def __init__(self, da=None, **kw):
super().__init__(da=da, **kw)
a, b, c, d = self.select_table, T('UnitID'), T('UserSettings'), T('EquipType')
date_col = 'DateAdded'
q = Query.from_(a) \
.left_join(b).on_field('Unit') \
.left_join(c).on(a.CreatedBy == c.UserName) \
.left_join(d).on(b.Model == d.Model) \
f.set_self(vars())
self.default_dtypes |= \
f.dtypes_dict('Int64', ['SMR', 'Unit SMR', 'Comp SMR', 'Part SMR', 'Pics']) | \
f.dtypes_dict('bool', ['Comp CO'])
def set_static_dfs(self, df: pd.DataFrame, reset: bool = False) -> None:
"""Set static dict copies of df string value + colors for faster display in table.
Parameters
----------
df : pd.DataFrame
full df or single row
reset : bool
reset static dfs if true, else append
"""
# update all int column display format
# NOTE this updates TableView's formats too (shared obj)
int_cols = list(df.select_dtypes(int).columns)
self.formats |= f.dtypes_dict('{:,.0f}', int_cols)
static_dfs_new = self.get_static_dfs(df=df)
static_dfs_orig = [self.m_display, self.m_color_bg, self.m_color_text]
if reset:
self.m_display, self.m_color_bg, self.m_color_text = static_dfs_new
else:
# called when adding a single row
for m_new, m_orig in zip(static_dfs_new, static_dfs_orig):
self.update_static_df(m_new=m_new, m_update=m_orig)
self.set_stylemap(df=df)
def __init__(self, da=None, **kw):
super().__init__(da=da, **kw)
a, b = pk.Tables('Downtime', 'UnitID')
q = Query.from_(a) \
.inner_join(b).on_field('Unit')
self.default_dtypes.update(
**f.dtypes_dict('float64', ['Total', 'SMS', 'Suncor']))
f.set_self(vars())
def __init__(self, **kw):
super().__init__(**kw)
a = self.select_table
cols = [
a.MineSite, a.Model, a.Unit, a.Component, a.Modifier, a.bench_smr,
a.CurrentUnitSMR, a.SMRLastCO, a.CurrentComponentSMR,
a.PredictedCODate, a.LifeRemaining, a.SNInstalled
]
q = Query.from_(a) \
.orderby(a.MineSite, a.Unit)
f.set_self(vars())
self.default_dtypes |= f.dtypes_dict('Int64', [
'Bench SMR', 'Curr Unit SMR', 'SMR Last CO', 'Curr Comp SMR',
'Life Remaining'
])
def __init__(self, da=None, **kw):
super().__init__(da=da, **kw)
a = self.select_table
b, c, d, e = pk.Tables('FCSummary', 'FCSummaryMineSite', 'UnitID', 'EquipType')
self.default_dtypes.update(
**f.dtypes_dict('Int64', ['SMR', 'Pics']))
self.formats.update({
'SMR': '{:,.0f}',
'Pics': '{:,.0f}'})
q = Query.from_(a) \
.left_join(b).on_field('FCNumber') \
.left_join(d).on(d.Unit == a.Unit) \
.left_join(c).on((c.FCNumber == a.FCNumber) & (c.MineSite == d.MineSite)) \
.left_join(e).on(d.Model == e.Model)
f.set_self(vars())
def __init__(self,
d_rng: Tuple[dt, dt] = None,
period_name: str = None,
model: str = '980%',
minesite: str = 'FortHills',
period: str = 'month',
unit: str = None):
super().__init__()
self.view_cols.update(ma_target='MA Target',
hrs_period_ma='Hrs Period MA',
hrs_period_pa='Hrs Period PA')
self.default_dtypes.update(
**f.dtypes_dict('float', ['ExcludeHours_MA', 'ExcludeHours_PA']))
self.formats.update({
'MA Target': '{:.2%}',
'MA': '{:.2%}',
'PA': '{:.2%}',
'Hrs Period MA': '{:,.0f}',
'Hrs Period PA': '{:,.0f}',
'Target Hrs Variance': '{:,.0f}',
'F300 SMR Operated': '{:,.0f}',
'Variance F300': '{:,.0f}'
})
# if not period_name is None:
# m = dict(month=df_months, week=df_weeks)
# d_rng = tuple(m[period]().loc[period_name][['StartDate', 'EndDate']])
if period == 'week':
# fmt = f'%Y-%{week_letter}-%w'
fmt = '%G-%V-%w'
freq = 'W'
# fmt_str = f'Week %{week_letter}'
fmt_str = 'Week %V'
else:
fmt = '%Y-%m'
freq = 'M'
fmt_str = fmt
f.set_self(vars())
def __init__(self, da=None, **kw):
super().__init__(da=da, **kw)
a, b, c, d, e = self.a, self.b, T('ComponentType'), self.d, T(
'ComponentBench')
life_achieved = Case().when(
a.SMR == 0,
None).else_(a.ComponentSMR - e.bench_smr).as_('Life Achieved')
q = self.q \
.inner_join(c).on_field('Floc') \
.left_join(e).on(
(a.Floc == e.floc) &
((b.Model == e.model) | (d.ModelBase == e.model_base) | (d.EquipClass == e.equip_class))) \
.orderby(a.Unit, a.DateAdded, c.Modifier, a.GroupCO)
f.set_self(vars())
self.default_dtypes |= f.dtypes_dict(
'Int64', ['Bench SMR', 'Life Achieved', 'Install SMR'])
def process_df(self, df):
"""Expand nested dicts of samples/flags to full columns"""
# drop row number col
if 'rn' in df.columns:
df = df.drop(columns=['rn'])
def expand_dict(df, col, suff):
return df.join(
pd.DataFrame(df.pop(col).apply(
json.loads).tolist()).add_suffix(suff))
# save full df with flags for styling
df = df \
.pipe(expand_dict, col='test_results', suff='') \
.pipe(expand_dict, col='test_flags', suff='_fg')
# set iso/opc cols to Int64
suffix = '_fg'
int_cols = [
col for col in df.columns if 'iso_' in col and not 'count' in col
]
opc_cols = [col for col in df.columns if 'opc_' in col]
int_cols.extend(opc_cols)
int_cols.extend(
['cutting', 'sliding', 'fatigue', 'non_metal', 'fibers'])
int_cols = [col for col in int_cols if not suffix in col]
self.default_dtypes.update(**f.dtypes_dict('Int64', int_cols))
# remove spaces between \ for iso and opc cols
for col in ('opc', 'iso_count'):
if col in df.columns:
df[col] = df[col].str.replace(' ', '')
flagged_cols = [col for col in df.columns if suffix in col]
self.flagged_cols = flagged_cols
self.df_flags = df.copy()
return df.drop(columns=flagged_cols) \
.replace('', pd.NA)
def __init__(self, **kw):
super().__init__(**kw)
limit_top = None
self.default_dtypes |= f.dtypes_dict('Int64',
['unit_smr', 'component_smr'])
a, b, c = self.select_table, T('UnitId'), T('EquipType')
# cols = [a.star]
cols = [
a.unit, a.component_id, a.modifier, a.sample_date, a.unit_smr,
a.oil_changed, a.sample_rank, a.test_results, a.test_flags
]
q = Query.from_(a) \
.left_join(b).on_field('Unit') \
.left_join(c).on(b.Model == c.Model) \
.orderby(a.unit, a.component_id, a.modifier) \
.orderby(a.sample_date, order=Order.desc)
f.set_self(vars())