added y calibration

src/modules/models.py

@@ -12,6 +12,7 @@
 import streamlit as st
 from streamlit.runtime.uploaded_file_manager import DeletedFile, UploadedFile
 
+
 from pydantic import BaseModel
 from typing import Literal
 
@@ -34,6 +35,15 @@ class SNIPBaselineArgs(BaseModel):
     niter: int = 30
 
 
+class StateSmooth(BaseModel):
+    use_smooth: bool = False
+    method: Literal['savgol', 'wiener', 'median',
+                    'gauss', 'lowess', 'boxcar'] = 'savgol'
+
+    savgol_window_length: int = 5
+    savgol_polyorder: int = 3
+
+
 class ALSBaselineArgs(BaseModel):
     niter: int = 30
     lam: float = 1e5
@@ -58,14 +68,25 @@ class StatePeakFind(BaseModel):
     # value_sharpening: str | None = Neone  # None | hhte
     value_strategy: str | None = None  # only string
 
+# class StateSmooth()
+
 
 class StateSpectrum(BaseModel):
     crop: StateCrop
-    normalize: StateNormalize
+    normalize: StateNormalize | None = None
     peak_find: StatePeakFind | None = None
     baseline_corr: StateBaselineCorrection | None = None
 
 
+class StateSpectrumSRMRef(BaseModel):
+
+    crop: StateCrop = StateCrop()
+    smooth: StateSmooth = StateSmooth()
+
+
+default_state_srm_ref = StateSpectrumSRMRef()
+
+
 default_peak_find_neon = StatePeakFind(value_sharpening=None,
                                        value_strategy='topo')
 

src/pages/apply_calibration.py

@@ -3,13 +3,13 @@
 
 import matplotlib.patches as mpatches
 import matplotlib.pyplot as plt
-
 import pandas as pd
 
 import streamlit as st
 from front_end.htmlTemplates import css
 
 from modules.navigation_bar import navbar
+from ramanchada2.io.output.write_csv import write_csv as io_write_csv
 
 from modules.models import default_state_target, StateNormalize, StateCrop
 from modules.util import (
@@ -350,16 +350,65 @@ def load_tabs_target_spectrum():
             "btn_press"
         ] = "apply_x_calib_btn"
 
+    apply_y_calib_btn = st.button("Apply Y-Calibration")
+
+    if apply_y_calib_btn:
+        if (
+            "target_spe_current"
+            not in st.session_state["cache_dicts"]["page01_load_spe"]
+        ):
+            st.error("Target spectrum not loaded")
+
+        assert "ycalibration_model" in st.session_state["cache_dicts"]["y_calibration"]
+        st.session_state["cache_dicts"]["page03_apply_calib"][
+            "btn_press"
+        ] = "apply_y_calib_btn"
+
 
 btn_press = None
 if "btn_press" in st.session_state["cache_dicts"]["page03_apply_calib"]:
     btn_press = st.session_state["cache_dicts"]["page03_apply_calib"]["btn_press"]
 
 # target_spe = st.session_state["cache_dicts"]["page01_load_spe"]["target_spe"]
 
-if btn_press == "apply_x_calib_btn":
+if btn_press == "apply_y_calib_btn":
+
+    spe_target = st.session_state["cache_dicts"]["page01_load_spe"][
+        "target_spe_current"]
+
+    ycalmodel = st.session_state["cache_dicts"]["y_calibration"]["ycalibration_model"]
+    spe_srm = st.session_state["cache_dicts"]["spectra_y_current"]["srm_ref"]
 
-    from matplotlib import pyplot as plt
+    # fig, ax = plt.subplots(1, 1, figsize=(15, 10))
+
+# with st.form("derive_y_calibration"):
+    # col_srm, col1, col2 = st.columns([1, 1, 1])
+    # with col_srm:
+    # btn_download_srm = st.button("Download Y-calibrated spectrum")
+
+    ax = spe_srm.plot(label="SRM experimental", color="red")
+
+    spe_target.plot(ax=ax, label="Target spectrum", color="blue")
+
+    spe_ycalibrated = ycalmodel.process(spe_target)
+
+    spe_ycalibrated.plot(label="Y-calibrated", color="green", ax=ax.twinx())
+    fig = ax.get_figure()
+    st.pyplot(fig)
+
+    csv = io_write_csv(spe_ycalibrated.x, spe_ycalibrated.y)
+    str_csv = ''.join(csv)
+    st.download_button(
+        "Download Y-Calibrated spectrum (CSV)",
+        data=str_csv,
+        file_name="ycalibrated_spectrum.csv",
+    )
+
+    # if btn_download_srm:
+    #     spe_ycalibrated.write_csv("ycalibrated_spectrum.csv")
+
+
+if btn_press == "apply_x_calib_btn":
 
     target_spe = st.session_state["cache_dicts"]["page01_load_spe"][
         "target_spe_current"
@@ -409,6 +458,13 @@ def load_tabs_target_spectrum():
 
     st.pyplot(fig)
 
+    csv = io_write_csv(target_calibrated.x, target_calibrated.y)
+    str_csv = ''.join(csv)
+    st.download_button(
+        "Download X-Calibrated spectrum (CSV)",
+        data=str_csv,
+        file_name="xcalibrated_spectrum.csv",
+    )
 
 elif btn_press == "target_spe_btn":