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allow empty charge or discharge data for get_cap
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@jepegit
jepegit committed Dec 25, 2023
1 parent 6a86bdd commit 2e7f7ab
Showing 1 changed file with 101 additions and 59 deletions.
160 changes: 101 additions & 59 deletions cellpy/readers/cellreader.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4228,11 +4228,23 @@ def get_cap(
# TODO: allow for fixing the interpolation range (so that it is possible
# to run the function on several cells and have a common x-axis)

# TODO: allow for missing steps (i.e. if you have a cell with only charge and no discharge in the first cycle)

# if cycle is not given, then this function should
# iterate through cycles

def last(df):
try:
return df.iat[-1]
except TypeError:
return 0.0

def first(df):
try:
return df.iat[0]
except TypeError:
return 0.0

experimental = True

cycle_mode = cycle_mode or self.cycle_mode

if cycle is None:
Expand Down Expand Up @@ -4260,6 +4272,9 @@ def get_cap(
else:
insert_nan = False

if insert_nan:
_nan = pd.DataFrame({"capacity": [np.nan], "voltage": [np.nan]})

converter_kwargs = dict()
if mass is not None:
logging.critical(
Expand Down Expand Up @@ -4306,6 +4321,15 @@ def get_cap(
as_frame=False,
**kwargs,
)

except NullData as e:
error = True
logging.critical(e)
if not ignore_errors:
logging.debug("breaking out of loop")
break

try:
dc, dv = self.get_dcap(
current_cycle,
converter=specific_converter,
Expand All @@ -4320,7 +4344,7 @@ def get_cap(
logging.debug("breaking out of loop")
break

if not error:
if not error or experimental:
if cc.empty:
logging.debug("get_ccap returns empty cc Series")

Expand All @@ -4347,32 +4371,36 @@ def get_cap(
_last_step_v = dv

if method == "back-and-forth":
# _last = np.amax(_first_step_c)
_last = _first_step_c.iat[-1]
# should change amax to last point
_last = last(_first_step_c)
_first = None
_new_first = None

if not inter_cycle_shift:
prev_end = 0.0

if _last_step_c is not None:
_last_step_c = _last - _last_step_c + prev_end

else:
logging.debug("no last charge step found")
logging.critical("no last charge step found")

if _first_step_c is not None:
_first = _first_step_c.iat[0]
_first = first(_first_step_c)
_first_step_c += prev_end
_new_first = _first_step_c.iat[0]
_new_first = first(_first_step_c)

else:
logging.debug("probably empty (_first_step_c is None)")
logging.critical("probably empty (_first_step_c is None)")
# logging.debug(f"current shifts used: prev_end = {prev_end}")
# logging.debug(f"shifting start from {_first} to "
# f"{_new_first}")

# prev_end = np.amin(_last_step_c)
prev_end = _last_step_c.iat[-1]
prev_end = last(_last_step_c)

elif method == "forth":
# _last = np.amax(_first_step_c)
_last = _first_step_c.iat[-1]
_last = last(_first_step_c)
if _last_step_c is not None:
_last_step_c += _last + prev_end
else:
Expand All @@ -4382,9 +4410,8 @@ def get_cap(
else:
logging.debug("no first charge step found")

# prev_end = np.amax(_last_step_c)
if inter_cycle_shift:
prev_end = _last_step_c.iat[-1]
prev_end = last(_last_step_c)
else:
prev_end = 0.0

Expand All @@ -4405,48 +4432,53 @@ def get_cap(
x_col, y_col = y_col, x_col

try:
_first_df = pd.DataFrame(
{
"voltage": _first_step_v,
"capacity": _first_step_c,
}
)
if interpolated:
_first_df = interpolate_y_on_x(
_first_df,
y=y_col,
x=x_col,
dx=dx,
number_of_points=number_of_points,
direction=first_interpolation_direction,
# processing first
if not _first_step_c.empty:
_first_df = pd.DataFrame(
{
"voltage": _first_step_v,
"capacity": _first_step_c,
}
)
if insert_nan:
_nan = pd.DataFrame(
{"capacity": [np.nan], "voltage": [np.nan]}
)
_first_df = pd.concat([_first_df, _nan])
if categorical_column:
_first_df["direction"] = -1

_last_df = pd.DataFrame(
{
"voltage": _last_step_v.values,
"capacity": _last_step_c.values,
}
)
if interpolated:
_last_df = interpolate_y_on_x(
_last_df,
y=y_col,
x=x_col,
dx=dx,
number_of_points=number_of_points,
direction=last_interpolation_direction,
if interpolated:
_first_df = interpolate_y_on_x(
_first_df,
y=y_col,
x=x_col,
dx=dx,
number_of_points=number_of_points,
direction=first_interpolation_direction,
)
if insert_nan:
_first_df = pd.concat([_first_df, _nan])
if categorical_column:
_first_df["direction"] = -1
else:
_first_df = pd.DataFrame()

# processing last
if not _last_step_c.empty:
_last_df = pd.DataFrame(
{
"voltage": _last_step_v.values,
"capacity": _last_step_c.values,
}
)
if insert_nan:
_last_df = pd.concat([_last_df, _nan])
if categorical_column:
_last_df["direction"] = 1
if interpolated:
_last_df = interpolate_y_on_x(
_last_df,
y=y_col,
x=x_col,
dx=dx,
number_of_points=number_of_points,
direction=last_interpolation_direction,
)
if insert_nan:
_last_df = pd.concat([_last_df, _nan])
if categorical_column:
_last_df["direction"] = 1
else:
_last_df = pd.DataFrame()

if interpolate_along_cap:
if method == "forth":
Expand Down Expand Up @@ -4477,11 +4509,21 @@ def get_cap(
cycle_df = cycle_df[new_cols]
else:
logging.warning("returning non-dataframe")
c = pd.concat([_first_step_c, _last_step_c], axis=0)
v = pd.concat([_first_step_v, _last_step_v], axis=0)

capacity = pd.concat([capacity, c], axis=0)
voltage = pd.concat([voltage, v], axis=0)
_non_empty_c = []
_non_empty_v = []
if not _first_step_c.empty:
_non_empty_c.append(_first_step_c)
_non_empty_v.append(_first_step_v)
if not _last_step_c.empty:
_non_empty_c.append(_last_step_c)
_non_empty_v.append(_last_step_v)

c = pd.concat(_non_empty_c, axis=0)
v = pd.concat(_non_empty_v, axis=0)

if not c.empty:
capacity = pd.concat([capacity, c], axis=0)
voltage = pd.concat([voltage, v], axis=0)

if return_dataframe:
return cycle_df
Expand Down

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