Renamed grd to gridder

--HG--
rename : cookbook/grd_cut.py => cookbook/grid_cut.py
rename : cookbook/grd_scatter.py => cookbook/grid_scatter.py
rename : doc/api/grd.rst => doc/api/gridder.rst
rename : fatiando/grd.py => fatiando/gridder.py

cookbook/grd_cut.py → cookbook/grid_cut.py

@@ -8,11 +8,11 @@
 log.info(__doc__)
 
 # Generate some synthetic data on a regular grid
-x, y = ft.grd.regular((-10, 10, -10, 10), (100,100))
+x, y = ft.gridder.regular((-10, 10, -10, 10), (100,100))
 # Using a 2D Gaussian
 z = ft.utils.gaussian2d(x, y, 1, 1)
 subarea = [-2, 2, -3, 3]
-subx, suby, subscalar = ft.grd.cut(x, y, [z], subarea)
+subx, suby, subscalar = ft.gridder.cut(x, y, [z], subarea)
 
 ft.vis.figure(figsize=(12, 5))
 ft.vis.subplot(1, 2, 1)

cookbook/grd_scatter.py → cookbook/grid_scatter.py

@@ -8,7 +8,7 @@
 log.info(__doc__)
 
 # Generate random points
-x, y = ft.grd.scatter((-2, 2, -2, 2), n=200)
+x, y = ft.gridder.scatter((-2, 2, -2, 2), n=200)
 # And calculate a 2D Gaussian on these points
 z = ft.utils.gaussian2d(x, y, 1, 1)
 

cookbook/msh_ddd_prismmesh_topo.py

@@ -12,7 +12,7 @@
 bounds = (x1, x2, y1, y2, -200, 0)
 
 log.info("Generating synthetic topography")
-x, y = ft.grd.regular((x1, x2, y1, y2), (50,50))
+x, y = ft.gridder.regular((x1, x2, y1, y2), (50,50))
 height = (100 +
           -50*ft.utils.gaussian2d(x, y, 100, 200, x0=-50, y0=-100, angle=-60) +
           100*ft.utils.gaussian2d(x, y, 50, 100, x0=80, y0=170))

cookbook/msh_ddd_prismrelief_gz.py

@@ -11,19 +11,19 @@
 log.info("Generating synthetic topography")
 area = (-150, 150, -300, 300)
 shape = (30, 15)
-x, y = ft.grd.regular(area, shape)
+x, y = ft.gridder.regular(area, shape)
 height = (-80*ft.utils.gaussian2d(x, y, 100, 200, x0=-50, y0=-100, angle=-60) +
           200*ft.utils.gaussian2d(x, y, 50, 100, x0=80, y0=170))
 
 log.info("Generating the 3D relief")
 nodes = (x, y, -1*height)
-relief = ft.msh.ddd.PrismRelief(0, ft.grd.spacing(area,shape), nodes)
+relief = ft.msh.ddd.PrismRelief(0, ft.gridder.spacing(area,shape), nodes)
 relief.addprop('density', (2670 for i in xrange(relief.size)))
 
 log.info("Calculating gz effect")
 gridarea = (-80, 80, -220, 220)
 gridshape = (100, 100)
-xp, yp, zp = ft.grd.regular(gridarea, gridshape, z=-200)
+xp, yp, zp = ft.gridder.regular(gridarea, gridshape, z=-200)
 gz = ft.pot.prism.gz(xp, yp, zp, relief)
 
 log.info("Plotting")

cookbook/msh_ddd_prismrelief_topo.py

@@ -10,14 +10,14 @@
 log.info("Generating synthetic topography")
 area = (-150, 150, -300, 300)
 shape = (100, 50)
-x, y = ft.grd.regular(area, shape)
+x, y = ft.gridder.regular(area, shape)
 height = (-80*ft.utils.gaussian2d(x, y, 100, 200, x0=-50, y0=-100, angle=-60) +
           100*ft.utils.gaussian2d(x, y, 50, 100, x0=80, y0=170))
 
 log.info("Generating the 3D relief")
 nodes = (x, y, -1*height) # -1 is to convert height to z coordinate
 reference = 0 # z coordinate of the reference surface
-relief = ft.msh.ddd.PrismRelief(reference, ft.grd.spacing(area, shape), nodes)
+relief = ft.msh.ddd.PrismRelief(reference, ft.gridder.spacing(area, shape), nodes)
 relief.addprop('density', (2670 for i in xrange(relief.size)))
 
