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-rw-r--r--wqflask/wqflask/my_pylmm/pyLMM/gn2.py17
-rw-r--r--wqflask/wqflask/my_pylmm/pyLMM/kinship.py17
-rw-r--r--wqflask/wqflask/my_pylmm/pyLMM/lmm.py5
-rw-r--r--wqflask/wqflask/my_pylmm/pyLMM/lmm2.py12
-rw-r--r--wqflask/wqflask/my_pylmm/pyLMM/standalone.py34
5 files changed, 71 insertions, 14 deletions
diff --git a/wqflask/wqflask/my_pylmm/pyLMM/gn2.py b/wqflask/wqflask/my_pylmm/pyLMM/gn2.py
index e0c6c8a7..4702c670 100644
--- a/wqflask/wqflask/my_pylmm/pyLMM/gn2.py
+++ b/wqflask/wqflask/my_pylmm/pyLMM/gn2.py
@@ -5,13 +5,25 @@
from __future__ import absolute_import, print_function, division
+import numpy as np
import sys
import logging
# logging.basicConfig(level=logging.DEBUG)
+# np.set_printoptions()
def progress(location, count, total):
- print("Progress: %s %i %i @%d%%" % (location,count,total,round(count*100.0/total)))
+ """
+ Progress update
+ """
+ logging.info("Progress: %s %d%%" % (location,round(count*100.0/total)))
+
+def mprint(msg,data):
+ """
+ Array/matrix print function
+ """
+ m = np.array(data)
+ print(msg,m.shape,"=\n",m)
def callbacks():
return dict(
@@ -22,7 +34,8 @@ def callbacks():
warning = logging.warning,
error = logging.error,
critical = logging.critical,
- progress = progress
+ progress = progress,
+ mprint = mprint
)
# ----- Minor test cases:
diff --git a/wqflask/wqflask/my_pylmm/pyLMM/kinship.py b/wqflask/wqflask/my_pylmm/pyLMM/kinship.py
index 0c43587e..43e7fe36 100644
--- a/wqflask/wqflask/my_pylmm/pyLMM/kinship.py
+++ b/wqflask/wqflask/my_pylmm/pyLMM/kinship.py
@@ -155,20 +155,21 @@ def kinship(G,computeSize=1000,numThreads=None,useBLAS=False,verbose=True):
# np.savetxt(outFile+".kve",Kve)
return K
-def kvakve(K, verbose=True):
+def kvakve(K, callbacks):
"""
Obtain eigendecomposition for K and return Kva,Kve where Kva is cleaned
of small values < 1e-6 (notably smaller than zero)
"""
- if verbose: sys.stderr.write("Obtaining eigendecomposition for %dx%d matrix\n" % (K.shape[0],K.shape[1]) )
-
+ info = callbacks()['info']
+ mprint = callbacks()['mprint']
+
+ info("Obtaining eigendecomposition for %dx%d matrix" % (K.shape[0],K.shape[1]) )
Kva,Kve = linalg.eigh(K)
- if verbose:
- print("Kva is: ", Kva.shape, Kva)
- print("Kve is: ", Kve.shape, Kve)
+ mprint("Kva",Kva)
+ mprint("Kve",Kve)
- if sum(Kva < 1e-6):
- if verbose: sys.stderr.write("Cleaning %d eigen values (Kva<0)\n" % (sum(Kva < 0)))
+ if sum(Kva < 0):
+ info("Cleaning %d eigen values (Kva<0)" % (sum(Kva < 0)))
Kva[Kva < 1e-6] = 1e-6
return Kva,Kve
diff --git a/wqflask/wqflask/my_pylmm/pyLMM/lmm.py b/wqflask/wqflask/my_pylmm/pyLMM/lmm.py
index 8a24d98b..5ad644e2 100644
--- a/wqflask/wqflask/my_pylmm/pyLMM/lmm.py
+++ b/wqflask/wqflask/my_pylmm/pyLMM/lmm.py
@@ -54,11 +54,14 @@ import genotype
import phenotype
import gwas
+# ---- A trick to decide on the environment:
try:
from wqflask.my_pylmm.pyLMM import chunks
+ from gn2 import callbacks
except ImportError:
print("WARNING: Standalone version missing the Genenetwork2 environment\n")
has_gn2=False
+ from standalone import callbacks
pass
#np.seterr('raise')
@@ -594,7 +597,7 @@ class LMM:
# if self.verbose: sys.stderr.write("Obtaining eigendecomposition for %dx%d matrix\n" % (K.shape[0],K.shape[1]) )
begin = time.time()
# Kva,Kve = linalg.eigh(K)
- Kva,Kve = kvakve(K)
+ Kva,Kve = kvakve(K,callbacks)
end = time.time()
if self.verbose: sys.stderr.write("Total time: %0.3f\n" % (end - begin))
print("sum(Kva),sum(Kve)=",sum(Kva),sum(Kve))
diff --git a/wqflask/wqflask/my_pylmm/pyLMM/lmm2.py b/wqflask/wqflask/my_pylmm/pyLMM/lmm2.py
index d4b3ac82..6aefb9d3 100644
--- a/wqflask/wqflask/my_pylmm/pyLMM/lmm2.py
+++ b/wqflask/wqflask/my_pylmm/pyLMM/lmm2.py
@@ -24,6 +24,16 @@ from scipy import optimize
from optmatrix import matrixMult
import kinship
+# A trick to decide on the environment:
+try:
+ from wqflask.my_pylmm.pyLMM import chunks
+ from gn2 import callbacks
+except ImportError:
+ print("WARNING: Standalone version missing the Genenetwork2 environment\n")
+ has_gn2=False
+ from standalone import callbacks
+ pass
+
def calculateKinship(W,center=False):
"""
W is an n x m matrix encoding SNP minor alleles.
