From a1526709644a193ca94f4e20e1ec50735b778720 Mon Sep 17 00:00:00 2001
From: jmcvey3 <53623232+jmcvey3@users.noreply.github.com>
Date: Tue, 12 Nov 2024 13:12:10 -0800
Subject: [PATCH 1/4] Code that got lost in translation, fixes, updated jupyter
 notebook

---
 examples/acoustics_example.ipynb | 386 +++++++++++++++++++++++++------
 mhkit/acoustics/analysis.py      |  92 +++++---
 mhkit/acoustics/graphics.py      |   6 +-
 3 files changed, 390 insertions(+), 94 deletions(-)

diff --git a/examples/acoustics_example.ipynb b/examples/acoustics_example.ipynb
index 41104f23..09837f09 100644
--- a/examples/acoustics_example.ipynb
+++ b/examples/acoustics_example.ipynb
@@ -14,6 +14,7 @@
     "2. Calibrate data\n",
     "3. Calculate spectral density\n",
     "4. Calculate other parameters\n",
+    "5. Create plots\n",
     "\n",
     "We'll import a couple plotting tools and the acoustics module:"
    ]
@@ -26,6 +27,7 @@
    "source": [
     "import numpy as np\n",
     "import matplotlib.dates as mdates\n",
+    "import matplotlib.pyplot as plt\n",
     "\n",
     "from mhkit import acoustics"
    ]
@@ -131,7 +133,7 @@
     "\n",
     "After the .wav file is read in, either in units of pressure or voltage, we calculate the mean square sound pressure spectral density (SPSD) of the timeseries using `sound_pressure_spectral_density`. This splits the timeseries into windows and uses fast Fourier transforms to convert the raw measurements into the frequency domain, with units of $Pa^2/Hz$ or $V^2/Hz$, depending on the input. The function takes the original datafile, the hydrophone's sampling rate, which is stored as an attribute of the measurement timeseries, and a window size in seconds as input.\n",
     "\n",
-    "The IEC-40 considers an acoustic sample to have a length of 1 second, so we'll set the window size as such here."
+    "The IEC-40 considers an acoustic sample to have a length of 1 second, so we'll set the bin length as such here."
    ]
   },
   {
@@ -152,14 +154,14 @@
     "\n",
     "For conducting scientific-grade analysis, it is critical to use calibration curves to correct the SPSD calculations. Hydrophones should be calibrated (i.e., a sensitivity calibration curve should be generated for a hydrophone) every few years. The IEC-40 asks that a hydrophone be calibrated both before and after the test deployment.\n",
     "\n",
-    "A calibration curve consists of the hydrophone's sensitivity (in units of dB rel $1 V^2/uPa^2$) vs frequency and should be applied to the spectral density we just calculated.\n",
+    "A calibration curve consists of the hydrophone's sensitivity (in units of $dB$ rel $1 V^2/uPa^2$) vs frequency and should be applied to the spectral density we just calculated.\n",
     "\n",
     "The easiest way to apply a sensitivity calibration curve in MHKiT is to first copy the calibration data into a CSV file, where the left column contains the calibrated frequencies and the right column contains the sensitivity values. Here we use the function in the following codeblock to read in a CSV file created with the column headers \"Frequency\" and \"Analog Sensitivity\"."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -200,7 +202,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -578,20 +580,20 @@
        "       -166.2 , -166.25, -166.28, -166.29, -166.29, -166.27, -166.24,\n",
        "       -166.17, -166.03, -165.79, -165.47, -164.87])\n",
        "Coordinates:\n",
-       "  * Frequency  (Frequency) float64 320B 1.0 1.183 1.399 ... 500.3 591.8 700.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'Analog Sensitivity'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>Frequency</span>: 40</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-c6d0953b-3ea8-4759-9328-aacec4fb79a4' class='xr-array-in' type='checkbox' checked><label for='section-c6d0953b-3ea8-4759-9328-aacec4fb79a4' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>-223.5 -220.8 -218.1 -215.4 -212.7 ... -166.0 -165.8 -165.5 -164.9</span></div><div class='xr-array-data'><pre>array([-223.49, -220.8 , -218.13, -215.41, -212.68, -209.91, -207.12,\n",
+       "  * Frequency  (Frequency) float64 320B 1.0 1.183 1.399 ... 500.3 591.8 700.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'Analog Sensitivity'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>Frequency</span>: 40</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-b5c0b57b-42cf-4d90-b7a2-c79988062e0d' class='xr-array-in' type='checkbox' checked><label for='section-b5c0b57b-42cf-4d90-b7a2-c79988062e0d' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>-223.5 -220.8 -218.1 -215.4 -212.7 ... -166.0 -165.8 -165.5 -164.9</span></div><div class='xr-array-data'><pre>array([-223.49, -220.8 , -218.13, -215.41, -212.68, -209.91, -207.12,\n",
        "       -204.29, -201.45, -198.58, -195.69, -192.79, -189.85, -186.9 ,\n",
        "       -183.93, -180.93, -177.92, -174.97, -172.16, -169.61, -167.69,\n",
        "       -166.52, -165.96, -165.81, -165.85, -165.95, -166.05, -166.13,\n",
        "       -166.2 , -166.25, -166.28, -166.29, -166.29, -166.27, -166.24,\n",
-       "       -166.17, -166.03, -165.79, -165.47, -164.87])</pre></div></div></li><li class='xr-section-item'><input id='section-f55018de-a33d-4ce1-acda-863155b5db51' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f55018de-a33d-4ce1-acda-863155b5db51' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>Frequency</span></div><div class='xr-var-dims'>(Frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 1.183 1.399 ... 591.8 700.0</div><input id='attrs-58dad91a-42f8-4179-85d4-557b10be10a0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-58dad91a-42f8-4179-85d4-557b10be10a0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5d899ad6-a9d6-43b9-9e8c-f4f438bad70b' class='xr-var-data-in' type='checkbox'><label for='data-5d899ad6-a9d6-43b9-9e8c-f4f438bad70b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  1.   ,   1.183,   1.399,   1.655,   1.958,   2.316,   2.74 ,   3.241,\n",
+       "       -166.17, -166.03, -165.79, -165.47, -164.87])</pre></div></div></li><li class='xr-section-item'><input id='section-17ea6d17-3d8b-4cdb-a2c2-06e1ad0cd939' class='xr-section-summary-in' type='checkbox'  checked><label for='section-17ea6d17-3d8b-4cdb-a2c2-06e1ad0cd939' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>Frequency</span></div><div class='xr-var-dims'>(Frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 1.183 1.399 ... 591.8 700.0</div><input id='attrs-366aa3af-24f9-4345-b6b3-b2ce1ee17056' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-366aa3af-24f9-4345-b6b3-b2ce1ee17056' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6e703b10-4c32-4f9a-b708-b60496744b10' class='xr-var-data-in' type='checkbox'><label for='data-6e703b10-4c32-4f9a-b708-b60496744b10' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  1.   ,   1.183,   1.399,   1.655,   1.958,   2.316,   2.74 ,   3.241,\n",
        "         3.834,   4.535,   5.364,   6.345,   7.506,   8.879,  10.5  ,  12.42 ,\n",
        "        14.7  ,  17.38 ,  20.56 ,  24.33 ,  28.78 ,  34.04 ,  40.26 ,  47.63 ,\n",
        "        56.34 ,  66.65 ,  78.84 ,  93.26 , 110.3  , 130.5  , 154.4  , 182.6  ,\n",
-       "       216.   , 255.5  , 302.2  , 357.5  , 422.9  , 500.3  , 591.8  , 700.   ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-00cf03c4-8049-45d9-b63e-bc60a4abcca3' class='xr-section-summary-in' type='checkbox'  ><label for='section-00cf03c4-8049-45d9-b63e-bc60a4abcca3' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>Frequency</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b6f7256f-a7b9-47f8-bab7-db407ab5e7f4' class='xr-index-data-in' type='checkbox'/><label for='index-b6f7256f-a7b9-47f8-bab7-db407ab5e7f4' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  1.0, 1.183, 1.399, 1.655, 1.958, 2.316,  2.74, 3.241, 3.834, 4.535,\n",
+       "       216.   , 255.5  , 302.2  , 357.5  , 422.9  , 500.3  , 591.8  , 700.   ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8138cb9e-803b-49d8-b786-c7b1fb18ee70' class='xr-section-summary-in' type='checkbox'  ><label for='section-8138cb9e-803b-49d8-b786-c7b1fb18ee70' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>Frequency</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-52ca0b16-c3a3-49d1-b7a6-57eea7100c0c' class='xr-index-data-in' type='checkbox'/><label for='index-52ca0b16-c3a3-49d1-b7a6-57eea7100c0c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  1.0, 1.183, 1.399, 1.655, 1.958, 2.316,  2.74, 3.241, 3.834, 4.535,\n",
        "       5.364, 6.345, 7.506, 8.879,  10.5, 12.42,  14.7, 17.38, 20.56, 24.33,\n",
        "       28.78, 34.04, 40.26, 47.63, 56.34, 66.65, 78.84, 93.26, 110.3, 130.5,\n",
        "       154.4, 182.6, 216.0, 255.5, 302.2, 357.5, 422.9, 500.3, 591.8, 700.0],\n",
-       "      dtype=&#x27;float64&#x27;, name=&#x27;Frequency&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b8c69746-039a-4427-80ab-f7c8f293429a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b8c69746-039a-4427-80ab-f7c8f293429a' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+       "      dtype=&#x27;float64&#x27;, name=&#x27;Frequency&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6b900d85-7ed8-4da5-ae94-23f1cfa281f9' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6b900d85-7ed8-4da5-ae94-23f1cfa281f9' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.DataArray 'Analog Sensitivity' (Frequency: 40)> Size: 320B\n",
