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Incorporate Julia Putko's changes #86

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merged 14 commits into from
Jun 16, 2022
Merged

Incorporate Julia Putko's changes #86

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4afbc5e
pyglider additions, adding argopandas as submodule
juliaputko Apr 27, 2022
cfedc65
Removed argopandas from pyglider
Jun 10, 2022
6b92f0e
Merge branch 'main' of https://github.com/c-proof/pyglider into jp_dev
Jun 15, 2022
2a5e8fd
Merge branch 'main' of https://github.com/c-proof/pyglider into jp_dev
Jun 15, 2022
24ed799
Changing plotting.py to correct an issue with date offsets
Jun 15, 2022
89bd103
Typo in fix for plotting.py
Jun 15, 2022
54eb3a1
Addressing Jody's comments on the PR
Jun 15, 2022
284f573
Removed some of Julia's changes from slocum.py
Jun 15, 2022
15d37d4
Removed the argopandas directory
Jun 15, 2022
4e1b8c6
Reverting changes to seaexplorer.py and slocum.py
Jun 15, 2022
caace07
Reverting changes to plotting.py
Jun 15, 2022
339093b
Removed mapplotting.py and website.py from the PR
Jun 15, 2022
f516ee7
Removed cmap.set_over("black") from plotting.py
Jun 15, 2022
0d3a214
Reverting changes in plotting.py
Jun 15, 2022
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206 changes: 182 additions & 24 deletions pyglider/plotting.py
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Original file line number Diff line number Diff line change
Expand Up @@ -50,24 +50,54 @@ def timeseries_plots(fname, plottingyaml):
except:
pass

with xr.open_dataset(fname) as ds0:
#with xr.open_dataset(fname) as ds0: #jpnote commented
with xr.open_dataset(fname, decode_times=True) as ds0:

ds = ds0.sel(time=slice(starttime, None))
# map!
fig, axs = plt.subplots(3, 1, gridspec_kw={'height_ratios': [3, 1, 1]})
# fig, axs = plt.subplots(3, 1, gridspec_kw={'height_ratios': [3, 1, 1]})
fig1, axs1 = plt.subplots()
# ax = axs[0]
ax = axs1
good = (ds.longitude < -125) ## jp added
ax.plot(ds.longitude[good], ds.latitude[good], '.',markersize=1)

#ax.plot(ds.longitude, ds.latitude, '.') #jp commented
# ax.set_aspect(1 / np.cos(np.deg2rad(ds.latitude.mean())))
fig1.set_size_inches(7.5, 7.5)
ax.set_ylabel('Lat [degrees north]')
ax.set_xlabel('Lon [degrees west]')
ax.grid()
fig1.savefig(config['figdir'] + '/jp1_map%s.png'%ds.attrs['deployment_name'], dpi=200)

#locator = mdates.AutoDateLocator()
#formatter = mdates.ConciseDateFormatter(locator)
#formatter.offset_formats = ['',
# '',
# '',]

#fig, axs = plt.subplots(3, 1, gridspec_kw={'height_ratios': [3, 1, 1]})
fig, axs = plt.subplots(2, 1, gridspec_kw={'height_ratios': [1, 1]})
# ax = axs[1]
ax = axs[0]
ax.plot(ds.longitude, ds.latitude, '.')
ax.set_aspect(1 / np.cos(np.deg2rad(ds.latitude.mean())))
ax.plot(ds.time[good], ds.longitude[good], '.',markersize=1)
# # ax.plot(ds.time, ds.longitude, '.') #jp commented
ax.set_ylabel('Lon [degrees west]')
ax.grid()
# ax.xaxis.set_major_locator(locator)
# ax.xaxis.set_major_formatter(formatter)

# ax = axs[2]
ax = axs[1]
ax.plot(ds.time[good], ds.latitude[good], '.',markersize=1)
# # ax.plot(ds.time, ds.latitude, '.')#jp commented
ax.set_ylabel('Lat [degrees north]')
ax.set_xlabel('Lon [degrees east]')
ax.grid()

ax = axs[1]
ax.plot(ds.time, ds.longitude, '.')
ax.set_ylabel('Lon [degrees east]')
# ax.xaxis.set_major_locator(locator)
# ax.xaxis.set_major_formatter(formatter)

ax = axs[2]
ax.plot(ds.time, ds.latitude, '.')
ax.set_ylabel('Lat [degrees north]')
fig.savefig(config['figdir'] + '/map%s.png'%ds.attrs['deployment_name'], dpi=200)
fig.savefig(config['figdir'] + '/jp2_map%s.png'%ds.attrs['deployment_name'], dpi=200)

