Skip to content
This repository has been archived by the owner on Aug 16, 2024. It is now read-only.

Commit

Permalink
clean up
Browse files Browse the repository at this point in the history
  • Loading branch information
Kavin Teenakul committed Aug 30, 2023
1 parent ee089a5 commit 16d2e99
Showing 1 changed file with 0 additions and 101 deletions.
101 changes: 0 additions & 101 deletions PySimpleCV/PySimpleCV_main_func.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -16,7 +16,6 @@ def search_string_in_file(file_name, string_to_search):
return list_of_results

def CV_file2df(CV_file,cv_format):
# match cv_format:
if cv_format == "CSV":
df_CV = pd.read_csv(CV_file,usecols=[0,1])
file_scan_rate = float(0)
Expand Down Expand Up @@ -44,7 +43,6 @@ def CV_file2df(CV_file,cv_format):
file_scan_rate = float(0)
footer = ln_count-end_segment
df_CV = pd.read_csv(CV_file, skiprows=start_segment, skipfooter=footer, usecols=[2,3], header=None, engine='python')
# volt = df_CV[:,0]
elif cv_format == "CorrWare":
start_segment = search_string_in_file(CV_file, 'End Comments')[0][0]

Expand Down Expand Up @@ -145,73 +143,6 @@ def ir_compen_func(volt,current,ir_compen):
volt_compen = volt - current*ir_compen
return volt_compen

# def get_CV_peak(inv_peak_trough,cv_size, volt, current, peak_range, peak_pos, trough_pos, jpa_lns, jpa_lne, jpc_lns, jpc_lne, peak_defl_bool, trough_defl_bool):
# # If peak range is given as 0, then peak is just where peak position is
# trough_range = peak_range
# if peak_defl_bool == 1:
# peak_range = 0
# peak_curr = current[peak_pos]
# peak_volt = volt[peak_pos]
# low_range_peak = peak_pos
# high_range_peak = peak_pos
# # Search for peak between peak_range.
# else:
# high_range_peak = np.where((peak_pos+peak_range)>=(cv_size-1),(cv_size-1),peak_pos+peak_range)
# low_range_peak = np.where((peak_pos-peak_range)>=0,peak_pos-peak_range,0)
# # print(low_range_peak,high_range_peak)
# peak_curr_range = current[low_range_peak:high_range_peak]

# if inv_peak_trough == False:
# peak_curr = max(peak_curr_range)
# else:
# peak_curr = min(peak_curr_range)

# peak_idx = np.argmin(np.abs(peak_curr_range-peak_curr))
# peak_volt = volt[low_range_peak:high_range_peak][peak_idx]

# if trough_defl_bool == 1:
# trough_range = 0
# trough_curr = current[trough_pos]
# trough_volt = volt[trough_pos]
# high_range_trough = trough_pos
# low_range_trough = trough_pos
# else:
# high_range_trough = np.where((trough_pos+trough_range)>=(cv_size-1),(cv_size-1),trough_pos+trough_range)
# low_range_trough = np.where((trough_pos-trough_range)>=0,trough_pos-trough_range,0)
# trough_curr_range = current[low_range_trough:high_range_trough]
# if inv_peak_trough == False:
# trough_curr = min(trough_curr_range)
# else:
# trough_curr = max(trough_curr_range)
# trough_idx = np.argmin(np.abs(trough_curr_range-trough_curr))
# trough_volt = volt[low_range_trough:high_range_trough][trough_idx]

# # If the extrapolation coordinate overlapped, just give horizontal line
# if (volt[jpa_lns:jpa_lne]).size == 0:
# volt_jpa = np.array([0, 1])
# current_jpa = np.array([0, 0])
# else:
# volt_jpa = volt[jpa_lns:jpa_lne]
# current_jpa = current[jpa_lns:jpa_lne]

# if (volt[jpc_lns:jpc_lne]).size == 0:
# volt_jpc = np.array([0, 1])
# current_jpc = np.array([0, 0])
# else:
# volt_jpc = volt[jpc_lns:jpc_lne]
# current_jpc = current[jpc_lns:jpc_lne]

# jpa_lnfit_coef,_ = poly.polyfit(volt_jpa,current_jpa, 1, full=True) # 1 for linear fit
# jpc_lnfit_coef,_ = poly.polyfit(volt_jpc,current_jpc, 1, full=True)

# jpa_poly1d = poly.Polynomial(jpa_lnfit_coef)
# jpc_poly1d = poly.Polynomial(jpc_lnfit_coef)

# jpa = peak_curr - jpa_poly1d(peak_volt)
# jpc = jpc_poly1d(trough_volt) - trough_curr
# return low_range_peak, high_range_peak, peak_volt, peak_curr, low_range_trough, high_range_trough, trough_volt, trough_curr, jpa, jpc, jpa_poly1d, jpc_poly1d#, jpa_base, jpc_base


def get_peak_CV(search_mode,cv_size, volt, current, peak_range, peak_pos, jp_lns, jp_lne, peak_defl_bool):
# If peak range is given as 0, then peak is just where peak position is
if peak_defl_bool == 1:
Expand Down Expand Up @@ -404,35 +335,6 @@ def deflection(cv_size,volt,current):
idx_intc_defl = idx_intercept(0,diff3_curr)
return idx_intc_peak, idx_intc_defl

# def find_alpha(volt_compen,current_den,jpa_lns,jpc_lns,peak_pos,trough_pos,jpa_poly1d,jpc_poly1d,jpa,jpc,peak_volt,trough_volt):
# volt_eval_jpa = volt_compen[jpa_lns:peak_pos]
# volt_eval_jpc = volt_compen[jpc_lns:trough_pos]
# curr_eval_jpa = current_den[jpa_lns:peak_pos]
# curr_eval_jpc = current_den[jpc_lns:trough_pos]
# try:
# baseline_eval_jpa = np.linspace(jpa_poly1d(volt_compen[jpa_lns]),jpa_poly1d(volt_compen[peak_pos]),volt_eval_jpa.size)
# curr_baseline_jpa = curr_eval_jpa-baseline_eval_jpa
# ep12_jpa_idx = (np.abs(curr_baseline_jpa-jpa/2)).argmin()
# ep12_jpa = volt_eval_jpa[ep12_jpa_idx] #Potential at peak current 1/2 (Ep 1/2)
# jp12_jpa = curr_eval_jpa[ep12_jpa_idx]
# alpha_jpa = 1-((47.7/1000)/np.abs(peak_volt - ep12_jpa))
# except (ValueError, IndexError):
# ep12_jpa = 0
# jp12_jpa = 0
# alpha_jpa = 0
# try:
# baseline_eval_jpc = np.linspace(jpc_poly1d(volt_compen[jpc_lns]),jpc_poly1d(volt_compen[trough_pos]),volt_eval_jpc.size)
# curr_baseline_jpc = curr_eval_jpc-baseline_eval_jpc
# ep12_jpc_idx = (np.abs(curr_baseline_jpc+jpc/2)).argmin()
# ep12_jpc = volt_eval_jpc[ep12_jpc_idx] #Potential at peak current 1/2 (Ep 1/2)
# jp12_jpc = curr_eval_jpc[ep12_jpc_idx]
# alpha_jpc = 1-((47.7/1000)/np.abs(trough_volt - ep12_jpc))
# except (ValueError, IndexError):
# ep12_jpc = 0
# jp12_jpc = 0
# alpha_jpc = 0
# return ep12_jpa, jp12_jpa, alpha_jpa, ep12_jpc, jp12_jpc, alpha_jpc

def find_alpha(volt,curr,jp_lns,peak_pos,jp_poly1d,jp,peak_volt):
volt_eval_jp = volt[jp_lns:peak_pos]
curr_eval_jp = curr[jp_lns:peak_pos]
Expand Down Expand Up @@ -475,11 +377,8 @@ def min_max_peak(search_mode,cv_size, volt, current, peak_range, peak_pos):
peak_volt = volt[low_range_peak:high_range_peak][peak_idx]
elif search_mode == 'none':
peak_curr = current[peak_pos]
# peak_idx = peak_pos
peak_volt = volt[peak_pos]
peak_real_idx = int(peak_pos-peak_range+peak_idx)
# peak_idx = np.argmin(np.abs(peak_curr_range-peak_curr))
# peak_volt = volt[low_range_peak:high_range_peak][peak_idx]
return high_range_peak, low_range_peak, peak_volt, peak_curr, peak_real_idx

def check_val(val, val_type, err_val):
Expand Down

0 comments on commit 16d2e99

Please sign in to comment.