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Code Issues Releases Wiki Activity

Embedded plots into GUI

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This commit is contained in:
Alexander Minges 2015-01-30 20:14:56 +01:00
parent 926fb01502
commit cf75c8ee09
7 changed files with 446 additions and 349 deletions
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2
.gitignore vendored
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@ -21,7 +21,7 @@ var/
*.egg-info/
.installed.cfg
*.egg
.idea
.idea/
# PyInstaller
# Usually these files are written by a python script from a template

583
pydsf.py
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@ -1,6 +1,7 @@
#! /usr/bin/env python2
# -*- coding: utf-8 -*-
import csv
import multiprocessing as mp
try:
import matplotlib as mpl
@ -23,54 +24,56 @@ except ImportError:
raise ImportError('----- NumPy must be installed. -----')
try:
from scipy.signal import filtfilt, butter
from scipy.signal import filtfilt, butter
from scipy import interpolate
from scipy import optimize
except ImportError:
raise ImportError('----- SciPy must be installed. -----')
class Well:
def __init__(self, owner):
def __init__(self, owner):
self.owner = owner
self.name = None
self.raw = np.zeros(self.owner.reads, dtype=np.float)
self.filtered = np.zeros(self.owner.reads, dtype=np.float)
self.derivatives = np.zeros((4, self.owner.reads))
self.splines = {"raw": None,
"filtered": None,
"derivative1": None}
self.raw = np.zeros(self.owner.reads, dtype=np.float)
self.filtered = np.zeros(self.owner.reads, dtype=np.float)
self.derivatives = np.zeros((4, self.owner.reads))
self.splines = {"raw": None,
"filtered": None,
"derivative1": None}
self.tm = np.NaN
self.tm_sd = np.NaN
self.baseline_correction = owner.baseline_correction
self.baseline = None
def filter_raw(self):
"""
Apply a filter to the raw data
"""
b, a = butter(3, 0.3)
self.filtered = filtfilt(b, a, self.raw)
def calc_spline(self, y):
"""
Calculate a spline that represents the smoothed data points
"""
spline = interpolate.InterpolatedUnivariateSpline(self.owner.temprange, y)
return spline
return spline
def calc_derivatives(self, spline='filtered'):
for t in self.owner.temprange:
temp = self.splines[spline].derivatives(t)
for i in range(4):
self.derivatives[i, t - self.owner.t1] = temp[i]
self.derivatives[i, t - self.owner.t1] = temp[i]
def calc_baseline(self, y):
@staticmethod
def calc_baseline(y):
try:
baseline = peakutils.baseline(y)
return baseline
except:
return np.NaN
def calc_tm(self):
"""
Calculate the Tm of the well. Returns either the Tm or 'np.NaN'.
@ -83,7 +86,7 @@ class Well:
self.owner.denatured_wells.append(self)
if self.owner.tm_cutoff_low != self.owner.t1 or self.owner.tm_cutoff_high != self.owner.t1:
x = np.arange(self.owner.tm_cutoff_low, self.owner.tm_cutoff_high + 1, self.owner.dt, dtype=float)
x = np.arange(self.owner.tm_cutoff_low, self.owner.tm_cutoff_high + 1, self.owner.dt, dtype=float)
x = self.owner.temprange
y = self.derivatives[1]
@ -93,83 +96,85 @@ class Well:
try:
peak_indexes = peakutils.indexes(y, min_dist=len(x)) # calculate a rough estimate of peaks; set min_dist
# temperature range to only find one/the highest peak
tm = peakutils.interpolate(x, y, ind=peak_indexes)[0] # increase resolution by fitting gaussian function
# to peak
# temperature range to only find one/the highest peak
tm = peakutils.interpolate(x, y, ind=peak_indexes)[0] # increase resolution by fitting gaussian function
# to peak
except:
return np.NaN # In case of error, return no peak
try:
# Check if the peak is within cutoff range
if tm and tm >= self.owner.tm_cutoff_low and tm <= self.owner.tm_cutoff_high:
self.owner.denatured_wells.remove(self) # If everything is fine, remove the denatured flag
return tm # and return the Tm
else:
return np.NaN # otherwise, return NaN
# Check if the peak is within cutoff range
if tm and tm >= self.owner.tm_cutoff_low and tm <= self.owner.tm_cutoff_high:
self.owner.denatured_wells.remove(self) # If everything is fine, remove the denatured flag
return tm # and return the Tm
else:
return np.NaN # otherwise, return NaN
except:
return np.NaN # In case of error, return NaN
def is_denatured(self):
"""
Check if the well is denatured. Returns true if the well has been already flagged as
denatured, no Tm was found, or if the initial signal intensity is above a user definded
threshold.
"""
denatured = True # Assumption is that the well is denatured
if self in self.owner.denatured_wells: # check if the well is already flagged as denatured
return denatured # return true if it is
denatured = True # Assumption is that the well is denatured
if self in self.owner.denatured_wells: # check if the well is already flagged as denatured
return denatured # return true if it is
if self.tm and (self.tm <= self.owner.tm_cutoff_low or self.tm >= self.owner.tm_cutoff_high):
denatured = True
return denatured
for i in self.derivatives[1]: # Iterate over all points in the first derivative
if i > 0: # If a positive slope is found
denatured = False # set denatured flag to False
reads = int(round(self.owner.reads/10)) # How many values should be checked against the signal threshold:
# 1/10 of the total number of data point
read = 0 # Initialize running variable representing the current data point
for i in self.derivatives[1]: # Iterate over all points in the first derivative
if i > 0: # If a positive slope is found
denatured = False # set denatured flag to False
reads = int(round(self.owner.reads / 10)) # How many values should be checked against the signal threshold:
# 1/10 of the total number of data point
read = 0 # Initialize running variable representing the current data point
if not denatured:
for j in self.filtered: # Iterate over the filtered data
if self.owner.signal_threshold: # If a signal threshold was defined
if j > self.owner.signal_threshold and read <= reads: # iterate over 1/10 of all data points
# and check for values larger than the threshold.
denatured = True # Set flag to True if a match is found
for j in self.filtered: # Iterate over the filtered data
if self.owner.signal_threshold: # If a signal threshold was defined
if j > self.owner.signal_threshold and read <= reads: # iterate over 1/10 of all data points
