Added mdtraj and mdtraj+cudf notebooks

.gitignore

 data/
+notebooks/.ipynb_checkpoints

notebooks/TrajectoryAnalysisBenchmark-mdtraj+cudf.ipynb

+%% Cell type:code id:355ef985 tags:
+
+``` python
+import sys
+sys.path
+sys.path.append('/dgx/home/userinternal/fcamerot/.conda/envs/mdtraj37/lib/python3.7/site-packages')
+print(sys.path)
+```
+
+%% Cell type:markdown id:42ef43af tags:
+
+## IMPORTS
+
+%% Cell type:code id:worthy-electric tags:
+
+``` python
+import mdtraj as md
+
+import pandas as pd
+import numpy as np
+import cupy as cu
+np.set_printoptions(suppress=True)
+
+import time
+
+from sklearn.decomposition import PCA
+
+import os
+import cudf
+import cuml
+```
+
+%% Cell type:markdown id:fe49c4d6 tags:
+
+## INITIAL PREPARATIONS
+
+%% Cell type:code id:narrow-retention tags:
+
+``` python
+dataDir = '/dgx/home/userinternal/fcamerot/ligatetrajectorybenchmark/data'
+fileName = dataDir + 'nsp16_nsp10_6wkq'  #~5GB trajectory
+#fileName = dataDir + 'NSP12-7-8_6M71'  #~10GB trajectory
+
+
+topol = fileName + '.pdb'
+trajs = fileName + '.xtc'
+```
+
+%% Cell type:code id:2b526c33 tags:
+
+``` python
+%%time
+Ref = md.load(topol)
+```
+
+%% Cell type:code id:a3a47162 tags:
+
+``` python
+%%time
+Ref.center_coordinates()
+top = Ref.topology
+```
+
+%% Cell type:markdown id:2ed57674 tags:
+
+## RMSD ANALYSIS
+
+%% Cell type:code id:8935173a tags:
+
+``` python
+def rmsd(a, b):
+
+    a = cu.asarray(a, dtype=cu.float64)
+    b = cu.asarray(b, dtype=cu.float64)
+    N = b.shape[0]
+    if a.shape[1:] != b.shape[1:]:
+        raise ValueError('a and b must have same shape')
+
+    return cu.sqrt(cu.sum((a - b) ** 2) / N)
+```
+
+%% Cell type:markdown id:d75ca8e1 tags:
+
+### First load, then compute
+
+%% Cell type:code id:3abf6f02 tags:
+
+``` python
+%%time
+trj = md.load(trajs,top=topol)
+```
+
+%% Cell type:code id:qualified-house tags:
+
+``` python
+%%time
+trj.center_coordinates()
+rmsd(trj.xyz, Ref.xyz)
+```
+
+%% Cell type:markdown id:5147257b tags:
+
+### Iterate and compute
+
+%% Cell type:code id:d5b26b6f tags:
+
+``` python
+%%time
+for chunks in md.iterload(trajs, top=top):
+    chunks.center_coordinates()
+    rmsd(chunks.xyz, Ref.xyz)
+```
+
+%% Cell type:markdown id:78c9f4d4 tags:
+
+## PCA ANALYSIS
+
+%% Cell type:code id:a606f5c0 tags:
+
+``` python
+%%time
+md_pca = cuml.PCA(n_components=20)
+```
+
+%% Cell type:code id:ed7f2f68 tags:
+
+``` python
+%%time
+# Snapshots are already loaded at 500ps intervals
+pca_trj = trj.xyz[:,:,:]
+pca_trj = pca_trj.reshape(pca_trj.shape[0] , -1 )
+df = cudf.DataFrame(pca_trj)
+```
+
+%% Cell type:code id:anticipated-edition tags:
+
+``` python
+%%time
+# fit_transform gives us PCA projections (/PCA space)
+proj = md_pca.fit_transform(df)
+```
+
+%% Cell type:code id:ef498b33 tags:
+
+``` python
+```

