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Christian Rickert authored Mar 10, 2018
1 parent 43c5f9d commit da077c9
Showing 1 changed file with 102 additions and 96 deletions.
198 changes: 102 additions & 96 deletions ParamAP.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,7 +3,7 @@

'''
ParamAP.py (parametrization of sinoatrial myocyte action potentials)
Copyright (C) 2017 Christian Rickert <christian.rickert@ucdenver.edu>
Copyright (C) 2018 Christian Rickert <christian.rickert@ucdenver.edu>
This program is free software; you can redistribute it and/or
modify it under the terms of the GNU General Public License
Expand Down Expand Up @@ -71,6 +71,18 @@ def askboolean(dlabel="custom boolean", dval=True):
continue


def askext(dlabel="custom extension", dext='atf'):
"""Returns a file extention provided by the user."""
while True:
uext = str(input("Enter " + dlabel + " [" + dext + "]: ")).lower() or dext
if uext not in ["dat", "log", "pdf"] and len(uext) == 3:
print(uext + "\n")
return uext # break
else:
print("Invalid file extension!\n")
continue


def askunit(dlabel="custom unit", daxis='', dunit=''):
"""Returns a unit provided by the user."""
while True:
Expand Down Expand Up @@ -191,35 +203,40 @@ def mpp_setup(title='Plot title', xlabel='Time [ ]', ylabel='Voltage [ ]'):

def readfile(inputfile='name'):
"""Extracts the xy pairs from an ASCII raw file and stores its values into a numpy array."""
defux = ["ms", "s"]
defuy = ["mV", "V"]
inpunits = False
with open(inputfile, 'r') as headerfile:
line = 1 # header line
with open(inputfile, 'r') as datafile:
line = 1
inpuxy = [] # header might be missing
while line <= 25: # arbitrary Clampfit header limit for ATF
tmp_header = headerfile.readline()
if tmp_header.startswith("\""):
headerline = datafile.readline()
if headerline.startswith("\""):
inpuxy = str(headerline).split() # last line of header contains units
skipline = line
lastline = tmp_header
if not inpuxy:
skipline = 0
line += 1
lastline = str(lastline).split() # contains units
try:
inpx = lastline[1][1:-2]
inpy = lastline[4][1:-2]
inpux = inpuxy[1][1:-2]
inpuy = inpuxy[4][1:-2]
except IndexError: # missing header
inpx, inpy = "", ""
inpux, inpuy = str(defux)[1:-1], str(defuy)[1:-1]
else: # header found
if inpx in ["ms", "s"] and inpy in ["mV", "V"]:
if inpux in defux and inpuy in defuy:
inpunits = True
inp_xy = np.loadtxt(inputfile, dtype='float64', delimiter='\t', skiprows=skipline, unpack=True) # slower than np.genfromtxt or native python, but uses less main memory at peak
return inp_xy, inpunits, inpx, inpy
datafile.seek(0) # reset the file index to the first byte
inp_xy = np.loadtxt(datafile, dtype='float64', delimiter='\t', skiprows=skipline, unpack=True) # slower than np.genfromtxt or native python, but uses less main memory at peak
return inp_xy, inpunits, inpux, inpuy


# main routine

AUTHOR = "Copyright (C) 2017 Christian Rickert"
AUTHOR = "Copyright (C) 2018 Christian Rickert"
SEPARBOLD = 79*'='
SEPARNORM = 79*'-'
SOFTWARE = "ParamAP"
VERSION = "version 1.0," # (2017-07-06)
VERSION = "version 1.1," # (2018-03-10)
WORKDIR = SOFTWARE # working directory for parameterization
print('{0:^79}'.format(SEPARBOLD) + os.linesep)
GREETER = '{0:<{w0}}{1:<{w1}}{2:<{w2}}'.format(SOFTWARE, VERSION, AUTHOR, w0=len(SOFTWARE)+1, w1=len(VERSION)+1, w2=len(AUTHOR)+1)
Expand All @@ -246,10 +263,13 @@ def readfile(inputfile='name'):
WORKPATH = os.path.abspath(WORKDIR)
if not os.path.exists(WORKPATH):
os.mkdir(WORKPATH)
print("FOLDER:\t" + WORKPATH)
print("FOLDER:\t" + WORKPATH + "\n")

