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Small tweaks to improve Durvo diagram scaling with high-TDS data #18

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Small tweaks to improve Durvo diagram scaling with high-TDS data #18

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98b35c4
Small tweaks to improve Durvo diagram scaling with high-TDS data
Benito7349 Oct 24, 2025
129a654
Small tweaks to improve overlapping legend
Benito7349 Oct 27, 2025
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144 changes: 100 additions & 44 deletions wqchartpy/durvo.py
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Original file line number Diff line number Diff line change
Expand Up @@ -55,7 +55,47 @@ def plot(df,
raise RuntimeError("""
Currently only mg/L and meq/L are supported.
Convert the unit manually if needed.""")
# Convert unit if needed
if unit == 'mg/L':
gmol = np.array([ions_WEIGHT['Ca'],
ions_WEIGHT['Mg'],
ions_WEIGHT['Na'],
ions_WEIGHT['K'],
ions_WEIGHT['HCO3'],
ions_WEIGHT['CO3'],
ions_WEIGHT['Cl'],
ions_WEIGHT['SO4'],
1, # Faked weight for pH
1000]) # Faked weight for TDS to convert mg/L to g/L
eqmol = np.array([ions_CHARGE['Ca'],
ions_CHARGE['Mg'],
ions_CHARGE['Na'],
ions_CHARGE['K'],
ions_CHARGE['HCO3'],
ions_CHARGE['CO3'],
ions_CHARGE['Cl'],
ions_CHARGE['SO4'],
1, # Faked charge for pH
1]) # Faked charge for TDS
tmpdf = df[['Ca', 'Mg', 'Na', 'K', 'HCO3', 'CO3', 'Cl', 'SO4', 'pH', 'TDS']]
dat = tmpdf.values

meqL = (dat / abs(gmol)) * abs(eqmol)

elif unit == 'meq/L':
meqL = df[['Ca', 'Mg', 'Na', 'K', 'HCO3', 'CO3', 'Cl', 'SO4', 'pH', 'TDS']].values

else:
raise RuntimeError("""
Currently only mg/L and meq/L are supported.
Convert the unit if needed.""")

# Get the maximum TDS value to set the TDS labels and figure size.
maxtds = round(meqL[:,9].max() * 1000)

# Set the labels limit for scaling tds axis.
limlabel = [3,4,6]

# Calculate the traingles' location
h = 0.5 * np.tan(np.pi / 3.0)
ltriangle_x = np.array([0, -h, 0, 0])
Expand All @@ -65,13 +105,24 @@ def plot(df,

# Calculate the rectangles' location
crectangle_x = np.array([0, 0, 1, 1, 0])
crectangle_y = np.array([0, 1, 1, 0, 0])
rrectangle_x = np.array([1, 2.618, 2.618, 1, 1])
crectangle_y = np.array([0, 1, 1, 0, 0])
# Depending on the order of magnitude of the TDS concentration, the label limit is chosen.
if maxtds < 1000:
rrectangle_x = np.array([1, limlabel[0], limlabel[0], 1, 1])
if maxtds > 1000 and maxtds < 10000:
rrectangle_x = np.array([1, limlabel[1], limlabel[1], 1, 1])
if maxtds > 10000 and maxtds < 100000:
rrectangle_x = np.array([1, limlabel[2], limlabel[2], 1, 1])
rrectangle_y = np.array([0, 0, 1, 1, 0])
brectangle_x = np.array([0, 1, 1, 0, 0])
brectangle_y = np.array([0, 0, -0.618, -0.618, 0])

# Plot the traingles and rectangles
# Depending on the order of magnitude of the TDS concentration, the figsize is chosen.
if maxtds < 10000:
fig_size = (10,10)
elif maxtds > 10000 and maxtds < 100000:
fig_size = (30,30)
fig = plt.figure(figsize=(10,10), dpi=100)
ax = fig.add_subplot(111, aspect='equal',
frameon=False, xticks=[], yticks=[])
Expand Down Expand Up @@ -160,54 +211,57 @@ def plot(df,
'k', lw=1.0)

