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Plotting updates #129

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merged 11 commits into from
Nov 20, 2024
Merged

Plotting updates #129

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862b4ae
adjust the aspect ratio of figures
eleanorfrajka Nov 19, 2024
9458bad
Clarify labels, hysteresis
eleanorfrajka Nov 19, 2024
630433f
Some changes to labels
eleanorfrajka Nov 19, 2024
b76645d
specify order
eleanorfrajka Nov 19, 2024
61948a4
Not sure how to PR without a commit
eleanorfrajka Nov 20, 2024
6489a6c
Fixed assertion for xlabel
eleanorfrajka Nov 20, 2024
ef0bd02
Updated to create fig then resize to set aspect ratio
eleanorfrajka Nov 20, 2024
f56c9e1
Adjusted dates / size on plot_quench_asses
eleanorfrajka Nov 20, 2024
ea7aea1
Created plotting utility _time_axis_formatter
eleanorfrajka Nov 20, 2024
8f8da12
Move _time_axis_formatter to utilities
eleanorfrajka Nov 20, 2024
161049c
Moved _time_axis_formatter to utilities
eleanorfrajka Nov 20, 2024
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96 changes: 78 additions & 18 deletions glidertest/plots.py
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Original file line number Diff line number Diff line change
Expand Up @@ -17,6 +17,37 @@
dir = os.path.dirname(os.path.realpath(__file__))
glidertest_style_file = f"{dir}/glidertest.mplstyle"

def _time_axis_formatter(ax, ds, format_x_axis=True):
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I wonder if this should go on utilities instead

start_time = ds.TIME.min().values
end_time = ds.TIME.max().values
if (end_time - start_time) < np.timedelta64(1, 'D'):
formatter = DateFormatter('%H:%M')
locator = mdates.HourLocator(interval=2)
start_date = pd.to_datetime(start_time).strftime('%Y-%b-%d')
end_date = pd.to_datetime(end_time).strftime('%Y-%b-%d')
xlabel = f'Time [UTC] ({start_date})' if start_date == end_date else f'Time [UTC] ({start_date} to {end_date})'
elif (end_time - start_time) < np.timedelta64(7, 'D'):
formatter = DateFormatter('%d-%b')
locator = mdates.DayLocator(interval=1)
start_date = pd.to_datetime(start_time).strftime('%Y-%b-%d')
end_date = pd.to_datetime(end_time).strftime('%Y-%b-%d')
xlabel = f'Time [UTC] ({start_date})' if start_date == end_date else f'Time [UTC] ({start_date} to {end_date})'
else:
formatter = DateFormatter('%d-%b')
locator = None
xlabel = 'Time [UTC]'

if format_x_axis:
ax.xaxis.set_major_formatter(formatter)
if locator:
ax.xaxis.set_major_locator(locator)
ax.set_xlabel(xlabel)
else:
ax.yaxis.set_major_formatter(formatter)
if locator:
ax.yaxis.set_major_locator(locator)
ax.set_ylabel(xlabel)

def plot_updown_bias(df: pd.DataFrame, ax: plt.Axes = None, xlabel='Temperature [C]', **kw: dict, ) -> tuple({plt.Figure, plt.Axes}):
"""
This function can be used to plot the up and downcast differences computed with the updown_bias function
Expand All @@ -38,6 +69,8 @@ def plot_updown_bias(df: pd.DataFrame, ax: plt.Axes = None, xlabel='Temperature
with plt.style.context(glidertest_style_file):
if ax is None:
fig, ax = plt.subplots()
third_width = fig.get_size_inches()[0] / 3.11
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I think this is good! Do we want to have the option to have the third/half/full in the parameters instead and put third as default here.
Something like:

def plot_updown_bias(df: pd.DataFrame, ax: plt.Axes = None, xlabel='Temperature [C]', size='third', '**kw: dict, ) -> tuple({plt.Figure, plt.Axes}):
if size=='third':
     third_width = fig.get_size_inches()[0] / 3.11
     fig.set_size_inches(third_width, third_width *1.1)
...