FILE = 0 # file
ATFFILES = getfiles(path=WORKDIR, pattern='*.atf')
EXTENSION = askext(dlabel="custom file type", dext='atf') # file extension used to filter files in working directory
if SERIES:
AVG_FRAME = askvalue(dlabel="analysis frame time", dval=5000.0, dunit=' ms') # time interval for series analysis (ms)
ATFFILES = getfiles(path=WORKDIR, pattern=("*." + EXTENSION))
for ATFFILE in ATFFILES: # iterate through files
name = os.path.splitext(os.path.split(ATFFILE)[1])[0]
print('{0:^79}'.format(SEPARNORM))
Expand All @@ -259,7 +279,6 @@ def readfile(inputfile='name'):
ap_hwd = 250.0 # maximum acceptable ap half width (ms)
ap_max = 50.0 # maximum acceptable ap value (mV)
ap_min = -10.0 # minimum acceptable ap value (mV)
avg_frame = 5000.0 # time interval for series analysis (ms)
mdp_max = -50.0 # maximum acceptable mdp value (mV)
mdp_min = -90.0 # minimum acceptable mdp value (mV)
wm_der = 1.0 # window multiplier for derivative filtering
Expand Down Expand Up @@ -293,19 +312,19 @@ def readfile(inputfile='name'):
sys.stdout.flush()

while True: # repeat data analysis for current file
try:
startpdf = True # overwrite existing file
segment = 0.0
while True: # time series analysis
startpdf = True # overwrite existing file
segment = 0.0
while True: # time series analysis

try:
# create raw data plot
sys.stdout.write(">> PLOTTING... ")
sys.stdout.flush()
mpp_setup(title="Raw data: " + name, xlabel='Time (ms)', ylabel='Voltage (mV)')
mpp.plot(raw_x, raw_y, '0.75') # raw data (grey line)

if startpdf:
pdf_file = mpbp.PdfPages(os.path.join(WORKDIR, name + ".pdf")) # multi-pdf file
pdf_file = mpbp.PdfPages(os.path.join(WORKDIR, name + ".pdf"), keep_empty=False) # multi-pdf file
startpdf = False # append existing file
mpp.tight_layout() # avoid label overlaps

Expand All @@ -326,8 +345,6 @@ def readfile(inputfile='name'):
if segment == 0.0: # initialize values
avg_start = askvalue(dlabel="analysis start time", dval=avg_start, dunit=' ms')
avg_stop = askvalue(dlabel="analysis stop time", dval=avg_stop, dunit=' ms')
if SERIES:
avg_frame = askvalue(dlabel="analysis frame time", dval=avg_frame, dunit=' ms')
ap_max = askvalue(dlabel="upper limit for maxima", dval=ap_max, dunit=' mV')
ap_min = askvalue(dlabel="lower limit for maxima", dval=ap_min, dunit=' mV')
mdp_max = askvalue(dlabel="upper limit for minima", dval=mdp_max, dunit=' mV')
Expand All @@ -342,8 +359,8 @@ def readfile(inputfile='name'):
mpp.clf() # clear canvas