@@ -184,7 +194,7 @@ class LMM2:
# if self.verbose: sys.stderr.write("Obtaining eigendecomposition for %dx%d matrix\n" % (K.shape[0],K.shape[1]) )
begin = time.time()
# Kva,Kve = linalg.eigh(K)
- Kva,Kve = kinship.kvakve(K)
+ Kva,Kve = kinship.kvakve(K,callbacks)
end = time.time()
if self.verbose: sys.stderr.write("Total time: %0.3f\n" % (end - begin))
print("sum(Kva),sum(Kve)=",sum(Kva),sum(Kve))
diff --git a/wqflask/wqflask/my_pylmm/pyLMM/standalone.py b/wqflask/wqflask/my_pylmm/pyLMM/standalone.py
index a806729e..bbee3cd7 100644
--- a/wqflask/wqflask/my_pylmm/pyLMM/standalone.py
+++ b/wqflask/wqflask/my_pylmm/pyLMM/standalone.py
@@ -8,13 +8,29 @@
from __future__ import absolute_import, print_function, division
+import numpy as np
import sys
import logging
logging.basicConfig(level=logging.DEBUG)
+np.set_printoptions(precision=3,suppress=True)
def progress(location, count, total):
- logging.info("Progress: %s %i %i @%d%%" % (location,count,total,round(count*100.0/total)))
+ logging.info("Progress: %s %d%%" % (location,round(count*100.0/total)))
+
+def mprint(msg,data):
+ """
+ Array/matrix print function
+ """
+ m = np.array(data)
+ if m.ndim == 1:
+ print(msg,m.shape,"=\n",m[0:3]," ... ",m[-3:])
+ if m.ndim == 2:
+ print(msg,m.shape,"=\n[",
+ m[0][0:3]," ... ",m[0][-3:],"\n ",
+ m[1][0:3]," ... ",m[1][-3:],"\n ...\n ",
+ m[-2][0:3]," ... ",m[-2][-3:],"\n ",
+ m[-1][0:3]," ... ",m[-1][-3:],"]")
def callbacks():
return dict(
@@ -25,7 +41,8 @@ def callbacks():
warning = logging.warning,
error = logging.error,
critical = logging.critical,
- progress = progress
+ progress = progress,
+ mprint = mprint
)
# ----- Minor test cases:
@@ -39,3 +56,16 @@ if __name__ == '__main__':
wrln("Hello %i" % 34)
progress = callbacks()['progress']
progress("I am half way",50,100)
+ list = [0.5,0.6096595 , -0.31559815, -0.52793285, 1.16573418e-15,
+ 0.5,0.6096595 , -0.31559815, -0.52793285, 1.16573418e-15,
+ 0.5,0.6096595 , -0.31559815, -0.52793285, 1.16573418e-15,
+ 0.5,0.6096595 , -0.31559815, -0.52793285, 1.16573418e-15,
+ 0.5,0.6096595 , -0.31559815, -0.52793285, 1.16573418e-15]
+ mprint("list",list)
+ matrix = [[1,0.5,0.6096595 , -0.31559815, -0.52793285, 1.16573418e-15],
+ [2,0.5,0.6096595 , -0.31559815, -0.52793285, 1.16573418e-15],
+ [3,0.5,0.6096595 , -0.31559815, -0.52793285, 1.16573418e-15],
+ [4,0.5,0.6096595 , -0.31559815, -0.52793285, 1.16573418e-15],
+ [5,0.5,0.6096595 , -0.31559815, -0.52793285, 1.16573418e-15],
+ [6,0.5,0.6096595 , -0.31559815, -0.52793285, 1.16573418e-15]]
+ mprint("matrix",matrix)