plot.py 10 KB
Newer Older
Martin Reinecke's avatar
Martin Reinecke committed
1
2
from __future__ import division
import numpy as np
Martin Reinecke's avatar
tweaks    
Martin Reinecke committed
3
from ..import Field, RGSpace, HPSpace, GLSpace, PowerSpace, dobj
Martin Reinecke's avatar
Martin Reinecke committed
4
5
6
7
8
9
10
11
12
13
14
import os

# 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
PEP8    
Martin Reinecke committed
15

Martin Reinecke's avatar
Martin Reinecke committed
16
17
18
def _mollweide_helper(xsize):
    xsize = int(xsize)
    ysize = xsize//2
Martin Reinecke's avatar
Martin Reinecke committed
19
    res = np.full(shape=(ysize, xsize), fill_value=np.nan, dtype=np.float64)
Martin Reinecke's avatar
Martin Reinecke committed
20
21
22
23
24
25
26
27
28
29
30
31
32
33
    xc = (xsize-1)*0.5
    yc = (ysize-1)*0.5
    u, v = np.meshgrid(np.arange(xsize), np.arange(ysize))
    u = 2*(u-xc)/(xc/1.02)
    v = (v-yc)/(yc/1.02)

    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
34

Martin Reinecke's avatar
Martin Reinecke committed
35
36
37
38
39
40
41
42
43
def _find_closest(A, target):
    # A must be sorted
    idx = A.searchsorted(target)
    idx = np.clip(idx, 1, len(A)-1)
    left = A[idx-1]
    right = A[idx]
    idx -= target - left < right - target
    return idx

Martin Reinecke's avatar
PEP8    
Martin Reinecke committed
44

Martin Reinecke's avatar
Martin Reinecke committed
45
def _makeplot(name):
46
    import matplotlib.pyplot as plt
Martin Reinecke's avatar
Martin Reinecke committed
47
    if dobj.rank != 0:
48
        plt.close()
Martin Reinecke's avatar
tweaks    
Martin Reinecke committed
49
        return
Martin Reinecke's avatar
Martin Reinecke committed
50
51
    if name is None:
        plt.show()
52
        plt.close()
Martin Reinecke's avatar
Martin Reinecke committed
53
54
        return
    extension = os.path.splitext(name)[1]
Martin Reinecke's avatar
PEP8    
Martin Reinecke committed
55
    if extension == ".pdf":
Martin Reinecke's avatar
Martin Reinecke committed
56
57
        plt.savefig(name)
        plt.close()
Martin Reinecke's avatar
PEP8    
Martin Reinecke committed
58
    elif extension == ".png":
Martin Reinecke's avatar
Martin Reinecke committed
59
60
        plt.savefig(name)
        plt.close()
Martin Reinecke's avatar
PEP8    
Martin Reinecke committed
61
62
63
64
65
66
67
68
69
70
    # elif extension==".html":
        # import mpld3
        # mpld3.save_html(plt.gcf(),fileobj=name,no_extras=True)
        # import plotly.offline as py
        # import plotly.tools as tls
        # plotly_fig = tls.mpl_to_plotly(plt.gcf())
        # py.plot(plotly_fig,filename=name)
        # py.plot_mpl(plt.gcf(),filename=name)
        # import bokeh
        # bokeh.mpl.to_bokeh(plt.gcf())
Martin Reinecke's avatar
Martin Reinecke committed
71
72
73
    else:
        raise ValueError("file format not understood")

Martin Reinecke's avatar
PEP8    
Martin Reinecke committed
74

Martin Reinecke's avatar
Martin Reinecke committed
75
def _limit_xy(**kwargs):
Martin Reinecke's avatar
Martin Reinecke committed
76
    import matplotlib.pyplot as plt
Martin Reinecke's avatar
PEP8    
Martin Reinecke committed
77
    x1, x2, y1, y2 = plt.axis()
Martin Reinecke's avatar
Martin Reinecke committed
78
79
80
81
    x1 = _get_kw("xmin", x1, **kwargs)
    x2 = _get_kw("xmax", x2, **kwargs)
    y1 = _get_kw("ymin", y1, **kwargs)
    y2 = _get_kw("xmax", y2, **kwargs)
Martin Reinecke's avatar
PEP8    
Martin Reinecke committed
82
83
    plt.axis((x1, x2, y1, y2))

Martin Reinecke's avatar
Martin Reinecke committed
84

Martin Reinecke's avatar
Martin Reinecke committed
85
86
87
88
89
90
91
92
93
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
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
    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
140
141
142

    plt.register_cmap(cmap=LinearSegmentedColormap("Planck-like", planckcmap))
    plt.register_cmap(cmap=LinearSegmentedColormap("High Energy", he_cmap))
Martin Reinecke's avatar
Martin Reinecke committed
143
    plt.register_cmap(cmap=LinearSegmentedColormap("Faraday Map", fd_cmap))
Martin Reinecke's avatar
Martin Reinecke committed
144
145
    plt.register_cmap(cmap=LinearSegmentedColormap("Faraday Uncertainty",
                                                   fdu_cmap))
Martin Reinecke's avatar
Martin Reinecke committed
146
    plt.register_cmap(cmap=LinearSegmentedColormap("Plus Minus", pm_cmap))
Martin Reinecke's avatar
Martin Reinecke committed
147

Martin Reinecke's avatar
Martin Reinecke committed
148

Martin Reinecke's avatar
Martin Reinecke committed
149
def _get_kw(kwname, kwdefault=None, **kwargs):
Martin Reinecke's avatar
Martin Reinecke committed
150
151
152
    if kwargs.get(kwname) is not None:
        return kwargs.get(kwname)
    return kwdefault
Martin Reinecke's avatar
Martin Reinecke committed
153
154


Martin Reinecke's avatar
Martin Reinecke committed
155
def plot(f, **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
173
174
    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
                    (isinstance(dom[0], RGSpace) and len(dom[0].shape)==1)):
                raise ValueError("PowerSpace or 1D RGSpace required")
Martin Reinecke's avatar
Martin Reinecke committed
175

176
    dom = dom[0]
Martin Reinecke's avatar
Martin Reinecke committed
177
    fig = plt.figure()
Martin Reinecke's avatar
PEP8    
Martin Reinecke committed
178
    ax = fig.add_subplot(1, 1, 1)
Martin Reinecke's avatar
Martin Reinecke committed
179

Martin Reinecke's avatar
Martin Reinecke committed
180
181
    xsize = _get_kw("xsize", 6, **kwargs)
    ysize = _get_kw("ysize", 6, **kwargs)
Martin Reinecke's avatar
PEP8    
Martin Reinecke committed
182
    fig.set_size_inches(xsize, ysize)
Martin Reinecke's avatar
Martin Reinecke committed
183
184
185
186
    ax.set_title(_get_kw("title", "", **kwargs))
    ax.set_xlabel(_get_kw("xlabel", "", **kwargs))
    ax.set_ylabel(_get_kw("ylabel", "", **kwargs))
    cmap = _get_kw("colormap", plt.rcParams['image.cmap'], **kwargs)
Martin Reinecke's avatar
Martin Reinecke committed
187
    if isinstance(dom, RGSpace):
Martin Reinecke's avatar
PEP8    
Martin Reinecke committed
188
        if len(dom.shape) == 1:
Martin Reinecke's avatar
Martin Reinecke committed
189
190
            npoints = dom.shape[0]
            dist = dom.distances[0]
Martin Reinecke's avatar
PEP8    
Martin Reinecke committed
191
            xcoord = np.arange(npoints, dtype=np.float64)*dist
192
193
194
            for fld in f:
                ycoord = dobj.to_global_data(fld.val)
                plt.plot(xcoord, ycoord)
Martin Reinecke's avatar
Martin Reinecke committed
195
196
            _limit_xy(**kwargs)
            _makeplot(kwargs.get("name"))
Martin Reinecke's avatar
Martin Reinecke committed
197
            return
Martin Reinecke's avatar
PEP8    
Martin Reinecke committed
198
        elif len(dom.shape) == 2:
199
            f = f[0]
Martin Reinecke's avatar
Martin Reinecke committed
200
201
202
203
            nx = dom.shape[0]
            ny = dom.shape[1]
            dx = dom.distances[0]
            dy = dom.distances[1]
Martin Reinecke's avatar
PEP8    
Martin Reinecke committed
204
205
            xc = np.arange(nx, dtype=np.float64)*dx
            yc = np.arange(ny, dtype=np.float64)*dy
Martin Reinecke's avatar
Martin Reinecke committed
206
207
            im = ax.imshow(dobj.to_global_data(f.val),
                           extent=[xc[0], xc[-1], yc[0], yc[-1]],
Martin Reinecke's avatar
PEP8    
Martin Reinecke committed
208
                           vmin=kwargs.get("zmin"),
Martin Reinecke's avatar
Martin Reinecke committed
209
                           vmax=kwargs.get("zmax"), cmap=cmap, origin="lower")
Martin Reinecke's avatar
PEP8    
Martin Reinecke committed
210
211
212
213
            # 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
214
            plt.colorbar(im)
Martin Reinecke's avatar
Martin Reinecke committed
215
216
            _limit_xy(**kwargs)
            _makeplot(kwargs.get("name"))
Martin Reinecke's avatar
Martin Reinecke committed
217
218
219
220
221
            return
    elif isinstance(dom, PowerSpace):
        plt.xscale('log')
        plt.yscale('log')
        plt.title('power')
222
223
224
225
        xcoord = dom.k_lengths
        for fld in f:
            ycoord = dobj.to_global_data(fld.val)
            plt.plot(xcoord, ycoord)
Martin Reinecke's avatar
Martin Reinecke committed
226
227
        _limit_xy(**kwargs)
        _makeplot(kwargs.get("name"))
Martin Reinecke's avatar
Martin Reinecke committed
228
229
        return
    elif isinstance(dom, HPSpace):
230
        f = f[0]
Martin Reinecke's avatar
Martin Reinecke committed
231
232
233
234
235
236
237
238
        import pyHealpix
        xsize = 800
        res, mask, theta, phi = _mollweide_helper(xsize)

