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pyglider additions, adding argopandas as submodule #51

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Jun 16, 2022
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pyglider additions, adding argopandas as submodule #51

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3 changes: 3 additions & 0 deletions .gitmodules
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Original file line number Diff line number Diff line change
@@ -0,0 +1,3 @@
[submodule "pyglider/pyglider/argopandas"]
path = pyglider/pyglider/argopandas
url = [email protected]:ArgoCanada/argopandas.git
1 change: 1 addition & 0 deletions pyglider/argopandas
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Submodule argopandas added at decbef
491 changes: 491 additions & 0 deletions pyglider/mapplotting.py
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221 changes: 192 additions & 29 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 = plt.cm.get_cmap('viridis') #jp
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 @@ -247,31 +395,46 @@ def grid_plots(fname, plottingyaml):
if vmax is not None:
max = vmax
# make time windows:
if ax == axs[0]:
vmax = 300
cmap.set_over("black")
ax.set_ylim([300, 0])

vmax = 300
cmap.set_over("black")
# 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],
rasterized=True, vmin=min, vmax=max, cmap=cmap, shading='auto')
rasterized=True, vmin=min, vmax=max,cmap=cmap, shading='auto')
ax.contour(ds.time[ind], ds.depth, ds.potential_density[:, ind], colors='0.5',
levels=np.arange(22, 28, 0.5)+1000, linewidths=0.5, alpha=0.7)

_log.debug(ds[k])

fig.colorbar(pc, ax=ax, extend='both', shrink=0.6)
ax.set_title(ds[k].attrs['long_name'] + ' [' +
ds[k].attrs['units'] + ']', loc='left', fontsize=9)
# 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) #jpnote commented
ax.set_title(ds[k].attrs['long_name'] + ' over Depth [m]', loc='left', fontsize=9)
t0 = ds.time[0]
t1 = ds.time[-1]
ax.set_xlim([t0, t1])
ax.set_ylim([depmax, 0])
if n == 0:
ax.set_ylabel('DEPTH [m]')
# ax.set_ylim([depmax, 0])
ax.set_ylim([300, 0]) #jp changed (or should I leave it as dep max? )
# if n == 0:
ax.set_ylabel('DEPTH [m]')
# ax.set_xlabel('TIME (May - June)')
ax.set_facecolor('0.8')
now = str(datetime.utcnow())[:-10]
lastdata = str(ds.time[-1].values)[:-13]
Expand Down
1 change: 1 addition & 0 deletions pyglider/pyglider/argopandas
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Submodule argopandas added at decbef
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