plotting tweaks

demos/plot_test.py

@@ -4,7 +4,7 @@ import numpy as np
 
 def plot_test():
     rg_space1 = ift.makeDomain(ift.RGSpace((100,)))
-    rg_space2 = ift.makeDomain(ift.RGSpace((80, 80)))
+    rg_space2 = ift.makeDomain(ift.RGSpace((80, 60), distances=1))
     hp_space = ift.makeDomain(ift.HPSpace(64))
     gl_space = ift.makeDomain(ift.GLSpace(128))
 
@@ -13,7 +13,7 @@ def plot_test():
     field_rg1_1 = ift.Field.from_global_data(rg_space1, np.random.randn(100))
     field_rg1_2 = ift.Field.from_global_data(rg_space1, np.random.randn(100))
     field_rg2 = ift.Field.from_global_data(
-        rg_space2, np.random.randn(80 ** 2).reshape((80, 80)))
+        rg_space2, np.random.randn(80*60).reshape((80, 60)))
     field_hp = ift.Field.from_global_data(hp_space, np.random.randn(12*64**2))
     field_gl = ift.Field.from_global_data(gl_space, np.random.randn(32640))
     field_ps = ift.power_analyze(fft.times(field_rg2))

nifty5/plotting/plot.py

@@ -45,11 +45,9 @@ def _mollweide_helper(xsize):
     xsize = int(xsize)
     ysize = xsize//2
     res = np.full(shape=(ysize, xsize), fill_value=np.nan, dtype=np.float64)
-    xc = (xsize-1)*0.5
-    yc = (ysize-1)*0.5
+    xc, yc = (xsize-1)*0.5, (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)
+    u, v = 2*(u-xc)/(xc/1.02), (v-yc)/(yc/1.02)
 
     mask = np.where((u*u*0.25 + v*v) <= 1.)
     t1 = v[mask]
@@ -62,11 +60,8 @@ def _mollweide_helper(xsize):
 
 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
+    idx = np.clip(A.searchsorted(target), 1, len(A)-1)
+    idx -= target - A[idx-1] < A[idx] - target
     return idx
 
 
@@ -80,10 +75,7 @@ def _makeplot(name):
         plt.close()
         return
     extension = os.path.splitext(name)[1]
-    if extension == ".pdf":
-        plt.savefig(name)
-        plt.close()
-    elif extension == ".png":
+    if extension in (".pdf", ".png"):
         plt.savefig(name)
         plt.close()
     else:
@@ -186,22 +178,16 @@ def _plot(f, ax, **kwargs):
                 raise ValueError("PowerSpace or 1D RGSpace required")
 
     label = kwargs.pop("label", None)
-    if label is None:
-        label = [None] * len(f)
     if not isinstance(label, list):
-        label = [label]
+        label = [label] * len(f)
 
-    linewidth = kwargs.pop("linewidth", None)
-    if linewidth is None:
-        linewidth = [1.] * len(f)
+    linewidth = kwargs.pop("linewidth", 1.)
     if not isinstance(linewidth, list):
-        linewidth = [linewidth]
+        linewidth = [linewidth] * len(f)
 
     alpha = kwargs.pop("alpha", None)
-    if alpha is None:
-        alpha = [None] * len(f)
     if not isinstance(alpha, list):
-        alpha = [alpha]
+        alpha = [alpha] * len(f)
 
     foo = kwargs.pop("norm", None)
     norm = {} if foo is None else {'norm': foo}
@@ -225,14 +211,12 @@ def _plot(f, ax, **kwargs):
                 plt.legend()
             return
         elif len(dom.shape) == 2:
-            f = f[0]
             nx, ny = dom.shape
             dx, dy = dom.distances
-            im = ax.imshow(fld.to_global_data().T,
-                           extent=[0, nx*dx, 0, ny*dy],
-                           vmin=kwargs.get("zmin"),
-                           vmax=kwargs.get("zmax"), cmap=cmap, origin="lower",
-                           **norm)
+            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)
             # from mpl_toolkits.axes_grid1 import make_axes_locatable
             # divider = make_axes_locatable(ax)
             # cax = divider.append_axes("right", size="5%", pad=0.05)
@@ -252,34 +236,23 @@ def _plot(f, ax, **kwargs):
         if label != ([None]*len(f)):
             plt.legend()
         return
-    elif isinstance(dom, HPSpace):
-        f = f[0]
+    elif isinstance(dom, (HPSpace, GLSpace)):
         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.size//12)), "RING")
-        res[mask] = f.to_global_data()[base.ang2pix(ptg)]
-        plt.axis('off')
-        plt.imshow(res, vmin=kwargs.get("zmin"), vmax=kwargs.get("zmax"),
-                   cmap=cmap, origin="lower")
-        plt.colorbar(orientation="horizontal")
-        return
-    elif isinstance(dom, GLSpace):
-        f = f[0]
-        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)
-        res[mask] = f.to_global_data()[ilat*dom.nlon + ilon]
-
+        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]
         plt.axis('off')
         plt.imshow(res, vmin=kwargs.get("zmin"), vmax=kwargs.get("zmax"),
                    cmap=cmap, origin="lower")