 log.info("Plotting")

cookbook/potential_euler_classic.py

@@ -13,7 +13,7 @@
 # Generate some data from the model
 shape = (200, 200)
 area = bounds[0:4]
-xp, yp, zp = ft.grd.regular(area, shape, z=-1)
+xp, yp, zp = ft.gridder.regular(area, shape, z=-1)
 # Add a constant baselevel
 baselevel = 10
 # Convert from nanoTesla to Tesla because euler and derivatives require things

cookbook/potential_euler_classic_expanding_window.py

@@ -15,7 +15,7 @@
 # Generate some data from the model
 shape = (100, 100)
 area = bounds[0:4]
-xp, yp, zp = ft.grd.regular(area, shape, z=-1)
+xp, yp, zp = ft.gridder.regular(area, shape, z=-1)
 # Add a constant baselevel
 baselevel = 10
 # Convert from nanoTesla to Tesla because euler and derivatives require things

cookbook/potential_euler_classic_noisy.py

@@ -13,7 +13,7 @@
 # Generate some data from the model
 shape = (100, 100)
 area = bounds[0:4]
-xp, yp, zp = ft.grd.regular(area, shape, z=-1)
+xp, yp, zp = ft.gridder.regular(area, shape, z=-1)
 # Add a constant baselevel
 baselevel = 10
 # Convert from nanoTesla to Tesla because euler and derivatives require things

cookbook/potential_fourier_deriv.py

@@ -14,7 +14,7 @@
 area = (-5000, 5000, -5000, 5000)
 shape = (51, 51)
 z0 = -500
-xp, yp, zp = ft.grd.regular(area, shape, z=z0)
+xp, yp, zp = ft.gridder.regular(area, shape, z=z0)
 gz = ft.utils.contaminate(ft.pot.prism.gz(xp, yp, zp, prisms), 0.001)
 
 log.info("Calculating the x-derivative")

cookbook/potential_grav_polyprism.py

@@ -23,7 +23,7 @@
             depths[i - 1], depths[i], {'density':500}))
 # Calculate the effect
 shape = (100, 100)
-xp, yp, zp = ft.grd.regular(area, shape, z=-1)
+xp, yp, zp = ft.gridder.regular(area, shape, z=-1)
 gz = ft.pot.polyprism.gz(xp, yp, zp, prisms)
 # and plot it
 ft.vis.figure()

cookbook/potential_grav_prism.py

@@ -13,7 +13,7 @@
           ft.msh.ddd.Prism(-1000,1000,-1000,1000,0,2000,{'density':-900}),
           ft.msh.ddd.Prism(2000,4000,3000,4000,0,2000,{'density':1300})]
 shape = (100,100)
-xp, yp, zp = ft.grd.regular((-5000, 5000, -5000, 5000), shape, z=-150)
+xp, yp, zp = ft.gridder.regular((-5000, 5000, -5000, 5000), shape, z=-150)
 log.info("Calculating fileds...")
 fields = [ft.pot.prism.pot(xp, yp, zp, prisms),
           ft.pot.prism.gx(xp, yp, zp, prisms),

cookbook/potential_grav_sphere.py

@@ -11,7 +11,7 @@
 spheres = [ft.msh.ddd.Sphere(0, 0, -2000, 1000, {'density':1000})]
 # Create a set of points at 100m height
 area = (-5000, 5000, -5000, 5000)
-xp, yp, zp = ft.grd.scatter(area, 500, z=-100)
+xp, yp, zp = ft.gridder.scatter(area, 500, z=-100)
 # Calculate the anomaly
 gz = ft.utils.contaminate(ft.pot.sphere.gz(xp, yp, zp, spheres), 0.1)
 # Plot

cookbook/potential_harvester_grav.py

@@ -13,7 +13,7 @@
 shape = (25, 25)
 bounds = [0, 1000, 0, 1000, 0, 1000]
 area = bounds[0:4]
-xp, yp, zp = ft.grd.regular(area, shape, z=-1)
+xp, yp, zp = ft.gridder.regular(area, shape, z=-1)
 noise = 0.1 # 0.1 mGal noise
 gz = ft.utils.contaminate(ft.pot.prism.gz(xp, yp, zp, model), noise)
 # plot the data