# and check for values larger than the threshold.
denatured = True # Set flag to True if a match is found
print("{}: {}".format(self.name, j))
return denatured # and return
return denatured # and return
read += 1
return denatured
def analyze(self):
self.filter_raw()
self.splines["raw"] = self.calc_spline(self.raw)
self.splines["filtered"] = self.calc_spline(self.filtered)
self.calc_derivatives()
if self.baseline_correction:
self.baseline = self.calc_baseline(self.derivatives[1])
if self.is_denatured():
self.owner.denatured_wells.append(self)
self.splines["derivative1"] = self.calc_spline(self.derivatives[1])
self.tm = self.calc_tm()
if self.tm is None:
self.tm = np.NaN
class Experiment:
def __init__(self, type, gui=None, files=None, replicates=None, t1=25, t2=95, dt=1, cols=12, rows=8, cutoff_low=None, cutoff_high=None, signal_threshold=None, color_range=None, baseline_correction=False):
def __init__(self, type, gui=None, files=None, replicates=None, t1=25, t2=95, dt=1, cols=12, rows=8,
cutoff_low=None, cutoff_high=None, signal_threshold=None, color_range=None, baseline_correction=False):
self.replicates = replicates
self.cols = cols
self.rows = rows
self.t1 = t1
self.t2 = t2
self.dt = dt
self.temprange = np.arange(self.t1, self.t2 + 1, self.dt, dtype=float)
self.temprange = np.arange(self.t1, self.t2 + 1, self.dt, dtype=float)
self.reads = int(round((t2 + 1 - t1) / dt))
self.wellnum = self.cols * self.rows
self.files = files
@ -178,10 +183,10 @@ class Experiment:
self.max_tm = None
self.min_tm = None
self.replicates = None
self.gui=gui
self.gui = gui
self.signal_threshold = signal_threshold
self.avg_plate = None
self.baseline_correction=baseline_correction
self.baseline_correction = baseline_correction
if cutoff_low:
self.tm_cutoff_low = cutoff_low
else:
@ -193,48 +198,54 @@ class Experiment:
if color_range:
self.color_range = color_range
else:
self.color_range = (self.t1, self.t2)
self.color_range = None
self.plates = []
i = 1
for file in files:
plate = Plate(type=self.type, owner=self, filename=file, t1=self.t1, t2=self.t2, dt=self.dt, cols=self.cols, rows=self.rows, cutoff_low=self.tm_cutoff_low, cutoff_high=self.tm_cutoff_high, signal_threshold=self.signal_threshold, color_range=self.color_range)
plate = Plate(type=self.type, owner=self, filename=file, t1=self.t1, t2=self.t2, dt=self.dt, cols=self.cols,
rows=self.rows, cutoff_low=self.tm_cutoff_low, cutoff_high=self.tm_cutoff_high,
signal_threshold=self.signal_threshold, color_range=self.color_range)
plate.id = i
self.plates.append(plate)
i += 1
if len(files) > 1:
self.avg_plate = Plate(type=self.type, owner=self, filename=None, t1=self.t1, t2=self.t2, dt=self.dt, cols=self.cols, rows=self.rows, cutoff_low=self.tm_cutoff_low, cutoff_high=self.tm_cutoff_high, signal_threshold=self.signal_threshold, color_range=self.color_range)
self.avg_plate = Plate(type=self.type, owner=self, filename=None, t1=self.t1, t2=self.t2, dt=self.dt,
cols=self.cols, rows=self.rows, cutoff_low=self.tm_cutoff_low,
cutoff_high=self.tm_cutoff_high, signal_threshold=self.signal_threshold,
color_range=self.color_range)
self.avg_plate.id = 'average'
def analyze(self):
for plate in self.plates:
plate.analyze(gui=self.gui)
if len(self.plates) > 1:
#self.tm_replicates = np.zeros( self.wellnum, dtype=float )
#self.tm_replicates_sd = np.zeros( self.wellnum, dtype=float )
# self.tm_replicates = np.zeros( self.wellnum, dtype=float )
# self.tm_replicates_sd = np.zeros( self.wellnum, dtype=float )
for i in range(self.wellnum):
tmp = []
tmp = []
for plate in self.plates:
tm = plate.wells[i].tm
self.avg_plate.wells[i].name = plate.wells[i].name
if plate.wells[i] not in plate.denatured_wells:
tmp.append(tm)
if len(tmp) > 0:
#self.avg_plate.wells[i].tm = (sum(tmp)/len(tmp))
# self.avg_plate.wells[i].tm = (sum(tmp)/len(tmp))
self.avg_plate.wells[i].tm = np.mean(tmp)
self.avg_plate.wells[i].tm_sd = np.std(tmp)
#self.tm_replicates[i] = (sum(tmp)/len(tmp))
# self.tm_replicates[i] = (sum(tmp)/len(tmp))
else:
self.avg_plate.denatured_wells.append(self.avg_plate.wells[i])
class Plate:
def __init__(self, type, owner, id=None, filename=None, replicates=None, t1=None, t2=None, dt=None, cols=12, rows=8, cutoff_low=None, cutoff_high=None, signal_threshold=None, color_range=None):
def __init__(self, type, owner, id=None, filename=None, replicates=None, t1=None, t2=None, dt=None, cols=12, rows=8,
cutoff_low=None, cutoff_high=None, signal_threshold=None, color_range=None):
self.cols = cols
self.rows = rows
self.owner = owner
@ -250,7 +261,7 @@ class Plate:
self.dt = dt
else:
self.dt = owner.dt
self.temprange = np.arange(self.t1, self.t2 + 1, self.dt, dtype=float)
self.temprange = np.arange(self.t1, self.t2 + 1, self.dt, dtype=float)
self.reads = int(round((t2 + 1 - t1) / dt))
self.wellnum = self.cols * self.rows
self.filename = filename
@ -274,28 +285,26 @@ class Plate:
self.color_range = color_range
else:
self.color_range = None
self.denatured_wells = []
self.tms = []
for i in range(self.wellnum):
well = Well(owner = self)
self.wells.append(well)
#self.analyze()
for i in range(self.wellnum):
well = Well(owner=self)
self.wells.append(well)
def analytikJena(self):
"""
Data processing for Analytik Jena qTower 2.0 export files
"""
with open(self.filename, 'r') as f:
reader = csv.reader(f, delimiter=';', quoting=csv.QUOTE_NONE)
with open(self.filename, 'r') as f:
reader = csv.reader(f, delimiter=';', quoting=csv.QUOTE_NONE)
i = 0
for row in reader:
temp = np.zeros(self.reads, dtype=float)
for read in range(self.reads+1):
temp = np.zeros(self.reads, dtype=float)
for read in range(self.reads + 1):
if read > 0:
try:
temp[read - 1] = row[read]
@ -306,15 +315,15 @@ class Plate:
self.wells[i].raw = temp
i += 1
def analyze(self, gui=None):
def analyze(self, gui=None):
try:
# Try to access data file in the given path
with open(self.filename) as f: pass
with open(self.filename) as f:
pass
except IOError as e:
# If the file is not found, or not accessible: abort
print('Error accessing file: {}'.format(e))
if self.type == 'Analytik Jena qTOWER 2.0/2.2':
self.analytikJena()
if gui:
@ -322,23 +331,23 @@ class Plate:
else:
# Raise exception, if the instrument's name is unknown
raise NameError('Unknown instrument type: {}'.format(self.type))
for well in self.wells:
well.analyze()
if gui:
update_progress_bar(gui.pb, 15)
self.tms.append(well.tm)
if self.replicates:
if self.replicates == 'rows':
print("rows")
if self.replicates == 'cols':
print("cols")
#print(self.tms)
# print(self.tms)
self.max_tm = max(self.tms)
self.min_tm = min(self.tms)
def write_tm_table(self, filename):
with open(filename, 'w') as f:
f.write('#{:<4s}{:>13s}\n'.format('ID', '"Tm [°C]"'))
@ -347,7 +356,7 @@ class Plate:
f.write('{:<5s}{:>12s}\n'.format(well.name, 'NaN'))
else:
f.write('{:<5s}{:>12s}\n'.format(well.name, str(well.tm)))
def write_avg_tm_table(self, filename):
with open(filename, 'w') as f:
f.write('#{:<4s}{:>13s}{:>13s}\n'.format('"ID"', '"Tm [°C]"', '"SD"'))
@ -356,7 +365,7 @@ class Plate:
f.write('{:<5s}{:>12s}{:>12s}\n'.format(well.name, 'NaN', 'NaN'))
else:
f.write('{:<5s}{:>12s}{:>12s}\n'.format(well.name, str(well.tm), str(well.tm_sd)))
def write_raw_table(self, filename):
with open(filename, 'w') as f:
f.write('#"Raw data"\n')
@ -364,16 +373,16 @@ class Plate:
for well in self.wells:
f.write('{:>15s}'.format(well.name))
f.write('\n')
i = 0
for t in self.temprange:
f.write('{:<10s}'.format(str(t)))
for well in self.wells:
d = well.raw[i]
f.write('{:>-15.3f}'.format(float(np.round(d, decimals=3))))
f.write('{:>-15.3f}'.format(float(np.round(d, decimals=3))))
f.write('\n')
i += 1
def write_filtered_table(self, filename):
with open(filename, 'w') as f:
f.write('#"Filtered data" \n')
@ -381,16 +390,16 @@ class Plate:
for well in self.wells:
f.write('{:>15s}'.format(well.name))
f.write('\n')
i = 0
for t in self.temprange:
f.write('{:<10s}'.format(str(t)))
for well in self.wells:
d = well.filtered[i]
f.write('{:>-15.3f}'.format(float(np.round(d, decimals=3))))
f.write('{:>-15.3f}'.format(float(np.round(d, decimals=3))))
f.write('\n')
i += 1
def write_derivative_table(self, filename):
with open(filename, 'w') as f:
f.write('#"Derivative dI/dT"\n')
@ -398,13 +407,13 @@ class Plate:
for well in self.wells:
f.write('{:>15s}'.format(well.name))
f.write('\n')
i = 0
for t in self.temprange:
f.write('{:<10s}'.format(str(t)))
for well in self.wells:
d = well.derivatives[1][i]
f.write('{:>-15.3f}'.format(float(np.round(d, decimals=3))))
f.write('{:>-15.3f}'.format(float(np.round(d, decimals=3))))
f.write('\n')
i += 1
@ -412,209 +421,185 @@ class Plate:
def write_baseline_corrected_table(self, filename):
raise NotImplementedError
def update_progress_bar(bar, value):
bar.setValue(value)
def plot_tm_heatmap_average(experiment, gui=None):
"""
Plot Tm heatmap (Fig. 1)
"""
x = 1 # Position in columns
y = 1 # Position in rows
x_values = [] # Array holding the columns
y_values = [] # Array holding the rows
c_values = [] # Array holding the color values aka Tm
# c = well.tm # If not, set color to Tm
# if c < experiment.tm_cutoff_low: # Check if Tm is lower that the cutoff
# c = experiment.tm_cutoff_low # If it is, set color to cutoff
# elif c > experiment.tm_cutoff_high: # Check if Tm is higher that the cutoff
# c = experiment.tm_cutoff_high # If it is, set color to cutoff
# else: # If the plate is denatured
# c = experiment.tm_cutoff_low # Set its color to the low cutoff
for c in experiment.tm_replicates:
class PlotResults():
x_values.append(x) # Add values to the respective arrays
y_values.append(y)
c_values.append(c)
x += 1 # Increase column by one
if x > experiment.cols: # If maximum column per row is reached
x = 1 # reset column to one
y += 1 # and increase row by one
def __init__(self, experiment):
self.experiment = experiment
fig1 = plt.figure() # new figure
ax1 = fig1.add_subplot(1, 1, 1) # A single canvas
ax1.autoscale(tight=True) # Scale plate size
ax1.xaxis.set_major_locator(ticker.MaxNLocator(experiment.cols + 1)) # n columns
ax1.yaxis.set_major_locator(ticker.MaxNLocator(experiment.rows + 1)) # n rows
if experiment.color_range:
cax = ax1.scatter(x_values, y_values, s=300, c=c_values, marker='s', vmin=experiment.color_range[0], vmax=experiment.color_range[1]) # plot wells and color using the colormap
else:
cax = ax1.scatter(x_values, y_values, s=300, c=c_values, marker='s') # plot wells and color using the colormap
ax1.invert_yaxis() # invert y axis to math plate layout
cbar = fig1.colorbar(cax) # show colorbar
ax1.set_xlabel('Columns') # set axis and colorbar label
ax1.set_ylabel('Rows')
ax1.set_title('$T_m$ heatmap (average)')
cbar.set_label(u"Temperature [°C]")
def plot_tm_heatmap_single(plate, gui=None):
"""
Plot Tm heatmap (Fig. 1)
"""
x = 1 # Position in columns
y = 1 # Position in rows
x_values = [] # Array holding the columns
y_values = [] # Array holding the rows
c_values = [] # Array holding the color values aka Tm
dx_values = []
dy_values = []
dc_values = []
for well in plate.wells: # Iterate over all wells
if well not in plate.denatured_wells: # Check if well is denatured (no Tm found)
c = well.tm # If not, set color to Tm
if c < plate.tm_cutoff_low: # Check if Tm is lower that the cutoff
c = plate.tm_cutoff_low # If it is, set color to cutoff
elif c > plate.tm_cutoff_high: # Check if Tm is higher that the cutoff
c = plate.tm_cutoff_high # If it is, set color to cutoff
else: # If the plate is denatured
c = plate.tm_cutoff_low # Set its color to the low cutoff
dx_values.append(x)
dy_values.append(y)
x_values.append(x) # Add values to the respective arrays
y_values.append(y)
