|
62 | 62 |
|
63 | 63 | pcm = ax[0].pcolor(X, Y, Z,
|
64 | 64 | norm=colors.LogNorm(vmin=Z.min(), vmax=Z.max()),
|
65 |
| - cmap='PuBu_r') |
| 65 | + cmap='PuBu_r', shading='auto') |
66 | 66 | fig.colorbar(pcm, ax=ax[0], extend='max')
|
67 | 67 |
|
68 |
| -pcm = ax[1].pcolor(X, Y, Z, cmap='PuBu_r') |
| 68 | +pcm = ax[1].pcolor(X, Y, Z, cmap='PuBu_r', shading='auto') |
69 | 69 | fig.colorbar(pcm, ax=ax[1], extend='max')
|
70 | 70 | plt.show()
|
71 | 71 |
|
|
99 | 99 | pcm = ax[0].pcolormesh(X, Y, Z,
|
100 | 100 | norm=colors.SymLogNorm(linthresh=0.03, linscale=0.03,
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101 | 101 | vmin=-1.0, vmax=1.0, base=10),
|
102 |
| - cmap='RdBu_r') |
| 102 | + cmap='RdBu_r', shading='auto') |
103 | 103 | fig.colorbar(pcm, ax=ax[0], extend='both')
|
104 | 104 |
|
105 |
| -pcm = ax[1].pcolormesh(X, Y, Z, cmap='RdBu_r', vmin=-np.max(Z)) |
| 105 | +pcm = ax[1].pcolormesh(X, Y, Z, cmap='RdBu_r', vmin=-np.max(Z), shading='auto') |
106 | 106 | fig.colorbar(pcm, ax=ax[1], extend='both')
|
107 | 107 | plt.show()
|
108 | 108 |
|
|
131 | 131 | fig, ax = plt.subplots(2, 1)
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132 | 132 |
|
133 | 133 | pcm = ax[0].pcolormesh(X, Y, Z1, norm=colors.PowerNorm(gamma=0.5),
|
134 |
| - cmap='PuBu_r') |
| 134 | + cmap='PuBu_r', shading='auto') |
135 | 135 | fig.colorbar(pcm, ax=ax[0], extend='max')
|
136 | 136 |
|
137 |
| -pcm = ax[1].pcolormesh(X, Y, Z1, cmap='PuBu_r') |
| 137 | +pcm = ax[1].pcolormesh(X, Y, Z1, cmap='PuBu_r', shading='auto') |
138 | 138 | fig.colorbar(pcm, ax=ax[1], extend='max')
|
139 | 139 | plt.show()
|
140 | 140 |
|
|
171 | 171 | # even bounds gives a contour-like effect
|
172 | 172 | bounds = np.linspace(-1, 1, 10)
|
173 | 173 | norm = colors.BoundaryNorm(boundaries=bounds, ncolors=256)
|
174 |
| -pcm = ax[0].pcolormesh(X, Y, Z, |
175 |
| - norm=norm, |
176 |
| - cmap='RdBu_r') |
| 174 | +pcm = ax[0].pcolormesh(X, Y, Z, norm=norm, cmap='RdBu_r', shading='auto') |
177 | 175 | fig.colorbar(pcm, ax=ax[0], extend='both', orientation='vertical')
|
178 | 176 |
|
179 | 177 | # uneven bounds changes the colormapping:
|
180 | 178 | bounds = np.array([-0.25, -0.125, 0, 0.5, 1])
|
181 | 179 | norm = colors.BoundaryNorm(boundaries=bounds, ncolors=256)
|
182 |
| -pcm = ax[1].pcolormesh(X, Y, Z, norm=norm, cmap='RdBu_r') |
| 180 | +pcm = ax[1].pcolormesh(X, Y, Z, norm=norm, cmap='RdBu_r', shading='auto') |
183 | 181 | fig.colorbar(pcm, ax=ax[1], extend='both', orientation='vertical')
|
184 | 182 |
|
185 |
| -pcm = ax[2].pcolormesh(X, Y, Z, cmap='RdBu_r', vmin=-np.max(Z)) |
| 183 | +pcm = ax[2].pcolormesh(X, Y, Z, cmap='RdBu_r', vmin=-np.max(Z), shading='auto') |
186 | 184 | fig.colorbar(pcm, ax=ax[2], extend='both', orientation='vertical')
|
187 | 185 | plt.show()
|
188 | 186 |
|
|
217 | 215 | # dynamic range:
|
218 | 216 | divnorm = colors.TwoSlopeNorm(vmin=-500., vcenter=0, vmax=4000)
|
219 | 217 |
|
220 |
| -pcm = ax.pcolormesh( |
221 |
| - longitude, latitude, topo, rasterized=True, norm=divnorm, cmap=terrain_map) |
| 218 | +pcm = ax.pcolormesh(longitude, latitude, topo, rasterized=True, norm=divnorm, |
| 219 | + cmap=terrain_map, shading='auto') |
222 | 220 | # Simple geographic plot, set aspect ratio beecause distance between lines of
|
223 | 221 | # longitude depends on latitude.
|
224 | 222 | ax.set_aspect(1 / np.cos(np.deg2rad(49)))
|
@@ -248,8 +246,8 @@ def __call__(self, value, clip=None):
|
248 | 246 | fig, ax = plt.subplots()
|
249 | 247 | midnorm = MidpointNormalize(vmin=-500., vcenter=0, vmax=4000)
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250 | 248 |
|
251 |
| -pcm = ax.pcolormesh( |
252 |
| - longitude, latitude, topo, rasterized=True, norm=midnorm, cmap=terrain_map) |
| 249 | +pcm = ax.pcolormesh(longitude, latitude, topo, rasterized=True, norm=midnorm, |
| 250 | + cmap=terrain_map, shading='auto') |
253 | 251 | ax.set_aspect(1 / np.cos(np.deg2rad(49)))
|
254 | 252 | fig.colorbar(pcm, shrink=0.6, extend='both')
|
255 | 253 | plt.show()
|
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