# timeseries of things....
_log.info('Plotting timeseries data')
Expand All @@ -78,18 +108,125 @@ def timeseries_plots(fname, plottingyaml):
sharex=True, sharey=False)
axs = axs.flat
for n, k in enumerate(keys):
a = [0,1,2,3]
b = [4,5]
_log.debug(f'key {k}')
# print(f'key {k}')
if config['timeseries'][k] == 'True':
ax = axs[n]
#convert 9999 to nan
ds[k] = ds[k].where(ds[k] != 9999, np.nan)
#ValueError: zero-size array to reduction operation minimum which has no identity
good = np.where(~np.isnan(ds[k]))[0]
pc = ax.plot(ds.time[good], ds[k][good], '.')
min, max = _autoclim(ds[k][good])
ax.set_ylim(min, max)
ax.set_title(ds[k].attrs['long_name'] + ' [' +
ds[k].attrs['units'] + ']', loc='left', fontsize=9)

if good.size != 0:

pc = ax.plot(ds.time[good], ds[k][good], '.',markersize=1)
min, max = _autoclim(ds[k][good])
ax.set_ylim(min, max)
ax.grid()

ax.set_ylabel(ds[k].attrs['long_name'] + ' [' +
ds[k].attrs['units'] + ']')
if n in a:
ax.xaxis.set_tick_params(labelbottom=True)
#ax.set_title(ds[k].attrs['long_name'] + ' [' +
# ds[k].attrs['units'] + ']', loc='left', fontsize=9)
# if n in b:
#jpnote: offset format fix -remove hanging date
# locator = mdates.AutoDateLocator()
# formatter = mdates.ConciseDateFormatter(locator)
# formatter.offset_formats = ['',
# '',
# '',]
# ax.xaxis.set_major_locator(locator)
# ax.xaxis.set_major_formatter(formatter)
#end offset format fix
ax.set_title(ds[k].attrs['long_name'] + ' over time', loc='left', fontsize=9)
fig.savefig(config['figdir'] + '/ts_%s.png'%ds.attrs['deployment_name'], dpi=200)

_log.info('Plotting timeseries data')
keys = config['timeseries'].keys()
N = len(keys)
if 1:
fig, axs = plt.subplots(int(N / 2), 2, figsize=(7, 12),
sharex=False, sharey=False)
axs = axs.flat
for n, k in enumerate(keys):
_log.debug(f'key {k}')
print(f'key {k}')
if config['timeseries'][k] == 'True':
ax = axs[n]
#convert 9999 to nan
# ds[k] = ds[k].where(ds[k] != 9999, np.nan)
# ds[k] = ds[k].where(ds[k] != 0, np.nan)
#ValueError: zero-size array to reduction operation minimum which has no identity
# good = np.where(~np.isnan(ds[k]))[0]

if ax == axs[1]:
ax.set_xlim(30,35) #jp hardcode?
# ds[k] = ds[k].where(ds[k] != 0, np.nan)
# good = np.where(~np.isnan(ds[k]))[0]
if ax == axs[3]:
ax.set_xlim(0,0.004) #jp hardcode
if ax == axs[4]:
ax.set_xlim(0,7.5)
if ax == axs[5]:
ax.set_xlim(0,4)

good = np.where(~np.isnan(ds[k]))[0]
pc = ax.plot(ds[k][good],ds.depth[good], '.',markersize=1)
ax.grid()
ax.set_ylabel('DEPTH [m]')
ax.xaxis.set_tick_params(labelbottom=True)
ax.invert_yaxis()

ax.set_xlabel(ds[k].attrs['long_name'] + ' [' +
ds[k].attrs['units'] + ']')
ax.set_title(ds[k].attrs['long_name'] + ' over depth', loc='left', fontsize=9)

fig.savefig(config['figdir'] + '/vv_%s.png'%ds.attrs['deployment_name'], dpi=200)


# _log.info('Plotting timeseries data')
keys = config['timeseries'].keys()
# N = len(keys)
##water temp v depth plot
if 1:
#fig, axs = plt.subplots(int(N / 2), 2,figsize=(7.5, 7),
# sharex=True, sharey=False)
fig, axs = plt.subplots(1, 1,figsize=(7.5, 7),
sharex=True, sharey=False)
# axs = axs.flat
for n, k in enumerate(keys):
if n == 0:
a = [0,1,2,3]
b = [4,5]
#_log.debug(f'key {k}')
#print(f'key {k}')
if config['timeseries'][k] == 'True':
ax = axs

good = np.where(~np.isnan(ds[k]))[0]
pc = ax.scatter(ds.temperature[good], ds.depth[good], c=ds.longitude[good], cmap='gray', s=1)

ax.grid()
ax.set_ylabel('DEPTH [m]')
x = np.random.randint(low=0, high=10, size=13)
plt.xticks(np.arange(4, len(x)+1, 1))

ax.set_title('water temp over depth')

ax.set_xlabel(ds[k].attrs['long_name'] + ' [' +
ds[k].attrs['units'] + ']')
plt.gca().invert_yaxis()

cbar = fig.colorbar(pc, ax=axs)
cbar.ax.set_yticklabels(["{:.4}".format(i) for i in cbar.get_ticks()])
cbar.ax.set_ylabel('Longitude [degrees west]')
fig.savefig(config['figdir'] + '/jp_ts_%s.png'%ds.attrs['deployment_name'], dpi=200)


