feat: add 22 08 2025

2025-08-22/main.py

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+# -*- coding: utf-8 -*-
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+from pathlib import Path
+
+# ==========================
+# CONFIG
+# ==========================
+CHEM_PATH  = "data_valider_Pierre_toutes_dates_hydro.xlsx"
+CHEM_SHEET = "tri_points"
+
+TYPE_COL  = "type"                 # 'rivière' / 'source'
+HYDRO_COL = "hydrodynamique"       # 'hautes-eaux' / 'moyennes-eaux' / 'étiage'
+KM_COL    = "km"
+CAMP_COL  = " nb campagne"         # (il y a un espace initial dans le fichier)
+
+# Dossier d’export
+EXPORT_DIR = Path("out")
+EXPORT_DIR.mkdir(parents=True, exist_ok=True)
+
+# Limites de l’axe X (km) pour tous les subplots
+KM_XLIM = (0, 50)   # mets à None pour auto; sinon tuple (min,max)
+
+# === COULEURS PAR ÉTAT HYDRODYNAMIQUE ===
+hautes_eaux_colors   = ["#EA66FF", "#E01EFF", "#C942FF", "#B300F9", "#8000B2", "#591D71", "#2C0E38"]
+moyennes_eaux_colors = ["#D8E6F2", "#B1CEE6", "#8BB5D9", "#649DCD", "#3E85C0", "#316A9A", "#254F73", "#5671F7", "#0000FF", "#18354D"]
+etiage_colors        = ["#FFE4B5", "#FFA500", "#FF0000", "#8B0000"]
+
+# Valeurs EXACTES présentes dans le fichier
+HYDRO_STATES = [
+    ("hautes-eaux",   hautes_eaux_colors),
+    ("moyennes-eaux", moyennes_eaux_colors),
+    ("étiage",        etiage_colors)
+]
+
+# ==========================
+# PARAMÈTRES À TRACER
+# (y_riv / y_src facultatifs — auto si omis)
+# ==========================
+parametres = [
+    {"variable": "Fe2+",        "ylabel": "Fe2+ (mg/L)"},
+    {"variable": "Alcalinité",  "ylabel": "HCO3- (mg/L)"},
+    {"variable": "Na+",         "ylabel": "Na+ (mg/L)"},
+    {"variable": "Mg2+",        "ylabel": "Mg2+ (mg/L)"},
+    {"variable": "T°C",         "ylabel": "Température (°C)"},
+    {"variable": "pH",          "ylabel": "pH"},
+    {"variable": "Cl-",         "ylabel": "Cl- (mg/L)"},
+    {"variable": "c25°C ",      "ylabel": "Conductivité (μS/cm)"},
+    {"variable": "DOC",         "ylabel": "DOC (mg/L)"},
+    {"variable": "SO42-",       "ylabel": "SO42- (mg/L)"},
+    {"variable": "SiO2",        "ylabel": "SiO2 (mg/L)"},
+    {"variable": "PO43-",       "ylabel": "PO43- (mg/L)"},
+    {"variable": "NO3-",        "ylabel": "NO3- (mg/L)"},
+    {"variable": "Ca recalculé","ylabel": "Ca2+ (mg/L)"},
+    {"variable": "O2 mg/L",     "ylabel": "O2 (mg/L)"},
+    {"variable": "Fluorure",    "ylabel": "Fl- (mg/L)"},
+    {"variable": "NO2-",        "ylabel": "NO2- (mg/L)"},
+    {"variable": "NH4+",        "ylabel": "NH4+ (mg/L)"},
+    {"variable": "δ13C VPDB",   "ylabel": "δ13C"},
+]
+
+# ==========================
+# UTILITAIRES
+# ==========================
+def sanitize_filename(s: str) -> str:
+    s = str(s).strip().replace("\n", " ")
+    for b in ['<','>',':','"','/','\\','|','?','*']:
+        s = s.replace(b, '_')
+    s = '_'.join(s.split())  # compresser espaces
+    return s
+
+def nice_camp_label(c):
+    try:
+        cf = float(c)
+        if cf.is_integer():
+            return f"camp. {int(cf)}"
+    except Exception:
+        pass
+    return f"camp. {c}"
+
+def get_ylim_for(param, df_sources, df_riviere, var, qlo=0.05, qhi=0.95, pad=0.05):
+    """
+    Calcule (y_src, y_riv).
+    - Si 'y_src'/'y_riv' sont fournis dans param -> on les respecte.
+    - Sinon: auto depuis les données (quantiles qlo–qhi) + marge 'pad'.
+      y_riv est calculé sur TOUTES les données 'rivière' (tous états) pour
+      que les 3 subplots partagent la même échelle.
+    """
+    # --- rivière
+    if "y_riv" in param:
+        y_riv = tuple(param["y_riv"])
+    else:
+        dr = df_riviere[[var]].dropna()
+        if dr.empty:
+            y_riv = (0, 1)
+        else:
+            lo, hi = dr[var].quantile([qlo, qhi]).values
+            if not np.isfinite(lo) or not np.isfinite(hi) or lo == hi:
+                lo, hi = float(dr[var].min()), float(dr[var].max())
+            span = max(hi - lo, 1e-12)
+            y_riv = (lo - pad*span, hi + pad*span)
+
+    # --- sources
+    if "y_src" in param:
+        y_src = tuple(param["y_src"])
+    else:
+        ds = df_sources[[var]].dropna()
+        if ds.empty:
+            y_src = y_riv
+        else:
+            lo, hi = ds[var].quantile([qlo, qhi]).values
+            if not np.isfinite(lo) or not np.isfinite(hi) or lo == hi:
+                lo, hi = float(ds[var].min()), float(ds[var].max())
+            span = max(hi - lo, 1e-12)
