def test_group_single(master=False, remove=True, show=False):
name = osjoin(MASTER, 'group_single_master') if master else 'group_single'
# Make the plot
fcp.boxplot(df=df,
y='Value',
groups='Batch',
show=SHOW,
filename=name + '.png',
inline=False,
jitter=False)
# Compare with master
if master:
return
elif show:
os.startfile(osjoin(MASTER, name + '_master.png'))
os.startfile(name + '.png')
compare = utl.img_compare(name + '.png',
osjoin(MASTER, name + '_master.png'),
show=True)
else:
compare = utl.img_compare(name + '.png',
osjoin(MASTER, name + '_master.png'))
if remove:
os.remove(name + '.png')
assert not compare
def test_groups_boxplot(master=False, remove=True, show=False):
name = osjoin(MASTER,
'groups_boxplot_master') if master else 'groups_boxplot'
# Make the plot
df_box = pd.read_csv(
osjoin(os.path.dirname(fcp.__file__), 'tests', 'fake_data_box.csv'))
fcp.boxplot(df=df_box,
y='Value',
groups=['Batch', 'Sample'],
legend='Region',
filename=name + '.png',
inline=False,
jitter=False)
# Compare with master
if master:
return
elif show:
os.startfile(osjoin(MASTER, name + '_master.png'))
os.startfile(name + '.png')
else:
compare = utl.img_compare(name + '.png',
osjoin(MASTER, name + '_master.png'))
if remove:
os.remove(name + '.png')
assert not compare
def test_violin_box_off(master=False, remove=True, show=False):
name = osjoin(MASTER,
'violin_box_off_master') if master else 'violin_box_off'
# Make the plot
fcp.boxplot(df=df,
y='Value',
groups=['Batch', 'Sample'],
show=SHOW,
violin=True,
violin_box_on=False,
violin_markers=True,
jitter=False,
filename=name + '.png',
inline=False)
# Compare with master
if master:
return
elif show:
os.startfile(osjoin(MASTER, name + '_master.png'))
os.startfile(name + '.png')
compare = utl.img_compare(name + '.png',
osjoin(MASTER, name + '_master.png'),
show=True)
else:
compare = utl.img_compare(name + '.png',
osjoin(MASTER, name + '_master.png'))
if remove:
os.remove(name + '.png')
assert not compare
def test_range_lines(master=False, remove=True, show=False):
name = osjoin(MASTER, 'range_lines_master') if master else 'range_lines'
# Make the plot
fcp.boxplot(df=df,
y='Value',
groups=['Batch', 'Sample'],
show=SHOW,
box_range_lines=False,
ax_size=[300, 300],
filename=name + '.png',
inline=False,
jitter=False)
# Compare with master
if master:
return
elif show:
os.startfile(osjoin(MASTER, name + '_master.png'))
os.startfile(name + '.png')
compare = utl.img_compare(name + '.png',
osjoin(MASTER, name + '_master.png'),
show=True)
else:
compare = utl.img_compare(name + '.png',
osjoin(MASTER, name + '_master.png'))
if remove:
os.remove(name + '.png')
assert not compare
def test_mean_diamonds(master=False, remove=True, show=False):
name = osjoin(MASTER,
'mean_diamonds_master') if master else 'mean_diamonds'
# Make the plot
fcp.boxplot(df=df,
y='Value',
groups=['Batch', 'Sample'],
show=SHOW,
mean_diamonds=True,
conf_coeff=0.95,
filename=name + '.png',
inline=False,
jitter=False)
# Compare with master
if master:
return
elif show:
os.startfile(osjoin(MASTER, name + '_master.png'))
os.startfile(name + '.png')
compare = utl.img_compare(name + '.png',
osjoin(MASTER, name + '_master.png'),
show=True)
else:
compare = utl.img_compare(name + '.png',
osjoin(MASTER, name + '_master.png'))
if remove:
os.remove(name + '.png')
assert not compare
def test_grid_wrap_y_no_share(master=False, remove=True, show=False):
name = osjoin(MASTER,
'grid_y-no-share_master') if master else 'grid_y-no-share'
# Make the plot
df['Value*2'] = 2 * df['Value']
fcp.boxplot(df=df,
y=['Value', 'Value*2'],
groups=['Batch', 'Sample', 'Region'],
wrap='y',
show=SHOW,
ax_size=[300, 300],
share_y=False,
filename=name + '.png',
inline=False,
jitter=False)
# Compare with master
if master:
return
elif show:
os.startfile(osjoin(MASTER, name + '_master.png'))
os.startfile(name + '.png')
compare = utl.img_compare(name + '.png',
osjoin(MASTER, name + '_master.png'),
show=True)
else:
compare = utl.img_compare(name + '.png',
osjoin(MASTER, name + '_master.png'))
if remove:
os.remove(name + '.png')
assert not compare
def test_simple(master=False, remove=True, show=False):
name = osjoin(MASTER, 'simple_master') if master else 'simple'
# Make the plot
fcp.boxplot(df=df,
y='Value',
show=SHOW,
tick_labels_minor=True,
grid_minor=True,
filename=name + '.png',
inline=False,
jitter=False)
# Compare with master
if master:
return
elif show:
os.startfile(osjoin(MASTER, name + '_master.png'))
os.startfile(name + '.png')
else:
compare = utl.img_compare(name + '.png',
