plot.py 19.7 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
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(
Martin Reinecke's avatar
cleanup  
Martin Reinecke committed
113
            [[3.2404542, -1.5371385, -0.4985314],
114
             [-0.9692660,  1.8760108,  0.0415560],
Martin Reinecke's avatar
cleanup  
Martin Reinecke committed
115
             [0.0556434, -0.2040259,  1.0572252]])
116 117 118 119 120 121

    def _gammacorr(inp):
        mask = np.zeros(inp.shape, dtype=np.float64)
        mask[inp <= 0.0031308] = 1.
        r1 = 12.92*inp
        a = 0.055
Martin Reinecke's avatar
cleanup  
Martin Reinecke committed
122
        r2 = (1 + a) * (np.maximum(inp, 0.0031308) ** (1/2.4)) - a
123 124 125
        return r1*mask + r2*(1.-mask)

    def lambda2xyz(lam):
Martin Reinecke's avatar
cleanup  
Martin Reinecke committed
126 127 128
        lammin = 380.
        lammax = 780.
        lam = np.asarray(lam, dtype=np.float64)
129 130 131 132 133 134
        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
Martin Reinecke's avatar
cleanup  
Martin Reinecke committed
135
        c = w1*_xyz[:, ii] + w2*_xyz[:, ii+1]
136 137 138 139 140 141 142
        return c

    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):
Martin Reinecke's avatar
cleanup  
Martin Reinecke committed
143
            res[:, i] = lambda2xyz(1./E[i])
144 145
        return res

Martin Reinecke's avatar
tweaks  
Martin Reinecke committed
146 147 148 149 150 151 152 153
    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

Philipp Arras's avatar
Philipp Arras committed
154
    shp = spectral_cube.shape[:-1]+(3,)
Martin Reinecke's avatar
tweaks  
Martin Reinecke committed
155
    spectral_cube = spectral_cube.reshape((-1, spectral_cube.shape[-1]))
156 157
    xyz = getxyz(spectral_cube.shape[-1])
    xyz_data = np.tensordot(spectral_cube, xyz, axes=[-1, -1])
Martin Reinecke's avatar
Martin Reinecke committed
158 159
    xyz_data /= xyz_data.max()
    xyz_data = to_logscale(xyz_data, max(1e-3, xyz_data.min()), 1.)
160
    rgb_data = xyz_data.copy()
Martin Reinecke's avatar
tweaks  
Martin Reinecke committed
161 162
    for x in range(xyz_data.shape[0]):
        rgb_data[x] = _gammacorr(np.matmul(MATRIX_SRGB_D65, xyz_data[x]))
Martin Reinecke's avatar
Martin Reinecke committed
163
    rgb_data = rgb_data.clip(0., 1.)
Philipp Arras's avatar
Philipp Arras committed
164
    return rgb_data.reshape(shp)
165 166


Martin Reinecke's avatar
Martin Reinecke committed
167 168
def _find_closest(A, target):
    # A must be sorted
Martin Reinecke's avatar
Martin Reinecke committed
169 170
    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
171 172
    return idx

Martin Reinecke's avatar
PEP8  
Martin Reinecke committed
173

Martin Reinecke's avatar
Martin Reinecke committed
174
def _makeplot(name):
175
    import matplotlib.pyplot as plt
Martin Reinecke's avatar
Martin Reinecke committed
176
    if dobj.rank != 0:
177
        plt.close()
Martin Reinecke's avatar
tweaks  
Martin Reinecke committed
178
        return
Martin Reinecke's avatar
Martin Reinecke committed
179 180
    if name is None:
        plt.show()
181
        plt.close()
Martin Reinecke's avatar
Martin Reinecke committed
182 183
        return
    extension = os.path.splitext(name)[1]
184
    if extension in (".pdf", ".png", ".svg"):
Martin Reinecke's avatar
Martin Reinecke committed
185 186 187 188 189
        plt.savefig(name)
        plt.close()
    else:
        raise ValueError("file format not understood")

Martin Reinecke's avatar
PEP8  
Martin Reinecke committed
190

Martin Reinecke's avatar
Martin Reinecke committed
191
def _limit_xy(**kwargs):
Martin Reinecke's avatar
Martin Reinecke committed
192
    import matplotlib.pyplot as plt
Martin Reinecke's avatar
PEP8  
Martin Reinecke committed
193
    x1, x2, y1, y2 = plt.axis()
clienhar's avatar
clienhar committed
194 195 196 197
    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
198 199
    plt.axis((x1, x2, y1, y2))

