Merge pull request #192 from h2020charisma/oranchada-related-fix

multiple updates , use position instead of center, nexusformat notebook

environment.yml

@@ -7,5 +7,7 @@ dependencies:
   - pip
   - pip:
     - jupyter
+    - ploomber
+    - pytest
     - -e .
 

examples/publication/pipeline_demo/README.md

@@ -0,0 +1,3 @@
+Run with 
+
+> ploomber build

examples/publication/pipeline_demo/env.yaml

@@ -0,0 +1 @@
+file: "../../../src/ramanchada2/auxiliary/spectra/datasets2/ICV_BW532/PST02_iRPlus532_Z050_100_2500msx5.txt"

examples/publication/pipeline_demo/nexusformat.py

@@ -0,0 +1,52 @@
+import ramanchada2 as rc2
+import pyambit.datamodel as mx
+from pyambit.nexus_spectra import spe2ambit
+import nexusformat.nexus.tree as nx
+import uuid
+import os.path
+
+# + tags=["parameters"]
+upstream = ["read_preprocess"]
+product = None
+sample = None
+laser_wl = None
+instrument_make = None
+instrument_model = None
+data_provider = None
+# -
+
+spe_raw = rc2.spectrum.from_chada(upstream["read_preprocess"]["cha"], dataset="/raw")
+spe_raw.plot()
+
+prefix = "DEMO"
+
+substances = []
+substance = mx.SubstanceRecord(name=sample, publicname=sample, ownerName="TEST")
+substance.i5uuid = "{}-{}".format(prefix, uuid.uuid5(uuid.NAMESPACE_OID, sample))
+protocol_application = spe2ambit(
+    x=spe_raw.x,
+    y=spe_raw.y,
+    meta=spe_raw.meta,
+    instrument=(instrument_make, instrument_model),
+    wavelength=laser_wl,
+    provider=data_provider,
+    investigation="My experiment",
+    sample=sample,
+    sample_provider="CHARISMA",
+    prefix=prefix,
+    endpointtype="RAW_DATA",
+    unit="cm-1",
+)
+substance.study = [protocol_application]
+substances.append(substance)
+
+output_file = product["nxs"]
+
+substances = mx.Substances(substance=substances)
+nxroot = nx.NXroot()
+nxroot.attrs["pyambit"] = "0.0.1"
+nxroot.attrs["file_name"] = os.path.basename(output_file)
+substances.to_nexus(nxroot)
+
+print(nxroot.tree)
+nxroot.save(output_file, mode="w")

examples/publication/pipeline_demo/pipeline.yaml

@@ -0,0 +1,19 @@
+tasks:
+
+  - source: read_preprocess.py
+    product: 
+      nb: "products/read_preprocess.ipynb"
+      cha: "products/spectrum.cha"
+    params:
+      input_file: "{{file}}"
+
+  - source: nexusformat.py
+    product: 
+      nb: "products/nexusformat.ipynb"
+      nxs: "products/spectrum.nxs"
+    params:
+      sample: "PST"
+      laser_wl: 532
+      instrument_make: "BWTek"
+      instrument_model: "iRamanPlus"
+      data_provider: "ICV"

examples/publication/pipeline_demo/read_preprocess.py

@@ -0,0 +1,22 @@
+import os.path
+import ramanchada2 as rc2
+
+# + tags=["parameters"]
+upstream = []
+product = None
+input_file = None
+# -
+
+file = os.path.abspath(input_file)
+
+# load spectrum from file system
+spe = rc2.spectrum.from_local_file(file)
+spe.plot()
+
+if os.path.isfile(product["cha"]):
+    os.remove(product["cha"])
+
+spe.write_cha(product["cha"], dataset="/raw")
+
+spe.subtract_baseline_rc1_snip(niter=40)
+spe.write_cha(product["cha"], dataset="/baseline")

src/ramanchada2/protocols/calibration/calibration_component.py

@@ -19,7 +19,7 @@ def __init__(self):
 
 
 class CalibrationComponent(Plottable):
-    nonmonotonic: Literal["ignore", "nan", "error"] = "nan"
+    nonmonotonic: Literal["ignore", "nan", "error", "drop"] = "error"
 
     def __init__(self, laser_wl, spe, spe_units, ref, ref_units, sample=None):
         super(CalibrationComponent, self).__init__()

src/ramanchada2/protocols/calibration/calibration_model.py

@@ -13,7 +13,7 @@
 
 
 class CalibrationModel(ProcessingModel, Plottable):
-    nonmonotonic: Literal["ignore", "nan", "error"] = "nan"
+    nonmonotonic: Literal["ignore", "nan", "error", "drop"] = "nan"
 
     """
     A class representing a calibration model for Raman spectrum.
@@ -210,7 +210,7 @@ def derive_model_curve(
             name=name,
             match_method=match_method,
             interpolator_method=interpolator_method,
-            extrapolate=True,
+            extrapolate=extrapolate,
         )
 
     def _derive_model_zero(
@@ -315,8 +315,8 @@ def calibration_model_factory(
         should_fit=False,
         prominence_coeff=3,
         si_profile="Pearson4",
-        match_method: Literal["cluster", "argmin2d", "assignment"] = "cluster",
-        interpolator_method: Literal["rbf", "pchip", "cubic_spline"] = "rbf",
+        match_method: Literal["cluster", "argmin2d", "assignment"] = "argmin2d",
+        interpolator_method: Literal["rbf", "pchip", "cubic_spline"] = "pchip",
         extrapolate=True,
     ):
         if neon_wl is None: