def find_all_slopes(self, filename_or_data, plotfun=None):
"""Returns a dict of regressoion objects.
A regression object has slots named intercept, slope, se_intercept,
se_slope, mse, start, and stop Each of these is a float. se is
standard error, mse is mean squared error.
"""
reg = regression.regression2
# regression.regression2 is a function which returns a regression object
if isinstance(filename_or_data, str):
data = get_data.get_file_data(filename_or_data)
else:
data = filename_or_data
# data is a dict with keys 'CO2', 'N2O', 'Wind', and so on
# data['CO2'][0] is a list of seconds
# data['CO2'][1] is a list of ppmv values
# similarly for 'N2O'
# Wind is a little bit different; it has not ppmv, but m/s
# We show here just the simple linear regression using all the data,
# but wind and self.options is available and may be used in this function,
print('this is my own regression function')
print('self.options is:', self.options)
print('wind was on average:', np.mean(data['Wind'][1]), 'm/s')
resdict = divide_left_and_right.group_all(data)
co2 = resdict['CO2']
n2o = resdict['N2O']
regressions = dict()
regressions['left'] = dict()
regressions['right'] = dict()
regressions['left']['CO2'] = reg(co2['left'][0], co2['left'][1])
regressions['left']['N2O'] = reg(n2o['left'][0], n2o['left'][1])
regressions['right']['CO2'] = reg(co2['right'][0], co2['right'][1])
regressions['right']['N2O'] = reg(n2o['right'][0], n2o['right'][1])
return regressions
def plot_gas(filename, gas='CO2'):
#fix single filename with directory path
if not os.path.isfile(filename):
filename = os.path.join(resdir.raw_data_path, filename)
#load data for one file
a = get_data.get_file_data(filename)
#make simple plot of either N2O or CO2
plt.plot(a[gas][0], a[gas][1], '.')
def plot_raw(examplefilename, key='N2O'):
"key may be 'N2O', 'CO2', 'Wind'"
if not os.path.isfile(examplefilename):
examplefilename = with_raw_dir(examplefilename)
a = get_data.get_file_data(examplefilename)
plt.plot(a[key][0], a[key][1], '.')
plt.gca().set_xlabel('seconds')
if key in ['N2O', 'CO2', 'CO']:
plt.gca().set_ylabel('ppm')
return a
def _write_raw(raw_filename, worksheet, column_start=0):
data = get_data.get_file_data(raw_filename)
reg = regr.find_all_slopes(raw_filename, do_plot=False)
segments = find_regressions.get_regression_segments(data, reg)
column = column_start
w = worksheet
w.write(0, column, raw_filename)
def write_columns(title, columns, column_start, under_titles):
w.write(1, column_start, title)
for i, vector in enumerate(columns):
w.write(2, column_start, under_titles[i])
for j, v in enumerate(vector):
w.write(j + 3, column_start, v)
column_start += 1
return column_start
for subst, vals in data.items():
if not (isinstance(vals, list) and len(vals)==2\
and isinstance(vals[0], list) and isinstance(vals[1], list)\
and len(vals[0])==len(vals[1])):
continue
column = write_columns(subst, vals, column, ['time', 'signal'])
t_orig, y_orig = vals
for side in ['right', 'left']:
if side in segments:
if subst in segments[side]:
tside, yside = segments[side][subst][2:]
yy = [
y if t_orig[i] in tside else None
for i, y in enumerate(y_orig)
]
deb.append([segments, side, subst, t_orig])
column = write_columns(
'%s_%s' % (subst, side),
[yy], #segments[side][subst][2:],
column,
['signal'])
column += 1
reg_attrs = ['slope', 'intercept', 'se_slope', 'se_intercept', 'mse']
for side, regs in reg.items():
for gas in regs.keys():
if regs[gas] is None:
continue
w.write(1, column, 'reg:%s_%s' % (side, gas))
for i, s in enumerate(reg_attrs):
w.write(i * 2 + 2, column, s)
w.write(i * 2 + 3, column, getattr(regs[gas], s))
column += 1
return column + 2
#OR change y limits (apparently can't use ymin or ymax alone)
plot_gas(filename)
plt.gca().set_ylim(ymin=200, ymax=800)
#custom
filename = '2018-01-03-13-06-39-x599263_542108-y6615221_28657-z0_0-h-2_39905751122_right_Plot_1_'
plot_gas(filename, gas='CO2')
plt.gca().set_ylim(ymin=200, ymax=800)
#%%
"""
Standard deviation of CO2
"""
for i in range(18691, 18875):
print(filenames[i])
a = get_data.get_file_data(filenames[i])
print(np.std(a['CO2'][1]))
#print(a['CO2'][1])
#%%
"""
A more extensive shart showing N2O, CO2, points used, and regression lines
"""
#%%
#Display charts for all files, or a subset: for filename in filenames[0:10]
#To run for only one file, don't highlight the for loop beginning line. will run file currently in "filename"
for filename in filenames[18645:18648]:
filename = '2018-01-04-14-17-31-x599263_5599-y6615221_32418-z0_0-h-2_40099505776_right_Plot_1_'
if not os.path.isfile(filename):
filename = os.path.join(resdir.raw_data_path, filename)
reg = regr.find_all_slopes(filename, do_plot=True)
def do_regressions(self, files, write_mode='w'):
def print_info_maybe(i, n, t0, n_on_line):
t = time.time()
if t - t0 > 10:
print('%d/%d ' % (i+1, n), end='')
t0 = t
n_on_line += 1
if n_on_line > 4:
n_on_line = 0
print('')
return t0, n_on_line
if not files:
print('\nNo regressions to do\n')
return dict(), []
print('Doing regressions')
n = len(files)
t0 = time.time()
resdict = {}
n_on_line = 0
errors = []
with open(self.slopes_file_name, write_mode) as f:
for i, name in enumerate(files): #do regression for each file
t0, n_on_line = print_info_maybe(i, n, t0, n_on_line)
try:
data = get_data.get_file_data(name)
reg = self.find_all_slopes(data)
self.write_result_to_file(reg, name, f)
resdict[os.path.split(name)[1]] = reg
# Save images of each regression if wanted
if self.save_options['show_images'] or self.save_options['save_images']:
title_filename = data['filename']
title_options = 'options: ' + self.options.get_options_string(data['filename'])
try:
left_QC = reg['left']['N2O'].quality_check
except:
left_QC = None
try:
right_QC = reg['right']['N2O'].quality_check
except:
right_QC = None
title_left_QC = 'Left: '+left_QC if left_QC else ""
title_right_QC = 'Right: '+right_QC if right_QC else ""
plt.title(title_filename + '\n' + title_options + '\n' + title_left_QC + '\n' + title_right_QC )
if self.save_options['save_images']:
plt.savefig(os.path.join(self.detailed_output_path+"\\images", title_filename +'.png'))
if left_QC:
plt.savefig(os.path.join(self.detailed_output_path+"\\Check\\"+left_QC, "LEFT " + left_QC +" "+ title_filename +'.png'))
elif right_QC:
plt.savefig(os.path.join(self.detailed_output_path+"\\Check\\"+right_QC, "RIGHT "+ right_QC +" "+ title_filename +'.png'))
if self.save_options['show_images']:
plt.show()
plt.clf()
# Save detailed raw excel if wanted
if self.save_options['save_detailed_excel']:
filename = data['filename']
xls_write_raw_data_file(filename,
self.detailed_output_path+'\\Values\\'+
'DetailedRawData_'+ filename+'.xls',
data, reg, False)
except Exception as e:
import traceback
errors.append([name, traceback.format_exc()])
# continue
print_info_maybe(i, n, 0, 100000)
print('Regression done on %d files with %d errors' %
(len(files), len(errors)))
if len(errors):
regression_errors.append(errors)
print('See find_regressions.regression_errors[-1]')
return resdict, errors
def find_all_slopes(self, filename_or_data, do_plot=False, given_specific_options=False):
"""Finds the regression lines for N2O and CO2, for left and right
side
returns {'left':{'CO2':(Regression, (x,y)),'N2O':...}, {'right': ...}}
given_specific_options may be given; if not, specific_options will be found from the filename
"""
if isinstance(filename_or_data, str):
data = get_data.get_file_data(filename_or_data)
else:
data = filename_or_data
if given_specific_options is False:
specific_options = self.options.get_specific_options(data['filename'])
else:
specific_options = given_specific_options
cut_param = self._get_divide_cut_param(specific_options)
rawdict = divide_left_and_right.group_all(data, **cut_param)
keys = ['CO2', 'N2O', 'CO', 'H2O', 'licor_H2O']
regressions = {'left': {}, 'right': {}}
regressions_tmp = {'left': {}, 'right': {}}
for side in list(regressions.keys()):
tbest = None
for key in keys:
tbest_orig = tbest
regressions[side][key], tbest = self._regress1(rawdict, side, key,
specific_options, tbest)
if(regressions[side][key] != None and self.options.options["correct_negatives"] == True):
specific_options_bcp = specific_options
#print(data['filename'],specific_options_bcp)
if((key=="N2O") and (regressions[side][key].slope < 0)):
specific_options["co2_guides"] = False
regressions_tmp[side][key], tbest_tmp = self._regress1(rawdict, side, key,
specific_options, tbest_orig)
#print(" trying co2 OFF")
if(regressions_tmp[side][key].slope < 0):
specific_options = specific_options_bcp
specific_options[side] = {'N2O': {'start': 1, 'stop': 190}}
regressions_tmp[side][key], tbest_tmp = self._regress1(rawdict, side, key,
specific_options, tbest_orig)
#print(", trying 190s")
if(regressions_tmp[side][key].slope > 0):
regressions[side][key] = regressions_tmp[side][key]
tbest = tbest_tmp
else:
specific_options = specific_options_bcp
#print(", positive N2O not found")
self.options.specific_options_dict[data['filename']] = specific_options #this is not updating properly
#print(specific_options)
if len(list(regressions[side].keys())) == 0:
regressions.pop(side)
# Begin image and detailed excel output functionality ... move to their own functions and call here?
if self.do_plot or do_plot or self.save_options['save_images'] or self.save_options['show_images']:
self.plot_fun(data, regressions) #this calls plot_regressions, also defined in this .py file
# if self.save_options['excel']: Fredrik was here!
# self.xls_write_raw_data_file(title_filename, os.path.join(self.detailed_output_path+"\\excel",'DetailedRawData_'
# +title_filename
# +'.xls'), do_open=False)
return regressions