notebooks/TrajectoryAnalysisBenchmark-mdtraj.ipynb

+%% Cell type:code id:355ef985 tags:
+
+``` python
+import sys
+sys.path
+sys.path.append('/dgx/home/userinternal/fcamerot/.conda/envs/mdtraj37/lib/python3.7/site-packages')
+print(sys.path)
+```
+
+%% Cell type:markdown id:42ef43af tags:
+
+## IMPORTS
+
+%% Cell type:code id:worthy-electric tags:
+
+``` python
+import mdtraj as md
+
+import pandas as pd
+import numpy as np
+np.set_printoptions(suppress=True)
+
+import time
+
+from sklearn.decomposition import PCA
+
+import os
+```
+
+%% Cell type:markdown id:fe49c4d6 tags:
+
+## INITIAL PREPARATIONS
+
+%% Cell type:code id:narrow-retention tags:
+
+``` python
+dataDir = '/dgx/home/userinternal/fcamerot/ligatetrajectorybenchmark/data'
+fileName = dataDir + 'nsp16_nsp10_6wkq'  #~5GB trajectory
+#fileName = dataDir + 'NSP12-7-8_6M71'  #~10GB trajectory
+
+
+topol = fileName + '.pdb'
+trajs = fileName + '.xtc'
+```
+
+%% Cell type:code id:diagnostic-dimension tags:
+
+``` python
+%%time
+Ref = md.load(topol)
+```
+
+%% Cell type:code id:ba5e890d tags:
+
+``` python
+%%time
+Ref.center_coordinates()
+top = Ref.topology
+```
+
+%% Cell type:markdown id:2ed57674 tags:
+
+## RMSD ANALYSIS
+
+%% Cell type:code id:qualified-house tags:
+
+``` python
+%%time
+for chunks in md.iterload(trajs, top=top):
+    chunks.center_coordinates()
+    md.rmsd(chunks,Ref,parallel=True,precentered=True)
+```
+
+%% Cell type:markdown id:78c9f4d4 tags:
+
+## PCA ANALYSIS
+
+%% Cell type:code id:empty-finland tags:
+
+``` python
+%%time
+trj = md.load(trajs,top=topol)
+```
+
+%% Cell type:code id:24b4e8ef tags:
+
+``` python
+%%time
+md_pca = PCA(n_components=20)
+```
+
+%% Cell type:code id:3fc13176 tags:
+
+``` python
+%%time
+# Snapshots are already loaded at 500ps intervals
+pca_trj = trj.xyz[:,:,:]
+pca_trj = pca_trj.reshape(pca_trj.shape[0] , -1 )
+```
+
+%% Cell type:code id:anticipated-edition tags:
+
+``` python
+%%time
+# fit_transform gives us PCA projections (/PCA space)
+proj = md_pca.fit_transform(pca_trj)
+```
+
+%% Cell type:code id:d5d00107 tags:
+
+``` python
+```

notebooks/TrajectoryAnalysisBenchmark.ipynb

+%% Cell type:code id:355ef985 tags:
+
+``` python
+import sys
+sys.path
+sys.path.append('/dgx/home/userinternal/fcamerot/.conda/envs/mdtraj37/lib/python3.7/site-packages')
+print(sys.path)
+```
+
+%% Cell type:markdown id:42ef43af tags:
+
+## IMPORTS
+
+%% Cell type:code id:worthy-electric tags:
+
+``` python
+import mdtraj as md
+
+import pandas as pd
+import numpy as np
+np.set_printoptions(suppress=True)
+
+import time
+
+from sklearn.decomposition import PCA
+
+import os
+```
+
+%% Cell type:markdown id:fe49c4d6 tags:
+
+## INITIAL PREPARATIONS
+
+%% Cell type:code id:narrow-retention tags:
+
+``` python
+topol = 'nsp16.pdb'
+trajs = 'nsp16_100ns.xtc'
+```
+
+%% Cell type:code id:diagnostic-dimension tags:
+
+``` python
+Ref = md.load(topol)
+Ref.center_coordinates()
+top = Ref.topology
+```
+
+%% Cell type:markdown id:2ed57674 tags:
+
+## RMSD ANALYSIS
+
+%% Cell type:code id:qualified-house tags:
+
+``` python
+for chunks in md.iterload(trajs, top=top):
+    chunks.center_coordinates()
+    md.rmsd(chunks,Ref,parallel=True,precentered=True)
+```
+
+%% Cell type:markdown id:78c9f4d4 tags:
+
+## PCA ANALYSIS
+
+%% Cell type:code id:empty-finland tags:
+
+``` python
+trj = md.load(trajs,top=topol)
+```
+
+%% Cell type:code id:anticipated-edition tags:
+
+``` python
+md_pca = PCA(n_components=20)
+
+# Snapshots are already loaded at 500ps intervals
+pca_trj = trj.xyz[:,:,:]
+pca_trj = pca_trj.reshape(pca_trj.shape[0] , -1 )
+
+# fit_transform gives us PCA projections (/PCA space)
+proj = md_pca.fit_transform(pca_trj)
+```