Skip to content

Python3 #1

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
renziyuan1997 wants to merge 2 commits into
base: master
Choose a base branch
from
Open

Python3 #1

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
b91238d
Adapting the code to Python3
DanielVillarreal09 Jul 20, 2020
7154aed
py3 agarpad
Jul 21, 2020
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
Binary file added .DS_Store
View file
Open in desktop
Binary file not shown.
87 changes: 39 additions & 48 deletions analysis/analysis.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -23,12 +23,12 @@
# yaml formats
npfloat_representer = lambda dumper,value: dumper.represent_float(float(value))
nparray_representer = lambda dumper,value: dumper.represent_list(value.tolist())
float_representer = lambda dumper,value: dumper.represent_scalar(u'tag:yaml.org,2002:float', "{:<.8e}".format(value))
float_representer = lambda dumper,value: dumper.represent_scalar('tag:yaml.org,2002:float', "{:<.8e}".format(value))
unicode_representer = lambda dumper,value: dumper.represent_unicode(value.encode('utf-8'))
yaml.add_representer(float,float_representer)
yaml.add_representer(np.float_,npfloat_representer)
yaml.add_representer(np.ndarray,nparray_representer)
yaml.add_representer(unicode,unicode_representer)
yaml.add_representer(str,unicode_representer)

# matplotlib controls
plt.rcParams['svg.fonttype'] = 'none' # to embed fonts in output ('path' is to convert as text as paths)
Expand All @@ -39,7 +39,7 @@
def default_parameters():
"""Generate a default parameter dictionary."""

print "Loading default parameters"
print("Loading default parameters")
params={}
# dimensions
params['dimensions']={}
Expand All @@ -66,20 +66,16 @@ def hist_dimensions(cells, outputdir='.', bins=['auto','auto','auto','auto'], un

# initialization
if mode == 'um':
titles = [u'length (\u03BCm)', u'width (\u03BCm)', u'area (\u03BCm\u00B2)', u'volume (\u03BCm\u00B3)']
titles = ['length (\u03BCm)', 'width (\u03BCm)', 'area (\u03BCm\u00B2)', 'volume (\u03BCm\u00B3)']
attrs = ['height_um','width_um','area_um2', 'volume_um3']
else:
titles = [u'length (px)', u'width (px)', u'area (px\u00B2)', u'volume (px\u00B3)']
titles = ['length (px)', 'width (px)', 'area (px\u00B2)', 'volume (px\u00B3)']
attrs = ['height','width','area', 'volume']

nattrs = len(attrs)
if bins is None:
bins = ['auto' for i in range(nattrs)]
elif len(bins) != nattrs:
if len(bins) != nattrs:
raise ValueError("bins has the wrong dimensions!")
if units_dx is None:
units_dx = [None for i in range(nattrs)]
elif len(units_dx) != nattrs:
if len(units_dx) != nattrs:
raise ValueError("units_dx has the wrong dimensions!")
ncells = len(cells)

Expand All @@ -90,7 +86,7 @@ def hist_dimensions(cells, outputdir='.', bins=['auto','auto','auto','auto'], un

# make lists
data = [ [] for i in range(nattrs)]
keys = cells.keys()
keys = list(cells.keys())
for n in range(ncells):
key = keys[n]
cell = cells[key]
Expand Down Expand Up @@ -118,13 +114,13 @@ def hist_dimensions(cells, outputdir='.', bins=['auto','auto','auto','auto'], un

for i in range(nattrs):
attr = attrs[i]
print "attr = {}".format(attr)
print("attr = {}".format(attr))
ax = axes[i]

# compute histogram
hist,edges = np.histogram(data[i], bins=bins[i], density=False)
nbins = len(edges)-1
print "nbins = {:d}".format(nbins)
print("nbins = {:d}".format(nbins))

