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hhourstonhhourston
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try to fix rounding of instrument_depth variable ending in .5 in pcolor plot names
1 parent 4172ba8 commit 5f851e7

1 file changed

Lines changed: 53 additions & 74 deletions

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‎pycurrents_ADCP_processing/plot_westcoast_nc_LX.py‎

Lines changed: 53 additions & 74 deletions
Original file line numberDiff line numberDiff line change
@@ -575,24 +575,22 @@ def make_pcolor_ne(nc: xr.Dataset, dest_dir, time_lim, bin_depths_lim,
575575
cbar.set_label('Velocity [m s$^{-1}$]', fontsize=14)
576576
ax.set_ylabel('Depth [m]', fontsize=14)
577577

578-
if filter_type == '30h':
579-
ax.set_title(
580-
'ADCP ({}North, 30h average) {}-{} {}m{}'.format(
581-
magnetic, nc.attrs['station'], nc.attrs['deployment_number'],
582-
instrument_depth, resampled_str), fontsize=14)
578+
if 'h' in filter_type: # xxh-average; e.g. '30h', '35h'
579+
filter_type_title = '{} average'.format(filter_type)
583580
elif filter_type == 'Godin':
584-
ax.set_title(
585-
'ADCP ({}North, Godin Filtered) {}-{} {}m{}'.format(
586-
magnetic, nc.attrs['station'], nc.attrs['deployment_number'],
587-
instrument_depth, resampled_str), fontsize=14)
581+
filter_type_title = 'Godin filtered'
588582
elif filter_type == 'raw':
589-
ax.set_title(
590-
'ADCP ({}North, raw) {}-{} {}m{}'.format(
591-
magnetic, nc.attrs['station'], nc.attrs['deployment_number'],
592-
instrument_depth, resampled_str), fontsize=14)
583+
filter_type_title = filter_type
593584
else:
594585
ValueError('Not a recognized data type; choose one of \'raw\', \'30h\' or \'Godin\'')
595586

587+
ax.set_title(
588+
'ADCP ({}North, {}) {}-{} {}m{}'.format(
589+
magnetic, filter_type_title, nc.attrs['station'], nc.attrs['deployment_number'],
590+
instrument_depth, resampled_str
591+
), fontsize=14
592+
)
593+
596594
ax.invert_yaxis()
597595

598596
ax2 = fig.add_subplot(2, 1, 2)
@@ -603,19 +601,14 @@ def make_pcolor_ne(nc: xr.Dataset, dest_dir, time_lim, bin_depths_lim,
603601
cbar.set_label('Velocity [m s$^{-1}$]', fontsize=14)
604602

605603
ax2.set_ylabel('Depth [m]', fontsize=14)
606-
if 'h' in filter_type: # xxh-average; e.g. '30h', '35h'
607-
ax2.set_title('ADCP ({}East, {} average) {}-{} {}m{}'.format(
608-
magnetic, filter_type, nc.attrs['station'], nc.attrs['deployment_number'],
609-
instrument_depth, resampled_str), fontsize=14)
610-
elif filter_type == 'Godin':
611-
ax2.set_title('ADCP ({}East, Godin Filtered) {}-{} {}m{}'.format(
612-
magnetic, nc.attrs['station'], nc.attrs['deployment_number'],
613-
instrument_depth, resampled_str), fontsize=14)
614-
elif filter_type == 'raw':
615-
ax2.set_title(
616-
'ADCP ({}East, raw) {}-{} {}m{}'.format(
617-
magnetic, nc.attrs['station'], nc.attrs['deployment_number'],
618-
instrument_depth, resampled_str), fontsize=14)
604+
605+
ax2.set_title(
606+
'ADCP ({}East, {}) {}-{} {}m{}'.format(
607+
magnetic, filter_type_title, nc.attrs['station'], nc.attrs['deployment_number'],
608+
instrument_depth, resampled_str
609+
),
610+
fontsize=14
611+
)
619612

620613
ax2.invert_yaxis()
621614

@@ -626,15 +619,15 @@ def make_pcolor_ne(nc: xr.Dataset, dest_dir, time_lim, bin_depths_lim,
626619
os.makedirs(plot_dir)
627620

628621
if level0:
629-
plot_name = plot_dir + '{}-{}_{}_{}m-magn_NE_{}{}.png'.format(
630-
nc.attrs['station'], nc.attrs['deployment_number'], nc.instrument_serial_number.data,
631-
int(np.round(instrument_depth)), filter_type, resampled_4fname
632-
)
622+
vel_type = 'magn_NE'
633623
else:
634-
plot_name = plot_dir + '{}-{}_{}_{}m-NE_{}{}.png'.format(
635-
nc.attrs['station'], nc.attrs['deployment_number'], nc.instrument_serial_number.data,
636-
int(np.round(instrument_depth)), filter_type, resampled_4fname
637-
)
624+
vel_type = 'NE'
625+
626+
# Have to round instrument depth twice due to behaviour of the float
627+
plot_name = plot_dir + '{}-{}_{}_{}m_{}_{}{}.png'.format(
628+
nc.attrs['station'], nc.attrs['deployment_number'], nc.instrument_serial_number.data,
629+
int(np.round(np.round(instrument_depth, 1))), vel_type, filter_type, resampled_4fname
630+
)
638631
fig.savefig(plot_name)
639632
plt.close()
640633

@@ -781,65 +774,50 @@ def make_pcolor_ac(nc: xr.Dataset, dest_dir, time_lim, bin_depths_lim, ns_lim, e
781774
vminvmax = colourmap_lim
782775

