=LinearSegmentedColormap("Faraday Map", fd_cmap))
Martin Reinecke's avatar
Martin Reinecke committed
289 290
    plt.register_cmap(cmap=LinearSegmentedColormap("Faraday Uncertainty",
                                                   fdu_cmap))
Martin Reinecke's avatar
Martin Reinecke committed
291
    plt.register_cmap(cmap=LinearSegmentedColormap("Plus Minus", pm_cmap))
Martin Reinecke's avatar
Martin Reinecke committed
292

Martin Reinecke's avatar
Martin Reinecke committed
293

294
def _plot1D(f, ax, **kwargs):
295
    import matplotlib.pyplot as plt
296

297 298 299 300 301
    for i, fld in enumerate(f):
        if not isinstance(fld, Field):
            raise TypeError("incorrect data type")
        if i == 0:
            dom = fld.domain
302 303
            if (len(dom) != 1):
                raise ValueError("input field must have exactly one domain")
304 305 306
        else:
            if fld.domain != dom:
                raise ValueError("domain mismatch")
307
    dom = dom[0]
Martin Reinecke's avatar
Martin Reinecke committed
308

clienhar's avatar
clienhar committed
309
    label = kwargs.pop("label", None)
310
    if not isinstance(label, list):
Martin Reinecke's avatar
Martin Reinecke committed
311
        label = [label] * len(f)
Martin Reinecke's avatar
Martin Reinecke committed
312

Martin Reinecke's avatar
Martin Reinecke committed
313
    linewidth = kwargs.pop("linewidth", 1.)
Philipp Arras's avatar
Philipp Arras committed
314
    if not isinstance(linewidth, list):
Martin Reinecke's avatar
Martin Reinecke committed
315
        linewidth = [linewidth] * len(f)
Philipp Arras's avatar
Philipp Arras committed
316

clienhar's avatar
clienhar committed
317
    alpha = kwargs.pop("alpha", None)
Philipp Arras's avatar
Philipp Arras committed
318
    if not isinstance(alpha, list):
Martin Reinecke's avatar
Martin Reinecke committed
319
        alpha = [alpha] * len(f)
Philipp Arras's avatar
Philipp Arras committed
320

clienhar's avatar
clienhar committed
321 322 323
    ax.set_title(kwargs.pop("title", ""))
    ax.set_xlabel(kwargs.pop("xlabel", ""))
    ax.set_ylabel(kwargs.pop("ylabel", ""))
324

Martin Reinecke's avatar
Martin Reinecke committed
325
    if isinstance(dom, RGSpace):
326
        plt.yscale(kwargs.pop("yscale", "linear"))
327 328 329 330 331 332 333 334 335 336 337
        npoints = dom.shape[0]
        dist = dom.distances[0]
        xcoord = np.arange(npoints, dtype=np.float64)*dist
        for i, fld in enumerate(f):
            ycoord = fld.to_global_data()
            plt.plot(xcoord, ycoord, label=label[i],
                     linewidth=linewidth[i], alpha=alpha[i])
        _limit_xy(**kwargs)
        if label != ([None]*len(f)):
            plt.legend()
        return
338
    elif isinstance(dom, LogRGSpace):
Martin Reinecke's avatar
fixes  
Martin Reinecke committed
339
        plt.yscale(kwargs.pop("yscale", "log"))
340 341 342 343 344 345 346 347 348 349
        npoints = dom.shape[0]
        xcoord = dom.t_0 + np.arange(npoints-1)*dom.bindistances[0]
        for i, fld in enumerate(f):
            ycoord = fld.to_global_data()[1:]
            plt.plot(xcoord, ycoord, label=label[i],
                     linewidth=linewidth[i], alpha=alpha[i])
        _limit_xy(**kwargs)
        if label != ([None]*len(f)):
            plt.legend()
        return
Martin Reinecke's avatar
Martin Reinecke committed
350
    elif isinstance(dom, PowerSpace):
351 352
        plt.xscale(kwargs.pop("xscale", "log"))
        plt.yscale(kwargs.pop("yscale", "log"))
Philipp Arras's avatar
Philipp Arras committed
353
        xcoord = dom.k_lengths
Martin Reinecke's avatar
Martin Reinecke committed
354
        for i, fld in enumerate(f):
Martin Reinecke's avatar
tweaks  
Martin Reinecke committed
355
            ycoord = fld.to_global_data()
Martin Reinecke's avatar
Martin Reinecke committed
356 357
            plt.plot(xcoord, ycoord, label=label[i],
                     linewidth=linewidth[i], alpha=alpha[i])
Martin Reinecke's avatar
Martin Reinecke committed
358
        _limit_xy(**kwargs)
359 360
        if label != ([None]*len(f)):
            plt.legend()
Martin Reinecke's avatar
Martin Reinecke committed
361
        return
362 363 364 365 366 367 368 369
    raise ValueError("Field type not(yet) supported")