# Right rectangle
tdslabels = ['0.0', '500', '', '1500', '', '2500', '', '3500']
for i, x in enumerate(np.linspace(1, 2.618, 9)):
# Depending on the order of magnitude of the TDS concentration, set the labels.
maxtds_str = int(str(maxtds)[1:])
if maxtds < 1000 and maxtds_str < 50:
maxtdslabel = (maxtds - maxtds_str) + 50
tdslabels = [str(i) for i in np.linspace(0, maxtdslabel, 11).astype(int)]
cantlabels = (np.linspace(1, len(tdslabels), len(tdslabels))).astype(int)
limlabel = limlabel[0]
poslabel = limlabel - 1
if maxtds < 1000 and maxtds_str > 50:
maxtdslabel = (maxtds - maxtds_str) + 100
tdslabels = [str(i) for i in np.linspace(0, maxtdslabel, 11).astype(int)]
cantlabels = (np.linspace(1, len(tdslabels), len(tdslabels))).astype(int)
limlabel = limlabel[0]
poslabel = limlabel - 1
if maxtds > 1000 and maxtds < 10000 and maxtds_str < 500:
maxtdslabel = (maxtds - maxtds_str) + 500
tdslabels = [str(i) for i in np.linspace(0, maxtdslabel, 11).astype(int)]
cantlabels = (np.linspace(1, len(tdslabels), len(tdslabels))).astype(int)
limlabel = limlabel[1]
poslabel = limlabel - 1
if maxtds > 1000 and maxtds < 10000 and maxtds_str > 500:
maxtdslabel = (maxtds - maxtds_str) + 1000
tdslabels = [str(i) for i in np.linspace(0, maxtdslabel, 11).astype(int)]
cantlabels = (np.linspace(1, len(tdslabels), len(tdslabels))).astype(int)
limlabel = limlabel[1]
poslabel = limlabel - 1
if maxtds > 10000 and maxtds < 100000 and maxtds_str < 5000:
maxtdslabel = (maxtds - maxtds_str) + 5000
tdslabels = [str(i) for i in np.linspace(0, maxtdslabel, 11).astype(int)]
cantlabels = (np.linspace(1, len(tdslabels), len(tdslabels))).astype(int)
limlabel = limlabel[2]
poslabel = limlabel - 1
if maxtds > 10000 and maxtds < 100000 and maxtds_str > 5000:
maxtdslabel = (maxtds - maxtds_str) + 10000
tdslabels = [str(i) for i in np.linspace(0, maxtdslabel, 11).astype(int)]
cantlabels = (np.linspace(1, len(tdslabels), len(tdslabels))).astype(int)
limlabel = limlabel[2]
poslabel = limlabel - 1

for i, x in enumerate(np.linspace(1, limlabel, len(cantlabels))):
ax.plot([x, x],
[0, ticklength],
'k', lw=1.0)
if i in [1, 2, 3, 4, 5, 6, 7]:
if i in cantlabels:
ax.text(x, -2 * ticklength, tdslabels[i], ha='center', va='top')
ax.text(1 + 1.618 / 2, -0.12, 'TDS (mg/L)', ha='center', va='top', fontsize=12)
ax.text(1 + poslabel / 2, -0.12, 'TDS (mg/L)', ha='center', va='top', fontsize=12)

# Label the watertypes in the central rectangle
ax.text(0.15, 0.1, 'NaCl', ha='center', va='center', fontsize=12)
ax.text(0.8, 0.9, 'CaHCO$_3$', ha='center', va='center', fontsize=12)

# Convert unit if needed
if unit == 'mg/L':
gmol = np.array([ions_WEIGHT['Ca'],
ions_WEIGHT['Mg'],
ions_WEIGHT['Na'],
ions_WEIGHT['K'],
ions_WEIGHT['HCO3'],
ions_WEIGHT['CO3'],
ions_WEIGHT['Cl'],
ions_WEIGHT['SO4'],
1, # Faked weight for pH
1000]) # Faked weight for TDS to convert mg/L to g/L
eqmol = np.array([ions_CHARGE['Ca'],
ions_CHARGE['Mg'],
ions_CHARGE['Na'],
ions_CHARGE['K'],
ions_CHARGE['HCO3'],
ions_CHARGE['CO3'],
ions_CHARGE['Cl'],
ions_CHARGE['SO4'],
1, # Faked charge for pH
1]) # Faked charge for TDS
tmpdf = df[['Ca', 'Mg', 'Na', 'K', 'HCO3', 'CO3', 'Cl', 'SO4', 'pH', 'TDS']]
dat = tmpdf.values

meqL = (dat / abs(gmol)) * abs(eqmol)

elif unit == 'meq/L':
meqL = df[['Ca', 'Mg', 'Na', 'K', 'HCO3', 'CO3', 'Cl', 'SO4', 'pH', 'TDS']].values

else:
raise RuntimeError("""
Currently only mg/L and meq/L are supported.
Convert the unit if needed.""")

# Calculate the percentages
sumcat = np.sum(meqL[:, 0:4], axis=1)
suman = np.sum(meqL[:, 4:8], axis=1)
Expand All @@ -228,7 +282,8 @@ def plot(df,
cat_y = np.sin(np.pi / 6.0) * (1 - cat[:, 2] - cat[:, 0]) + cat[:, 0]
an_x = np.sin(np.pi / 6.0) * (1 - an[:, 2]) + np.sin(np.pi / 6.0) * an[:, 0]
an_y = 1 + np.sin(np.pi / 3.0) * (1 - an[:, 2] - an[:, 0])
tds_x = 1 + (meqL[:, 9] - 0) / (4 - 0) * 1.618
tds_x = [(i * (limlabel - 1) / (maxtdslabel / 1000)) + 1 for i in meqL[:,9]]
#tds_x = 1 + (meqL[:, 9] - 0) / (4 - 0) * 1.618
ph_y = -(meqL[:, 8] - minpH) / (maxpH - minpH) * 0.618

# Plot the scatters
Expand Down Expand Up @@ -293,8 +348,9 @@ def plot(df,
plt.text(-0.25, -0.618 / 2, 'pH', rotation=90,
ha='center', va='center', fontsize=12)

# Creat the legend
plt.legend(loc='upper left', markerscale=1, frameon=False, fontsize=12,
# Create the legend
# "bbox_to_anchor" help to put the legend out of the figure.
plt.legend(bbox_to_anchor=(1,1), loc='upper left', markerscale=1, frameon=False, fontsize=12,
labelspacing=0.25, handletextpad=0.25)

# Display the info
Expand Down