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Update readme with new installation instructions #30

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Update readme with new installation instructions #30

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Update readme with new installation instructions and demos
panne027 Nov 13, 2024
e05f8ad
Fix prints in run_scenario
panne027 Nov 13, 2024
92dc84e
Fix typos
panne027 Nov 13, 2024
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49 changes: 21 additions & 28 deletions README.md
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Expand Up @@ -9,61 +9,54 @@

This repo houses T3CO (Transportation Technology Total Cost of Ownership), software for modeling total cost of ownership for commercial vehicles with advanced powertrains.

To get started, read the [Quick Start Guide](https://github.com/NREL/T3CO/blob/1eefffc251fcbd2b0c0515512f51d1b27bb978fd/docs/quick_start.md)
To get started, read the [Quick Start Guide](https://github.com/NREL/T3CO/blob/main/docs/quick_start.md)

For information on the T3CO models, go to the [Overview](https://github.com/NREL/T3CO/blob/264a730de942671eb2345a5afca7e1afd6d67666/docs/T3CO_Overview.md)
For information on the T3CO models, go to the [Overview](https://github.com/NREL/T3CO/blob/main/docs/T3CO_Overview.md)

## Usage

**T3CO** is a general framework allowing a user to determine the total cost of ownership (TCO) of a FASTSim vehicle (paired with a FASTSim DriveCycle(s) for determining fuel efficiency). The user can also determine performance of gradability, acceleration, and range. In addition to straight TCO computation there is also the option to optimize a vehicle powertrain such that it meets performance optional targets while also optionally minimizing TCO.
**T3CO** is a general framework allowing a user to determine the total cost of ownership (TCO) of a FASTSim vehicle (paired with a FASTSim DriveCycle(s) for determining fuel efficiency). The user can also determine performance of gradeability, acceleration, and range. In addition to straight TCO computation there is also the option to optimize a vehicle powertrain such that it meets performance optional targets while also optionally minimizing TCO.

## Installation
### Installing From [PyPI](https://pypi.org/project/t3co/)
T3CO can be easily installed from PyPI. This is the preferred method when using T3CO as a dependency for a project. To install the latest release:
T3CO is available on PyPI and as a public access GitHub repository. This gives the user two ways of installing the T3CO Python Package.
### 1. Installing From [PyPI](https://pypi.org/project/t3co/)
```bash
pip install t3co
```

To install a specific version (for example T3CO v1.0.8):
```bash
pip install t3co==1.0.8
```

### From GitHub
T3CO can also be installed directly from the GitHub repository for accessing demo input files and running T3CO using the Command Line Interface.
### 2. Cloning the [GitHub Repo](https://github.com/NREL/T3CO)
T3CO can also be installed directly from a clone of the GitHub repository which makes it easier to access input files and run the tool using a Command Line Interface.

First, clone the repository from [GitHub](https://github.com/NREL/T3CO):
First, [clone](https://git-scm.com/docs/git-clone) the repository from [GitHub](https://github.com/NREL/T3CO) from your desired directory:
```bash
git clone https://github.com/NREL/T3CO.git T3CO
```

From within the [Python environment](#setting-up-env) Navigate to the parent directory containing the T3CO repository e.g. `cd github/T3CO/` and run:
From within the [Python environment](./docs/installation.md#setting-up-env), navigate to the parent directory containing the T3CO repository (e.g. `cd GitHub/T3CO/`) and run:
```bash
pip install -e .
```
This installs the local version of the T3CO clone along with all its [dependencies](https://github.com/NREL/T3CO/blob/29b0e848360b3b2de84b555bf52c52bf6e76134e/requirements.txt).


## Demo
**Using the [T3CO Config](https://github.com/NREL/T3CO/blob/c3df6421033cef7d35b7d7cd575ab94e85fcd9a9/t3co/resources/T3COConfig.csv) file**

Create a new `analysis_id` on `./t3co/resources/T3COConfig.csv` or update the existing rows and use them to run T3CO.
This installs the local version of the T3CO clone along with all its [dependencies](https://github.com/NREL/T3CO/blob/main/requirements.txt).

