updated picture

clean_python/ditact_pic.py

@@ -6,7 +6,7 @@ import numpy as np
 import matplotlib.pyplot as plt
 
 
-plt.style.use("two_column")
+plt.style.use(["style", "colors","two_column"])
 
 
 def simulate():
@@ -14,19 +14,19 @@ def simulate():
     lat = VO2_New(LEN, LEN)
     plot = Plotter(lat)
     si = SpinImage(lat.get_phases())
-    mask_misk = np.ones((LEN, 2*LEN))
+    mask_misk = np.ones((2*LEN, 2*LEN))
     ind = np.arange(mask_misk.size)
     np.random.shuffle(ind)
     mask_misk[np.unravel_index(
         ind[:int(mask_misk.size/2)], mask_misk.shape)] = 0
     print(mask_misk.shape)
 
-    si.apply_mask(lat.parse_mask(np.zeros((LEN, 2*LEN))))
+    si.apply_mask(lat.parse_mask(np.ones((2*LEN, 2*LEN))))
     si.gaussian(20)
     intens_mono = si.fft()
     intens_mono.clean()
 
-    si.apply_mask(lat.parse_mask(np.ones((LEN, 2*LEN))))
+    si.apply_mask(lat.parse_mask(np.zeros((2*LEN, 2*LEN))))
     si.gaussian(20)
     intens_rutile = si.fft()
     intens_rutile.clean()
@@ -43,18 +43,25 @@ def simulate():
 
 
 def plot(fft, ax):
-    ax.imshow(
+    return ax.imshow(
         fft.intens,
         extent=fft.extents(),
-        norm=matplotlib.colors.LogNorm(),
+        norm=matplotlib.colors.LogNorm(vmin=1e-10, vmax=1),
+        #norm=matplotlib.colors.Normalize(vmax=1, vmin=1e-10),
         cmap="magma",
         origin="lower"
     )
 
+def norm(*intenss):
+    max = 1e-10
+    for intens in intenss:
+        m = np.max(intens.intens)
+        max = np.maximum(max,m)
+    return max
 
 def plot_all(intens_rutile, intens_mono, intens_mixed):
-    fig, axs = plt.subplots(4, 2)
+    fig, axs = plt.subplots(3, 2)
-    fig.set_figheight(6)
+    fig.set_figheight(5.2)
     for ax in axs.flatten():
         ax.axis("off")
     axs = axs[:, 1]
@@ -83,33 +90,20 @@ def plot_all(intens_rutile, intens_mono, intens_mixed):
     ax.add_patch(c)
 
     ax = axs[2]
-    plot(intens_mixed, ax)
+    cmap = plot(intens_mixed, ax)
-    # c = matplotlib.patches.Ellipse((0., 0.), width=0.2, height=1.4, angle=45,
-    #                               label='patch', fill=False, ec="w", ls=":")
-    # height = 1.4
-    # width = 0.0
-    # c = matplotlib.patches.Rectangle((-width/2, -height/2), width=width, height=height,
-    #                                 angle=45, rotation_point="center",
-    #                                 label='patch', fill=False, ec="w", ls=":")
-    # ax.add_patch(c)
-    ax.plot([-1, 1], [1, -1], "w", linestyle=(0, (2, 6)))
-
-    ax = axs[3]
-    plot(intens_mixed, ax)
-    ax.plot([-1, 1], [0, 0], "w", linestyle=(0, (2, 6)))
-    ax.plot([-1, 1], [2 * y_shift, 2 * y_shift], "w", linestyle=(0, (2, 6)))
-    ax.plot([-1, 1], [-2*y_shift, -2*y_shift], "w", linestyle=(0, (2, 6)))
-
-    ax.plot([-100*l_shift + big_shift*.5, 100*l_shift + big_shift*.5],
-            [y_shift*100, -y_shift*100], "w", linestyle=(0, (2, 6)))
-    ax.plot([-100*l_shift - big_shift*.5, 100*l_shift - big_shift*.5],
-            [y_shift*100, -y_shift*100], "w", linestyle=(0, (2, 6)))
 
+    cut_off = 0.8
     for ax in axs:
         ax.axis("off")
-        ax.set_xlim(-0.5, 0.5)
+        ax.set_xlim(-cut_off, cut_off)
-        ax.set_ylim(-0.5, 0.5)
+        ax.set_ylim(-cut_off, cut_off)
     plt.tight_layout()
+    fig.subplots_adjust(bottom=0.1,right=0.95,left=0.15,wspace=0.)
+    cbar_ax = fig.add_axes([0.55, 0.07, 0.4, 0.015])
+    cbar = fig.colorbar(cmap, cax=cbar_ax, orientation="horizontal", ticks=[1e-10, 1e-5, 1e0])
+    #cbar.ax.set_xticklabels(['Low', 'Medium', 'High'])
+
+
     fig.savefig("erklaerbaer.pdf")
     fig.savefig("erklaerbaer.png")
     # Plotting cuts
@@ -128,9 +122,13 @@ def load():
 
 if __name__ == "__main__":
     np.random.seed(1234)
-    simulate()
+    #simulate()
     # np.savez("intens.npz", r=r, mo=mo, mi=mi)
     r, mo, mi = load()
+    max = norm(r,mo,mi)
+    r.intens = r.intens/max
+    mo.intens = mo.intens/max
+    mi.intens = mi.intens/max
     plot_all(r, mo, mi)
 
     plt.show()

clean_python/lattices.py

@@ -111,7 +111,7 @@ class VO2_Lattice(Lattice):
         # offset_a_m = -offset_a_m
 
         offset_a_r, offset_c_r = self._mono_2_rutile(offset_c_m, offset_a_m)
-        # offset_a_r = -offset_a_r
+        offset_a_r = -offset_a_r
         # offset_c_r = -offset_c_r
 
         x = offset_a_r + self.X * \
@@ -153,21 +153,5 @@ class VO2_Lattice(Lattice):
 
 
 class VO2_New(VO2_Lattice):
-    # def parse_mask(self, mask: np.ndarray) -> np.ndarray:
-    #    maske = np.empty((mask.shape[0]*2, mask.shape[1]*2))
-    #    maske[0::2, 0::2] = mask
-    #    maske[1::2, 0::2] = mask
-    #    maske[0::2, 1::2] = mask
-    #    maske[1::2, 1::2] = mask
-    #    maske[0::4, :] = np.roll(maske[0::4, :], axis=1, shift=1)
-    #    maske[1::4, :] = np.roll(maske[1::4, :], axis=1, shift=1)
-    #    return maske
-    # def parse_mask(self, mask: np.ndarray) -> np.ndarray:
-    #    print(mask.shape)
-    #    maske = np.empty((mask.shape[0]*2, mask.shape[1]))
-    #    maske[0::2, :] = mask
-    #    maske[1::2, :] = mask
-    #    print(maske.shape)
-    #    return maske
     def parse_mask(self, mask: np.ndarray):
         return mask

clean_python/main.py

@@ -24,8 +24,9 @@ logger.addHandler(ch)
 def random(seed):
     np.random.seed(seed)
     LEN = 40
-    lat = VO2_New(LEN, LEN)
+    #lat = VO2_New(LEN, LEN)
-    maske = np.zeros((LEN*2, LEN*2))
+    lat = VO2_Lattice(LEN, LEN)
+    maske = np.zeros((LEN, LEN))
     ind = np.arange(maske.size)
     np.random.shuffle(ind)
     rect = Rect_Evaluator(lat.get_spots())