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Expand Battsmall functionality

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rasmusthog 2022-10-09 18:39:28 +02:00
parent 3998005334
commit 65de5ecf45
1 changed files with 45 additions and 1 deletions
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46
nafuma/electrochemistry/io.py
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@ -144,6 +144,9 @@ def process_batsmall_data(df, options=None):
set_units(options) set_units(options)
options['old_units'] = get_old_units(df, options) options['old_units'] = get_old_units(df, options)
df = add_columns(df=df, options=options) # adds columns to the DataFrame if active material weight and/or molecular weight has been passed in options
df = unit_conversion(df=df, options=options) df = unit_conversion(df=df, options=options)
@ -177,6 +180,9 @@ def process_batsmall_data(df, options=None):
if chg_df.empty and dchg_df.empty: if chg_df.empty and dchg_df.empty:
continue continue
chg_df['reaction_coordinate'] = chg_df['time'] * np.abs(chg_df['current'].mean())
dchg_df['reaction_coordinate'] = dchg_df['time'] * np.abs(dchg_df['current'].mean())
if options['reverse_discharge']: if options['reverse_discharge']:
max_capacity = dchg_df['capacity'].max() max_capacity = dchg_df['capacity'].max()
dchg_df['capacity'] = np.abs(dchg_df['capacity'] - max_capacity) dchg_df['capacity'] = np.abs(dchg_df['capacity'] - max_capacity)
@ -480,6 +486,7 @@ def process_biologic_data(df, options=None):
def add_columns(df, options): def add_columns(df, options):
from . import unit_tables
if options['kind'] == 'neware': if options['kind'] == 'neware':
@ -513,6 +520,28 @@ def add_columns(df, options):
df["IonsExtracted"] = (df["SpecificCapacity({}/mg)".format(options['old_units']['capacity'])]*options['molecular_weight'])*1000/f df["IonsExtracted"] = (df["SpecificCapacity({}/mg)".format(options['old_units']['capacity'])]*options['molecular_weight'])*1000/f
if options['kind'] == 'batsmall':
if options['active_material_weight']:
active_material_weight = options['active_material_weight'] * unit_tables.mass()['mg'].loc[options['units']['mass']]
capacity = options['old_units']['capacity']
df[f'Capacity [{options["old_units"]["capacity"]}]'] = df[f'C [{options["old_units"]["capacity"]}/{options["old_units"]["mass"]}]'] * active_material_weight
if options['molecular_weight']:
faradays_constant = 96485.3365 # [F] = C mol^-1 = As mol^-1
seconds_per_hour = 3600 # s h^-1
f = faradays_constant / seconds_per_hour * 1000.0 # [f] = mAh mol^-1
molecular_weight = options['molecular_weight'] * unit_tables.mass()['g'].loc[options['units']['mass']]
df["IonsExtracted"] = (df[f'C [{options["old_units"]["capacity"]}/{options["old_units"]["mass"]}]'] * molecular_weight)/f
#df['reaction_coordinate'] = (df[f'TT [{options["old_units"]["time"]}]'] * unit_tables.time()[options['old_units']["time"]].loc["h"]) / np.abs(df[f'I [{options["old_units"]["current"]}]'] * unit_tables.current()[options['old_units']["current"]].loc['A'])
return df return df
@ -545,7 +574,22 @@ def unit_conversion(df, options):
df["I [{}]".format(options['old_units']["current"])] = df["I [{}]".format(options['old_units']["current"])] * unit_tables.current()[options['old_units']["current"]].loc[options['units']['current']] df["I [{}]".format(options['old_units']["current"])] = df["I [{}]".format(options['old_units']["current"])] * unit_tables.current()[options['old_units']["current"]].loc[options['units']['current']]
df["C [{}/{}]".format(options['old_units']["capacity"], options['old_units']["mass"])] = df["C [{}/{}]".format(options['old_units']["capacity"], options['old_units']["mass"])] * (unit_tables.capacity()[options['old_units']["capacity"]].loc[options['units']["capacity"]] / unit_tables.mass()[options['old_units']["mass"]].loc[options['units']["mass"]]) df["C [{}/{}]".format(options['old_units']["capacity"], options['old_units']["mass"])] = df["C [{}/{}]".format(options['old_units']["capacity"], options['old_units']["mass"])] * (unit_tables.capacity()[options['old_units']["capacity"]].loc[options['units']["capacity"]] / unit_tables.mass()[options['old_units']["mass"]].loc[options['units']["mass"]])
df.columns = ['time', 'voltage', 'current', 'count', 'specific_capacity', 'comment'] columns = ['time', 'voltage', 'current', 'count', 'specific_capacity', 'comment']
# Add column labels for specific capacity and ions if they exist
if f'Capacity [{options["old_units"]["capacity"]}]' in df.columns:
df[f'Capacity [{options["old_units"]["capacity"]}]'] = df[f'Capacity [{options["old_units"]["capacity"]}]'] * unit_tables.capacity()[options['old_units']['capacity']].loc[options['units']['capacity']]
columns.append('capacity')
if 'IonsExtracted' in df.columns:
columns.append('ions')
#columns.append('reaction_coordinate')
df.columns = columns
if options['kind'] == 'neware': if options['kind'] == 'neware':