def _plot2D(f, ax, **kwargs):
    import matplotlib.pyplot as plt

    dom = f.domain

370 371 372 373 374 375 376 377 378 379
    if len(dom) > 2:
        raise ValueError("DomainTuple can have at most two entries.")

    # check for multifrequency plotting
    have_rgb = False
    if len(dom) == 2:
        if (not isinstance(dom[1], RGSpace)) or len(dom[1].shape) != 1:
            raise TypeError("need 1D RGSpace as second domain")
        rgb = _rgb_data(f.to_global_data())
        have_rgb = True
380 381 382 383 384

    label = kwargs.pop("label", None)

    foo = kwargs.pop("norm", None)
    norm = {} if foo is None else {'norm': foo}
385 386
    aspect = kwargs.pop("aspect", None)
    aspect = {} if foo is None else {'aspect': foo}
387 388 389 390 391

    ax.set_title(kwargs.pop("title", ""))
    ax.set_xlabel(kwargs.pop("xlabel", ""))
    ax.set_ylabel(kwargs.pop("ylabel", ""))
    dom = dom[0]
392 393
    if not have_rgb:
        cmap = kwargs.pop("colormap", plt.rcParams['image.cmap'])
394 395 396 397

    if isinstance(dom, RGSpace):
        nx, ny = dom.shape
        dx, dy = dom.distances
398 399 400 401 402 403 404 405 406 407
        if have_rgb:
            im = ax.imshow(
                rgb, extent=[0, nx*dx, 0, ny*dy], origin="lower", **norm,
                **aspect)
        else:
            im = ax.imshow(
                f.to_global_data().T, extent=[0, nx*dx, 0, ny*dy],
                vmin=kwargs.get("zmin"), vmax=kwargs.get("zmax"),
                cmap=cmap, origin="lower", **norm, **aspect)
            plt.colorbar(im)
408 409
        _limit_xy(**kwargs)
        return
Martin Reinecke's avatar
Martin Reinecke committed
410
    elif isinstance(dom, (HPSpace, GLSpace)):
Martin Reinecke's avatar
Martin Reinecke committed
411 412 413
        import pyHealpix
        xsize = 800
        res, mask, theta, phi = _mollweide_helper(xsize)
414 415 416
        if have_rgb:
            res = np.full(shape=res.shape+(3,), fill_value=1., dtype=np.float64)

Martin Reinecke's avatar
Martin Reinecke committed
417 418 419 420
        if isinstance(dom, HPSpace):
            ptg = np.empty((phi.size, 2), dtype=np.float64)
            ptg[:, 0] = theta
            ptg[:, 1] = phi
421
            base = pyHealpix.Healpix_Base(int(np.sqrt(dom.size//12)), "RING")
422 423 424 425
            if have_rgb:
                res[mask] = rgb[base.ang2pix(ptg)]
            else:
                res[mask] = f.to_global_data()[base.ang2pix(ptg)]
Martin Reinecke's avatar
Martin Reinecke committed
426 427 428 429 430 431
        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)
432 433 434 435
            if have_rgb:
                res[mask] = rgb[ilat*dom[0].nlon + ilon]
            else:
                res[mask] = f.to_global_data()[ilat*dom.nlon + ilon]
Martin Reinecke's avatar
Martin Reinecke committed
436
        plt.axis('off')
437 438 439 440 441 442
        if have_rgb:
            plt.imshow(res, origin="lower")
        else:
            plt.imshow(res, vmin=kwargs.get("zmin"), vmax=kwargs.get("zmax"),
                       cmap=cmap, origin="lower")
            plt.colorbar(orientation="horizontal")
443 444 445 446 447 448 449 450 451 452 453 454 455 456
        return
    raise ValueError("Field type not(yet) supported")


