Refactor code

graphs/nc-fd-convergence.py

@@ -1,6 +1,6 @@
 import numpy as np
 import matplotlib.pyplot as plt
-from notebooks.lib import read_load
+from lib.lib import read_load
 
 alpha = read_load("../data/alpha")
 meaned_by_N = alpha.groupby('N').agg({'fd': ['mean', 'std']}) \

graphs/rmax-n.py

@@ -1,7 +1,7 @@
 import matplotlib.pyplot as plt
 
-from notebooks.graphs import cr_n
+from lib.graphs import cr_n
-from notebooks.lib import read_load
+from lib.lib import read_load
 
 alpha = read_load("../data/alpha")
 

graphs/sp-fd-3d.py

@@ -1,6 +1,6 @@
 from matplotlib import pyplot as plt
 
-from notebooks.lib import read_sp, read_xyz_alt, aggregate_sp_fd
+from lib.lib import read_sp, read_xyz_alt, aggregate_sp_fd
 
 data_3d_sp = read_sp("../data/rust-3d-offaxis-sp", read_xyz_alt)
 sp_fd_data = aggregate_sp_fd(data_3d_sp)

graphs/sp-fd-rust-vs-c.py

@@ -1,7 +1,6 @@
-import numpy as np
 from matplotlib import pyplot as plt
 
-from notebooks.lib import read_sp, aggregate_sp_fd
+from lib.lib import read_sp, aggregate_sp_fd
 
 c_sp = read_sp("../data/stick-probability")
 rust_sp = read_sp("../data/rust-sticking-probability")

graphs/sp-fd.py

@@ -1,6 +1,6 @@
 from matplotlib import pyplot as plt
 
-from notebooks.lib import read_sp, aggregate_sp_fd
+from lib.lib import read_sp, aggregate_sp_fd
 
 data_2d_sp = read_sp("../data/stick-probability")
 sp_fd_data = aggregate_sp_fd(data_2d_sp)

lib/graphs.py

@@ -2,7 +2,7 @@ import numpy as np
 import scipy
 from matplotlib import pyplot as plt
 
-from notebooks.lib import linear
+from lib.lib import linear
 
 
 def cr_n(df, ignore_prefix=0, data_color="tab:blue", fit_color="tab:red"):

notebooks/3d.ipynb

@@ -13,7 +13,7 @@
     "import matplotlib.pyplot as plt\n",
     "import scipy\n",
     "from glob import glob\n",
-    "from notebooks.lib import read_xyz_alt, read_load, linear, mean_across"
+    "from lib.lib import read_xyz_alt, read_load, linear, mean_across"
    ]
   },
   {