<jupyter_start><jupyter_text>3d Scatter<jupyter_code>import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
%matplotlib inline
fig = plt.figure(figsize=(12, 12))
ax = fig.add_subplot(111, projection='3d')
sc = ax.scatter(data['xmid'], data['ymid'], data['zmid'],
                c=data['ly'])
plt.colorbar(sc, label='Relative light yield')
plt.show()<jupyter_output>C:\Anaconda3\lib\site-packages\matplotlib\collections.py:590: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison
  if self._edgecolors == str('face'):<jupyter_text>Now we'll plot the map using pax, to verify everything went correctly. Note this picks up the version of the map we just placed in the current directory, rather than the versionin pax/data!<jupyter_code>mypax = core.Processor(config_names='XENON100', config_dict=dict(pax=dict(output='Dummy.DummyOutput')))
s1map = mypax.simulator.s1_light_yield_map
from tqdm import tqdm
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
%matplotlib inline
#%matplotlib qt
fig = plt.figure(figsize=(12, 12))
ax = fig.add_subplot(111, projection='3d')
points = []
values = []
for i in tqdm(range(len(data['xmid']))):
    points.append((data[i]['xmid'], data[i]['ymid'], data[i]['zmid']))
    values.append(s1map.get_value(*points[-1]))
points = np.array(points)
values = np.array(values)
                          
sc = ax.scatter(*points.T, c=values)
plt.colorbar(sc, label='Relative light yield')
plt.show()<jupyter_output>C:\Anaconda3\lib\site-packages\matplotlib\collections.py:590: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison
  if self._edgecolors == str('face'):<jupyter_text>Z-slices<jupyter_code># Z-slices of map (compare with gallery 5 in Cecilia's note)
points = {}
for z in np.unique(data['zmid']):
    plt.figure(figsize=(12, 10))
    for r in np.unique(data['rmid']):    
        this_data = data[(data['rmid'] == r) & (data['zmid'] == z)]
        plt.errorbar(this_data['tmid'], this_data['ly'], yerr=this_data['errly'], 
                     label='r=%s cm' % (r/10))
    plt.xlabel('Theta (degrees)')
    plt.ylabel('Light yield')
    plt.legend()
    plt.title('z = %s cm' % (z/10))
    plt.show()<jupyter_output><empty_output>
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