if segment == 0.0: # set first frame
tmp_start = avg_start + (segment*avg_frame if SERIES else 0.0)
tmp_stop = (tmp_start + avg_frame) if SERIES else avg_stop
tmp_start = avg_start + (segment*AVG_FRAME if SERIES else 0.0)
tmp_stop = (tmp_start + AVG_FRAME) if SERIES else avg_stop
raw_i = np.argwhere((RAW_XY[0] >= tmp_start) & (RAW_XY[0] <= tmp_stop)).ravel()
raw_x = RAW_XY[0][raw_i[0]:raw_i[-1]+1]
raw_y = RAW_XY[1][raw_i[0]:raw_i[-1]+1]
Expand Down Expand Up @@ -567,7 +584,7 @@ def readfile(inputfile='name'):
else: # all other averages
i = 0 # array index
nw = (1.0/(n+1.0)) # new data weight
pw = (1.0-nw) # previous data weight
pw = (n/(n+1.0)) # previous data weight
for y in np.nditer(avg_y, op_flags=['readwrite']):
y[...] = pw*y + nw*tmp_y[i] # integrate raw data into averaged data
i += 1
Expand Down Expand Up @@ -757,16 +774,16 @@ def readfile(inputfile='name'):
# data summary
sys.stdout.write(">> SAVING... ")
sys.stdout.flush()
avg_file = os.path.join(WORKDIR, name + "_" + timestamp + "_avg.txt")
avg_file = os.path.join(WORKDIR, name + "_" + timestamp + "_avg.dat")
uheader = "" +\
"Analysis start time: " + 3*"\t" + str(tmp_start) + " ms\n" + \
"Analysis stop time:" + 3*"\t" + str(tmp_stop) + " ms\n" + \
"Upper limit for maxima:" + 2*"\t" + str(ap_max) + " mV\n" + \
"Lower limit for maxima:" + 2*"\t" + str(ap_min) + " mV\n" + \
"Upper limit for minima:" + 2*"\t" + str(mdp_max) + " mV\n" + \
"Lower limit for minima:" + 2*"\t" + str(mdp_min) + " mV\n" + \
"Maximum peak half width:" + 2*"\t" + str(ap_hwd) + " ms\n" + \
"Minimum peak amplitude:" + 2*"\t" + str(ap_amp) + " mV\n" + \
"Analysis start time: " + 4*"\t" + str(tmp_start) + " ms\n" + \
"Analysis stop time:" + 4*"\t" + str(tmp_stop) + " ms\n" + \
"Upper limit for maxima:" + 3*"\t" + str(ap_max) + " mV\n" + \
"Lower limit for maxima:" + 3*"\t" + str(ap_min) + " mV\n" + \
"Upper limit for minima:" + 3*"\t" + str(mdp_max) + " mV\n" + \
"Lower limit for minima:" + 3*"\t" + str(mdp_min) + " mV\n" + \
"Maximum peak half width:" + 3*"\t" + str(ap_hwd) + " ms\n" + \
"Minimum peak amplitude:" + 3*"\t" + str(ap_amp) + " mV\n" + \
"Running average window size:" + 2*"\t" + str(runavg) + "\n" + \
"Window multiplier for derivative:" + "\t" + str(wm_der) + "\n" + \
"Window multiplier for maxima:" + 2*"\t" + str(wm_max) + "\n" + \
Expand All @@ -775,7 +792,7 @@ def readfile(inputfile='name'):
np.savetxt(avg_file, np.column_stack((avg_x, avg_y, avgf_y)), fmt='%e', delimiter='\t', header=uheader)
mpp.tight_layout()
mpp.savefig(pdf_file, format='pdf', dpi=600)
sum_file = os.path.join(WORKDIR, "ParamAP.txt")
sum_file = os.path.join(WORKDIR, "ParamAP.log")
newfile = not bool(os.path.exists(sum_file))
with open(sum_file, 'a') as targetfile: # append file
if newfile: # write header
Expand All @@ -791,69 +808,58 @@ def readfile(inputfile='name'):
if not AUTORUN:
mpp.show()

if SERIES: # check for next frame
if tmp_stop + avg_frame <= avg_stop:
segment += 1.0
tmp_start = avg_start + (segment*avg_frame if SERIES else 0.0) # prepare next frame for preview
tmp_stop = (tmp_start + avg_frame) if SERIES else avg_stop
raw_i = np.argwhere((RAW_XY[0] >= tmp_start) & (RAW_XY[0] <= tmp_stop)).ravel()
raw_x = RAW_XY[0][raw_i[0]:raw_i[-1]+1]
raw_y = RAW_XY[1][raw_i[0]:raw_i[-1]+1]
print()
print("RUN:\t" + str(int(segment + 1)) + "/" + str(math.floor((avg_stop-avg_start)/avg_frame)))
print()
continue
else: # not enough data left in file
break
else: # no time series analysis
break

