higher resolution
"metadata": {},
"outputs": [],
"source": [
- "dose_criteria = np.arange(0.1, 3.1, 0.1) # %\n",
- "distance_criteria = np.arange(0.1, 2.5, 0.1) # mm"
+ "dose_criteria = np.arange(0.1, 3.01, 0.01) # %\n",
+ "distance_criteria = np.arange(0.1, 2.51, 0.01) # mm"
]
},
{
" 'distance_mm_threshold': distance_criteria,\n",
" 'lower_percent_dose_cutoff': lower_percent_dose_cutoff,\n",
" 'interp_fraction': 10, # Should be 10 or more for more accurate results\n",
- " 'max_gamma': 2,\n",
+ " 'max_gamma': 1.1,\n",
" 'random_subset': None,\n",
" 'local_gamma': local,\n",
- " 'ram_available': 2**29, # 1/2 GB\n",
- " 'quiet': True\n",
+ " 'ram_available': 2**32, # 4 GB\n",
+ " 'quiet': False\n",
"}"
]
},
" c1.set_label('Pass rate (%)', rotation=270, labelpad=12)"
]
},
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## FlashGamma's pass rates"
+ ]
+ },
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
- "# Now let's plot the gamma surface.\n",
- "\n",
- "\n",
"plot_passing_rates(pass_rates)"
]
},
]
},
{
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "plot_passing_rates(pymedphys_pass_rates)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
+ "cell_type": "markdown",
"metadata": {},
- "outputs": [],
"source": [
- "diff = pymedphys_pass_rates - pass_rates"
+ "## PyMedPhys' pass rates"
]
},
{
"metadata": {},
"outputs": [],
"source": [
- "plot_passing_rates(diff)"
+ "plot_passing_rates(pymedphys_pass_rates)"
]
}
],