c_values.append(c)
x += 1 # Increase column by one
if x > plate.cols: # If maximum column per row is reached
x = 1 # reset column to one
y += 1 # and increase row by one
def plot_tm_heatmap_single(self, plate, widget):
"""
Plot Tm heatmap (Fig. 1)
"""
x = 1 # Position in columns
y = 1 # Position in rows
x_values = [] # Array holding the columns
y_values = [] # Array holding the rows
c_values = [] # Array holding the color values aka Tm
dx_values = []
dy_values = []
dc_values = []
canvas = widget.canvas
canvas.clear()
for well in plate.wells: # Iterate over all wells
if well not in plate.denatured_wells: # Check if well is denatured (no Tm found)
c = well.tm # If not, set color to Tm
if c < plate.tm_cutoff_low: # Check if Tm is lower that the cutoff
c = plate.tm_cutoff_low # If it is, set color to cutoff
elif c > plate.tm_cutoff_high: # Check if Tm is higher that the cutoff
c = plate.tm_cutoff_high # If it is, set color to cutoff
else: # If the plate is denatured
c = plate.tm_cutoff_low # Set its color to the low cutoff
dx_values.append(x)
dy_values.append(y)
x_values.append(x) # Add values to the respective arrays
y_values.append(y)
c_values.append(c)
x += 1 # Increase column by one
if x > plate.cols: # If maximum column per row is reached
x = 1 # reset column to one
y += 1 # and increase row by one
fig1 = plt.figure() # new figure
ax1 = fig1.add_subplot(1, 1, 1) # A single canvas
ax1.autoscale(tight=True) # Scale plate size
ax1.xaxis.set_major_locator(ticker.MaxNLocator(plate.cols + 1)) # n columns
ax1.yaxis.set_major_locator(ticker.MaxNLocator(plate.rows + 1)) # n rows
if plate.color_range:
cax = ax1.scatter(x_values, y_values, s=305, c=c_values, marker='s', vmin=plate.color_range[0], vmax=plate.color_range[1]) # plot wells and color using the colormap
else:
cax = ax1.scatter(x_values, y_values, s=305, c=c_values, marker='s') # plot wells and color using the colormap
cax2 = ax1.scatter(dx_values, dy_values, s=80, c='white', marker='x', linewidths=(1.5,))
ax1.invert_yaxis() # invert y axis to math plate layout
cbar = fig1.colorbar(cax) # show colorbar
ax1.set_xlabel('Columns') # set axis and colorbar label
ax1.set_ylabel('Rows')
if str(plate.id) == 'average':
title = '$T_m$ heatmap (average)'
else:
title = '$T_m$ heatmap (plate #{})'.format(str(plate.id))
ax1.set_title(title)
cbar.set_label(u"Temperature [°C]")
#magenta_patch = mpatches.Patch(color='magenta', label='Denatured')
#fig1.legend([magenta_patch], 'Denatured', loc='lower right', bbox_to_anchor=[0.5, 0.5])
# if gui:
# update_progress_bar(gui.pb, 50)
def plot_derivative(plate, gui=None):
"""
Plot derivatives (Fig. 2)
"""
fig2 = plt.figure() # new figure
fig2.suptitle('Individual Derivatives (plate #{})'.format(str(plate.id))) # set title
for plot_num in range(1, plate.wellnum + 1): # iterate over all wells
well = plate.wells[plot_num - 1] # get single well based on current plot number
ax = fig2.add_subplot(plate.rows, plate.cols, plot_num) # add new subplot
ax.autoscale(tight=True) # scale to data
ax.set_title(well.name, size='xx-small') # set title of current subplot to well identifier
if well in plate.denatured_wells:
ax.patch.set_facecolor('#FFD6D6')
if plot_num == plate.wellnum - plate.cols + 1: # add axis label to the subplot in the bottom left corner of the figure
ax.set_xlabel(u'T [°C]', size='xx-small')
ax.set_ylabel('dI/dT', size='xx-small')
x = plate.temprange # set values for the x axis to the given temperature range
if well.baseline_correction:
print(well.baseline)
y = well.derivatives[1] - well.baseline
fig1 = canvas.fig # new figure
ax1 = fig1.add_subplot(1, 1, 1) # A single canvas
ax1.autoscale(tight=True) # Scale plate size
ax1.xaxis.set_major_locator(ticker.MaxNLocator(plate.cols + 1)) # n columns
ax1.yaxis.set_major_locator(ticker.MaxNLocator(plate.rows + 1)) # n rows
if plate.color_range:
cax = ax1.scatter(x_values, y_values, s=305, c=c_values, marker='s', vmin=plate.color_range[0],
vmax=plate.color_range[1]) # plot wells and color using the colormap
else:
y = well.derivatives[1] # grab y values from the first derivative of the well
ax.xaxis.set_major_locator(ticker.MaxNLocator(4)) # only show three tickmarks on both axes
ax.yaxis.set_major_locator(ticker.MaxNLocator(4))
if well not in plate.denatured_wells: # check if well is denatured (without determined Tm)
tm = well.tm # if not, grab its Tm
cax = ax1.scatter(x_values, y_values, s=305, c=c_values, marker='s') # plot wells and color using the colormap
cax2 = ax1.scatter(dx_values, dy_values, s=80, c='white', marker='x', linewidths=(1.5,))
ax1.invert_yaxis() # invert y axis to math plate layout
cbar = fig1.colorbar(cax) # show colorbar
ax1.set_xlabel('Columns') # set axis and colorbar label
ax1.set_ylabel('Rows')
if str(plate.id) == 'average':
title = '$T_m$ heatmap (average)'
else:
tm = np.NaN # else set Tm to np.NaN
if tm:
ax.axvline(x=tm) # plot vertical line at the Tm
ax.axvspan(plate.t1, plate.tm_cutoff_low, facecolor='0.8', alpha=0.5) # shade lower cutoff area
ax.axvspan(plate.tm_cutoff_high, plate.t2, facecolor='0.8', alpha=0.5) # shade higher cutoff area
for label in ax.get_xticklabels() + ax.get_yticklabels(): # set fontsize for all tick labels to xx-small
label.set_fontsize('xx-small')
cax = ax.plot(x, y) # plot data to the current subplot
# if gui:
# update_progress_bar(gui.pb, 75)
def plot_raw(plate, gui=None):
"""
Plot raw data (Fig. 3)
"""
fig3 = plt.figure() # new figure
fig3.suptitle('Raw Data (plate #{})'.format(str(plate.id))) # set title
for plot_num in range(1, plate.wellnum + 1): # iterate over all wells
well = plate.wells[plot_num - 1] # get single well based on current plot number
ax = fig3.add_subplot(plate.rows, plate.cols, plot_num) # add new subplot
ax.autoscale(tight=True) # scale to data