cookbook/potential_harvester_grav2.py

@@ -22,7 +22,7 @@
 # and generate synthetic data from it
 shape = (25, 25)
 area = bounds[0:4]
-xp, yp, zp = ft.grd.regular(area, shape, z=-1)
+xp, yp, zp = ft.gridder.regular(area, shape, z=-1)
 noise = 0.1 # 0.1 mGal noise
 gz = ft.utils.contaminate(ft.pot.polyprism.gz(xp, yp, zp, model), noise)
 # Create a mesh

cookbook/potential_harvester_tensor.py

@@ -35,7 +35,7 @@
 shape = (51, 51)
 area = bounds[0:4]
 noise = 2
-x, y, z = ft.grd.regular(area, shape, z=-150)
+x, y, z = ft.gridder.regular(area, shape, z=-150)
 gyy = ft.utils.contaminate(ft.pot.prism.gyy(x, y, z, model), noise)
 gyz = ft.utils.contaminate(ft.pot.prism.gyz(x, y, z, model), noise)
 gzz = ft.utils.contaminate(ft.pot.prism.gzz(x, y, z, model), noise)

cookbook/potential_harvester_tensor2.py

@@ -26,7 +26,7 @@
 # and use it to generate some tensor data
 shape = (25, 25)
 area = bounds[0:4]
-x, y, z = ft.grd.regular(area, shape, z=-650)
+x, y, z = ft.gridder.regular(area, shape, z=-650)
 gxy = ft.utils.contaminate(ft.pot.prism.gxy(x, y, z, model), 1)
 gzz = ft.utils.contaminate(ft.pot.prism.gzz(x, y, z, model), 1)
 # Create a prism mesh

cookbook/potential_imaging_compare.py

@@ -28,7 +28,7 @@
         ft.msh.ddd.PolygonalPrism(polygon, depths[i - 1], depths[i],
             {'density':500}))
 meshshape = (30, 30, 30)
-xp, yp, zp = ft.grd.regular(area, meshshape[1:], z=-10)
+xp, yp, zp = ft.gridder.regular(area, meshshape[1:], z=-10)
 gz = ft.pot.polyprism.gz(xp, yp, zp, prisms)
 
 # Plot the data

cookbook/potential_imaging_geninv.py

@@ -11,7 +11,7 @@
 # Make some synthetic gravity data from a simple prism model
 prisms = [ft.msh.ddd.Prism(-1000,1000,-3000,3000,0,5000,{'density':1000})]
 shape = (25, 25)
-xp, yp, zp = ft.grd.regular((-5000, 5000, -5000, 5000), shape, z=-10)
+xp, yp, zp = ft.gridder.regular((-5000, 5000, -5000, 5000), shape, z=-10)
 gz = ft.pot.prism.gz(xp, yp, zp, prisms)
 
 # Plot the data

cookbook/potential_imaging_geninv2.py

@@ -13,7 +13,7 @@
           ft.msh.ddd.Prism(-1000,1000,-1000,1000,1000,6000,{'density':-800}),
           ft.msh.ddd.Prism(2000,4000,3000,4000,0,4000,{'density':600})]
 shape = (25, 25)
-xp, yp, zp = ft.grd.regular((-5000, 5000, -5000, 5000), shape, z=-10)
+xp, yp, zp = ft.gridder.regular((-5000, 5000, -5000, 5000), shape, z=-10)
 gz = ft.utils.contaminate(ft.pot.prism.gz(xp, yp, zp, prisms), 0.1)
 
 # Plot the data

cookbook/potential_imaging_migration.py

@@ -11,7 +11,7 @@
 # Make some synthetic gravity data from a simple prism model
 prisms = [ft.msh.ddd.Prism(-1000,1000,-2000,2000,2000,4000,{'density':500})]
 shape = (50, 50)
-xp, yp, zp = ft.grd.regular((-10000, 10000, -10000, 10000), shape, z=-10)
+xp, yp, zp = ft.gridder.regular((-10000, 10000, -10000, 10000), shape, z=-10)
 gz = ft.pot.prism.gz(xp, yp, zp, prisms)
 
