{ "cells": [ { "cell_type": "markdown", "id": "033c064b", "metadata": {}, "source": [ "# Running Your First Models with Objects\n", "\n", "In this notebook, we demonstrate the basic use of UCLCHEM's python module by running a simple model and then using the analysis functions to examine the output. Otherwise, it is identical to notebook 3." ] }, { "cell_type": "code", "execution_count": 1, "id": "d7e3396e", "metadata": { "execution": { "iopub.execute_input": "2026-01-27T12:59:41.049239Z", "iopub.status.busy": "2026-01-27T12:59:41.048988Z", "iopub.status.idle": "2026-01-27T12:59:42.371679Z", "shell.execute_reply": "2026-01-27T12:59:42.370934Z" } }, "outputs": [], "source": [ "import uclchem" ] }, { "cell_type": "markdown", "id": "549a6bcf", "metadata": {}, "source": [ "## A Simple Cloud\n", "\n", "UCLCHEM's `Cloud` class, models a spherical cloud of isothermal gas. We can keep a constant density or have it increase over time following a freefall equation. This model is generally useful whenever you want to model a homogeneous cloud of gas under constant conditions. For example, in the inner parts of a molecular cloud where Av $\\gtrsim$ 10 there are very few depth dependent processes. You may wish to model the whole of this UV shielded portion of the cloud with a single `Cloud` model.\n", "\n", "Due to the large number of parameters in a chemical model and the way fortran and python interaction, we find it is easiest to do parameter input through python dictionaries. In this block, we define param_dict which contains the parameters we wish to modify for this run. Every `uclchem.model` class accepts a dictionary as an optional argument. Every parameter has a default value which is overridden if that parameter is specified in this dictionary. You can find a complete list of modifiable parameters and their default values in [our parameter docs](/docs/parameters)." ] }, { "cell_type": "code", "execution_count": 2, "id": "1c6ea598", "metadata": { "execution": { "iopub.execute_input": "2026-01-27T12:59:42.373856Z", "iopub.status.busy": "2026-01-27T12:59:42.373549Z", "iopub.status.idle": "2026-01-27T12:59:45.441881Z", "shell.execute_reply": "2026-01-27T12:59:45.441108Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Model ran successfully.\n" ] } ], "source": [ "# set a parameter dictionary for phase 1 collapse model\n", "out_species = [\"SO\", \"CO\"]\n", "param_dict = {\n", " \"endAtFinalDensity\": False, # stop at finalTime\n", " \"freefall\": False, # don't increase density in freefall\n", " \"initialDens\": 1e4, # starting density\n", " \"initialTemp\": 10.0, # temperature of gas\n", " \"finalTime\": 1.0e6, # final time\n", " \"rout\": 0.1, # radius of cloud in pc\n", " \"baseAv\": 1.0, # visual extinction at cloud edge.\n", "}\n", "cloud = uclchem.model.Cloud(param_dict=param_dict, out_species=out_species)\n", "cloud.check_error()" ] }, { "cell_type": "markdown", "id": "a5ddfcc4", "metadata": {}, "source": [ "## Checking the output\n", "\n", "The code above produced the object `cloud` which holds the variables associated to the model that UCLCHEM calculated. Calling `cloud.success_flag` would exposes the variable `success_flag` which will be 0 if the model was run successfully, and negative if not. You can check an error value by calling cloud.check_error() to get a more detailed error message.\n", "\n", "Additionally, the `cloud` object holds the physical parameters and chemical abundance arrays calculated by UCLCHEM. These are stored in `cloud.physics_array` and `cloud.chemical_abun_array` respectively. If we wish to see just the abundances of the final time step, we can get that array with `cloud.next_starting_chemistry`, bearing in mind that the variable `cloud.starting_chemistry` contains the array of abundances that the model started with, if it was provided to the object.\n", "\n", "If `abundSaveFile` was added to the `param_dict`, then the final abundances of all species would be written to the file listed in `abundSaveFile`. If `outputFile` is added, then all abundances and physical parameters for all time steps will be written to the file `outputFile`.\n", "\n", "The UCLCHEM model classes have methods to reformat the output arrays into pandas dataframes, as well as having the option to read previously run model output files. To retrieve a pandas dataframe of a model we can call `cloud.get_dataframes(point = 0)` where the point optional input allows us to choose which point we wish to retrieve the dataframe for, if we ran a multipoint model. This method defaults the `point` value to 0 to retrieve the central point." ] }, { "cell_type": "code", "execution_count": 3, "id": "ecbe41da", "metadata": { "execution": { "iopub.execute_input": "2026-01-27T12:59:45.443733Z", "iopub.status.busy": "2026-01-27T12:59:45.443561Z", "iopub.status.idle": "2026-01-27T12:59:45.464726Z", "shell.execute_reply": "2026-01-27T12:59:45.464003Z" } }, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " Time Density gasTemp dustTemp Av radfield zeta \\\n", "0 1.000000e-07 10000.0 10.0 10.0 2.92875 1.0 2.910002 \n", "1 1.000000e-06 10000.0 10.0 10.0 2.92875 1.0 2.910002 \n", "2 1.000000e-05 10000.0 10.0 10.0 2.92875 1.0 2.910002 \n", "3 1.000000e-04 10000.0 10.0 10.0 2.92875 1.0 2.910002 \n", "4 1.000000e-03 10000.0 10.0 10.0 2.92875 1.0 2.910002 \n", "\n", " dstep H H+ ... @OCS @C4N @SIC3 \\\n", "0 1.0 0.5 9.674388e-18 ... 