ax.set_title(well.name, size='xx-small') # set title of current subplot to well identifier
if well in plate.denatured_wells:
ax.patch.set_facecolor('#FFD6D6')
if plot_num == plate.wellnum - plate.cols + 1: # add axis label to the subplot in the bottom left corner of the figure
ax.set_xlabel(u'T [°C]', size='xx-small')
ax.set_ylabel('I', size='xx-small')
x = plate.temprange # set values for the x axis to the given temperature range
y = well.raw # grab y values from the raw data of the well
ax.xaxis.set_major_locator(ticker.MaxNLocator(4)) # only show three tickmarks on both axes
ax.yaxis.set_major_locator(ticker.MaxNLocator(4))
ax.axvspan(plate.t1, plate.tm_cutoff_low, facecolor='0.8', alpha=0.5) # shade lower cutoff area
ax.axvspan(plate.tm_cutoff_high, plate.t2, facecolor='0.8', alpha=0.5) # shade higher cutoff area
for label in ax.get_xticklabels() + ax.get_yticklabels(): # set fontsize for all tick labels to xx-small
label.set_fontsize('xx-small')
cax = ax.plot(x, y) # plot data to the current subplot
# if gui:
# update_progress_bar(gui.pb, 100)
# gui.pb.hide()
title = '$T_m$ heatmap (plate #{})'.format(str(plate.id))
ax1.set_title(title)
cbar.set_label(u"Temperature [°C]")
def plot(experiment, gui=None):
for plate in experiment.plates:
plot_raw(plate)
plot_derivative(plate)
plot_tm_heatmap_single(plate)
if len(experiment.plates) > 1:
plot_tm_heatmap_single(experiment.avg_plate)
#plot_tm_heatmap_average(experiment)
plt.show()
canvas.draw()
def plot_derivative(self, plate, widget):
"""
Plot derivatives (Fig. 2)
"""
canvas = widget.canvas
canvas.clear()
fig2 = canvas.fig # new figure
fig2.suptitle('Individual Derivatives (plate #{})'.format(str(plate.id))) # set title
for plot_num in range(1, plate.wellnum + 1): # iterate over all wells
well = plate.wells[plot_num - 1] # get single well based on current plot number
ax = fig2.add_subplot(plate.rows, plate.cols, plot_num) # add new subplot
ax.autoscale(tight=True) # scale to data
ax.set_title(well.name, size='xx-small') # set title of current subplot to well identifier
if well in plate.denatured_wells:
ax.patch.set_facecolor('#FFD6D6')
if plot_num == plate.wellnum - plate.cols + 1: # add axis label to the subplot in the bottom left corner of the figure
ax.set_xlabel(u'T [°C]', size='xx-small')
ax.set_ylabel('dI/dT', size='xx-small')
x = plate.temprange # set values for the x axis to the given temperature range
if well.baseline_correction:
print(well.baseline)
y = well.derivatives[1] - well.baseline
else:
y = well.derivatives[1] # grab y values from the first derivative of the well
ax.xaxis.set_major_locator(ticker.MaxNLocator(4)) # only show three tickmarks on both axes
ax.yaxis.set_major_locator(ticker.MaxNLocator(4))
if well not in plate.denatured_wells: # check if well is denatured (without determined Tm)
tm = well.tm # if not, grab its Tm
else:
tm = np.NaN # else set Tm to np.NaN
if tm:
ax.axvline(x=tm) # plot vertical line at the Tm
ax.axvspan(plate.t1, plate.tm_cutoff_low, facecolor='0.8', alpha=0.5) # shade lower cutoff area
ax.axvspan(plate.tm_cutoff_high, plate.t2, facecolor='0.8', alpha=0.5) # shade higher cutoff area
for label in ax.get_xticklabels() + ax.get_yticklabels(): # set fontsize for all tick labels to xx-small
label.set_fontsize('xx-small')
cax = ax.plot(x, y) # plot data to the current subplot
canvas.draw()
def plot_raw(self, plate, widget):
"""
Plot raw data (Fig. 3)
"""
canvas = widget.canvas
canvas.clear()
fig3 = canvas.fig # new figure
fig3.suptitle('Raw Data (plate #{})'.format(str(plate.id))) # set title
for plot_num in range(1, plate.wellnum + 1): # iterate over all wells
well = plate.wells[plot_num - 1] # get single well based on current plot number
ax = fig3.add_subplot(plate.rows, plate.cols, plot_num) # add new subplot
ax.autoscale(tight=True) # scale to data
ax.set_title(well.name, size='xx-small') # set title of current subplot to well identifier
if well in plate.denatured_wells:
ax.patch.set_facecolor('#FFD6D6')
if plot_num == plate.wellnum - plate.cols + 1: # add axis label to the subplot in the bottom left corner of the figure
ax.set_xlabel(u'T [°C]', size='xx-small')
ax.set_ylabel('I', size='xx-small')
x = plate.temprange # set values for the x axis to the given temperature range
y = well.raw # grab y values from the raw data of the well
ax.xaxis.set_major_locator(ticker.MaxNLocator(4)) # only show three tickmarks on both axes
ax.yaxis.set_major_locator(ticker.MaxNLocator(4))
ax.axvspan(plate.t1, plate.tm_cutoff_low, facecolor='0.8', alpha=0.5) # shade lower cutoff area
ax.axvspan(plate.tm_cutoff_high, plate.t2, facecolor='0.8', alpha=0.5) # shade higher cutoff area
for label in ax.get_xticklabels() + ax.get_yticklabels(): # set fontsize for all tick labels to xx-small
label.set_fontsize('xx-small')
cax = ax.plot(x, y) # plot data to the current subplot
canvas.draw()
# def _plot_wrapper(self, plot, plate):
#
# if plot == 'raw':
# fig, ax = self._plot_raw(plate)
# elif plot == 'derivative':
# fig, ax = self._plot_derivative(plate)
# elif plot == 'tm_heatmap':
# fig, ax = self._plot_tm_heatmap_single(plate)
# else:
# raise NotImplementedError
# fig = None
# ax = None
# return (fig, ax)
#
# def plot_all(self):
#
# figures = []
#
# for plate in self.experiment.plates:
#
# figures.append(self._plot_wrapper('raw', plate))
# figures.append(self._plot_wrapper('derivative', plate))
# figures.append(self._plot_wrapper('tm_heatmap', plate))
#
# if len(self.experiment.plates) > 1:
# figures.append(self._plot_wrapper('tm_heatmap', self.experiment.avg_plate))
#
# return figures
#plate = Plate('/home/alex/Dokumente/Universitaet/Promotion/Denaturierung/26092012/26092012-MG.csv', type='analytikJena', cutoff_low=35.0, cutoff_high=60.0, signal_threshold=50000, color_range=(42, 50))
#plot(plate)

57
ui/Ui_mainwindow.py
View file