 # Plot the data

cookbook/potential_imaging_migration2.py

@@ -14,7 +14,7 @@
           ft.msh.ddd.Prism(2000,4000,3000,4000,0,2000,{'density':600})]
 # Calculate on a scatter of points to show that migration doesn't need gridded
 # data
-xp, yp, zp = ft.grd.scatter((-6000, 6000, -6000, 6000), 1000, z=-10)
+xp, yp, zp = ft.gridder.scatter((-6000, 6000, -6000, 6000), 1000, z=-10)
 gz = ft.utils.contaminate(ft.pot.prism.gz(xp, yp, zp, prisms), 0.1)
 
 # Plot the data

cookbook/potential_imaging_sandwich.py

@@ -11,7 +11,7 @@
 # Make some synthetic gravity data from a simple prism model
 prisms = [ft.msh.ddd.Prism(-1000,1000,-2000,2000,2000,4000,{'density':500})]
 shape = (25, 25)
-xp, yp, zp = ft.grd.regular((-5000, 5000, -5000, 5000), shape, z=-10)
+xp, yp, zp = ft.gridder.regular((-5000, 5000, -5000, 5000), shape, z=-10)
 gz = ft.pot.prism.gz(xp, yp, zp, prisms)
 
 # Plot the data

cookbook/potential_imaging_sandwich2.py

@@ -13,7 +13,7 @@
           ft.msh.ddd.Prism(-1000,1000,-1000,1000,1000,7000,{'density':-300}),
           ft.msh.ddd.Prism(2000,4000,3000,4000,0,2000,{'density':600})]
 shape = (25, 25)
-xp, yp, zp = ft.grd.regular((-10000, 10000, -10000, 10000), shape, z=-10)
+xp, yp, zp = ft.gridder.regular((-10000, 10000, -10000, 10000), shape, z=-10)
 gz = ft.pot.prism.gz(xp, yp, zp, prisms)
 
 # Plot the data

cookbook/potential_mag_polyprism.py

@@ -19,7 +19,7 @@
         0, 2000, {'magnetization':2})]
 # Calculate the effect
 shape = (100, 100)
-xp, yp, zp = ft.grd.regular(area, shape, z=-500)
+xp, yp, zp = ft.gridder.regular(area, shape, z=-500)
 tf = ft.pot.polyprism.tf(xp, yp, zp, prisms, 30, -15)
 # and plot it
 ft.vis.figure()

cookbook/potential_mag_prism.py

@@ -21,7 +21,7 @@
 # Create a regular grid at 100m height
 shape = (200, 200)
 area = bounds[:4]
-xp, yp, zp = ft.grd.regular(area, shape, z=-500)
+xp, yp, zp = ft.gridder.regular(area, shape, z=-500)
 # Calculate the anomaly for a given regional field
 tf = ft.pot.prism.tf(xp, yp, zp, prisms, 30, -15)
 # Plot

cookbook/potential_mag_sphere.py

@@ -14,7 +14,7 @@
 # Create a regular grid at 100m height
 shape = (100, 100)
 area = (-5000, 5000, -5000, 5000)
-xp, yp, zp = ft.grd.regular(area, shape, z=-100)
+xp, yp, zp = ft.gridder.regular(area, shape, z=-100)
 # Calculate the anomaly for a given regional field
 tf = ft.pot.sphere.tf(xp, yp, zp, spheres, 30, 0)
 # Plot

cookbook/potential_prism_irregular_grid.py

@@ -9,7 +9,7 @@
 log.info(__doc__)
 
 prisms = [ft.msh.ddd.Prism(-2000, 2000, -2000, 2000, 0, 2000, {'density':1000})]
-xp, yp, zp = ft.grd.scatter((-5000, 5000, -5000, 5000), n=100, z=-100)
+xp, yp, zp = ft.gridder.scatter((-5000, 5000, -5000, 5000), n=100, z=-100)
 gz = ft.pot.prism.gz(xp, yp, zp, prisms)
 
 shape = (100,100)

cookbook/potential_tensor_centerofmass.py

@@ -12,7 +12,7 @@
 # Generate some synthetic data
 prisms = [ft.msh.ddd.Prism(-1000,1000,-1000,1000,1000,3000,{'density':1000})]
 shape = (100, 100)
-xp, yp, zp = ft.grd.regular((-5000, 5000, -5000, 5000), shape, z=-150)
+xp, yp, zp = ft.gridder.regular((-5000, 5000, -5000, 5000), shape, z=-150)
 noise = 2
 tensor = [ft.utils.contaminate(ft.pot.prism.gxx(xp, yp, zp, prisms), noise),
           ft.utils.contaminate(ft.pot.prism.gxy(xp, yp, zp, prisms), noise),