Or if we want 3 styles and the font size is also adjusted

fig.set_size_inches(third_width, third_width *1.1)
force_plot = True
else:
fig = plt.gcf()
Expand Down Expand Up @@ -105,6 +138,9 @@ def plot_basic_vars(ds: xr.Dataset, v_res=1, start_prof=0, end_prof=-1):
with warnings.catch_warnings():
warnings.simplefilter("ignore", category=RuntimeWarning)
fig, ax = plt.subplots(1, 2)
# Resize to half-width
half_width = fig.get_size_inches()[0] / 2.07
fig.set_size_inches(half_width, half_width * 0.85)
ax1 = ax[0].twiny()
ax2 = ax[0].twiny()
ax2.spines["top"].set_position(("axes", 1.2))
Expand All @@ -115,26 +151,30 @@ def plot_basic_vars(ds: xr.Dataset, v_res=1, start_prof=0, end_prof=-1):
ax1.axhline(halo, linestyle='dashed', c='red')
ax2.axhline(pycno, linestyle='dashed', c='black')

ax[0].set(xlabel=f'Average Temperature [C] \nbetween profile {start_prof} and {end_prof}', ylabel='Depth (m)')
ax[0].set(xlabel=f'Temperature [C]', ylabel='Depth (m)')
ax[0].tick_params(axis='x', colors='blue')
ax[0].xaxis.label.set_color('blue')
ax1.spines['bottom'].set_color('blue')
ax1.set(xlabel=f'Average Salinity [PSU] \nbetween profile {start_prof} and {end_prof}')
ax1.set(xlabel=f'Salinity [PSU]')
ax1.xaxis.label.set_color('red')
ax1.spines['top'].set_color('red')
ax1.tick_params(axis='x', colors='red')
ax2.spines['bottom'].set_color('black')
ax2.set(xlabel=f'Average Density [kg m-3] \nbetween profile {start_prof} and {end_prof}')
ax2.set(xlabel=f'Density [kg m-3]')
ax2.xaxis.label.set_color('black')
ax2.spines['top'].set_color('black')
ax2.tick_params(axis='x', colors='black')

# Add text annotation to the right, outside of the plot
ax2.text(1.2, 1.25, f'Averaged profiles {start_prof}-{end_prof}', transform=ax2.transAxes,
verticalalignment='center', horizontalalignment='left', rotation=0, fontsize=12, bbox=dict(facecolor='white', alpha=0.5))

if 'CHLA' in ds.variables:
chlaG, profG, depthG = utilities.construct_2dgrid(ds.PROFILE_NUMBER, ds.DEPTH, ds.CHLA, p, z)
chlaG = chlaG[start_prof:end_prof, :]
ax2_1 = ax[1].twiny()
ax2_1.plot(np.nanmean(chlaG, axis=0), depthG[0, :], c='green')
ax2_1.set(xlabel=f'Average Chlorophyll-a [mg m-3] \nbetween profile {start_prof} and {end_prof}')
ax2_1.set(xlabel=f'Chlorophyll-a [mg m-3]')
ax2_1.xaxis.label.set_color('green')
ax2_1.spines['top'].set_color('green')
ax2_1.tick_params(axis='x', colors='green')
Expand All @@ -145,14 +185,14 @@ def plot_basic_vars(ds: xr.Dataset, v_res=1, start_prof=0, end_prof=-1):
oxyG, profG, depthG = utilities.construct_2dgrid(ds.PROFILE_NUMBER, ds.DEPTH, ds.DOXY, p, z)
oxyG = oxyG[start_prof:end_prof, :]
ax[1].plot(np.nanmean(oxyG, axis=0), depthG[0, :], c='orange')
ax[1].set(xlabel=f'Average Oxygen [mmol m-3] \nbetween profile {start_prof} and {end_prof}')
ax[1].set(xlabel=f'Oxygen [mmol m-3]')
ax[1].xaxis.label.set_color('orange')
ax[1].spines['top'].set_color('orange')
ax[1].tick_params(axis='x', colors='orange')
ax[1].spines['bottom'].set_color('orange')
else:
ax[1].text(0.3, 0.5, 'Oxygen data unavailable', va='top', transform=ax[1].transAxes)
[a.set_ylim(depthG.max() + 10, -5) for a in ax]
[a.set_ylim(depthG.max(), 0) for a in ax]
[a.grid() for a in ax]
plt.show()
return fig, ax
Expand Down Expand Up @@ -199,10 +239,12 @@ def process_optics_assess(ds, var='CHLA'):
bottom_opt_data = ds[var].where(ds[var].DEPTH > ds.DEPTH.max() - (ds.DEPTH.max() * 0.1)).dropna(
dim='N_MEASUREMENTS')
slope, intercept, r_value, p_value, std_err = stats.linregress(np.arange(0, len(bottom_opt_data)), bottom_opt_data)