Martin Reinecke's avatar
Martin Reinecke committed
200

Martin Reinecke's avatar
Martin Reinecke committed
201 202 203 204 205 206 207 208 209
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
210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255
    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
256 257 258

    plt.register_cmap(cmap=LinearSegmentedColormap("Planck-like", planckcmap))
    plt.register_cmap(cmap=LinearSegmentedColormap("High Energy", he_cmap))
Martin Reinecke's avatar
Martin Reinecke committed
259
    plt.register_cmap(cmap=LinearSegmentedColormap("Faraday Map", fd_cmap))
Martin Reinecke's avatar
Martin Reinecke committed
260 261
    plt.register_cmap(cmap=LinearSegmentedColormap("Faraday Uncertainty",
                                                   fdu_cmap))
Martin Reinecke's avatar
Martin Reinecke committed
262
    plt.register_cmap(cmap=LinearSegmentedColormap("Plus Minus", pm_cmap))
Martin Reinecke's avatar
Martin Reinecke committed
263

Martin Reinecke's avatar
Martin Reinecke committed
264

265
def _plot1D(f, ax, **kwargs):
266
    import matplotlib.pyplot as plt
267

268 269 270 271 272
    for i, fld in enumerate(f):
        if not isinstance(fld, Field):
            raise TypeError("incorrect data type")
        if i == 0:
            dom = fld.domain
273 274
            if (len(dom) != 1):
                raise ValueError("input field must have exactly one domain")
275 276 277
        else:
            if fld.domain != dom:
                raise ValueError("domain mismatch")
278
    dom = dom[0]
Martin Reinecke's avatar
Martin Reinecke committed
279

clienhar's avatar
clienhar committed
280
    label = kwargs.pop("label", None)
281
    if not isinstance(label, list):
Martin Reinecke's avatar
Martin Reinecke committed
282
        label = [label] * len(f)
Martin Reinecke's avatar
Martin Reinecke committed
283

Martin Reinecke's avatar
Martin Reinecke committed
284
    linewidth = kwargs.pop("linewidth", 1.)
Philipp Arras's avatar
Philipp Arras committed
285
    if not isinstance(linewidth, list):
Martin Reinecke's avatar
Martin Reinecke committed
286
        linewidth = [linewidth] * len(f)
Philipp Arras's avatar
Philipp Arras committed
287

clienhar's avatar
clienhar committed
288
    alpha = kwargs.pop("alpha", None)
Philipp Arras's avatar
Philipp Arras committed
289
    if not isinstance(alpha, list):
Martin Reinecke's avatar
Martin Reinecke committed
290
        alpha = [alpha] * len(f)
Philipp Arras's avatar
Philipp Arras committed
291

clienhar's avatar
clienhar committed
292 293 294
    ax.set_title(kwargs.pop("title", ""))
    ax.set_xlabel(kwargs.pop("xlabel", ""))
    ax.set_ylabel(kwargs.pop("ylabel", ""))
295

Martin Reinecke's avatar
Martin Reinecke committed
296
    if isinstance(dom, RGSpace):
297
        plt.yscale(kwargs.pop("yscale", "linear"))
298 299 300 301 302 303 304 305 306 307 308
        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
309
    elif isinstance(dom, LogRGSpace):
Martin Reinecke's avatar
fixes  
Martin Reinecke committed
310
        plt.yscale(kwargs.pop("yscale", "log"))
311 312 313 314 315 316 317 318 319 320
        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
321
    elif isinstance(dom, PowerSpace):
322 323
        plt.xscale(kwargs.pop("xscale", "log"))
        plt.yscale(kwargs.pop("yscale", "log"))
Philipp Arras's avatar
Philipp Arras committed
324
        xcoord = dom.k_lengths
Martin Reinecke's avatar
Martin Reinecke committed
325
        for i, fld in enumerate(f):
326 327
            ycoord = fld.to_global_data_rw()
            ycoord[0] = ycoord[1]
Martin Reinecke's avatar
Martin Reinecke committed
328 329
            plt.plot(xcoord, ycoord, label=label[i],
                     linewidth=linewidth[i], alpha=alpha[i])
Martin Reinecke's avatar
Martin Reinecke committed
330
        _limit_xy(**kwargs)
331 332
        if label != ([None]*len(f)):
            plt.legend()
Martin Reinecke's avatar
Martin Reinecke committed
333
        return
334 335 336 337 338 339 340 341
    raise ValueError("Field type not(yet) supported")