@ -2,7 +2,7 @@
# Form implementation generated from reading ui file 'mainwindow.ui'
#
# Created: Fri Jan 30 14:07:06 2015
# Created: Fri Jan 30 19:20:59 2015
# by: PyQt5 UI code generator 5.4
#
# WARNING! All changes made in this file will be lost!
@ -12,7 +12,7 @@ from PyQt5 import QtCore, QtGui, QtWidgets
class Ui_MainWindow(object):
def setupUi(self, MainWindow):
MainWindow.setObjectName("MainWindow")
MainWindow.resize(388, 642)
MainWindow.resize(808, 646)
MainWindow.setLocale(QtCore.QLocale(QtCore.QLocale.English, QtCore.QLocale.UnitedStates))
self.centralWidget = QtWidgets.QWidget(MainWindow)
self.centralWidget.setLocale(QtCore.QLocale(QtCore.QLocale.English, QtCore.QLocale.UnitedStates))
@ -24,11 +24,11 @@ class Ui_MainWindow(object):
self.groupBox_experiment.setFlat(False)
self.groupBox_experiment.setCheckable(False)
self.groupBox_experiment.setObjectName("groupBox_experiment")
self.gridLayout = QtWidgets.QGridLayout(self.groupBox_experiment)
self.gridLayout.setObjectName("gridLayout")
self.formLayout_3 = QtWidgets.QFormLayout(self.groupBox_experiment)
self.formLayout_3.setObjectName("formLayout_3")
self.label_instrument = QtWidgets.QLabel(self.groupBox_experiment)
self.label_instrument.setObjectName("label_instrument")
self.gridLayout.addWidget(self.label_instrument, 0, 0, 1, 1)
self.formLayout_3.setWidget(0, QtWidgets.QFormLayout.LabelRole, self.label_instrument)
self.comboBox_instrument = QtWidgets.QComboBox(self.groupBox_experiment)
sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Fixed)
sizePolicy.setHorizontalStretch(0)
@ -37,7 +37,7 @@ class Ui_MainWindow(object):
self.comboBox_instrument.setSizePolicy(sizePolicy)
self.comboBox_instrument.setObjectName("comboBox_instrument")
self.comboBox_instrument.addItem("")
self.gridLayout.addWidget(self.comboBox_instrument, 0, 1, 1, 1)
self.formLayout_3.setWidget(0, QtWidgets.QFormLayout.FieldRole, self.comboBox_instrument)
self.groupBox_data = QtWidgets.QGroupBox(self.groupBox_experiment)
self.groupBox_data.setEnabled(True)
self.groupBox_data.setObjectName("groupBox_data")
@ -72,7 +72,7 @@ class Ui_MainWindow(object):
self.listWidget_data.setAlternatingRowColors(True)
self.listWidget_data.setObjectName("listWidget_data")
self.gridLayout_4.addWidget(self.listWidget_data, 0, 0, 2, 1)
self.gridLayout.addWidget(self.groupBox_data, 1, 0, 1, 2)
self.formLayout_3.setWidget(1, QtWidgets.QFormLayout.SpanningRole, self.groupBox_data)
self.groupBox_temp = QtWidgets.QGroupBox(self.groupBox_experiment)
self.groupBox_temp.setEnabled(True)
self.groupBox_temp.setAutoFillBackground(False)
@ -108,7 +108,7 @@ class Ui_MainWindow(object):
self.doubleSpinBox_dt.setProperty("value", 1.0)
self.doubleSpinBox_dt.setObjectName("doubleSpinBox_dt")
self.formLayout.setWidget(2, QtWidgets.QFormLayout.FieldRole, self.doubleSpinBox_dt)
self.gridLayout.addWidget(self.groupBox_temp, 2, 0, 1, 1)
self.formLayout_3.setWidget(2, QtWidgets.QFormLayout.LabelRole, self.groupBox_temp)
self.groupBox_cutoff = QtWidgets.QGroupBox(self.groupBox_experiment)
self.groupBox_cutoff.setEnabled(True)
self.groupBox_cutoff.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter)
@ -135,7 +135,7 @@ class Ui_MainWindow(object):
self.doubleSpinBox_lower.setDecimals(1)
self.doubleSpinBox_lower.setObjectName("doubleSpinBox_lower")
self.formLayout_2.setWidget(1, QtWidgets.QFormLayout.FieldRole, self.doubleSpinBox_lower)
self.gridLayout.addWidget(self.groupBox_cutoff, 2, 1, 1, 1)
self.formLayout_3.setWidget(2, QtWidgets.QFormLayout.FieldRole, self.groupBox_cutoff)
self.groupBox_signal_threshold = QtWidgets.QGroupBox(self.groupBox_experiment)
self.groupBox_signal_threshold.setEnabled(True)
self.groupBox_signal_threshold.setCheckable(True)
@ -147,7 +147,7 @@ class Ui_MainWindow(object):
self.spinBox_signal_threshold.setMaximum(1000000)
self.spinBox_signal_threshold.setObjectName("spinBox_signal_threshold")
self.verticalLayout.addWidget(self.spinBox_signal_threshold)
self.gridLayout.addWidget(self.groupBox_signal_threshold, 3, 0, 1, 1)
self.formLayout_3.setWidget(3, QtWidgets.QFormLayout.LabelRole, self.groupBox_signal_threshold)
self.groupBox_cbar = QtWidgets.QGroupBox(self.groupBox_experiment)
self.groupBox_cbar.setEnabled(True)
self.groupBox_cbar.setCheckable(True)
@ -170,15 +170,31 @@ class Ui_MainWindow(object):
self.doubleSpinBox_cbar_end.setDecimals(1)
self.doubleSpinBox_cbar_end.setObjectName("doubleSpinBox_cbar_end")
self.formLayout_4.setWidget(2, QtWidgets.QFormLayout.FieldRole, self.doubleSpinBox_cbar_end)
self.gridLayout.addWidget(self.groupBox_cbar, 3, 1, 1, 1)
self.gridLayout_2.addWidget(self.groupBox_experiment, 0, 0, 1, 1)
self.buttonBox_process = QtWidgets.QDialogButtonBox(self.centralWidget)
self.formLayout_3.setWidget(3, QtWidgets.QFormLayout.FieldRole, self.groupBox_cbar)
self.buttonBox_process = QtWidgets.QDialogButtonBox(self.groupBox_experiment)
self.buttonBox_process.setStandardButtons(QtWidgets.QDialogButtonBox.Cancel|QtWidgets.QDialogButtonBox.Ok)
self.buttonBox_process.setObjectName("buttonBox_process")
self.gridLayout_2.addWidget(self.buttonBox_process, 1, 0, 1, 1)
self.formLayout_3.setWidget(4, QtWidgets.QFormLayout.FieldRole, self.buttonBox_process)
self.gridLayout_2.addWidget(self.groupBox_experiment, 0, 0, 1, 1)
self.tabWidget = QtWidgets.QTabWidget(self.centralWidget)
self.tabWidget.setObjectName("tabWidget")
self.tab_raw = MplWidget()
self.tab_raw.setObjectName("tab_raw")
self.tabWidget.addTab(self.tab_raw, "")
self.tab_derivative = MplWidget()
self.tab_derivative.setObjectName("tab_derivative")
self.tabWidget.addTab(self.tab_derivative, "")
self.tab_heatmap = MplWidget()
self.tab_heatmap.setObjectName("tab_heatmap")
self.tabWidget.addTab(self.tab_heatmap, "")
self.tab_heatmap_avg = MplWidget()
self.tab_heatmap_avg.setEnabled(False)
self.tab_heatmap_avg.setObjectName("tab_heatmap_avg")
self.tabWidget.addTab(self.tab_heatmap_avg, "")
self.gridLayout_2.addWidget(self.tabWidget, 0, 1, 1, 1)
MainWindow.setCentralWidget(self.centralWidget)
