def main():
# first read the data file
pathname_in = sys.argv[1]
X = util.file_to_comma_separated_matrix(pathname_in, has_headers=True)
logging.debug('matrix size: ' + str(X.shape))
# now read the newick file
pathname_in = sys.argv[2]
fin = open(pathname_in)
newick_string = fin.read()
fin.close()
ordered_indices = heatmap.get_newick_order(newick_string)
logging.debug('newick order size: ' + str(len(ordered_indices)))
# reorder the rows of the data file
X = heatmap.get_permuted_rows(X, ordered_indices)
# create the standardized data for drawing the small heatmap
Z = khorr.get_standardized_matrix(X)
# initialize the progress bar
reduction = 100
npixels, remainder = divmod(len(X), reduction)
if remainder:
npixels += 1
pbar = progress.Bar((npixels*(npixels+1))/2)
# show the small heatmap
pathname_out = 'small.png'
im = heatmap.get_reduced_heatmap_image(Z, reduction=reduction, pixel_callback=pbar.update)
fout = open(pathname_out, 'wb')
im.save(fout)
fout.close()
# finish the progress bar
pbar.finish()
def analyze(input_data_path, output_image_path, tree_building_function):
logging.debug('read the matrix')
X = util.file_to_comma_separated_matrix(input_data_path, has_headers=True)
logging.debug('build the tree')
root = tree_building_function(X)
logging.debug('extract ordered indices from the tree')
ordered_indices = root.ordered_labels()
logging.debug('create the elementwise squared correlation matrix')
R = np.corrcoef(X)
logging.debug('permute the elementwise squared correlation matrix according to the ordering')
M = heatmap.get_permuted_rows_and_columns(R, ordered_indices)
logging.debug('create the heatmap')
f = gradient.correlation_to_rgb
heatmap.get_heatmap_with_dendrogram(M, root, f, output_image_path)
def main():
pathname_in = 'mmc-data-files/Starvation_Residual.TXT'
X = util.file_to_comma_separated_matrix(pathname_in, has_headers=True)
print X.shape
# create the tree from the data
root = treebuilder.build_tree(X)
ordered_indices = root.ordered_labels()
X = heatmap.get_permuted_rows(X, ordered_indices)
# create the standardized data for drawing the small heatmap
Z = khorr.get_standardized_matrix(X)
# show the big heatmap
pathname_out = 'big.png'
color_function = gradient.correlation_to_rgb
im = heatmap.get_heatmap_image(np.dot(Z, Z.T), color_function)
fout = open(pathname_out, 'wb')
im.save(fout)
fout.close()
# show the small heatmap
pathname_out = 'small.png'
im = heatmap.get_reduced_heatmap_image(Z, reduction=5)
fout = open(pathname_out, 'wb')
im.save(fout)
fout.close()
def __init__(self, parent, npixels, data_filename, tree_filename, low_zoom_image_filename):
"""
@param parent: the parent frame
@param npixels: larger for larger windows
@param data_filename: the path to a csv file
@param tree_filename: the path to a newick tree
@param low_zoom_image_filename: the path to a low resolution image
"""
# save some args
self.parent = parent
# define some options
self.npixels = npixels
# create the tkinter image
print 'creating the low resolution image...'
raw_pil_image = Image.open(low_zoom_image_filename)
low_zoom_pil_image = raw_pil_image.resize((self.npixels, self.npixels), Image.ANTIALIAS)
low_zoom_image = ImageTk.PhotoImage(low_zoom_pil_image)
# create the list of ordered gene names
print 'creating the list of ordered gene names...'
self.mtree_root = mtree.newick_file_to_mtree(tree_filename)
names = get_gene_names(data_filename)
ordered_gene_names = [names[row_index] for row_index in self.mtree_root.ordered_labels()]
# create the standardized and sorted data matrix
print 'creating the ordered correlation square root...'
X = util.file_to_comma_separated_matrix(data_filename, has_headers=True)
Z = khorr.get_standardized_matrix(X)
Z = np.vstack(Z[row_index] for row_index in self.mtree_root.ordered_labels())
#Z = None
# create the label to leaf map
print 'creating the map from labels to leaves...'
self.label_to_leaf = dict((tip.label, tip) for tip in self.mtree_root.ordered_tips())
# initialize the windows individually
self._init_windows(low_zoom_image, Z, ordered_gene_names)
# redo the layout of the windows
self.repack()
# initialize the connections among the windows
self._connect_windows()