783776
fig = plt.figure(figsize=(13.75, 10))
784-
ax1 = fig.add_subplot(2, 1, 1)
777+
ax1 = fig.add_subplot(2, 1, 1) # along-shore subplot
785778

786779
f1 = ax1.pcolormesh(time_lim, bin_depths_lim, AS[:, :], cmap='RdBu_r', vmin=vminvmax[0],
787780
vmax=vminvmax[1], shading='auto')
788781
cbar = fig.colorbar(f1, shrink=0.8)
789782
cbar.set_label('Velocity [m s$^{-1}$]', fontsize=14)
790783

791784
ax1.set_ylabel('Depth [m]', fontsize=14)
792-
if 'h' in filter_type:
793-
# XXh-type filter (e.g., 30h rolling mean, etc)
794-
ax1.set_title(
795-
'ADCP (along, {} average) {}$^\circ$ (CCW from E) {}-{} {}m{}'.format(
796-
filter_type, along_angle, nc.attrs['station'], nc.attrs['deployment_number'],
797-
instrument_depth, resampled_str),
798-
fontsize=14)
785+
786+
if 'h' in filter_type: # xxh-average; e.g. '30h', '35h'
787+
filter_type_title = '{} average'.format(filter_type)
799788
elif filter_type == 'Godin':
800-
ax1.set_title(
801-
'ADCP (along, Godin Filtered) {}$^\circ$ (CCW from E) {}-{} {}m{}'.format(
802-
along_angle, nc.attrs['station'], nc.attrs['deployment_number'],
803-
instrument_depth, resampled_str),
804-
fontsize=14)
789+
filter_type_title = 'Godin filtered'
805790
elif filter_type == 'raw':
806-
ax1.set_title('ADCP (along, raw) {}$^\circ$ (CCW from E) {}-{} {}m{}'.format(
807-
along_angle, nc.attrs['station'], nc.attrs['deployment_number'],
808-
instrument_depth, resampled_str),
809-
fontsize=14)
791+
filter_type_title = filter_type
810792
else:
811793
ValueError('Not a recognized data type; choose one of \'raw\', \'30h\' or \'Godin\'')
812794

795+
ax1.set_title(
796+
'ADCP (along, {}) {}$^\circ$ (CCW from E) {}-{} {}m{}'.format(
797+
filter_type_title, along_angle, nc.attrs['station'], nc.attrs['deployment_number'],
798+
instrument_depth, resampled_str
799+
),
800+
fontsize=14
801+
)
802+
813803
ax1.invert_yaxis()
814804

815-
ax2 = fig.add_subplot(2, 1, 2)
805+
ax2 = fig.add_subplot(2, 1, 2) # cross-shore subplot
816806

817807
f2 = ax2.pcolormesh(time_lim, bin_depths_lim, CS[:, :], cmap='RdBu_r', vmin=vminvmax[0],
818808
vmax=vminvmax[1], shading='auto')
819809
cbar = fig.colorbar(f2, shrink=0.8)
820810
cbar.set_label('Velocity [m s$^{-1}$]', fontsize=14)
821811

822812
ax2.set_ylabel('Depth [m]', fontsize=14)
823-
if 'h' in filter_type: # xxh-average; e.g. '30h', '35h'
824-
ax2.set_title(
825-
'ADCP (cross, {} average) {}$^\circ$ (CCW from E) {}-{} {}m{}'.format(
826-
filter_type, cross_angle, nc.attrs['station'], nc.attrs['deployment_number'],
827-
instrument_depth, resampled_str),
828-
fontsize=14)
829-
elif filter_type == 'Godin':
830-
ax2.set_title(
831-
'ADCP (cross, Godin Filtered) {}$^\circ$ (CCW from E) {}-{} {}m{}'.format(
832-
str(cross_angle), nc.attrs['station'], nc.attrs['deployment_number'],
833-
instrument_depth, resampled_str),
834-
fontsize=14)
835-
elif filter_type == 'raw':
836-
ax2.set_title(
837-
'ADCP (cross, raw) {}$^\circ$ (CCW from E) {}-{} {}m{}'.format(
838-
str(cross_angle), nc.attrs['station'], nc.attrs['deployment_number'],
839-
instrument_depth, resampled_str),
840-
fontsize=14)
841-
else:
842-
ValueError('Not a recognized data type; choose one of \'raw\', \'30h\' or \'Godin\'')
813+
814+
ax2.set_title(
815+
'ADCP (cross, {}) {}$^\circ$ (CCW from E) {}-{} {}m{}'.format(
816+
filter_type_title, str(cross_angle), nc.attrs['station'], nc.attrs['deployment_number'],
817+
instrument_depth, resampled_str
818+
),
819+
fontsize=14
820+
)
843821

844822
ax2.invert_yaxis()
845823

@@ -848,9 +826,10 @@ def make_pcolor_ac(nc: xr.Dataset, dest_dir, time_lim, bin_depths_lim, ns_lim, e
848826
if not os.path.exists(plot_dir):
849827
os.makedirs(plot_dir)
850828

851-
plot_name = '{}-{}_{}_{}m-AC_{}{}.png'.format(
829+
# have to round instrument depth twice due to behaviour of float
830+
plot_name = '{}-{}_{}_{}m_AC_{}{}.png'.format(
852831
nc.attrs['station'], nc.attrs['deployment_number'], nc.instrument_serial_number.data,
853-
int(np.round(instrument_depth)), filter_type, resampled_4fname
832+
int(np.round(np.round(instrument_depth, 1))), filter_type, resampled_4fname
854833
)
855834
fig.savefig(plot_dir + plot_name)
856835
plt.close()

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