if not AUTORUN: # check for next file
print()
nextfile = askboolean("Continue with next file?", True)
if nextfile:
except IndexError as ierr: # check running average and window multiplier
sys.stdout.write("\n" + 9*"\t" + " [ER]")
print("\r ## Run failed. Detection of extrema or threshold failed.")
except PermissionError as perr: # file already opened or storage read-only
sys.stdout.write("\n" + 9*"\t" + " [ER]")
print("\r ## Run failed. File access denied by system.")
except Warning as werr: # increase averaging window time
sys.stdout.write("\n" + 9*"\t" + " [ER]")
print("\r ## Run failed. Identification of action potentials failed.")
except Exception as uerr: # unknown
sys.stdout.write("\n" + 9*"\t" + " [UN]")
print("\r ## Run failed. Error was: {0}".format(uerr) + ".")
except KeyboardInterrupt as kerr: # user canceled this file
sys.stdout.write("\n" + 9*"\t" + " [KO]")
print("\r ## Run skipped. Canceled by user.")
if SERIES: # check for next frame
if tmp_stop + AVG_FRAME <= avg_stop:
segment += 1.0
tmp_start = avg_start + segment*AVG_FRAME # prepare next frame for preview
tmp_stop = tmp_start + AVG_FRAME
raw_i = np.argwhere((RAW_XY[0] >= tmp_start) & (RAW_XY[0] <= tmp_stop)).ravel()
raw_x = RAW_XY[0][raw_i[0]:raw_i[-1]+1]
raw_y = RAW_XY[1][raw_i[0]:raw_i[-1]+1]
print()
print("RUN:\t" + str(int(segment + 1)) + "/" + str(math.floor((avg_stop-avg_start)/AVG_FRAME)))
print()
else: # not enough data left in file
break
else: # re-run current file
raw_x = RAW_XY[0] # recover original rawdata
raw_y = RAW_XY[1]
continue
else: # autorun
else: # no time series analysis
break

except IndexError as ierr: # check running average and window multiplier
sys.stdout.write("\n" + 9*"\t" + " [ER]")
print("\r ## Run failed. Detection of extrema or threshold failed.")
if not AUTORUN:
continue
except PermissionError as perr: # file already opened or storage read-only
sys.stdout.write("\n" + 9*"\t" + " [ER]")
print("\r ## Run failed. File access denied by system.")
if not AUTORUN:
continue
except Warning as werr: # increase averaging window time
sys.stdout.write("\n" + 9*"\t" + " [ER]")
print("\r ## Run failed. Identification of action potentials failed.")
if not AUTORUN:
continue
except Exception as uerr: # unknown
sys.stdout.write("\n" + 9*"\t" + " [UN]")
print("\r ## Run failed. Error was: {0}".format(uerr) + ".")
if not AUTORUN:
if not AUTORUN: # check for next file
print()
nextfile = askboolean("Continue with next file?", True)
if nextfile:
break
else: # re-run current file
raw_x = RAW_XY[0] # recover original rawdata
raw_y = RAW_XY[1]
continue
except KeyboardInterrupt as kerr: # user canceled this file
sys.stdout.write("\n" + 9*"\t" + " [KO]")
print("\r ## Run skipped. Canceled by user.")
else: # autorun
break
finally: # both with or without exception
# clear memory and canvas
FILE += 1
sys.stdout.write(">> CLEANING... ")
sys.stdout.flush()
pdf_file.close() # close multi-pdf file
mpp.clf()
gc.collect() # start garbage collection to prevent memory fragmentation
sys.stdout.write(8*"\t" + " [OK]\n")
sys.stdout.flush()

# housekeeping after each file
FILE += 1
sys.stdout.write(">> CLEANING... ")
sys.stdout.flush()
pdf_file.close() # close multi-pdf file and remove if empty
mpp.clf() # clear canvas
gc.collect() # start garbage collection to prevent memory fragmentation
sys.stdout.write(8*"\t" + " [OK]\n")
sys.stdout.flush()

# print summary
print('{0:^79}'.format(SEPARBOLD))
Expand Down

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