improved tests

Author: MKastek

README.md

@@ -24,7 +24,7 @@ pip install SimulatedLIBS
 ## Import
 
 ```python
-from SimulatedLIBS import simulation
+from SimulatedLIBS import SimulatedLIBS
 ```
 ## Example
 Parameters:
@@ -40,15 +40,15 @@ Parameters:
 
 ### Static websraping
 ```python
-libs = simulation.SimulatedLIBS(Te=1.0,
-                                Ne=10**17,
-                                elements=['W','Fe','Mo'],
-                                percentages=[50,25,25],
-                                resolution=1000,
-                                low_w=200,
-                                upper_w=1000,
-                                max_ion_charge=3,
-                                webscraping='static')
+libs = SimulatedLIBS(Te=1.0,
+                     Ne=10**17,
+                     elements=['W','Fe','Mo'],
+                     percentages=[50,25,25],
+                     resolution=1000,
+                     low_w=200,
+                     upper_w=1000,
+                     max_ion_charge=3,
+                     webscraping='static')
 ```
 
 ### Plot
@@ -75,15 +75,15 @@ libs.get_raw_spectrum()
 ```
 ### Dynamic webscraping
 ```python
-libs = simulation.SimulatedLIBS(Te=1.0,
-                                Ne=10**17,
-                                elements=['W','Fe','Mo'],
-                                percentages=[50,25,25],
-                                resolution=1000,
-                                low_w=200,
-                                upper_w=1000,
-                                max_ion_charge=3,
-                                webscraping='dynamic')
+libs = SimulatedLIBS(Te=1.0,
+                     Ne=10**17,
+                     elements=['W','Fe','Mo'],
+                     percentages=[50,25,25],
+                     resolution=1000,
+                     low_w=200,
+                     upper_w=1000,
+                     max_ion_charge=3,
+                     webscraping='dynamic')
 ```
 
 ### Plot
@@ -102,7 +102,7 @@ libs.plot_ion_spectra()
 Based on .csv file with chemical composition of samples, one can generate dataset of simulated LIBS measurements
 with different Te and Ne values.
 
-Example of input .csv file:
+Example of input_composition_df pd.DataFrame:
 
 |W  |H  |He |name|
 |---|---|---|----|
@@ -111,13 +111,12 @@ Example of input .csv file:
 |40 |40 |20 |C   |
 
 ```python
-simulation.SimulatedLIBS.create_dataset(input_csv_file="data.csv",
-                                        output_csv_file='output.csv',
-                                        size=100,
-                                        Te_min=1.0,
-                                        Te_max=2.0,
-                                        Ne_min=10**17,
-                                        Ne_max=10**18)
+SimulatedLIBS.create_dataset(input_composition_df,
+                             size=100,
+                             Te_min=1.0,
+                             Te_max=2.0,
+                             Ne_min=10**17,
+                             Ne_max=10**18)
 ```
 
 Example of output .csv file:

SimulatedLIBS/simulation.py

@@ -295,7 +295,6 @@ def plot(
         plt.ylabel("Line Intensity [a.u.]")
 
     def plot_ion_spectra(self):
-
         self.ion_spectra.drop(["Sum(calc)"], axis=1).plot(
             x="Wavelength (nm)",
             xlabel=r"$\lambda$ [nm]",
@@ -413,7 +412,6 @@ def create_dataset(
 
         for spectra in spectra_pool:
             intensity = spectra.result()["spectrum"]["intensity"].values.tolist()
-
             percentages = spectra.result()["composition"]["percentages"].values.tolist()
             intensity.extend(percentages)
             intensity.append(spectra.result()["name"])

tests/test_SimulatedLIBS.py

@@ -35,6 +35,12 @@ def test_values():
 def test_dataset():
     input_df = pd.read_csv("data.csv")
     libs_df = SimulatedLIBS.create_dataset(input_df, size=1)
+    assert (
+        input_df[
+            input_df["name"] == libs_df.iloc[:, -6:-2]["name"].iloc[0]
+        ].values.tolist()[0]
+        == libs_df.iloc[:, -6:-2].iloc[0].values.tolist()
+    )
     assert libs_df.iloc[:, :-6].max().max() > 0
     if os.path.exists("out_put.csv"):
         os.remove("out_put.csv")