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

    dom = f.domain

342 343 344 345 346 347 348 349 350 351
    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
352 353 354

    foo = kwargs.pop("norm", None)
    norm = {} if foo is None else {'norm': foo}
Philipp Arras's avatar
Philipp Arras committed
355 356

    foo = kwargs.pop("aspect", None)
357
    aspect = {} if foo is None else {'aspect': foo}
358 359 360 361 362

    ax.set_title(kwargs.pop("title", ""))
    ax.set_xlabel(kwargs.pop("xlabel", ""))
    ax.set_ylabel(kwargs.pop("ylabel", ""))
    dom = dom[0]
363 364
    if not have_rgb:
        cmap = kwargs.pop("colormap", plt.rcParams['image.cmap'])
365 366 367 368

    if isinstance(dom, RGSpace):
        nx, ny = dom.shape
        dx, dy = dom.distances
369 370 371 372 373 374 375 376 377 378
        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)
379 380
        _limit_xy(**kwargs)
        return
Martin Reinecke's avatar
Martin Reinecke committed
381
    elif isinstance(dom, (HPSpace, GLSpace)):
Martin Reinecke's avatar
Martin Reinecke committed
382 383 384
        import pyHealpix
        xsize = 800
        res, mask, theta, phi = _mollweide_helper(xsize)
385
        if have_rgb:
Martin Reinecke's avatar
cleanup  
Martin Reinecke committed
386 387
            res = np.full(shape=res.shape+(3,), fill_value=1.,
                          dtype=np.float64)
388

Martin Reinecke's avatar
Martin Reinecke committed
389 390 391 392
        if isinstance(dom, HPSpace):
            ptg = np.empty((phi.size, 2), dtype=np.float64)
            ptg[:, 0] = theta
            ptg[:, 1] = phi
393
            base = pyHealpix.Healpix_Base(int(np.sqrt(dom.size//12)), "RING")
394 395 396 397
            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
398 399 400 401 402 403
        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)
404 405 406 407
            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
408
        plt.axis('off')
409 410 411 412 413 414
        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")
415 416 417 418 419 420 421 422 423 424 425 426
        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):
Martin Reinecke's avatar
Martin Reinecke committed
427
        raise TypeError("incorrect data type")
428
    dom1 = f[0].domain
Martin Reinecke's avatar
Martin Reinecke committed
429 430
    if (len(dom1) == 1 and
        (isinstance(dom1[0], PowerSpace) or
431 432
            (isinstance(dom1[0], (RGSpace, LogRGSpace)) and
             len(dom1[0].shape) == 1))):
433 434 435 436 437 438
        _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
439 440
        return
    raise ValueError("Field type not(yet) supported")
Martin Reinecke's avatar
Martin Reinecke committed
441

Martin Reinecke's avatar
tweaks  
Martin Reinecke committed
442

443 444 445 446 447 448 449 450 451 452
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
453 454
        After doing one or more calls `add()`, one needs to call `output()` to
        show or save the plot.
455 456 457

        Parameters
        ----------
Philipp Arras's avatar
Philipp Arras committed
458
        f: Field or list of Field
Philipp Arras's avatar
Philipp Arras committed
459
            If `f` is a single Field, it must be defined on a single `RGSpace`,
Martin Reinecke's avatar
typo  
Martin Reinecke committed
460
            `PowerSpace`, `HPSpace`, `GLSpace`.
Philipp Arras's avatar
Philipp Arras committed
461
            If it is a list, all list members must be Fields defined over the
462 463
            same one-dimensional `RGSpace` or `PowerSpace`.
        title: string
Philipp Arras's avatar
Docs  
Philipp Arras committed
464
            Title of the plot.
465
        xlabel: string
Philipp Arras's avatar
Philipp Arras committed
466
            Label for the x axis.
467
        ylabel: string
Philipp Arras's avatar
Philipp Arras committed
468
            Label for the y axis.
469
        [xyz]min, [xyz]max: float
Philipp Arras's avatar
Philipp Arras committed
470
            Limits for the values to plot.
471
        colormap: string
Philipp Arras's avatar
Philipp Arras committed
472
            Color map to use for the plot (if it is a 2D plot).
473
        linewidth: float or list of floats
Philipp Arras's avatar
Philipp Arras committed
474
            Line width.
475
        label: string of list of strings
Philipp Arras's avatar
Philipp Arras committed
476
            Annotation string.
477
        alpha: float or list of floats
Philipp Arras's avatar
Docs  
Philipp Arras committed
478
            Transparency value.
479 480 481 482 483 484 485 486 487 488
        """
        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
489 490 491 492 493 494 495 496
            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,
497
            otherwise it will be written to a file with the given name.
Philipp Arras's avatar
Philipp Arras committed
498
            Supported extensions: .png and .pdf. Default: None.
499 500 501 502 503 504
        """
        import matplotlib.pyplot as plt
        nplot = len(self._plots)
        fig = plt.figure()
        if "title" in kwargs:
            plt.suptitle(kwargs.pop("title"))
505 506 507 508 509 510 511 512
        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)
513 514 515 516 517 518 519 520 521 522 523 524 525
        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))