Update docs

docs/examples/transmission_ftir/PyIRoGlass_Transmission.ipynb

@@ -418,7 +418,7 @@
    "source": [
     "# Concentrations\n",
     "\n",
-    "We now want to convert all those peak heights (with uncertainties) to concentrations (with uncertainties), by applying the Beer-Lambert Law. We do so by using the Concentration_Output function, which takes in these parameters and samples over N samples for a secondary MCMC: \n",
+    "We now want to convert all those peak heights (with uncertainties) to concentrations (with uncertainties), by applying the Beer-Lambert Law. We do so by using the calculate_concentrations function, which takes in these parameters and samples over N samples for a secondary MCMC: \n",
     "\n",
     "- DF_OUTPUT: Output from Run_All_Spectra\n",
     "- N: Number of samples for this MCMC\n",
@@ -440,10 +440,9 @@
     "P_ROOM = 1 # Bar\n",
     "\n",
     "N = 500000 # MCMC samples\n",
-    "DENSITY_EPSILON, MEGA_SPREADSHEET = pig.calculate_concentrations(DF_OUTPUT, N, CHEMISTRY, THICKNESS, T_ROOM, P_ROOM)\n",
+    "concentrations_df = pig.calculate_concentrations(DF_OUTPUT, N, CHEMISTRY, THICKNESS, T_ROOM, P_ROOM)\n",
     "\n",
-    "DENSITY_EPSILON.to_csv('DensityEpsilon.csv')\n",
-    "MEGA_SPREADSHEET.to_csv('H2OCO2.csv')"
+    "concentrations_df.to_csv('H2OCO2.csv')"
    ]
   },
   {
@@ -461,14 +460,14 @@
    },
    "outputs": [],
    "source": [
-    "MEGA_SPREADSHEET"
+    "concentrations_df"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "There are a few things to note. Each column with the suffix _MEAN represents the mean value, _BP represents the best-parameter from MCMC, and _STD represents the standard deviation. We recommend the use of the 'H2OT_MEAN', 'H2OT_STD', 'CO2_MEAN', and 'CO2_STD' columns. The columns with the suffix _S2N show the signal-to-noise ratio of the NIR peaks, and the columns with the prefix ERR_ just process this information, returning a '-' if the peaks are meaningful and a '*' if the signal is too low. \n",
+    "There are a few things to note. Each column with the suffix _MEAN represents the mean value, _BP represents the best-parameter from MCMC, and _STD represents the standard deviation. We recommend the use of the 'H2OT_MEAN', 'H2OT_STD', 'CO2_MEAN', and 'CO2_STD' columns. The columns with the suffix _STN show the signal-to-noise ratio of the NIR peaks, and the columns with the prefix ERR_ just process this information, returning a '-' if the peaks are meaningful and a '*' if the signal is too low. \n",
     "\n",
     "Concentrations of $\\mathrm{H_2O}$ depend on whether your sample is saturated or not. If your sample is unsaturated (marked by H2OT_3550_SAT == '-'), the column 'H2OT_MEAN'=='H2OT_3550_M'. If your sample is saturated (marked by H2OT_3550_SAT == '*'), the column of 'H2OT_MEAN'=='H2Om_1635_BP'+'OH_4500_M'. The $\\mathrm{H_2O_{t, 3550}}$ peak cannot be used, given potential nonlinearity in the Beer-Lambert Law. See the discussion of this handling of speciation in the paper. \n"
    ]
@@ -477,22 +476,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Here is also all the other relevant information for calculating these concentrations. All the density and molar absorptivity information is stored in this dataframe. \n",
-    "\n",
     "The column 'Density' contains the densities used for the final concentration. The values between 'Density' and 'Density_Sat' will be different if the sample is saturated, showing the difference in densities when using variable concentrations of $\\mathrm{H_2O_m}$. \n",
     "\n",
-    "'Tau' and 'Na/Na+Ca' calculate the compositional parameters required for determining molar absorptivity. All calculated molar absorptivities and their uncertainties (sigma_ prefix) from the inversion are provided in the dataframe. \n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "DENSITY_EPSILON"
+    "'Tau' and 'Eta' calculate the compositional parameters required for determining molar absorptivity. All calculated molar absorptivities and their uncertainties (sigma_ prefix) from the inversion are provided in the dataframe. \n"
    ]
   },
   {