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hhourston
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try again to fix rounding of instrument_depth variable in pcolor plot titles and names
1 parent 2d0c207 commit 4172ba8

1 file changed

Lines changed: 29 additions & 25 deletions

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‎pycurrents_ADCP_processing/plot_westcoast_nc_LX.py‎

Lines changed: 29 additions & 25 deletions
Original file line numberDiff line numberDiff line change
@@ -564,6 +564,8 @@ def make_pcolor_ne(nc: xr.Dataset, dest_dir, time_lim, bin_depths_lim,
564564
else:
565565
vminvmax = colourmap_lim
566566

567+
instrument_depth = np.round(float(nc.instrument_depth.data), 1)
568+
567569
fig = plt.figure(figsize=(13.75, 10))
568570
ax = fig.add_subplot(2, 1, 1)
569571

@@ -577,17 +579,17 @@ def make_pcolor_ne(nc: xr.Dataset, dest_dir, time_lim, bin_depths_lim,
577579
ax.set_title(
578580
'ADCP ({}North, 30h average) {}-{} {}m{}'.format(
579581
magnetic, nc.attrs['station'], nc.attrs['deployment_number'],
580-
np.round(nc.instrument_depth.data, 1), resampled_str), fontsize=14)
582+
instrument_depth, resampled_str), fontsize=14)
581583
elif filter_type == 'Godin':
582584
ax.set_title(
583585
'ADCP ({}North, Godin Filtered) {}-{} {}m{}'.format(
584586
magnetic, nc.attrs['station'], nc.attrs['deployment_number'],
585-
np.round(nc.instrument_depth.data, 1), resampled_str), fontsize=14)
587+
instrument_depth, resampled_str), fontsize=14)
586588
elif filter_type == 'raw':
587589
ax.set_title(
588590
'ADCP ({}North, raw) {}-{} {}m{}'.format(
589591
magnetic, nc.attrs['station'], nc.attrs['deployment_number'],
590-
np.round(nc.instrument_depth.data, 1), resampled_str), fontsize=14)
592+
instrument_depth, resampled_str), fontsize=14)
591593
else:
592594
ValueError('Not a recognized data type; choose one of \'raw\', \'30h\' or \'Godin\'')
593595

@@ -604,16 +606,16 @@ def make_pcolor_ne(nc: xr.Dataset, dest_dir, time_lim, bin_depths_lim,
604606
if 'h' in filter_type: # xxh-average; e.g. '30h', '35h'
605607
ax2.set_title('ADCP ({}East, {} average) {}-{} {}m{}'.format(
606608
magnetic, filter_type, nc.attrs['station'], nc.attrs['deployment_number'],
607-
np.round(nc.instrument_depth.data, 1), resampled_str), fontsize=14)
609+
instrument_depth, resampled_str), fontsize=14)
608610
elif filter_type == 'Godin':
609611
ax2.set_title('ADCP ({}East, Godin Filtered) {}-{} {}m{}'.format(
610612
magnetic, nc.attrs['station'], nc.attrs['deployment_number'],
611-
np.round(nc.instrument_depth.data, 1), resampled_str), fontsize=14)
613+
instrument_depth, resampled_str), fontsize=14)
612614
elif filter_type == 'raw':
613615
ax2.set_title(
614616
'ADCP ({}East, raw) {}-{} {}m{}'.format(
615617
magnetic, nc.attrs['station'], nc.attrs['deployment_number'],
616-
np.round(nc.instrument_depth.data, 1), resampled_str), fontsize=14)
618+
instrument_depth, resampled_str), fontsize=14)
617619

618620
ax2.invert_yaxis()
619621

@@ -626,12 +628,12 @@ def make_pcolor_ne(nc: xr.Dataset, dest_dir, time_lim, bin_depths_lim,
626628
if level0:
627629
plot_name = plot_dir + '{}-{}_{}_{}m-magn_NE_{}{}.png'.format(
628630
nc.attrs['station'], nc.attrs['deployment_number'], nc.instrument_serial_number.data,
629-
int(np.round(nc.instrument_depth.data)), filter_type, resampled_4fname
631+
int(np.round(instrument_depth)), filter_type, resampled_4fname
630632
)
631633
else:
632634
plot_name = plot_dir + '{}-{}_{}_{}m-NE_{}{}.png'.format(
633635
nc.attrs['station'], nc.attrs['deployment_number'], nc.instrument_serial_number.data,
634-
int(np.round(nc.instrument_depth.data)), filter_type, resampled_4fname
636+
int(np.round(instrument_depth)), filter_type, resampled_4fname
635637
)
636638
fig.savefig(plot_name)
637639
plt.close()
@@ -730,11 +732,11 @@ def determine_dom_angle(u_true, v_true):
730732
return along_angle, cross_angle
731733

732734

733-
def make_pcolor_ac(data: xr.Dataset, dest_dir, time_lim, bin_depths_lim, ns_lim, ew_lim,
735+
def make_pcolor_ac(nc: xr.Dataset, dest_dir, time_lim, bin_depths_lim, ns_lim, ew_lim,
734736
filter_type='raw', along_angle=None, colourmap_lim=None, resampled=None):
735737
"""
736738
Function for plotting north and east velocities from ADCP data.
737-
:param data: ADCP dataset from a netCDF file read in using the xarray package
739+
:param nc: ADCP dataset from a netCDF file read in using the xarray package
738740
:param dest_dir: name of directory for containing output files
739741
:param time_lim: cleaned time data; array type
740742
:param bin_depths_lim: cleaned bin depth data; array type
@@ -767,6 +769,8 @@ def make_pcolor_ac(data: xr.Dataset, dest_dir, time_lim, bin_depths_lim, ns_lim,
767769
cross_angle = along_angle - 90 # deg
768770
# print(along_angle, cross_angle)
769771

