diff --git a/tests/integration/run_align b/tests/integration/run_align
new file mode 100755
index 0000000..ed665e0
--- /dev/null
+++ b/tests/integration/run_align
@@ -0,0 +1,3 @@
+#!/bin/bash
+
+./multishift align 
diff --git a/tests/integration/run_translate b/tests/integration/run_translate
new file mode 100755
index 0000000..f21eb1d
--- /dev/null
+++ b/tests/integration/run_translate
@@ -0,0 +1,3 @@
+#!/bin/bash
+
+./multishift translate -s settings.json
diff --git a/tests/projects/Al-mush/al.vasp b/tests/projects/Al-mush/al.vasp
deleted file mode 100644
index 0dd6621..0000000
--- a/tests/projects/Al-mush/al.vasp
+++ /dev/null
@@ -1,9 +0,0 @@
-Al1
-1.0
-        2.8559546471         0.0000000000         0.0000000000
-        1.4279773235         2.4733292764         0.0000000000
-        1.4279773235         0.8244430921         2.3318772046
-   Al
-    1
-Direct
-     0.000000000         0.000000000         0.000000000
diff --git a/tests/projects/Al-mush/symplot.py b/tests/projects/Al-mush/symplot.py
deleted file mode 100644
index 372a12c..0000000
--- a/tests/projects/Al-mush/symplot.py
+++ /dev/null
@@ -1,75 +0,0 @@
-import json
-import os
-import numpy as np
-import pandas as pd
-import matplotlib
-import matplotlib.pyplot as plt
-
-font = {'family' : 'normal',
-        'size'   : 16}
-
-matplotlib.rc('font', **font)
-
-def load_record(record_file):
-    with open(record_file) as f:
-        records = json.load(f)
-    return records
-
-def write_json(data,target_file):
-    with open(target_file,'w') as f:
-        json.dump(data,f)
-    return
-
-def tabulize_record(record):
-    df=pd.read_json(json.dumps(record["ids"]), orient="index")
-    return df
-
-def scatter_equivalent_shifts(ax,record,**kwargs):
-    unwinded=tabulize_record(record)
-
-    #Find shifts for any cleave entry (if you just ran "shift" you don't need this step)
-    nocleave=unwinded.loc[unwinded["cleavage"]==unwinded["cleavage"].iloc[0]]
-
-    #Get in plane shift vectors
-    xy=np.array(nocleave["shift"].to_list())
-    ab=np.array(nocleave["grid_point"].to_list())
-    #We'll use their equivalent group value to color the plot
-    c=nocleave["group"].to_numpy()
-
-    #This is all we need, we save it to a single array
-    points=np.hstack((ab,xy,c[:,np.newaxis]))
-
-    #We'll duplicate the "walls" along a and b onto the next periodic image
-    a,b=record["grid"]
-    au,bu=record["shift_units"]
-    avec,bvec=np.array(au)*a,np.array(bu)*b
-
-    #Get the walls and repeat them on the next boundary
-    aarg=points[:,1].argsort()[0:a]
-    awall=points[aarg]
-    awall[:,[2,3]]+=bvec
-    points=np.vstack((points,awall))
-
-    barg=points[:,0].argsort()[0:b+1]
-    bwall=points[barg]
-    bwall[:,[2,3]]+=avec
-    points=np.vstack((points,bwall))
-
-    #Scatter the grid points, coloring symmetrically equivalent ones with the same value
-    ax.scatter(points[:,2],points[:,3],c=points[:,4],**kwargs) 
-
-    ax.set_aspect('equal')
-    ax.set_xticks([])
-    ax.set_yticks([])
-
-def main():
-    record=load_record("./record.json")
-
-    fig=plt.figure()
-    ax=fig.add_subplot(111)
-
-    scatter_equivalent_shifts(ax,record,s=85,cmap=matplotlib.cm.get_cmap("twilight"))
-    plt.show()
-
-if __name__ == "__main__":
-    main()