def plot(cls_num):
os.chdir(os.path.join(wltpdb.mydir, wltpdb.samples_dir))
cls_name = class_name_from_num(cls_num)
data = data_meanN_gears(cls_num)
cols = data.keys()
assert len(cols) == 4, cols
parts = zip(model.get_class_part_names(), [
dict(data_fmt='1', data_kws=dict(color='#0000ff', markersize=4.8, ),
diff_kws=dict(linestyle=':', linewidth=4)
),
dict(data_fmt='_', data_kws=dict(color='#0033cc', markersize=4.8, fillstyle='none'),
diff_kws=dict(linestyle='-.',linewidth=4)
),
dict(data_fmt='o', data_kws=dict(color='#006699', markersize=4.8, fillstyle='none'),
diff_kws=dict(linestyle='-',linewidth=4)
),
dict(data_fmt='+', data_kws=dict(color='#009966', markersize=4.8, fillstyle='none'),
diff_kws=dict(linestyle='--', linewidth=4)
),
])
axes_tuple = None
for (part, kws) in parts:
try:
## veh part N/gear/Py/Heinz
X = data.loc[(slice(None), part), cols[0]]
Y = data.loc[(slice(None), part), cols[1]]
X_REF = data.loc[(slice(None), part), cols[2]]
Y_REF = data.loc[(slice(None), part), cols[3]]
except KeyError:
continue
axes_tuple, artist_tuple = plots.plot_xy_diffs_arrows(
X, Y, X_REF, Y_REF,
data_label='Python, %s'%part, diff_label='Diffs %s'%part,
diff_cmap=cm.cool, #@UndefinedVariable
title="%s: Python(arrow-heads) compared to AccessDb-2secAccel (arrow-tails)" % cls_name,
x_label=r'Mean Gear',
y_label='$Mean EngineSpeed [rpm]$',
axes_tuple=axes_tuple,
**kws
)
axes_tuple[0].legend(loc=1, fancybox=True, framealpha=0.5)
axes_tuple[1].legend(loc=2, fancybox=True, framealpha=0.5)
return data, axes_tuple
from wltp.test import wltp_db_tests as wltpdb
def prepare_data(gened_column, heinz_column):
gened_column='rpm'
heinz_column='n'
vehdata = wltpdb.aggregate_single_columns_means(gened_column, heinz_column)
vehdata['pmr'] = 1000.0 * vehdata['rated_power'] / vehdata['kerb_mass']
return vehdata.pmr, vehdata.gened, vehdata.heinz
if __name__ == '__main__':
os.chdir(os.path.join(wltpdb.mydir, wltpdb.samples_dir))
(X, Y, Y_REF) = prepare_data(gened_column='rpm', heinz_column='n')
kws = dict(data_fmt='ok', data_kws=dict(markersize=4.5, fillstyle='none'), )
plots.plot_xy_diffs_arrows(
X, Y, X, Y_REF,
title="Python(arrow-heads) vs AccessDb-2secAccel (arrow-tails)",
x_label=r'$PMR [W/kg]$',
y_label='EngineSpeed [rpm]',
ref_label='Access-db', data_label='Python',
mark_sections='classes',
**kws
)
plt.show()
from wltp.test import wltp_db_tests as wltpdb
def prepare_data(gened_column, heinz_column):
gened_column='rpm'
heinz_column='n'
vehdata = wltpdb.aggregate_single_columns_means(gened_column, heinz_column)
vehdata['pmr'] = 1000.0 * vehdata['rated_power'] / vehdata['kerb_mass']
return vehdata.pmr, vehdata.gened, vehdata.heinz
if __name__ == '__main__':
os.chdir(os.path.join(wltpdb.mydir, wltpdb.samples_dir))
(X, Y, Y_REF) = prepare_data(gened_column='rpm', heinz_column='n')
kws = dict(data_fmt='ok', data_kws=dict(markersize=4.5, fillstyle='none'), )
plots.plot_xy_diffs_arrows(
X, Y, X, Y_REF,
title="Python(arrow-heads) vs AccessDb-2secAccel (arrow-tails)",
x_label=r'$PMR [W/kg]$',
y_label='EngineSpeed [rpm]',
ref_label='Access-db', data_label='Python',
mark_sections='classes',
**kws
)
plt.show()
def prepare_data(gened_column, heinz_column):
gened_column = "rpm"
heinz_column = "n"
vehdata = wltpdb.aggregate_single_columns_means(gened_column, heinz_column)
vehdata["pmr"] = 1000.0 * vehdata["rated_power"] / vehdata["kerb_mass"]
return vehdata.pmr, vehdata.gened, vehdata.heinz
if __name__ == "__main__":
os.chdir(os.path.join(wltpdb.mydir, wltpdb.samples_dir))
(X, Y, Y_REF) = prepare_data(gened_column="rpm", heinz_column="n")
kws = dict(data_fmt="ok", data_kws=dict(markersize=4.5, fillstyle="none"))
plots.plot_xy_diffs_arrows(
X,
Y,
X,
Y_REF,
title="Python(arrow-heads) vs AccessDb-2secAccel (arrow-tails)",
x_label=r"$PMR [W/kg]$",
y_label="EngineSpeed [rpm]",
ref_label="Access-db",
data_label="Python",
mark_sections="classes",
**kws)
plt.show()