cookbook/potential_tensor_centerofmass2.py

@@ -14,7 +14,7 @@
           ft.msh.ddd.Prism(-1000,1000,-1000,1000,1000,1500,{'density':1000}),
           ft.msh.ddd.Prism(-500,500,-500,500,1500,2000,{'density':1000})]
 shape = (100, 100)
-xp, yp, zp = ft.grd.regular((-5000, 5000, -5000, 5000), shape, z=-150)
+xp, yp, zp = ft.gridder.regular((-5000, 5000, -5000, 5000), shape, z=-150)
 noise = 1
 tensor = [ft.utils.contaminate(ft.pot.prism.gxx(xp, yp, zp, prisms), noise),
           ft.utils.contaminate(ft.pot.prism.gxy(xp, yp, zp, prisms), noise),

cookbook/potential_tensor_centerofmass3.py

@@ -14,7 +14,7 @@
           ft.msh.ddd.Prism(-1000,1000,-1000,1000,1000,1500,{'density':1000}),
           ft.msh.ddd.Prism(-2000,2000,-2000,2000,1500,2000,{'density':1000})]
 shape = (100, 100)
-xp, yp, zp = ft.grd.regular((-5000, 5000, -5000, 5000), shape, z=-150)
+xp, yp, zp = ft.gridder.regular((-5000, 5000, -5000, 5000), shape, z=-150)
 noise = 1
 tensor = [ft.utils.contaminate(ft.pot.prism.gxx(xp, yp, zp, prisms), noise),
           ft.utils.contaminate(ft.pot.prism.gxy(xp, yp, zp, prisms), noise),

cookbook/potential_tensor_centerofmass4.py

@@ -12,7 +12,7 @@
 # Generate some synthetic data
 prisms = [ft.msh.ddd.Prism(-4000,4000,-500,500,500,1000,{'density':1000})]
 shape = (100, 100)
-xp, yp, zp = ft.grd.regular((-5000, 5000, -5000, 5000), shape, z=-150)
+xp, yp, zp = ft.gridder.regular((-5000, 5000, -5000, 5000), shape, z=-150)
 noise = 2
 tensor = [ft.utils.contaminate(ft.pot.prism.gxx(xp, yp, zp, prisms), noise),
           ft.utils.contaminate(ft.pot.prism.gxy(xp, yp, zp, prisms), noise),

cookbook/potential_tensor_centerofmass5.py

@@ -12,7 +12,7 @@
 # Generate some synthetic data
 prisms = [ft.msh.ddd.Prism(-500,500,-500,500,000,4000,{'density':1000})]
 shape = (100, 100)
-xp, yp, zp = ft.grd.regular((-5000, 5000, -5000, 5000), shape, z=-150)
+xp, yp, zp = ft.gridder.regular((-5000, 5000, -5000, 5000), shape, z=-150)
 noise = 1
 tensor = [ft.utils.contaminate(ft.pot.prism.gxx(xp, yp, zp, prisms), noise),
           ft.utils.contaminate(ft.pot.prism.gxy(xp, yp, zp, prisms), noise),

cookbook/potential_tensor_centerofmass6.py

@@ -12,7 +12,7 @@
 # Generate some synthetic data
 prisms = [ft.msh.ddd.Prism(-1000,1000,-1000,1000,500,700,{'density':1000})]
 shape = (100, 100)
-xp, yp, zp = ft.grd.regular((-5000, 5000, -5000, 5000), shape, z=-150)
+xp, yp, zp = ft.gridder.regular((-5000, 5000, -5000, 5000), shape, z=-150)
 noise = 1
 tensor = [ft.utils.contaminate(ft.pot.prism.gxx(xp, yp, zp, prisms), noise),
           ft.utils.contaminate(ft.pot.prism.gxy(xp, yp, zp, prisms), noise),

