def get_rowsidematrix(Features, Arguments):
'''
'''
GrayScale = {
-9: "gray10",
-8: "gray20",
-7: "gray30",
-6: "gray40",
-5: "gray50",
-4: "gray60",
-3: "gray70",
-2: "gray80"
}
Matrix = dict([(Row.split()[0], Row.split()[1])
for Row in file(get_path("RowSideColors"))])
PValues = []
for Feature in Features:
PValues.append(Matrix[Feature])
Label = ["Mesenchymal"]
Variates = [
int(("%0.2e" % float(PValue)).split("e")[1]) for PValue in PValues
]
Variates = [
"black" if Variate <= -10 else
("white" if Variate >= -1 else GrayScale[Variate])
for Variate in Variates
]
return string_matrix(Features, Label, [Variates], Arguments)
def heatmap(Arguments):
'''
'''
Data = load_data(Arguments)
if Arguments.OrderBy: Data = reorder_data(Data, Arguments)
#This is specifically the part you want plotted on the heatmap, NOT the sidebars
Features, Variates = get_heatmap_data(Data, Arguments)
Features = [Feature[:Feature.index(":")] for Feature in Features]
ClusteredMatrix = ro.r["hierarchical_cluster_distance_matrix"](
float_matrix(Data.Labels, Features, Variates, Arguments))
Columns = list(ClusteredMatrix.colnames)
Rows = list(ClusteredMatrix.rownames)
Matrix = np.array(ClusteredMatrix)
ZMatrix = z_matrix(Matrix)
ColorPalette = list(ro.r["colorRampPalette"](ro.StrVector(
["blue", "white", "red"]))(100))
ColorMatrix = [float2color(Vector, ColorPalette) for Vector in ZMatrix]
exit()
Heatmap = float_matrix(Data.Labels, Features, Variates, Arguments)
Legend = False #overwrite if ColSideColors is called
if "colsidecolors" in [Option.lower() for Option in Arguments.Heatmap]:
ColorFeatures, ColSideMatrix, Legend = get_colsidematrix(
Data, Arguments)
ColSideMatrix = transpose_matrix(
string_matrix(Data.Labels, ColorFeatures, ColSideMatrix,
Arguments))
else:
ColSideMatrix = False
if "rowsidecolors" in [Option.lower() for Option in Arguments.Heatmap]:
RowSideMatrix = get_rowsidematrix(Features, Arguments)
else:
RowSideMatrix = False
ro.r['pdf'](Arguments.Filename + '.pdf')
if Legend: ro.r['par'](mar=ro.IntVector([1, 1, 1, 1]))
ro.r['par'](**{'cex.axis': 0.8})
get_heatmap(Heatmap,
ColSideMatrix=ColSideMatrix,
RowSideMatrix=RowSideMatrix,
Legend=Legend)
ro.r['dev.off']()
return
def get_rowsidematrix(Features, Arguments):
'''
'''
GrayScale = {-9:"gray10", -8:"gray20", -7:"gray30", -6:"gray40", -5:"gray50", -4:"gray60", -3:"gray70", -2:"gray80"}
Matrix = dict([(Row.split()[0], Row.split()[1]) for Row in file(get_path("RowSideColors"))])
PValues = []
for Feature in Features:
PValues.append(Matrix[Feature])
Label = ["Mesenchymal"]
Variates = [int(("%0.2e" %float(PValue)).split("e")[1]) for PValue in PValues]
Variates = ["black" if Variate <= -10 else ("white" if Variate >= -1 else GrayScale[Variate]) for Variate in Variates]
return string_matrix(Features, Label, [Variates], Arguments)
def heatmap(Arguments):
'''
'''
Data = load_data(Arguments)
if Arguments.OrderBy: Data = reorder_data(Data, Arguments)
#This is specifically the part you want plotted on the heatmap, NOT the sidebars
Features, Variates = get_heatmap_data(Data, Arguments)
Features = [Feature[:Feature.index(":")] for Feature in Features]
ClusteredMatrix = ro.r["hierarchical_cluster_distance_matrix"](float_matrix(Data.Labels, Features, Variates, Arguments))
Columns = list(ClusteredMatrix.colnames)
Rows = list(ClusteredMatrix.rownames)
Matrix = np.array(ClusteredMatrix)
ZMatrix = z_matrix(Matrix)
ColorPalette = list(ro.r["colorRampPalette"](ro.StrVector(["blue", "white", "red"]))(100))
ColorMatrix = [float2color(Vector, ColorPalette) for Vector in ZMatrix]
exit()
Heatmap = float_matrix(Data.Labels, Features, Variates, Arguments)
Legend = False #overwrite if ColSideColors is called
if "colsidecolors" in [Option.lower() for Option in Arguments.Heatmap]:
ColorFeatures, ColSideMatrix, Legend = get_colsidematrix(Data, Arguments)
ColSideMatrix = transpose_matrix(string_matrix(Data.Labels, ColorFeatures, ColSideMatrix, Arguments))
else:
ColSideMatrix = False
if "rowsidecolors" in [Option.lower() for Option in Arguments.Heatmap]:
RowSideMatrix = get_rowsidematrix(Features, Arguments)
else:
RowSideMatrix = False
ro.r['pdf'](Arguments.Filename + '.pdf')
if Legend: ro.r['par'](mar=ro.IntVector([1,1,1,1]))
ro.r['par'](**{'cex.axis':0.8})
get_heatmap(Heatmap, ColSideMatrix=ColSideMatrix, RowSideMatrix=RowSideMatrix, Legend=Legend)
ro.r['dev.off']()
return