### Copying the Demo Input Files
The [`t3co.resources`](https://github.com/NREL/T3CO/tree/main/t3co/resources) folder contains all the necessary input files needed for running T3CO. To get an offline copy of this folder in your preferred directory, run:
```bash
cd t3co
python sweep.py --analysis-id=0
install_t3co_demo_inputs
```

**Using Command Line Arguments**
More information on the demo input files can be found in the [Installation Guide](https://github.com/NREL/T3CO/blob/main/docs/installation.md#copy-demo-inputs)


## Running T3CO
T3CO needs three main input files (*Vehicles*, *Scenarios*, and *Config*) to run an analysis. The analysis settings, file paths to main and auxiliary input files, and other parameter overrides are saved as an entry on the *Config* file. The user is provided with 500+ *Vehicle-Scenario* pairs inputs and four *Config* sample analyses to choose from to modify parameters and/or run their first T3CO analysis. The main module for T3CO,`t3co.sweep`, can be run using:

```bash
cd t3co
python sweep.py --skip_all_opt --selections [1,2,3,4,5] --dst_dir .t3co_results/demodata
python -m t3co.sweep --analysis-id=0 --config=<path/to/T3COConfig.csv>
```

Point the `--config` argument to the `T3COConfig.csv` file path (either the t3co/resource/T3COConfig.csv file in a repo clone or the demo_inputs/T3COConfig.csv file after copying the demo input files. This parameter defaults to the T3COConfig.csv file in the t3co.resources module) and `--analysis-id` to the desired `config.analysis_id` (either an existing row or a newly added "Analysis" row in the `T3COConfig.csv` file. Default = `0`).

**using optimiztion in sweep module** [see](https://github.com/NREL/T3CO/blob/master/docs/optimization.md#optimization-from-sweep-module-)

Additional information on the inputs, the Batch Mode feature, other CLI arguments, and description of T3CO results are mentioned in the [Quick Start Guide](https://github.com/NREL/T3CO/blob/main/docs/quick_start.md)

## Acknowledgements
This tool was developed with funding support from the US Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE)'s Vehicle Technology Office.
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2 changes: 1 addition & 1 deletion docs/installation.md
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Expand Up @@ -30,7 +30,7 @@ T3CO depends on [Python](https://www.python.org/downloads/)>=3.8 and <=3.10. To
## Installing T3CO Python Package
T3CO is available on PyPI and as a public access GitHub repository. This gives the user two ways of installing the T3CO Python Package.
### 1. Installing From [PyPI](https://pypi.org/project/t3co/) <a name=install-from-pypi></a>
T3CO can be easily installed from PyPI. This is the preferred method when using T3CO to run analysis using input files. To install the latest release:
T3CO can be easily installed from PyPI. This is the preferred method for using T3CO to run analysis with input files. To install the latest release:
```bash
pip install t3co
```
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6 changes: 1 addition & 5 deletions t3co/run/run_scenario.py
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Expand Up @@ -734,14 +734,12 @@ def load_design_cycle_from_scenario(
sdc = str(config.dc_files[dc_id])
else:
sdc = str(scenario.drive_cycle)
print(f"sdc: {sdc}")
print(f"Drivecycle: {sdc}")
if "[" in sdc and "]" in sdc and "(" in sdc and ")" in sdc:
scenario.drive_cycle = ast.literal_eval(sdc)
range_cyc = []
for dc_weight in scenario.drive_cycle:
cycle_file_name = Path(dc_weight[0]).name
print(f"Drivecycle= {cycle_file_name} weight = {dc_weight[1]}")

dc = load_design_cycle_from_path(
cyc_file_path=Path(cyc_file_path) / dc_weight[0]
)
Expand All @@ -750,7 +748,6 @@ def load_design_cycle_from_scenario(
range_cyc.append((dc, weight))
else:
cycle_file_name = Path(sdc).name
print(f"Drivecycle= {cycle_file_name}")
range_cyc = load_design_cycle_from_path(cyc_file_path=sdc)
range_cyc.name = cycle_file_name

Expand All @@ -773,7 +770,6 @@ def load_design_cycle_from_path(cyc_file_path: str) -> fastsim.cycle.Cycle:

else:
finalized_path = cyc_file_path
print(f"Drivecycle final path: {finalized_path}")
range_cyc = cycle.Cycle.from_file(finalized_path)
range_cyc = range_cyc.to_rust()
return range_cyc
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