osjoin(MASTER, name + '_master.png'))
if remove:
os.remove(name + '.png')
assert not compare
def test_boxplot_iqr(master=False, remove=True, show=False):
name = osjoin(MASTER, 'boxplot_iqr_master') if master else 'boxplot_iqr'
# Make the plot
fcp.boxplot(df=df_box,
y='Value',
groups=['Batch', 'Sample'],
filter='Batch==101',
show=SHOW,
ymin='1.5*iqr',
ymax='1.5*iqr',
filename=name + '.png',
inline=False,
jitter=False)
# Compare with master
if master:
return
elif show:
os.startfile(osjoin(MASTER, name + '_master.png'))
os.startfile(name + '.png')
compare = utl.img_compare(name + '.png',
osjoin(MASTER, name + '_master.png'),
show=True)
else:
compare = utl.img_compare(name + '.png',
osjoin(MASTER, name + '_master.png'))
if remove:
os.remove(name + '.png')
assert not compare
def test_violin_styled(master=False, remove=True, show=False):
name = osjoin(MASTER,
'violin_styled_master') if master else 'violin_styled'
# Make the plot
fcp.boxplot(df=df,
y='Value',
groups=['Batch', 'Sample'],
show=SHOW,
violin=True,
violin_fill_color='#eaef1a',
violin_fill_alpha=1,
violin_edge_color='#555555',
violin_edge_width=2,
violin_box_color='#ffffff',
violin_whisker_color='#ff0000',
violin_median_marker='+',
violin_median_color='#00ffff',
violin_median_size=10,
filename=name + '.png',
inline=False)
# Compare with master
if master:
return
elif show:
os.startfile(osjoin(MASTER, name + '_master.png'))
os.startfile(name + '.png')
compare = utl.img_compare(name + '.png',
osjoin(MASTER, name + '_master.png'),
show=True)
else:
compare = utl.img_compare(name + '.png',
osjoin(MASTER, name + '_master.png'))
if remove:
os.remove(name + '.png')
assert not compare
def test_marker_boxplot(master=False, remove=True, show=False):
name = osjoin(MASTER, 'boxplot_master') if master else 'boxplot'
# Make the plot
df_box = pd.read_csv(
osjoin(os.path.dirname(fcp.__file__), 'tests', 'fake_data_box.csv'))
fcp.boxplot(df=df_box,
y='Value',
groups=['Batch', 'Sample'],
show=SHOW,
box_fill_color=[0, 0, 1, 1, 2, 2],
box_fill_alpha=0.3,
box_edge_width=0,
marker_edge_color=[0, 0, 1, 1, 2, 2],
marker_type=['o', '+'],
box_whisker_color=[0, 0, 1, 1, 2, 2],
box_whisker_width=1,
jitter=False,
filename=name + '.png',
inline=False)
# Compare with master
if master:
return
elif show:
os.startfile(osjoin(MASTER, name + '_master.png'))
os.startfile(name + '.png')
compare = utl.img_compare(name + '.png',
osjoin(MASTER, name + '_master.png'),
show=True)
else:
compare = utl.img_compare(name + '.png',
osjoin(MASTER, name + '_master.png'))
if remove:
os.remove(name + '.png')
assert not compare
# Fig groups example
d = fcp.plot(df=df, x='Voltage', y='I [A]', leg_groups='Die',
fig_groups=['Substrate'],
row='Boost Level', col='Temperature [C]', ax_scale='logx',
ytrans=('pow',4), ymin=1E-8, ymax=1E-2, show=True) #issues here with ranges, ticks
d = fcp.plot(df=df, x='Voltage', y='I [A]', leg_groups='Die',
fig_groups=['Substrate', 'Target Wavelength'],
row='Boost Level', col='Temperature [C]', ax_scale='logx',
ytrans=('pow',4), ymin=1E-8, ymax=1E-2, show=True) #issues here with ranges, ticks
# Multiple y on same axis with filter
filt = 'Substrate=="Si" & Target_Wavelength==450 & Boost_Level==0.2 & ' \
'Temperature_C==25'
d = fcp.plot(df=df, x='Voltage', y=['I [A]', 'Voltage'], filter=filt,
leg_groups='Die', ylabel='Values', show=True)
# Multiple y on same axis with filter and twinx
filt = 'Substrate=="Si" & Target_Wavelength==450 & Boost_Level==0.2 & ' \
'Temperature_C==25'
d = fcp.plot(df=df, x='Voltage', y=['I [A]', 'Voltage'], filter=filt,
show=True, leg_groups='Die', ylabel='I [A]', ylabel2='Voltage')
# Boxplot test
d = fcp.boxplot(df=df_box, y='Value', groups=['Batch', 'Sample'], show=True)
d = fcp.boxplot(df=df_box, y='Value', groups=['Batch', 'Region'], row='Sample',
show=True, ax_size=[300,300])
# Contour test
d = fcp.contour(df=df_c, x='X', y='Y', z='Value')
d = fcp.plot(df=df,
x='Voltage',
y=['I [A]', 'Voltage'],
filter=filt,
leg_groups='Die',
ylabel='Values',
show=True)
# Multiple y on same axis with filter and twinx
filt = 'Substrate=="Si" & Target_Wavelength==450 & Boost_Level==0.2 & ' \
'Temperature_C==25'
d = fcp.plot(df=df,
x='Voltage',
y=['I [A]', 'Voltage'],
filter=filt,
show=True,
leg_groups='Die',
ylabel='I [A]',
ylabel2='Voltage')
# Boxplot test
d = fcp.boxplot(df=df_box, y='Value', groups=['Batch', 'Sample'], show=True)
d = fcp.boxplot(df=df_box,
y='Value',
groups=['Batch', 'Region'],
row='Sample',
show=True,
ax_size=[300, 300])
# Contour test
d = fcp.contour(df=df_c, x='X', y='Y', z='Value')