# colorline?
if 0:
fig, axs = plt.subplots(int(N / 2), 2, figsize=(7.5, 7),
Expand Down Expand Up @@ -156,6 +293,7 @@ def timeseries_plots(fname, plottingyaml):
fig, axs = plt.subplots(1, 2, constrained_layout=True, sharey=True)
ax = axs[0]

ds['oxygen_concentration'][ ds['oxygen_concentration']==9999]=np.nan
good = ~np.isnan(ds.salinity)
smin, smax = _autoclim(ds.salinity[good])
good = ~np.isnan(ds.temperature)
Expand All @@ -175,13 +313,14 @@ def timeseries_plots(fname, plottingyaml):
ax.set_ylabel('$T\ [^oC]$')
ax.set_xlim(smin, smax)
ax.set_ylim(tmin, tmax)

ax.grid()
try:
ax = axs[1]

ax.plot(ds['oxygen_concentration'], ds['temperature'],
'.', markersize=1)
ax.set_xlabel('$O^2\ [mmol/L]$')
ax.grid()
except:
pass
add_suptitle(fig, ds)
Expand Down Expand Up @@ -213,7 +352,8 @@ def grid_plots(fname, plottingyaml):
except:
pass

with xr.open_dataset(fname) as ds0:
#with xr.open_dataset(fname) as ds0: #jpnote changed
with xr.open_dataset(fname, decode_times=True) as ds0:
ds = ds0.sel(time=slice(starttime, None))
_log.debug(str(ds))

Expand All @@ -223,21 +363,29 @@ def grid_plots(fname, plottingyaml):
tmean = ds.temperature.mean(axis=1)
indmax = np.where(~np.isnan(tmean))[0][-1]
depmax = ds.depth[indmax]
fig, axs = plt.subplots(math.ceil(N/2), 2, figsize=(7.5, 7),
# fig, axs = plt.subplots(math.ceil(N/2), 2, figsize=(7.5, 7), #jpnote changed
# sharex=True, sharey=True)
fig, axs = plt.subplots(int(N / 2), 2, figsize=(7.5, 7),
sharex=True, sharey=True)
axs = axs.flat
for n, k in enumerate(keys):
_log.debug(f'key {k}')

pconf = config['pcolor']['vars'][k]
_log.debug(pconf)
cmap = pconf.get('cmap', 'viridis')

cmap = pconf.get('cmap','viridis')
vmin = pconf.get('vmin', None)
vmax = pconf.get('vmax', None)

ax = axs[n]
locator = mdates.AutoDateLocator(minticks=3, maxticks=7)
ax.yaxis.set_tick_params(labelbottom=True)
ax.xaxis.set_tick_params(labelbottom=True)
locator = mdates.AutoDateLocator()
formatter = mdates.ConciseDateFormatter(locator)
formatter.offset_formats = ['',
'',
'',]
ax.xaxis.set_major_locator(locator)
ax.xaxis.set_major_formatter(formatter)

Expand All @@ -247,13 +395,20 @@ def grid_plots(fname, plottingyaml):
if vmax is not None:
max = vmax
# make time windows:
if ax == axs[0]:
vmax = 300
ax.set_ylim([300, 0])

vmax = 300
# get good profiles. i.e. those w data
ind = np.where(np.sum(np.isfinite(ds[k].values), axis=0)>10)[0]
_log.debug(ind)
_log.debug(len(ds.time))
if len(ind) > 1:
time = ds.time[ind[1:]] + np.diff(ds.time[ind]) / 2
# print('tim1',time)
time = np.hstack((time[0] - (time[1]-time[0]) / 2, time))
# print('tim2',time)
depth = ds.depth[:-1] - np.diff(ds.depth)
depth = np.hstack((depth, depth[-1] + np.diff(ds.depth)[-1]))
pc = ax.pcolormesh(time, depth, ds[k][:, ind],
Expand All @@ -263,9 +418,12 @@ def grid_plots(fname, plottingyaml):

_log.debug(ds[k])

fig.colorbar(pc, ax=ax, extend='both', shrink=0.6)
# fig.colorbar(pc, ax=ax, extend='both', shrink=0.6) #jpnote commented
cbar = fig.colorbar(pc, ax=ax, extend='both', shrink=0.6)
cbar.ax.set_ylabel(ds[k].attrs['long_name'] + ' [' +
ds[k].attrs['units'] + ']', fontsize=9)
ax.set_title(ds[k].attrs['long_name'] + ' [' +
ds[k].attrs['units'] + ']', loc='left', fontsize=9)
ds[k].attrs['units'] + ']', loc='left', fontsize=9) #jpnote commented
t0 = ds.time[0]
t1 = ds.time[-1]
ax.set_xlim([t0, t1])
Expand Down
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