        ptg = np.empty((phi.size, 2), dtype=np.float64)
        ptg[:, 0] = theta
        ptg[:, 1] = phi
        base = pyHealpix.Healpix_Base(int(np.sqrt(f.val.size//12)), "RING")
Martin Reinecke's avatar
Martin Reinecke committed
239
        res[mask] = dobj.to_global_data(f.val)[base.ang2pix(ptg)]
Martin Reinecke's avatar
Martin Reinecke committed
240
        plt.axis('off')
Martin Reinecke's avatar
PEP8    
Martin Reinecke committed
241
        plt.imshow(res, vmin=kwargs.get("zmin"), vmax=kwargs.get("zmax"),
Martin Reinecke's avatar
Martin Reinecke committed
242
                   cmap=cmap, origin="lower")
Martin Reinecke's avatar
Martin Reinecke committed
243
        plt.colorbar(orientation="horizontal")
Martin Reinecke's avatar
Martin Reinecke committed
244
        _makeplot(kwargs.get("name"))
Martin Reinecke's avatar
Martin Reinecke committed
245
246
        return
    elif isinstance(dom, GLSpace):
247
        f = f[0]
Martin Reinecke's avatar
Martin Reinecke committed
248
249
250
251
252
253
254
255
        import pyHealpix
        xsize = 800
        res, mask, theta, phi = _mollweide_helper(xsize)
        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)
Martin Reinecke's avatar
Martin Reinecke committed
256
        res[mask] = dobj.to_global_data(f.val)[ilat*dom.nlon + ilon]
Martin Reinecke's avatar
Martin Reinecke committed
257
258

        plt.axis('off')
Martin Reinecke's avatar
PEP8    
Martin Reinecke committed
259
        plt.imshow(res, vmin=kwargs.get("zmin"), vmax=kwargs.get("zmax"),
Martin Reinecke's avatar
Martin Reinecke committed
260
                   cmap=cmap, origin="lower")
Martin Reinecke's avatar
Martin Reinecke committed
261
        plt.colorbar(orientation="horizontal")
Martin Reinecke's avatar
Martin Reinecke committed
262
        _makeplot(kwargs.get("name"))
Martin Reinecke's avatar
Martin Reinecke committed
263
264
265
        return

    raise ValueError("Field type not(yet) supported")