self.menuBar = QtWidgets.QMenuBar(MainWindow)
self.menuBar.setGeometry(QtCore.QRect(0, 0, 388, 29))
self.menuBar.setGeometry(QtCore.QRect(0, 0, 808, 29))
self.menuBar.setLocale(QtCore.QLocale(QtCore.QLocale.English, QtCore.QLocale.UnitedStates))
self.menuBar.setObjectName("menuBar")
self.menuFile = QtWidgets.QMenu(self.menuBar)
@ -215,6 +231,7 @@ class Ui_MainWindow(object):
self.label_cbar_end.setBuddy(self.doubleSpinBox_cbar_end)
self.retranslateUi(MainWindow)
self.tabWidget.setCurrentIndex(3)
QtCore.QMetaObject.connectSlotsByName(MainWindow)
def retranslateUi(self, MainWindow):
@ -236,7 +253,7 @@ class Ui_MainWindow(object):
self.label_dt.setText(_translate("MainWindow", "<html><head/><body><p>&Delta;T</p></body></html>"))
self.doubleSpinBox_dt.setSuffix(_translate("MainWindow", " °C"))
self.groupBox_cutoff.setToolTip(_translate("MainWindow", "<html><head/><body><p>Only T<span style=\" vertical-align:sub;\">m</span> values within this limit are considered valid.</p></body></html>"))
self.groupBox_cutoff.setTitle(_translate("MainWindow", "Cutoff"))
self.groupBox_cutoff.setTitle(_translate("MainWindow", "&Cutoff"))
self.label_cutoff_high.setText(_translate("MainWindow", "&Upper"))
self.doubleSpinBox_upper.setSuffix(_translate("MainWindow", " °C"))
self.label_cutoff_low.setText(_translate("MainWindow", "Lower"))
@ -249,8 +266,14 @@ class Ui_MainWindow(object):
self.doubleSpinBox_cbar_start.setSuffix(_translate("MainWindow", " °C"))
self.label_cbar_end.setText(_translate("MainWindow", "En&d"))
self.doubleSpinBox_cbar_end.setSuffix(_translate("MainWindow", " °C"))
self.tabWidget.setTabText(self.tabWidget.indexOf(self.tab_raw), _translate("MainWindow", "Raw Data"))
self.tabWidget.setTabText(self.tabWidget.indexOf(self.tab_derivative), _translate("MainWindow", "&1st derivative"))
self.tabWidget.setTabText(self.tabWidget.indexOf(self.tab_heatmap), _translate("MainWindow", "Heatmap"))
self.tabWidget.setTabText(self.tabWidget.indexOf(self.tab_heatmap_avg), _translate("MainWindow", "Heatmap average"))
self.menuFile.setTitle(_translate("MainWindow", "Fi&le"))
self.menuHelp.setTitle(_translate("MainWindow", "Help"))
self.menuHelp.setTitle(_translate("MainWindow", "Hel&p"))
self.actionQuit.setText(_translate("MainWindow", "&Quit"))
self.actionAbout.setText(_translate("MainWindow", "&About"))
self.actionAbout_Qt.setText(_translate("MainWindow", "About &Qt"))
from .mplwidget import MplWidget

4
ui/icons.qrc
View file

@ -1,5 +1,3 @@
<RCC>
<qresource prefix="/">
<file>qtlogo.svg</file>
</qresource>
<qresource prefix="/"/>
</RCC>

64
ui/mainwindow.py
View file

@ -17,6 +17,7 @@ class MainWindow(QMainWindow, Ui_MainWindow):
"""
Class documentation goes here.
"""
def __init__(self, parent=None):
"""
Constructor
@ -33,6 +34,7 @@ class MainWindow(QMainWindow, Ui_MainWindow):
self.statusBar.showMessage("Welcome to PyDSF")
@pyqtSlot("QAbstractButton*")
def on_buttonBox_open_reset_clicked(self, button):
"""
@ -47,8 +49,8 @@ class MainWindow(QMainWindow, Ui_MainWindow):
elif button == self.buttonBox_open_reset.button(QDialogButtonBox.Reset):
self.listWidget_data.clear()
print("Data cleared")
# self.radioButton_rep_rows.setEnabled(False)
# self.radioButton_rep_columns.setEnabled(False)
# self.radioButton_rep_rows.setEnabled(False)
# self.radioButton_rep_columns.setEnabled(False)
@pyqtSlot("QString")
@ -61,10 +63,10 @@ class MainWindow(QMainWindow, Ui_MainWindow):
self.groupBox_temp.setEnabled(True)
else:
self.groupBox_temp.setEnabled(False)
# self.groupBox_data.setEnabled(True)
# self.groupBox_cutoff.setEnabled(True)
# self.groupBox_cbar.setEnabled(True)
# self.groupBox_signal_threshold.setEnabled(True)
# self.groupBox_data.setEnabled(True)
# self.groupBox_cutoff.setEnabled(True)
# self.groupBox_cbar.setEnabled(True)
# self.groupBox_signal_threshold.setEnabled(True)
@pyqtSlot()
def on_buttonBox_process_accepted(self):
@ -76,7 +78,8 @@ class MainWindow(QMainWindow, Ui_MainWindow):
QMessageBox.critical(self, 'Error', "No data file loaded!", QMessageBox.Close, QMessageBox.Close)
return
if self.spinBox_signal_threshold.value() == 0 and self.groupBox_signal_threshold.isChecked():
QMessageBox.warning(self, 'Warning', "Signal threshold is currently set to zero.", QMessageBox.Ok, QMessageBox.Ok)
QMessageBox.warning(self, 'Warning', "Signal threshold is currently set to zero.", QMessageBox.Ok,
QMessageBox.Ok)
self.progressBar.setEnabled(True)
self.statusBar.showMessage("Processing...")
@ -90,7 +93,7 @@ class MainWindow(QMainWindow, Ui_MainWindow):
c_lower = self.doubleSpinBox_lower.value()
c_upper = self.doubleSpinBox_upper.value()
if self.groupBox_cbar.isChecked():
cbar_range = (self.doubleSpinBox_cbar_start, self.doubleSpinBox_cbar_end)
cbar_range = (self.doubleSpinBox_cbar_start, self.doubleSpinBox_cbar_end)
if self.groupBox_signal_threshold.isChecked():
signal_threshold = self.spinBox_signal_threshold.value()
@ -99,29 +102,53 @@ class MainWindow(QMainWindow, Ui_MainWindow):
files = []
for item in items:
files.append(item.text())
exp = Experiment(type=type, files=files, t1=self.doubleSpinBox_tmin.value(), t2=self.doubleSpinBox_tmax.value(), dt=self.doubleSpinBox_dt.value(), cols=12, rows=8, cutoff_low=c_lower, cutoff_high=c_upper, signal_threshold=signal_threshold, color_range=cbar_range)
exp = Experiment(type=type, files=files, t1=self.doubleSpinBox_tmin.value(), t2=self.doubleSpinBox_tmax.value(),
dt=self.doubleSpinBox_dt.value(), cols=12, rows=8, cutoff_low=c_lower, cutoff_high=c_upper,
signal_threshold=signal_threshold, color_range=cbar_range)
exp.analyze()
# plate = Plate(type=type, filename=self.lineEdit_data_file.text(), t1=self.doubleSpinBox_tmin.value(), t2=self.doubleSpinBox_tmax.value(), dt=self.doubleSpinBox_dt.value(), cols=12, rows=8, cutoff_low=c_lower, cutoff_high=c_upper, signal_threshold=signal_threshold, color_range=cbar_range)
# self.statusBar.addWidget(self.pb, 100)
#plate.analyze(gui=self)
# plate.analyze(gui=self)
save_data = QMessageBox.question(self, 'Save data', "Calculations are finished. Save results?",