# Generate the plot
with plt.style.context(glidertest_style_file):
ax = sns.regplot(data=ds, x=np.arange(0, len(bottom_opt_data)), y=bottom_opt_data,
scatter_kws={"color": "grey"},
line_kws={"color": "red", "label": "y={0:.8f}x+{1:.5f}".format(slope, intercept)},
line_kws={"color": "red", "label": "y={0:.8f} x+{1:.5f}".format(slope, intercept)},
)
ax.legend(loc=2)
ax.grid()
Expand Down Expand Up @@ -301,6 +343,8 @@ def plot_quench_assess(ds: xr.Dataset, sel_var: str, ax: plt.Axes = None, start_
with plt.style.context(glidertest_style_file):
if ax is None:
fig, ax = plt.subplots()
full_width = fig.get_size_inches()[0]
fig.set_size_inches(full_width, full_width * 0.5)
else:
fig = plt.gcf()

Expand All @@ -319,6 +363,7 @@ def plot_quench_assess(ds: xr.Dataset, sel_var: str, ax: plt.Axes = None, start_
else:
ds_sel = ds.sel(TIME=slice(start_time, end_time))


if len(ds_sel.TIME) == 0:
msg = f"supplied limits start_time: {start_time} end_time: {end_time} do not overlap with dataset TIME range {str(ds.TIME.values.min())[:10]} - {str(ds.TIME.values.max())[:10]}"
raise ValueError(msg)
Expand All @@ -333,6 +378,11 @@ def plot_quench_assess(ds: xr.Dataset, sel_var: str, ax: plt.Axes = None, start_
for m in np.unique(sunrise):
ax.axvline(np.unique(m), c='orange')
ax.set_ylabel('Depth [m]')

# Set x-tick labels based on duration of the selection
# Could pop out as a utility plotting function?
_time_axis_formatter(ax, ds_sel, format_x_axis=True)

plt.colorbar(c, label=f'{sel_var} [{ds[sel_var].units}]')
plt.show()
return fig, ax
Expand Down Expand Up @@ -366,7 +416,9 @@ def check_temporal_drift(ds: xr.Dataset, var: str, ax: plt.Axes = None, **kw: di
fig = plt.gcf()

ax[0].scatter(mdates.date2num(ds.TIME), ds[var], s=10)
ax[0].xaxis.set_major_formatter(DateFormatter('%d-%b'))
# Set x-tick labels based on duration of the selection
_time_axis_formatter(ax[0], ds, format_x_axis=True)

ax[0].set(ylim=(np.nanpercentile(ds[var], 0.01), np.nanpercentile(ds[var], 99.99)), ylabel=var)

c = ax[1].scatter(ds[var], ds.DEPTH, c=mdates.date2num(ds.TIME), s=10)
Expand Down Expand Up @@ -408,9 +460,10 @@ def plot_prof_monotony(ds: xr.Dataset, ax: plt.Axes = None, **kw: dict, ) -> tup
fig = plt.gcf()

ax[0].plot(ds.TIME, ds.PROFILE_NUMBER)
ax[0].set(ylabel='Profile_Number')
ylabel = ds.PROFILE_NUMBER.attrs.get('long_name', 'Profile Number')
ax[0].set(ylabel=ylabel)
if len(np.where((np.diff(ds.PROFILE_NUMBER) != 0) & (np.diff(ds.PROFILE_NUMBER) != 1))[0]) == 0:
ax[1].text(0.2, 0.5, 'Data in monotonically increasing and no issues can be observed',
ax[1].text(0.2, 0.5, 'Data are monotonically increasing - no issues identified',
transform=ax[1].transAxes)
else:
ax[1].scatter(ds.TIME[np.where((np.diff(ds.PROFILE_NUMBER) != 0) & (np.diff(ds.PROFILE_NUMBER) != 1))],
Expand All @@ -420,6 +473,7 @@ def plot_prof_monotony(ds: xr.Dataset, ax: plt.Axes = None, **kw: dict, ) -> tup
ax[1].set(ylabel='Depth')
ax[1].invert_yaxis()
ax[1].xaxis.set_major_locator(plt.MaxNLocator(8))
_time_axis_formatter(ax[1], ds, format_x_axis=True)
[a.grid() for a in ax]
plt.show()
return fig, ax
Expand Down Expand Up @@ -511,6 +565,8 @@ def plot_grid_spacing(ds: xr.Dataset, ax: plt.Axes = None, **kw: dict) -> tuple(
with plt.style.context(glidertest_style_file):
if ax is None:
fig, ax = plt.subplots(1, 2)
# Set aspect ration of plot to be 2:1
fig.set_size_inches(fig.get_size_inches()[0], fig.get_size_inches()[0] / 2)
else:
fig = plt.gcf()
# Set font sizes for all annotations
Expand Down Expand Up @@ -763,8 +819,8 @@ def plot_vertical_speeds_with_histograms(ds, start_prof=None, end_prof=None):
ax1.set_xlabel('Time')
ax1.set_ylabel('Vertical Velocity (cm/s)')
ax1.legend(loc='lower left')
ax1.xaxis.set_major_formatter(DateFormatter('%d-%b'))
ax1.legend(loc='lower right')
_time_axis_formatter(ax1, ds, format_x_axis=True)

# Upper right subplot for histogram of vertical velocity
ax1_hist = axs[0, 1]
Expand All @@ -791,7 +847,7 @@ def plot_vertical_speeds_with_histograms(ds, start_prof=None, end_prof=None):
ax2.set_xlabel('Time')
ax2.set_ylabel('Vertical Water Speed (cm/s)')
ax2.legend(loc='upper left')
ax2.xaxis.set_major_formatter(DateFormatter('%d-%b'))
_time_axis_formatter(ax2, ds, format_x_axis=True)

# Lower right subplot for histogram of vertical water speed
ax2_hist = axs[1, 1]
Expand Down Expand Up @@ -887,7 +943,9 @@ def plot_combined_velocity_profiles(ds_out_dives: xr.Dataset, ds_out_climbs: xr.
w_upper_climbs = ds_out_climbs.w_upper.values * conv_factor
with plt.style.context(glidertest_style_file):
fig, ax = plt.subplots(1, 1)

# Resize to half-width
half_width = fig.get_size_inches()[0] / 2.07
fig.set_size_inches(half_width, half_width * 0.9)
ax.tick_params(axis='both', which='major')

# Plot dives
Expand Down Expand Up @@ -962,15 +1020,17 @@ def plot_hysteresis(ds, var='DOXY', v_res=1, perct_err=2, ax=None):
[a.grid() for a in ax]
[a.invert_yaxis() for a in ax]
ax[0].set_ylabel('Depth (m)')
ax[0].set_xlabel(f'{var} concentration \n({ds[var].units})')
ax[1].set_xlabel(f'Absolute difference between mean dive and climb \n({ds[var].units})')
ax[2].set_xlabel('Percentage error between up and downcast \n(%)')
ax[0].set_xlabel(f'{var} concentration $=mean$ \n({ds[var].units})')
ax[1].set_xlabel(f'Absolute difference = |$\Delta$| \n({ds[var].units})')
ax[2].set_xlabel('Percent error = |$\Delta$|/$mean$ \n(%)')
for ax1 in ax[:-1]:
ax1.xaxis.set_label_position('top')
c = ax[3].pcolor(profG[:-1, :], depthG[:-1, :], np.diff(varG, axis=0),
vmin=np.nanpercentile(np.diff(varG, axis=0), 0.5),
vmax=np.nanpercentile(np.diff(varG, axis=0), 99.5), cmap='seismic')
plt.colorbar(c, ax=ax[3], label=f'Difference between up and downcast \n({ds[var].units})', fraction=0.05)
plt.colorbar(c, ax=ax[3], label=f'Difference dive-climb \n({ds[var].units})', fraction=0.05)
ax[3].set(ylabel='Depth (m)', xlabel='Profile number')
fig.suptitle(var, y=0.94)
fig.suptitle(var, y=.98)
if force_plot:
plt.show()
return fig, ax
8 changes: 3 additions & 5 deletions notebooks/demo.ipynb
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -302,9 +302,7 @@
"outputs": [],
"source": [
"# Let's visually check a section of chlorphyll and see if we observe any NPQ\n",
"fig, ax = plt.subplots(1, 1, figsize=(15, 5))\n",
"\n",
"plots.plot_quench_assess(ds, 'CHLA', ax, ylim=35);"
"plots.plot_quench_assess(ds, 'CHLA', ax=None, ylim=35);"
]
},
{
Expand Down Expand Up @@ -478,7 +476,7 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
Expand All @@ -492,7 +490,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.12"
"version": "3.12.7"
}
},
"nbformat": 4,
Expand Down
2 changes: 1 addition & 1 deletion tests/test_plots.py
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Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,7 @@ def test_plots(start_prof=0, end_prof=100):
ds = ds.drop_vars(['DENSITY'])
fig, ax = plots.plot_basic_vars(ds,start_prof=start_prof, end_prof=end_prof)
assert ax[0].get_ylabel() == 'Depth (m)'
assert ax[0].get_xlabel() == f'Average Temperature [C] \nbetween profile {start_prof} and {end_prof}'
assert ax[0].get_xlabel() == f'Temperature [C]'


def test_up_down_bias(v_res=1, xlabel='Salinity'):
Expand Down