@@ -605,7 +607,7 @@
        "  * Frequency  (Frequency) float64 320B 1.0 1.183 1.399 ... 500.3 591.8 700.0"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -616,7 +618,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -631,14 +633,14 @@
    "source": [
     "### Mean Square Sound Pressure Spectral Density Level\n",
     "\n",
-    "We can use the function `sound_pressure_spectral_density_level` to calculate the mean square sound pressure spectral density levels (SPSDLs) from the calibrated SPSD. This function converts absolute pressure into relative pressure in log-space, the traditional means with which we measure sound, in units of decibels relative to 1 uPa (dB rel 1 uPa), the standard for underwater sound. \n",
+    "We can use the function `sound_pressure_spectral_density_level` to calculate the mean square sound pressure spectral density levels (SPSDLs) from the calibrated SPSD. This function converts absolute pressure into relative pressure in log-space, the traditional means with which we measure sound, in units of decibels relative to 1 uPa ($dB$ rel $1 uPa$), the standard for underwater sound. \n",
     "    \n",
     "Sidenote: Sound in air is measured in decibels relative to 20 uPa, the minimum pressure level humans can hear. To convert between dB rel 1 uPa and dB rel 20 uPa, one simply needs to subtract 26 dB from the dB rel 1 uPa value."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -658,7 +660,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -667,7 +669,7 @@
        "48000.0"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -679,7 +681,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
@@ -718,7 +720,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -731,11 +733,69 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Window Averaging\n",
+    "### IEC-40 Stats\n",
     "\n",
     "The IEC-40 requires a few aggregate statistics for characterizing the sound of marine energy devices. For the first, the IEC-40 asks for plots showing the 25%, 50%, and 75% quantiles of the SPSDL during specific marine energy device states. For current energy devices, the IEC-40 requires 10 SPSDL samples at a series of turbine states (braked, freewheel, 25% power, 50% power, 75% power, 100% power). For wave energy devices, the spec requires 30 SPSDL samples in each wave height and period bin observed.\n",
     "\n",
-    "In the following code block, we'll take our 5 minutes of measurements, `time_aggregate` them into 30 second intervals, and find the median, 25% and 75% quantiles of each interval. For the IEC-40, the sets 10 or 30 samples can either be continuous timeseries or pieced together from individual 1 s measurements. For this example notebook we'll keep it simple and just use the first 30 s interval."
+    "For this example notebook we'll keep it simple and use a random set of 30 samples and collate them together. Otherwise one can pick and choose which to use. Then we can find the median and quantiles of those 30 samples."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'Median and Quantile Sound Pressure Spectral Density Level')"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 600x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import random\n",
+    "samples = random.sample(range(spsdl[\"time\"].size), 30)\n",
+    "spsdl_clip = spsdl.isel(time=samples)\n",
+    "\n",
+    "spsdl_median = spsdl_clip.median(\"time\")\n",
+    "spsdl_q25 = spsdl_clip.quantile(0.25, \"time\")\n",
+    "spsdl_q75 = spsdl_clip.quantile(0.75, \"time\")\n",
+    "\n",
+    "# Plot medians and quantiles\n",
+    "fig, ax = acoustics.graphics.plot_spectra(spsdl_median, fmin, fmax)\n",
+    "ax.fill_between(\n",
+    "    spsdl_clip[\"freq\"],\n",
+    "    spsdl_q25,\n",
+    "    spsdl_q75,\n",
+    "    alpha=0.5,\n",
+    "    facecolor=\"C0\",\n",
+    "    edgecolor=None\n",
+    ")\n",
+    "ax.set(ylabel=\"dB rel 1 uPa^2/Hz^2\", ylim=(20, 80))\n",
+    "ax.set_title(\"Median and Quantile Sound Pressure Spectral Density Level\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Window Aggregating\n",
+    "\n",
+    "If desired, one can also group a series of measurements into blocks of time. In the following block, we'll take our 5 minutes of measurements, `time_aggregate` them into 30 second intervals, and find the median, 25% and 75% quantiles of each interval. We then plot the stats of the first time block (block #0)."
