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category data and plot selection update|

This commit is contained in:
Arnar Flatberg 2006-04-19 10:37:44 +00:00
parent a8937ededb
commit 1091bea0e9
3 changed files with 89 additions and 21 deletions

View File

@ -1,6 +1,9 @@
from sets import Set as set
set.update = set.union_update
import dataset
import scipy
class AnnotationsException(Exception):
pass
@ -63,3 +66,28 @@ class Annotations:
"""
return self.dimensions.has_key(dim)
def to_dataset(self,dim):
""" Returns a dataset representation of annotations.
"""
if self.has_dimension(dim):
num_dim1 = len(set(self.dimensions[dim])) #number of unique genes
all_genes = set(self.dimensions[dim])
all_categories = set()
for cat in self.dimensions[dim].values():
all_categories.update(cat)
num_dim1 = len(all_genes) #number of unique genes
num_dim2 = len(all_categories) #number of unique categories
gene_list=[]
cat_list=[]
matrix = scipy.zeros((num_dim1,num_dim2),'bwu')
for i,gene in enumerate(all_genes):
gene_list.append(gene)
for j,cat in enumerate(all_categories):
cat_list.append(cat)
matrix[i,j] = 1
def_list = [['genes',gene_list],['go',cat_list]]
return dataset.Dataset(matrix,def_list)

View File

@ -1,5 +1,5 @@
import logger
from scipy import array,take,asarray,shape
from scipy import array,take,asarray,shape,nonzero
import project
from itertools import izip
@ -10,19 +10,14 @@ class Dataset:
A Dataset is an n-way array with defined string identifiers across
all dimensions.
"""
def __init__(self,input_array,def_list,parents=None):
def __init__(self,input_array,def_list):
self._data = asarray(input_array)
self.dims = shape(self._data)
self.parents = parents
self.def_list = def_list
self._ids_set = set()
self.ids={}
self.children=[]
self._dim_num = {}
self._dim_names = []
if parents!=None:
for parent in self.parents:
parent.children.append(self)
if len(def_list)!=len(self.dims):
raise ValueError,"array dims and identifyer mismatch"
for axis,(dim_name,ids) in enumerate(def_list):
@ -37,11 +32,6 @@ class Dataset:
self._ids_set = self._ids_set.union(set(ids))
self._dim_num[dim_name] = axis
self._dim_names.append(dim_name)
#if dim_name in project.c_p.dim_names:
# if ids:
# # check that identifers are same as before
# raise NotImplementedError
# else:
for df,d in izip(def_list,self.dims): #check that data and labels match
df=df[1]
@ -75,10 +65,50 @@ class Dataset:
n_dim = self.dims[axis]
return [str(axis) + '_' + str(i) for i in range(n_dim)]
def index_to_id(self,dim_name,index):
def extract_id_from_index(self,dim_name,index):
"""Returns a set of ids from array/list of indexes."""
dim_ids = self.ids[dim_name]
return [id for id,ind in dim_ids.items() if ind in index]
return set([id for id,ind in dim_ids.items() if ind in index])
def extract_index_from_id(self,dim_name,id):
"""Returns an array of indexes from a set/list of identifiers
(or a single id)"""
dim_ids = self.ids[dim_name]
return array([ind for name,ind in dim_ids.items() if name in id])
class CategoryDataset(Dataset):
def __init__(self,array,def_list):
Dataset.__init__(self,array,def_list)
def get_elements_by_category(self,dim,category):
"""Returns all elements along input dim belonging to category.
Assumes a two-dim category data only!
"""
if type(category)!=list:
raise ValueError, "category must be list"
gene_ids = []
axis_dim = self._dim_num[dim]
cat_index = self.extract_index_from_id(category)
for ind in cat_index:
if axis_dim==0:
gene_indx = nonzero(self._data[:,ind])
elif axis_dim==1:
gene_indx = nonzero(self._data[ind,:])
else:
ValueError, "Only support for 2-dim data"
gene_ids.append(self.extract_id_from_index(dim,gene_index))
return gene_ids
class Selection:
"""Handles selected identifiers along each dimension of a dataset"""
def __init__(self):

View File

@ -237,9 +237,9 @@ class ScatterPlot (Plot):
self.ax = ax = fig.add_subplot(111)
self.x_dataset = project.c_p.datasets[0]
x = self.x_dataset._data
self.a = a = x[:,0]
self.b = b = x[:,1]
ax.plot(a,b,'og')
self.xaxis_data = xaxis_data = x[:,0]
self.yaxis_data = yaxis_data = x[:,1]
ax.plot(xaxis_data,yaxis_data,'og')
self.canvas = FigureCanvas(fig)
self.add(self.canvas)
rectprops = dict(facecolor='blue', edgecolor = 'black',
@ -256,14 +256,24 @@ class ScatterPlot (Plot):
logger.log('debug', "(%3.2f, %3.2f) --> (%3.2f, %3.2f)"%(x1,y1,x2,y2))
logger.log('debug',"The button you used were:%s, %s "%(event1.button, event2.button))
# get all points within x1, y1, x2, y2
ydata = self.b
xdata = self.a
index =scipy.nonzero((xdata<x2) & (xdata>x1) & (ydata<y1) & (ydata>y2))
ydata = self.yaxis_data
xdata = self.xaxis_data
if x1>x2:
if y1<y2:
index =scipy.nonzero((xdata<x1) & (xdata>x2) & (ydata>y1) & (ydata<y2))
else:
index =scipy.nonzero((xdata<x1) & (xdata>x2) & (ydata<y1) & (ydata>y2))
else:
if y1<y2:
index =scipy.nonzero((xdata>x2) & (xdata<x1) & (ydata>y1) & (ydata<y2))
else:
index =scipy.nonzero((xdata>x2) & (xdata<x1) & (ydata<y1) & (ydata>y2))
if len(index)==0:
logger.log('debug','No points selected!')
else:
logger.log('debug','Selected:\n%s'%index)
ids = self.x_dataset.index_to_id('samples',index)
ids = self.x_dataset.extract_id_from_index('samples',index)
logger.log('debug','Selected identifiers:\n%s'%ids)
xdata_new = scipy.take(xdata,index)
ydata_new = scipy.take(ydata,index)