QMessageBox.Yes|QMessageBox.No, QMessageBox.Yes)
QMessageBox.Yes | QMessageBox.No, QMessageBox.Yes)
if save_data == QMessageBox.Yes:
dialog = QFileDialog()
dialog.setFileMode(QFileDialog.Directory)
folder = dialog.getExistingDirectory(self, 'Choose path for results')
for plate in exp.plates:
plate.write_tm_table('{}/plate_{}_04_tm.csv'.format(folder, str(plate.id)))
plate.write_derivative_table('{}/plate_{}_03_dI_dT.csv'.format(folder, str(plate.id)))
plate.write_filtered_table('{}/plate_{}_02_filtered_data.csv'.format(folder, str(plate.id)))
plate.write_raw_table('{}/plate_{}_01_raw_data.csv'.format(folder, str(plate.id)))
plate.write_tm_table('{}/plate_{}_04_tm.csv'.format(folder, str(plate.id)))
plate.write_derivative_table('{}/plate_{}_03_dI_dT.csv'.format(folder, str(plate.id)))
plate.write_filtered_table('{}/plate_{}_02_filtered_data.csv'.format(folder, str(plate.id)))
plate.write_raw_table('{}/plate_{}_01_raw_data.csv'.format(folder, str(plate.id)))
if exp.avg_plate:
exp.avg_plate.write_avg_tm_table('{}/plate_{}_05_tm_avg.csv'.format(folder, str(exp.avg_plate.id)))
#plot(plate, self)
exp.avg_plate.write_avg_tm_table('{}/plate_{}_05_tm_avg.csv'.format(folder, str(exp.avg_plate.id)))
#plot(plate, self)
plot(exp)
plotter = PlotResults(exp)
for i in range(self.tabWidget.count()):
for plate in exp.plates:
if i == 0:
plotter.plot_raw(plate, self.tabWidget.widget(i))
elif i == 1:
plotter.plot_derivative(plate, self.tabWidget.widget(i))
elif i == 2:
plotter.plot_tm_heatmap_single(plate, self.tabWidget.widget(i))
elif exp.avg_plate and i == 3:
plotter.plot_tm_heatmap_single(exp.avg_plate, self.tabWidget.widget(i))
self.tabWidget.setTabEnabled(i, True)
else:
self.tabWidget.setTabEnabled(i, False)
#for i in range(self.tabWidget.count()):
# self.tabWidget.widget(i).canvas.clear()
#fig, ax = figures[0]
#self.tabWidget.widget(0).canvas.fig = fig
#self.tabWidget.widget(0).canvas.ax = ax
#self.tabWidget.widget(0).canvas.draw()
self.progressBar.setEnabled(False)
self.statusBar.showMessage("Finished!")
@ -135,6 +162,7 @@ class MainWindow(QMainWindow, Ui_MainWindow):
QApplication.quit()
pyqtSlot()
def on_actionQuit_triggered(self):
"""
Slot documentation goes here.

60
ui/mainwindow.ui
View file

@ -6,8 +6,8 @@
<rect>
<x>0</x>
<y>0</y>
<width>388</width>
<height>642</height>
<width>808</width>
<height>646</height>
</rect>
</property>
<property name="windowTitle">
@ -35,7 +35,7 @@
<property name="checkable">
<bool>false</bool>
</property>
<layout class="QGridLayout" name="gridLayout">
<layout class="QFormLayout" name="formLayout_3">
<item row="0" column="0">
<widget class="QLabel" name="label_instrument">
<property name="text">
@ -247,7 +247,7 @@
<string>&lt;html&gt;&lt;head/&gt;&lt;body&gt;&lt;p&gt;Only T&lt;span style=&quot; vertical-align:sub;&quot;&gt;m&lt;/span&gt; values within this limit are considered valid.&lt;/p&gt;&lt;/body&gt;&lt;/html&gt;</string>
</property>
<property name="title">
<string>Cutoff</string>
<string>&amp;Cutoff</string>
</property>
<property name="alignment">
<set>Qt::AlignLeading|Qt::AlignLeft|Qt::AlignVCenter</set>
@ -406,14 +406,44 @@
</layout>
</widget>
</item>
<item row="4" column="1">
<widget class="QDialogButtonBox" name="buttonBox_process">
<property name="standardButtons">
<set>QDialogButtonBox::Cancel|QDialogButtonBox::Ok</set>
</property>
</widget>
</item>
</layout>
</widget>
</item>
<item row="1" column="0">
<widget class="QDialogButtonBox" name="buttonBox_process">
<property name="standardButtons">
<set>QDialogButtonBox::Cancel|QDialogButtonBox::Ok</set>
<item row="0" column="1">
<widget class="QTabWidget" name="tabWidget">
<property name="currentIndex">
<number>3</number>
</property>
<widget class="MplWidget" name="tab_raw">
<attribute name="title">
<string>Raw Data</string>
</attribute>
</widget>
<widget class="MplWidget" name="tab_derivative">
<attribute name="title">
<string>&amp;1st derivative</string>
</attribute>
</widget>
<widget class="MplWidget" name="tab_heatmap">
<attribute name="title">
<string>Heatmap</string>
</attribute>
</widget>
<widget class="MplWidget" name="tab_heatmap_avg">
<property name="enabled">
<bool>false</bool>
</property>
<attribute name="title">
<string>Heatmap average</string>
</attribute>
</widget>
</widget>
</item>
</layout>
@ -423,7 +453,7 @@
<rect>
<x>0</x>
<y>0</y>
<width>388</width>
<width>808</width>
<height>29</height>
</rect>
</property>
@ -444,7 +474,7 @@
<locale language="English" country="UnitedStates"/>
</property>
<property name="title">
<string>Help</string>
<string>Hel&amp;p</string>
</property>
<addaction name="actionAbout"/>
<addaction name="actionAbout_Qt"/>
@ -465,7 +495,7 @@
</action>
<action name="actionAbout_Qt">
<property name="icon">
<iconset resource="icons.qrc">
<iconset>
<normaloff>:/qtlogo.svg</normaloff>:/qtlogo.svg</iconset>
</property>
<property name="text">
@ -473,6 +503,14 @@
</property>
</action>
</widget>
<customwidgets>
<customwidget>
<class>MplWidget</class>
<extends>QWidget</extends>
<header>mplwidget</header>
<container>1</container>
</customwidget>
</customwidgets>
<resources>
<include location="icons.qrc"/>
</resources>

25
ui/mplwidget.py Normal file
View file

@ -0,0 +1,25 @@
from PyQt5 import QtWidgets
from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas
from matplotlib.backends.backend_qt5agg import NavigationToolbar2QTAgg as NavigationToolbar
from matplotlib.figure import Figure
class MplCanvas(FigureCanvas):
def __init__(self):
self.fig = Figure()
self.ax = self.fig.add_subplot(111)
FigureCanvas.__init__(self, self.fig)
FigureCanvas.setSizePolicy(self, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Expanding)
FigureCanvas.updateGeometry(self)
def clear(self):
self.ax.clear()
self.fig.clear()
class MplWidget(QtWidgets.QWidget):
def __init__(self, parent = None):
QtWidgets.QWidget.__init__(self, parent)
self.canvas = MplCanvas()
self.vbl = QtWidgets.QVBoxLayout()
self.vbl.addWidget(self.canvas)
self.setLayout(self.vbl)