def _plot(f, ax, **kwargs):
    _register_cmaps()
    if isinstance(f, Field):
        f = [f]
    f = list(f)
    if len(f) == 0:
        raise ValueError("need something to plot")
    if not isinstance(f[0], Field):
            raise TypeError("incorrect data type")
    dom1 = f[0].domain
Martin Reinecke's avatar
Martin Reinecke committed
457 458
    if (len(dom1) == 1 and
        (isinstance(dom1[0], PowerSpace) or
459 460
            (isinstance(dom1[0], (RGSpace, LogRGSpace)) and
             len(dom1[0].shape) == 1))):
461 462 463 464 465 466
        _plot1D(f, ax, **kwargs)
        return
    else:
        if len(f) != 1:
            raise ValueError("need exactly one Field for 2D plot")
        _plot2D(f[0], ax, **kwargs)
Martin Reinecke's avatar
Martin Reinecke committed
467 468
        return
    raise ValueError("Field type not(yet) supported")
Martin Reinecke's avatar
Martin Reinecke committed
469

Martin Reinecke's avatar
tweaks  
Martin Reinecke committed
470

471 472 473 474 475 476 477 478 479 480
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
        -----
Philipp Arras's avatar
Docs  
Philipp Arras committed
481 482
        After doing one or more calls `add()`, one needs to call `output()` to
        show or save the plot.
483 484 485

        Parameters
        ----------
Philipp Arras's avatar
Philipp Arras committed
486
        f: Field or list of Field
Philipp Arras's avatar
Philipp Arras committed
487
            If `f` is a single Field, it must be defined on a single `RGSpace`,
Martin Reinecke's avatar
typo  
Martin Reinecke committed
488
            `PowerSpace`, `HPSpace`, `GLSpace`.
Philipp Arras's avatar
Philipp Arras committed
489
            If it is a list, all list members must be Fields defined over the
490 491
            same one-dimensional `RGSpace` or `PowerSpace`.
        title: string
Philipp Arras's avatar
Docs  
Philipp Arras committed
492
            Title of the plot.
493
        xlabel: string
Philipp Arras's avatar
Philipp Arras committed
494
            Label for the x axis.
495
        ylabel: string
Philipp Arras's avatar
Philipp Arras committed
496
            Label for the y axis.
497
        [xyz]min, [xyz]max: float
Philipp Arras's avatar
Philipp Arras committed
498
            Limits for the values to plot.
499
        colormap: string
Philipp Arras's avatar
Philipp Arras committed
500
            Color map to use for the plot (if it is a 2D plot).
501
        linewidth: float or list of floats
Philipp Arras's avatar
Philipp Arras committed
502
            Line width.
503
        label: string of list of strings
Philipp Arras's avatar
Philipp Arras committed
504
            Annotation string.
505
        alpha: float or list of floats
Philipp Arras's avatar
Docs  
Philipp Arras committed
506
            Transparency value.
507 508 509 510 511 512 513 514 515 516
        """
        self._plots.append(f)
        self._kwargs.append(kwargs)

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

        Parameters
        ----------
        title: string
Philipp Arras's avatar
Philipp Arras committed
517 518 519 520 521 522 523 524
            Title of the full plot.
        nx, ny: int
            Number of subplots to use in x- and y-direction.
            Default: square root of the numer of plots, rounded up.
        xsize, ysize: float
            Dimensions of the full plot in inches. Default: 6.
        name: string
            If left empty, the plot will be shown on the screen,
525
            otherwise it will be written to a file with the given name.
Philipp Arras's avatar
Philipp Arras committed
526
            Supported extensions: .png and .pdf. Default: None.
527 528 529 530 531 532
        """
        import matplotlib.pyplot as plt
        nplot = len(self._plots)
        fig = plt.figure()
        if "title" in kwargs:
            plt.suptitle(kwargs.pop("title"))
533 534 535 536 537 538 539 540
        nx = kwargs.pop("nx", 0)
        ny = kwargs.pop("ny", 0)
        if nx == ny == 0:
            nx = ny = int(np.ceil(np.sqrt(nplot)))
        elif nx == 0:
            nx = np.ceil(nplot/ny)
        elif ny == 0:
            ny = np.ceil(nplot/nx)
541 542 543 544 545 546 547 548 549 550 551 552 553
        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))