# plot histogram
color = 'grey'
Expand Down Expand Up @@ -165,7 +161,7 @@ def hist_dimensions(cells, outputdir='.', bins=['auto','auto','auto','auto'], un
for ext in exts:
fileout = os.path.join(outputdir,filename+ext)
fig.savefig(fileout, bbox_inches='tight', pad_inches=0)
print "Fileout: {:<s}".format(fileout)
print("Fileout: {:<s}".format(fileout))
return

def hist_dimensions_other(cells, outputdir='.', bins=None, units_dx=None, alpha=0.):
Expand Down Expand Up @@ -203,7 +199,7 @@ def hist_dimensions_other(cells, outputdir='.', bins=None, units_dx=None, alpha=

# make lists
data = [ [] for i in range(nattrs)]
keys = cells.keys()
keys = list(cells.keys())
for n in range(ncells):
key = keys[n]
cell = cells[key]
Expand All @@ -230,15 +226,15 @@ def hist_dimensions_other(cells, outputdir='.', bins=None, units_dx=None, alpha=
axes.append(ax)

for i in range(nattrs):
print "attr number = {:d}".format(i)
print("attr number = {:d}".format(i))
ax = axes[i]

# remove outliers
data_sorted = np.sort(data[i])
ntot = len(data_sorted)
n0 = int(0.5*alpha*float(ntot))
n1 = ntot - n0
print "{:2s}n0 = {:d} n1 = {:d}".format("", n0, n1)
print("{:2s}n0 = {:d} n1 = {:d}".format("", n0, n1))
data_trunc = data_sorted[n0:n1]

mu = np.nanmean(data_trunc)
Expand All @@ -250,7 +246,7 @@ def hist_dimensions_other(cells, outputdir='.', bins=None, units_dx=None, alpha=
# compute histogram
hist,edges = np.histogram(data_trunc, bins=bins[i], density=False)
nbins = len(edges)-1
print "{:2s}nbins = {:d}".format("",nbins)
print("{:2s}nbins = {:d}".format("",nbins))

# plot histogram
color = 'grey'
Expand Down Expand Up @@ -281,7 +277,7 @@ def hist_dimensions_other(cells, outputdir='.', bins=None, units_dx=None, alpha=
for ext in exts:
fileout = os.path.join(outputdir,filename+ext)
fig.savefig(fileout, bbox_inches='tight', pad_inches=0)
print "Fileout: {:<s}".format(fileout)
print("Fileout: {:<s}".format(fileout))
return

def hist_channels(cells, outputdir='.', bins=None, units_dx=None, titles=None, mode='total',qcut=0, bg_val=None, backgrounds=None):
Expand All @@ -291,11 +287,11 @@ def hist_channels(cells, outputdir='.', bins=None, units_dx=None, titles=None, m

# initialization
if mode == 'concentration_fl':
print "concentration_fl mode"
print("concentration_fl mode")
fl_dtype = np.float_
fmt = "$\\mu = {mu:,.2f}$\n$\\sigma = {sig:,.2f}$\n$N = {N:,d}$\n$\\mathrm{{med}} = {med:,.2f}$"
elif mode == 'total_fl':
print "total_fl mode"
print("total_fl mode")
fl_dtype = np.uint16
fmt = "$\\mu = {mu:,d}$\n$\\sigma = {sig:,d}$\n$N = {N:,d}$\n$\\mathrm{{med}} = {med:,d}$"
else:
Expand All @@ -304,7 +300,7 @@ def hist_channels(cells, outputdir='.', bins=None, units_dx=None, titles=None, m
data_bg = []

# filling up the fluorescence
cellref = cells.values()[0]
cellref = list(cells.values())[0]
nchannel = len(cellref['fluorescence']['total'])

if bins is None:
Expand All @@ -322,7 +318,7 @@ def hist_channels(cells, outputdir='.', bins=None, units_dx=None, titles=None, m
BG = []

# make lists
keys = cells.keys()
keys = list(cells.keys())
for n in range(ncells):
key = keys[n]
cell = cells[key]
Expand Down Expand Up @@ -360,7 +356,7 @@ def hist_channels(cells, outputdir='.', bins=None, units_dx=None, titles=None, m
else:
bgcolor='g'
bgs = [np.float_(backgrounds[i]) for i in range(nchannel)]
#print bgs
print(bgs)

