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Merged
merged 5 commits into from
Aug 19, 2016
Merged

Matplotlib #13

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760d1f7
Converted to matplotlib. Added KM and ScatterPair functions.
cooperlab Aug 19, 2016
4dc87b7
Updated submodule name to "analysis".
cooperlab Aug 19, 2016
d27dc06
Moved matrix conversion into function.
cooperlab Aug 19, 2016
cf7f54d
Added stdout messaging. Removed unused input parameter. Reduced defau…
cooperlab Aug 19, 2016
0ef86de
Fixed imports, added docstrings.
cooperlab Aug 19, 2016
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4 changes: 2 additions & 2 deletions survivalnet/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -8,7 +8,7 @@
from .train import train

# sub-packages with no internal dependencies
from . import sensitivity
from . import analysis

# must be imported before Bayesian_Optimizaiton
#from .CostFunction import cost_func, aggr_st_cost_func, st_cost_func
Expand All @@ -26,5 +26,5 @@
# sub-packages
'model',
'optimization',
'sensitivity',
'analysis',
)
8 changes: 4 additions & 4 deletions survivalnet/analysis/RiskCluster.py
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Original file line number Diff line number Diff line change
@@ -1,5 +1,5 @@
import matplotlib as mpl
import matplotlib.pyplot as pylab
import matplotlib.pyplot as plt
import numpy as np
import scipy.cluster.hierarchy as sch
import scipy.spatial.distance as dist
Expand Down Expand Up @@ -85,7 +85,7 @@ def RiskCluster(Gradients, Raw, Symbols, N=30, Tau=0.05):
Normalized = Normalized.transpose()

# generate figure
Figure = pylab.figure(figsize=(WINDOW_WIDTH, WINDOW_HEIGHT))
Figure = plt.figure(figsize=(WINDOW_WIDTH, WINDOW_HEIGHT))

# cluster samples and generate dendrogram
SampleDist = dist.pdist(Normalized.T, 'correlation')
Expand Down Expand Up @@ -137,7 +137,7 @@ def RiskCluster(Gradients, Raw, Symbols, N=30, Tau=0.05):
Heatmap = Figure.add_axes([HEATMAP_X, HEATMAP_Y, HEATMAP_W, HEATMAP_H],
frame_on=False)
Heatmap.matshow(Reordered, aspect='auto', origin='lower',
cmap=pylab.cm.bwr)
cmap=plt.cm.bwr)
Heatmap.set_xticks([])
Heatmap.set_yticks([])

Expand Down Expand Up @@ -175,7 +175,7 @@ def RiskCluster(Gradients, Raw, Symbols, N=30, Tau=0.05):
cnv = Figure.add_axes([TRACK_X, TRACK_Y,
TRACK_W, TRACK_H - len(SigMut)*TRACK],
frame_on=False)
cnv.matshow(CNVs, aspect='auto', origin='lower', cmap=pylab.cm.bwr)
cnv.matshow(CNVs, aspect='auto', origin='lower', cmap=plt.cm.bwr)
for i in range(len(SigCNV)):
cnv.text(-SPACING, i / np.float(len(SigCNV)) +
1/np.float(2*len(SigCNV)),
Expand Down
5 changes: 4 additions & 1 deletion survivalnet/analysis/RiskCohort.py
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Expand Up @@ -36,9 +36,12 @@ def RiskCohort(Model, Features):
# initialize container for risk gradient profiles
Gradients = np.zeros(Features.shape)

# copy input to matrix for Theano
Matrix = np.matrix(Features)

# iterate through samples, calculating risk gradient profile for each
for i in np.arange(Features.shape[0]):
Gradients[i, :] = _RiskBackpropagate(Model, Features[i, :])
Gradients[i, :] = _RiskBackpropagate(Model, Matrix[i, :])

return Gradients

Expand Down
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