772+
instrument_depth = np.round(float(nc.instrument_depth.data), 1)
773+
770774
u_along, u_cross = resolve_to_alongcross(ew_lim, ns_lim, along_angle)
771775
AS = u_along
772776
CS = u_cross
@@ -789,19 +793,19 @@ def make_pcolor_ac(data: xr.Dataset, dest_dir, time_lim, bin_depths_lim, ns_lim,
789793
# XXh-type filter (e.g., 30h rolling mean, etc)
790794
ax1.set_title(
791795
'ADCP (along, {} average) {}$^\circ$ (CCW from E) {}-{} {}m{}'.format(
792-
filter_type, along_angle, data.attrs['station'], data.attrs['deployment_number'],
793-
np.round(data.instrument_depth.data, 1), resampled_str),
796+
filter_type, along_angle, nc.attrs['station'], nc.attrs['deployment_number'],
797+
instrument_depth, resampled_str),
794798
fontsize=14)
795799
elif filter_type == 'Godin':
796800
ax1.set_title(
797801
'ADCP (along, Godin Filtered) {}$^\circ$ (CCW from E) {}-{} {}m{}'.format(
798-
along_angle, data.attrs['station'], data.attrs['deployment_number'],
799-
np.round(data.instrument_depth.data, 1), resampled_str),
802+
along_angle, nc.attrs['station'], nc.attrs['deployment_number'],
803+
instrument_depth, resampled_str),
800804
fontsize=14)
801805
elif filter_type == 'raw':
802806
ax1.set_title('ADCP (along, raw) {}$^\circ$ (CCW from E) {}-{} {}m{}'.format(
803-
along_angle, data.attrs['station'], data.attrs['deployment_number'],
804-
np.round(data.instrument_depth.data, 1), resampled_str),
807+
along_angle, nc.attrs['station'], nc.attrs['deployment_number'],
808+
instrument_depth, resampled_str),
805809
fontsize=14)
806810
else:
807811
ValueError('Not a recognized data type; choose one of \'raw\', \'30h\' or \'Godin\'')
@@ -819,34 +823,34 @@ def make_pcolor_ac(data: xr.Dataset, dest_dir, time_lim, bin_depths_lim, ns_lim,
819823
if 'h' in filter_type: # xxh-average; e.g. '30h', '35h'
820824
ax2.set_title(
821825
'ADCP (cross, {} average) {}$^\circ$ (CCW from E) {}-{} {}m{}'.format(
822-
filter_type, cross_angle, data.attrs['station'], data.attrs['deployment_number'],
823-
np.round(data.instrument_depth.data, 1), resampled_str),
826+
filter_type, cross_angle, nc.attrs['station'], nc.attrs['deployment_number'],
827+
instrument_depth, resampled_str),
824828
fontsize=14)
825829
elif filter_type == 'Godin':
826830
ax2.set_title(
827831
'ADCP (cross, Godin Filtered) {}$^\circ$ (CCW from E) {}-{} {}m{}'.format(
828-
str(cross_angle), data.attrs['station'], data.attrs['deployment_number'],
829-
np.round(data.instrument_depth.data, 1), resampled_str),
832+
str(cross_angle), nc.attrs['station'], nc.attrs['deployment_number'],
833+
instrument_depth, resampled_str),
830834
fontsize=14)
831835
elif filter_type == 'raw':
832836
ax2.set_title(
833837
'ADCP (cross, raw) {}$^\circ$ (CCW from E) {}-{} {}m{}'.format(
834-
str(cross_angle), data.attrs['station'], data.attrs['deployment_number'],
835-
np.round(data.instrument_depth.data, 1), resampled_str),
838+
str(cross_angle), nc.attrs['station'], nc.attrs['deployment_number'],
839+
instrument_depth, resampled_str),
836840
fontsize=14)
837841
else:
838842
ValueError('Not a recognized data type; choose one of \'raw\', \'30h\' or \'Godin\'')
839843

840844
ax2.invert_yaxis()
841845

842846
# Create plots subfolder if not made already
843-
plot_dir = get_plot_dir(data.filename, dest_dir)
847+
plot_dir = get_plot_dir(nc.filename, dest_dir)
844848
if not os.path.exists(plot_dir):
845849
os.makedirs(plot_dir)
846850

847851
plot_name = '{}-{}_{}_{}m-AC_{}{}.png'.format(
848-
data.attrs['station'], data.attrs['deployment_number'], data.instrument_serial_number.data,
849-
int(np.round(data.instrument_depth.data)), filter_type, resampled_4fname
852+
nc.attrs['station'], nc.attrs['deployment_number'], nc.instrument_serial_number.data,
853+
int(np.round(instrument_depth)), filter_type, resampled_4fname
850854
)
851855
fig.savefig(plot_dir + plot_name)
852856
plt.close()

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