#!/usr/bin/env python-i
# example of using summatrix from within python
# load summon matrix library
from summon import matrix
# read in matrix (stored in Index Format 'imat')
mat = matrix.Matrix()
matrix.open_matrix("human_mouse.imat", mat, format="imat")
# create and show matrix viewer
viewer = matrix.MatrixViewer(mat, title="human vs mouse")
viewer.show()
if row not in mat: mat[row] = {}
mat[row][col] = val
if symmetrize:
if col not in mat: mat[col] = {}
mat[col][row] = val
ff.close()
return nnodes, nedges
infile, mtype, size, view = parse_arguments(sys.argv[1:])
from summon import matrix
if mtype == "hmat":
mat = matrix.Matrix()
matrix.open_matrix(infile, mat, format=mtype, symmetrize=True)
else:
mat = {}
nnodes, nedges = my_open_matrix(infile, mat, mtype, True)
mini = minj = maxi = maxj = 1
for i, cols in mat.iteritems():
maxi = max(maxi, i)
mini = min(mini, i)
for j, val in cols.iteritems():
maxj = max(maxj, j)
minj = min(minj, j)
maxy = maxx = max(maxi, maxj)
print mini, minj, maxi, maxj
if size == 0: size = maxx
#!/usr/bin/env python-i
# example of using summatrix from within python
# load summon matrix library
from summon import matrix
# read in matrix (stored in Compressed Row Format 'rmat')
mat = matrix.Matrix()
matrix.open_matrix("dog_human.mat", mat, format="rmat")
# create and show matrix viewer
viewer = matrix.MatrixViewer(mat, title="dog vs human")
viewer.show()
#!/usr/bin/env python-i
# use summatrix to visualize a dense matrix
#
# load summon matrix library
import summon
from summon import matrix, util
# read in matrix (stored in Index Format 'imat')
mat = matrix.Matrix()
matrix.open_matrix("data.mat", mat, format="dmat")
# set colormap
mat.colormap = summon.PosNegColorMap()
# read row and column labels
mat.rowlabels = util.read_strings("data.rlabels")
mat.collabels = util.read_strings("data.clabels")
# create and show matrix viewer
viewer = matrix.MatrixViewer(mat, title="unclustered data",
show_labels=True,
bgcolor=(1,1,1),
style="quads",
winsize=(400, 600))
viewer.show()
if row not in mat: mat[row] = {}
mat[row][col] = val
if symmetrize:
if col not in mat: mat[col] = {}
mat[col][row] = val
ff.close()
return nnodes, nedges
infile, mtype, size, view = parse_arguments(sys.argv[1:])
from summon import matrix
if mtype == "hmat":
mat = matrix.Matrix()
matrix.open_matrix(infile, mat, format = mtype, symmetrize = True)
else:
mat = {}
nnodes, nedges = my_open_matrix(infile, mat, mtype, True)
mini = minj = maxi = maxj = 1
for i, cols in mat.iteritems():
maxi = max(maxi, i)
mini = min(mini, i)
for j, val in cols.iteritems():
maxj = max(maxj, j)
minj = min(minj, j)
maxy = maxx = max(maxi, maxj)
print mini, minj, maxi, maxj
if size == 0: size = maxx
# example of using summatrix from within python
# view a matrix in label format
print
print "NOTE: try quering matrix values using the following syntax:"
print " mat['human']['Cow']"
print
# load summon matrix library
import summon
from summon import matrix
# read in matrix (stored in Labeled Format 'limat')
mat = matrix.Matrix()
mat.order = "mammals_distances.labels" # set the labels needed for matrix
matrix.open_matrix("mammals_distances.lmat", mat, format="lmat")
# read color map for matrix
mat.colormap = summon.read_color_map("mammals_distances.colormap")
# create and show matrix viewer
viewer = matrix.MatrixViewer(mat, title="Mammals distances",
bgcolor=(1,1,1), # use white background (r,g,b)
style="quads", # use squares for matrix entries
show_labels=True, # show labels
show_label_windows=True) # use a separate window
# for labels
viewer.show()