# make figure
fig = plt.figure(num=None, facecolor='w', figsize=(nchannel*4,3))
Expand All @@ -373,7 +369,7 @@ def hist_channels(cells, outputdir='.', bins=None, units_dx=None, titles=None, m
axes.append(ax)

for i in range(nchannel):
print "channel = {}".format(i)
print("channel = {}".format(i))
ax = axes[i]

# compute histogram
Expand All @@ -385,7 +381,7 @@ def hist_channels(cells, outputdir='.', bins=None, units_dx=None, titles=None, m
d = d[n0:n1+1]
hist,edges = np.histogram(d, bins=bins[i], density=False)
nbins = len(edges)-1
print "nbins = {:d}".format(nbins)
print("nbins = {:d}".format(nbins))

# plot histogram
color = 'grey'
Expand Down Expand Up @@ -434,7 +430,7 @@ def hist_channels(cells, outputdir='.', bins=None, units_dx=None, titles=None, m
for ext in exts:
fileout = os.path.join(outputdir,filename+ext)
fig.savefig(fileout, bbox_inches='tight', pad_inches=0)
print "Fileout: {:<s}".format(fileout)
print("Fileout: {:<s}".format(fileout))
return

def make_plot_queen(cells, outputdir='.', bins=['auto','auto','auto'], titles=['I1','I2','QUEEN'], channels=[0,1], colors=['darkblue', 'darkgreen', 'darkblue'], units_dx=[None, None, None], mode='total_fl', bgcolor='r',qcut=0, backgrounds=None):
Expand All @@ -455,12 +451,12 @@ def make_plot_queen(cells, outputdir='.', bins=['auto','auto','auto'], titles=['
QUEEN=[]

if mode == 'concentration_fl':
print "concentration_fl mode"
print("concentration_fl mode")
fl_dtype = np.float_
fl_fmt = "$\\mu = {mu:,.2f}$\n$\\sigma = {sig:,.2f}$\n$N = {N:,d}$\n$\\mathrm{{med}} = {med:,.2f}$"

elif mode == 'total_fl':
print "total_fl mode"
print("total_fl mode")
fl_dtype = np.uint16
fl_fmt = "$\\mu = {mu:,d}$\n$\\sigma = {sig:,d}$\n$N = {N:,d}$\n$\\mathrm{{med}} = {med:,d}$"
else:
Expand All @@ -472,7 +468,7 @@ def make_plot_queen(cells, outputdir='.', bins=['auto','auto','auto'], titles=['
bgcolor='g'

# make lists
keys = cells.keys()
keys = list(cells.keys())
for n in range(ncells):
key = keys[n]
cell = cells[key]
Expand All @@ -498,12 +494,7 @@ def make_plot_queen(cells, outputdir='.', bins=['auto','auto','auto'], titles=['
bg_y = backgrounds[c2]
elif mode == 'total_fl':
pass
try:
z = (float(x)-float(bg_x))/(float(y)-float(bg_y))
except ZeroDivisionError:
print("x = {:.6f} bg_x = {:.6f} y = {:.6f} bg_y = {:.6f}".format(x,bg_x,y,bg_y))
print("Skipping cell {:s}".format(cell['id']))
continue
z = (float(x)-float(bg_x))/(float(y)-float(bg_y))
I1.append(x)
BG1.append(bg_x)
I2.append(y)
Expand All @@ -516,8 +507,8 @@ def make_plot_queen(cells, outputdir='.', bins=['auto','auto','auto'], titles=['
I2 = np.array(I2, dtype=fl_dtype)
BG2 = np.array(BG2, dtype=fl_dtype)
QUEEN = np.array(QUEEN, dtype=np.float_)
#print np.unique(BG1)
#print np.unique(BG2)
print(np.unique(BG1))
print(np.unique(BG2))