1.000000e-30 1.000000e-30 1.000000e-30 \n", "1 1.0 0.5 2.630577e-16 ... 1.000001e-30 1.000001e-30 1.000001e-30 \n", "2 1.0 0.5 2.798139e-15 ... 1.000015e-30 1.000015e-30 1.000015e-30 \n", "3 1.0 0.5 2.827256e-14 ... 1.000147e-30 1.000147e-30 1.000147e-30 \n", "4 1.0 0.5 2.943250e-13 ... 1.001110e-30 1.001110e-30 1.001110e-30 \n", "\n", " @SO2 @S2 @HS2 @H2S2 E- \\\n", "0 1.000000e-30 1.000000e-30 1.000000e-30 1.000000e-30 0.000182 \n", "1 1.000001e-30 1.000001e-30 1.000001e-30 1.000001e-30 0.000182 \n", "2 1.000015e-30 1.000015e-30 1.000015e-30 1.000015e-30 0.000182 \n", "3 1.000147e-30 1.000147e-30 1.000147e-30 1.000148e-30 0.000182 \n", "4 1.001110e-30 1.000926e-30 1.001081e-30 1.001335e-30 0.000182 \n", "\n", " BULK SURFACE \n", "0 5.613460e-20 7.478491e-13 \n", "1 5.546864e-18 7.434018e-12 \n", "2 5.538897e-16 7.428646e-11 \n", "3 5.418362e-14 7.347047e-10 \n", "4 3.072463e-12 5.530733e-09 \n", "\n", "[5 rows x 343 columns]" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cloud.get_dataframes().head()" ] }, { "cell_type": "markdown", "id": "2e6a0006", "metadata": {}, "source": [ "We can also test whether the model run went well by checking for element conservation. We do this because integrator errors often show up as a failure to conserve elemental abundances.\n", "\n", "We can use `cloud.check_conservation(element_list=[\"H\", \"N\", \"C\", \"O\", \"S\"])` to test whether we conserve elements in this run. This method prints the conservation results of elements listed in the argument `element_list` as a percentage of the original abundance by default. In an ideal case, these values are 0\\% indicating the total abundance at the end of the model is exactly the same as the total at the start.\n", "\n", "Changes of less than 1\\% are fine for many cases but if they are too high, you could consider changing the `reltol` and `abstol` parameters that control the integrator accuracy. They are error tolerance, so smaller values lead to smaller errors and (usually) longer integration times. The default values were chosen by running a large grid of models and choosing the tolerances with the lowest average run time from those that conserved elements well and rarely failed. Despite this, there are no one-size-fits-all perfect tolerances, and you may run into issues with different networks or models." ] }, { "cell_type": "code", "execution_count": 4, "id": "2a68bd1c", "metadata": { "execution": { "iopub.execute_input": "2026-01-27T12:59:45.466351Z", "iopub.status.busy": "2026-01-27T12:59:45.466192Z", "iopub.status.idle": "2026-01-27T12:59:45.490932Z", "shell.execute_reply": "2026-01-27T12:59:45.490079Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Element conservation report\n", "{'H': '0.000%', 'N': '0.000%', 'C': '0.000%', 'O': '0.000%', 'S': '0.000%'}\n" ] } ], "source": [ "cloud.check_conservation(element_list=[\"H\", \"N\", \"C\", \"O\", \"S\"])" ] }, { "cell_type": "markdown", "id": "09f0b7ad", "metadata": {}, "source": [ "## Plotting Results\n", "Finally, you will want to plot your results. This can be done with any plotting library but UCLCHEM does provide a few functions to make quick plots. Note the use of $ symbols in the species list below, this gets the total ice abundance of a species. For two phase models, this is just the surface abudance but for three phase it is the sum of surface and bulk." ] }, { "cell_type": "code", "execution_count": 5, "id": "33249934", "metadata": { "execution": { "iopub.execute_input": "2026-01-27T12:59:45.492615Z", "iopub.status.busy": "2026-01-27T12:59:45.492457Z", "iopub.status.idle": "2026-01-27T12:59:45.955037Z", "shell.execute_reply": "2026-01-27T12:59:45.954382Z" } }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, ax = cloud.create_abundance_plot(\n", " species=[\"H\", \"H2\", \"$H\", \"$H2\", \"H2O\", \"$H2O\", \"CO\", \"$CO\", \"$CH3OH\", \"CH3OH\"],\n", " figsize=(10, 7),\n", ")\n", "ax = ax.set(xscale=\"log\", ylim=(1e-15, 1), xlim=(1e3, 1e6))" ] }, { "cell_type": "markdown", "id": "79502141", "metadata": {}, "source": [ "and that's it! You've run your first UCLCHEM model, checked that the element conservation is correct, and plotted the abundances." ] } ], "metadata": { "jupytext": { "formats": "ipynb,py:light" }, "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.13.11" } }, "nbformat": 4, "nbformat_minor": 5 }