+            y_src = (lo - pad*span, hi + pad*span)
+
+    return y_src, y_riv
+
+def build_campaign_color_map(df_riv, hydro_col, camp_col):
+    """Map {state: {camp_id: color}} avec palettes par état (boucle si nécessaire)."""
+    mapping = {}
+    for state, palette in HYDRO_STATES:
+        sub = df_riv.loc[df_riv[hydro_col] == state]
+        camps = pd.unique(sub[camp_col].dropna())
+        camps_sorted = np.sort(camps)
+        if len(camps_sorted) == 0:
+            mapping[state] = {}
+            continue
+        colors = (palette * ((len(camps_sorted) // len(palette)) + 1))[:len(camps_sorted)]
+        mapping[state] = {c: col for c, col in zip(camps_sorted, colors)}
+    return mapping
+
+# ==========================
+# LECTURE & PRÉPA
+# ==========================
+chem = pd.read_excel(CHEM_PATH, sheet_name=CHEM_SHEET)
+
+# Harmoniser 'type'
+chem[TYPE_COL] = chem[TYPE_COL].astype(str).str.strip().str.lower()
+
+# Numériques utiles
+chem[KM_COL]   = pd.to_numeric(chem[KM_COL], errors="coerce")
+chem[CAMP_COL] = pd.to_numeric(chem[CAMP_COL], errors="coerce")
+
+# Tri logique (km puis campagne)
+chem = chem.sort_values([KM_COL, CAMP_COL])
+
+# Sous-ensembles
+df_sources = chem.loc[chem[TYPE_COL] == "source"].copy()
+df_riviere = chem.loc[chem[TYPE_COL] == "rivière"].copy()
+
+# Colonnes indispensables côté rivière
+for c in [HYDRO_COL, KM_COL, CAMP_COL]:
+    if c not in df_riviere.columns:
+        raise KeyError(f"Colonne manquante pour 'rivière': {c}")
+
+# Couleurs par campagne×état
+camp_color_map = build_campaign_color_map(df_riviere, HYDRO_COL, CAMP_COL)
+
+# ==========================
+# TRAÇAGE
+# ==========================
+for p in parametres:
+    var, ylabel = p["variable"], p["ylabel"]
+    if var not in chem.columns:
+        print(f"[AVERTISSEMENT] '{var}' absent → figure ignorée.")
+        continue
+
+    y_src_limits, y_riv_limits = get_ylim_for(p, df_sources, df_riviere, var, qlo=0, qhi=1)
+
+    fig, axes = plt.subplots(nrows=4, ncols=1, sharex=False, figsize=(12, 9))
+    # Réserve de l'espace à droite pour la légende
+    fig.subplots_adjust(hspace=0.18, right=0.80)
+    fig.suptitle(f"{var} — X = km (campagnes en courbes pour la rivière)", fontsize=12, x=0.01, ha="left")
+
+    # 1) SOURCES — X = km (nuage gris)
+    ax_src = axes[0]
+    if not df_sources.empty:
+        ds = df_sources[[KM_COL, var]].dropna()
+        ax_src.scatter(ds[KM_COL], ds[var], s=24, alpha=0.7,
+                       edgecolors="white", linewidths=0.4, color="#666666")
+    ax_src.set_ylabel(ylabel + "\n(sources)")
+    ax_src.set_xlabel("km")
+    if KM_XLIM: ax_src.set_xlim(*KM_XLIM)
+    ax_src.set_ylim(*y_src_limits)
+    ax_src.grid(True, linestyle=":", alpha=0.35)
+
+    # 2–4) RIVIÈRE par ÉTAT — X = km ; une courbe par 'nb campagne'
+    legend_handles, legend_labels = [], []
+    for i, (state, palette) in enumerate(HYDRO_STATES, start=1):
+        ax = axes[i]
+        sub = df_riviere.loc[df_riviere[HYDRO_COL] == state, [KM_COL, CAMP_COL, var]]
+        sub = sub.dropna(subset=[KM_COL, var])
+
+        if not sub.empty:
+            for camp, grp in sub.groupby(CAMP_COL):
+                grp = grp.sort_values(KM_COL)
+                color = camp_color_map.get(state, {}).get(camp, (palette[0] if palette else "C0"))
+                h = ax.plot(grp[KM_COL], grp[var], marker="o", ms=4, lw=1.6, color=color)[0]
+                lab = nice_camp_label(camp)
+                if lab not in legend_labels:
+                    legend_handles.append(h)
+                    legend_labels.append(lab)
+
+        ax.set_ylabel(f"{ylabel}\n({state})")
+        ax.set_xlabel("km")
+        if KM_XLIM: ax.set_xlim(*KM_XLIM)
+        ax.set_ylim(*y_riv_limits)
+        ax.grid(True, linestyle=":", alpha=0.35)
+
+    # Légende globale (campagnes) à droite, hors du tracé
+    if legend_handles:
+        axes[1].legend(
+            legend_handles, legend_labels,
+            loc="center left", bbox_to_anchor=(1.02, 0.5),
+            frameon=False, ncol=1, title="Campagnes", borderaxespad=0.0
+        )
+
+    # Export
+    fname = sanitize_filename(f"{var}_rivieres_sources.png")
+    outpath = EXPORT_DIR / fname
+    fig.savefig(outpath, dpi=200, bbox_inches="tight")
+    plt.close(fig)
+    print(f"[OK] Export: {outpath.resolve()}")

2025-08-22/requirements.txt

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+pandas==2.3.2
+matplotlib==3.10.5
+openpyxl==3.1.5