# make plot
N = len(I1)
Expand All @@ -529,7 +520,7 @@ def make_plot_queen(cells, outputdir='.', bins=['auto','auto','auto'], titles=['
mu_bg1 = np.median(BG1)
mu_bg2 = np.median(BG2)
data_bg = [BG1, BG2]
print "bg1 = {:.2f} bg2 = {:.2f}".format(mu_bg1,mu_bg2)
print("bg1 = {:.2f} bg2 = {:.2f}".format(mu_bg1,mu_bg2))
fmts = [fl_fmt,fl_fmt,"$\\mu = {mu:.2f}$\n$\\sigma = {sig:.2f}$\n$N = {N:,d}$\n$\\mathrm{{med}} = {med:.2f}$"]

fig = plt.figure(num=None, facecolor='w', figsize=(3*4,3))
Expand All @@ -553,7 +544,7 @@ def make_plot_queen(cells, outputdir='.', bins=['auto','auto','auto'], titles=['
d = d[n0:n1+1]
hist,edges = np.histogram(d, bins=bins[i], density=False)
nbins = len(edges)-1
print "nbins = {:d}".format(nbins)
print("nbins = {:d}".format(nbins))

# plot histogram
color = colors[i]
Expand Down Expand Up @@ -606,7 +597,7 @@ def make_plot_queen(cells, outputdir='.', bins=['auto','auto','auto'], titles=['
for ext in exts:
fileout = os.path.join(outputdir,filename+ext)
fig.savefig(fileout, bbox_inches='tight', pad_inches=0)
print "Fileout: {:<s}".format(fileout)
print("Fileout: {:<s}".format(fileout))
return

#################### main ####################
Expand All @@ -628,7 +619,7 @@ def make_plot_queen(cells, outputdir='.', bins=['auto','auto','auto'], titles=['

cells = load_json2dict(cellfile)
ncells = len(cells)
print "ncells = {:d}".format(ncells)
print("ncells = {:d}".format(ncells))

# output directory
outputdir = namespace.outputdir
Expand All @@ -639,7 +630,7 @@ def make_plot_queen(cells, outputdir='.', bins=['auto','auto','auto'], titles=['
outputdir = os.path.join(outputdir,'analysis')
if not os.path.isdir(outputdir):
os.makedirs(outputdir)
print "{:<20s}{:<s}".format("outputdir", outputdir)
print("{:<20s}{:<s}".format("outputdir", outputdir))

# parameter file
if namespace.paramfile is None:
Expand All @@ -660,30 +651,30 @@ def make_plot_queen(cells, outputdir='.', bins=['auto','auto','auto'], titles=['
mydir = os.path.join(outputdir,'dimensions')
if not os.path.isdir(mydir):
os.makedirs(mydir)
print "{:<20s}{:<s}".format("outputdir", mydir)
print("{:<20s}{:<s}".format("outputdir", mydir))
hist_dimensions(cells, outputdir=mydir, **allparams['dimensions'])

# dimensions other
if 'dimensions_other' in allparams:
mydir = os.path.join(outputdir,'dimensions')
if not os.path.isdir(mydir):
os.makedirs(mydir)
print "{:<20s}{:<s}".format("outputdir", mydir)
print("{:<20s}{:<s}".format("outputdir", mydir))
hist_dimensions_other(cells, outputdir=mydir, **allparams['dimensions_other'])

# make queen analysis
if 'fluorescence' in allparams:
mydir = os.path.join(outputdir,'fluorescence')
if not os.path.isdir(mydir):
os.makedirs(mydir)
print "{:<20s}{:<s}".format("outputdir", mydir)
print("{:<20s}{:<s}".format("outputdir", mydir))
hist_channels(cells, outputdir=mydir, **allparams['fluorescence'])

# make queen analysis
if 'queen' in allparams:
mydir = os.path.join(outputdir,'queen')
if not os.path.isdir(mydir):
os.makedirs(mydir)
print "{:<20s}{:<s}".format("outputdir", mydir)
print("{:<20s}{:<s}".format("outputdir", mydir))
make_plot_queen(cells, outputdir=mydir, **allparams['queen'])

Loading