cookbook/potential_tensor_centerofmass7.py

@@ -12,7 +12,7 @@
 # Generate some synthetic data
 prisms = [ft.msh.ddd.Prism(-3000,3000,-3000,3000,500,1000,{'density':1000})]
 shape = (100, 100)
-xp, yp, zp = ft.grd.regular((-5000, 5000, -5000, 5000), shape, z=-150)
+xp, yp, zp = ft.gridder.regular((-5000, 5000, -5000, 5000), shape, z=-150)
 noise = 1
 tensor = [ft.utils.contaminate(ft.pot.prism.gxx(xp, yp, zp, prisms), noise),
           ft.utils.contaminate(ft.pot.prism.gxy(xp, yp, zp, prisms), noise),

cookbook/potential_tensor_centerofmass8.py

@@ -13,7 +13,7 @@
 prisms = [ft.msh.ddd.Prism(-2500,-500,-1000,1000,500,2500,{'density':1000}),
           ft.msh.ddd.Prism(500,2500,-1000,1000,500,2500,{'density':1000})]
 shape = (100, 100)
-xp, yp, zp = ft.grd.regular((-5000, 5000, -5000, 5000), shape, z=-150)
+xp, yp, zp = ft.gridder.regular((-5000, 5000, -5000, 5000), shape, z=-150)
 noise = 2
 tensor = [ft.utils.contaminate(ft.pot.prism.gxx(xp, yp, zp, prisms), noise),
           ft.utils.contaminate(ft.pot.prism.gxy(xp, yp, zp, prisms), noise),

cookbook/potential_tensor_invariants.py

@@ -25,7 +25,7 @@
             0, depth, {'density':500}))
 # Calculate the effect
 shape = (100, 100)
-xp, yp, zp = ft.grd.regular(dataarea, shape, z=-500)
+xp, yp, zp = ft.gridder.regular(dataarea, shape, z=-500)
 tensor = [
     ft.pot.polyprism.gxx(xp, yp, zp, prisms),
     ft.pot.polyprism.gxy(xp, yp, zp, prisms),

cookbook/potential_tensor_polyprism.py

@@ -18,7 +18,7 @@
         0, 1000, {'density':500})]
 # Calculate the effect
 shape = (100, 100)
-xp, yp, zp = ft.grd.regular(area, shape, z=-500)
+xp, yp, zp = ft.gridder.regular(area, shape, z=-500)
 tensor = [
     ft.pot.polyprism.gxx(xp, yp, zp, prisms),
     ft.pot.polyprism.gxy(xp, yp, zp, prisms),

cookbook/potential_tensor_prism_noisy.py

@@ -9,7 +9,7 @@
 
 prisms = [ft.msh.ddd.Prism(-1000,1000,-1000,1000,0,2000,{'density':1000})]
 shape = (100,100)
-xp, yp, zp = ft.grd.regular((-5000, 5000, -5000, 5000), shape, z=-200)
+xp, yp, zp = ft.gridder.regular((-5000, 5000, -5000, 5000), shape, z=-200)
 components = [ft.pot.prism.gxx, ft.pot.prism.gxy, ft.pot.prism.gxz,
               ft.pot.prism.gyy, ft.pot.prism.gyz, ft.pot.prism.gzz]
 log.info("Calculate the tensor components and contaminate with 5 Eotvos noise")

cookbook/potential_upcontinue.py

@@ -14,12 +14,12 @@
 area = (-5000, 5000, -5000, 5000)
 shape = (50, 50)
 z0 = -100
-xp, yp, zp = ft.grd.regular(area, shape, z=z0)
+xp, yp, zp = ft.gridder.regular(area, shape, z=z0)
 gz = ft.utils.contaminate(ft.pot.prism.gz(xp, yp, zp, prisms), 0.5)
 
 # Now do the upward continuation using the analytical formula
 height = 2000
-dims = ft.grd.spacing(area, shape)
+dims = ft.gridder.spacing(area, shape)
 gzcont = ft.pot.trans.upcontinue(gz, height, xp, yp, dims)
 
 log.info("Computing true values at new height")

cookbook/seismic_epic2d.py

@@ -46,7 +46,7 @@
 
 log.info("Build a map of the goal function")
 shape = (100, 100)
-xs, ys = ft.grd.regular(area, shape)
+xs, ys = ft.gridder.regular(area, shape)
 goals = ft.seis.epic2d.mapgoal(xs, ys, ttresiduals, recs, vp, vs)
 
 log.info("Plotting")