    ]
   },
   {
@@ -799,13 +859,176 @@
     "ax.set_title(\"Median and Quantile Sound Pressure Spectral Density Level\")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Band Averaging\n",
+    "\n",
+    "Analysis can also be completed by grouping the data into specific frequency bands, called \"band aggregating here. In other words, instead of aggregating by the time dimension, we do this in the frequency dimension. The band_aggregate function operates by taking the SPSDL and grouping it based on a specified octave.\n",
+    "\n",
+    "If one wants to do more analysis on the grouped frequency bands than the simple statistical methods that xarray offers, it is possible to use the \"map\" function to apply a custom function to a file. Ih the following block of code, we find the empirical quantile function (the empirical version of the cumulative distribution function, CDF) to each decidecade (10th octave) frequency band and plot the 160 Hz band. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "c:\\users\\mcve343\\mhkit-python\\mhkit\\acoustics\\analysis.py:83: UserWarning: `fmax` = 100000 is greater than the Nyquist frequency. Settingfmax = 48000.0\n",
+      "  warnings.warn(\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "[Text(0.5, 1.0, '160.0 Hz'),\n",
+       " Text(0, 0.5, 'Exceedance Probability'),\n",
+       " Text(0.5, 0, 'Decidecade SPSDL [dB re 1 uPa^2/Hz]')]"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 400x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "def cdf(x):\n",
+    "    # Empirical CDF/Quantile Function/Exceedance Probability\n",
+    "    # Use the median of the coordinate we're grouped in\n",
+    "    x = x.median(\"freq\")\n",
+    "    # Squeeze to remove frequency dimension\n",
+    "    shape = np.shape(x)\n",
+    "    x_sorted = np.sort(np.squeeze(x))\n",
+    "    # calculate the proportional values of samples\n",
+    "    p = 1.0 - np.arange(len(x)) / (len(x) + 1)\n",
+    "    # recreate dataarray\n",
+    "    x = x.assign_coords({\"time\": p}).rename({\"time\": \"probability\"})\n",
+    "    x.values = np.reshape(x_sorted, shape)\n",
+    "    return x\n",
+    "\n",
+    "\n",
+    "cdfs = acoustics.band_aggregate(spsdl, octave=10, method={\"map\": cdf})\n",
+    "# Plot\n",
+    "fig, ax = plt.subplots(figsize=(4, 4))\n",
+    "ax.plot(cdfs[40].values, cdfs[\"probability\"].values)\n",
+    "ax.set(\n",
+    "    title=f\"{np.round(cdfs['freq_bins'][40].values, 2)} Hz\",\n",
+    "    ylabel=\"Exceedance Probability\",\n",
+    "    xlabel=\"Decidecade SPSDL [dB re 1 uPa^2/Hz]\",\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Another plot that is useful for IEC-40 compliance are decidecade boxplots of the SPSDL. We can also use the aggregate methods to apply plotting functions, like matplotlib's native boxplot. In this case, we supply the \"map\" function and an iterable of the custom function inputs, in this case the figure axes we want to use to plot.\n",
+    "\n",
+    "This plot shows significant spread in sound measurements due to the vessel noise, with whiskers stretching to the 1st and 99th quantiles. Generally any significant spread in a frequency band is caused by sound generated by an external source, and not the ambient soundscape."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "c:\\users\\mcve343\\mhkit-python\\mhkit\\acoustics\\analysis.py:83: UserWarning: `fmax` = 100000 is greater than the Nyquist frequency. Settingfmax = 48000.0\n",
+      "  warnings.warn(\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "[[<matplotlib.axis.XTick at 0x1c000041f90>,\n",
+       "  <matplotlib.axis.XTick at 0x1c00007d410>,\n",
+       "  <matplotlib.axis.XTick at 0x1c033af9a10>,\n",
+       "  <matplotlib.axis.XTick at 0x1c002c2b290>,\n",
+       "  <matplotlib.axis.XTick at 0x1c000be4e50>,\n",
+       "  <matplotlib.axis.XTick at 0x1c002b19350>],\n",
+       " [Text(0.0, 0, '0'),\n",
+       "  Text(1.0, 0, '1'),\n",
+       "  Text(2.0, 0, '2'),\n",
+       "  Text(3.0, 0, '3'),\n",
+       "  Text(4.0, 0, '4'),\n",
+       "  Text(5.0, 0, '5')],\n",
+       " (1.68, 4.7),\n",
+       " (20.0, 100.0),\n",
+       " Text(0.5, 0, 'log(Frequency) [Hz]'),\n",
+       " Text(0, 0.5, 'Decidecade SPSDL [dB re 1 uPa^2/Hz]')]"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 900x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "def boxplot(x, ax):\n",
+    "    # Use the median of the coordinate we're grouped in\n",
+    "    freq = x[\"freq\"].median()\n",
+    "    x = x.mean(\"freq\")\n",
+    "    # Create boxplots\n",
+    "    ax.boxplot(\n",
+    "        x.values,\n",
+    "        whis=(1, 99),\n",
+    "        showfliers=False,\n",
+    "        positions=[np.log10(freq.values)],\n",
+    "        widths=0.015,\n",
+    "        flierprops={\"marker\": \".\", \"markersize\": 2},\n",
+    "    )\n",
+    "    return x\n",
+    "\n",
+    "fig, ax = plt.subplots(figsize=(9, 5))\n",
+    "acoustics.band_aggregate(\n",
+    "    spsdl, octave=10, method={\"map\": (boxplot, [ax])}\n",
+    ")\n",
+    "xticks = np.linspace(0, 5, 6)\n",
+    "ax.set(\n",
+    "    xticks=xticks,\n",
+    "    xticklabels=xticks.astype(int),\n",
+    "    xlim=(1.68, 4.7),\n",
+    "    ylim=(20, 100),\n",
+    "    xlabel=\"log(Frequency) [Hz]\",\n",
+    "    ylabel=\"Decidecade SPSDL [dB re 1 uPa^2/Hz]\",\n",
+    ")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "### Sound Pressure Level\n",
     "\n",
-    "The next two requirements from the IEC-40 are calculations of sound pressure level (SPL). We'll first calculate the SPL over the full frequency range of the turbine and/or hydrophone. The IEC-40 asks that the range be set from 10 to 100,000 Hz, though the lower limit can be increased due to flow noise or low frequency signal loss due to shallow water. \n",
+    "The IEC-40 has two requirements considering calculations of sound pressure level (SPL). We'll first calculate the SPL over the full frequency range of the turbine and/or hydrophone. The IEC-40 asks that the range be set from 10 to 100,000 Hz, though the lower limit can be increased due to flow noise or low frequency signal loss due to shallow water. \n",
     "\n",
     "#### Shallow water cutoff frequency\n",
     "Low frequency sound is absorbed into the seabed in shallow water depths. We can use the function `minimum_frequency` to get an approximation of what our minimum frequency should be. This approximation uses the water depth, estimates of the in-water sound speed and sea/riverbed sound speed to determine what the cutoff frequency will be. The difficult part with this approximation is figuring out the speed of sound in the bed material, which generally ranges from 1450-1800 m/s. \n",
@@ -815,7 +1038,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
@@ -860,7 +1083,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
@@ -898,29 +1121,44 @@
     "\n",
     "To explain, an octave is a frequency band where the upper frequency is double (2^1) that of the lower frequency. The one-third octave is a frequency band where the upper frequency is 2^(1/3) times the lower frequency. The decidecade is a frequency band with a bandwidth of 2^(1/10), which means it's the tenth octave, not the third. Wherever the IEC-40 says third octave they actually mean the decidecade band.\n",
     "\n",
-    "We can calculate the SPL in each decidecade band using the function `decidecade_sound_pressure_level`. This function uses the same calculation as `sound_pressure_level` above and run it on each tenth octave band. Note that the SPL in smaller frequency bands will be smaller than the SPL in larger ones."
+    "We can calculate the SPL in each decidecade band using the function `decidecade_sound_pressure_level`. This function uses the same calculation as `sound_pressure_level` above and runs it on each tenth octave band. It returns 1 SPL in each frequency band every timestamp, so our boxplots show 5 minutes worth of SPL measurements in each decidecade band. You'll notice a similar spread as in the SPSDL boxplots, especially in the upper quantile. Boats are loud."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "Text(0.5, 1.0, 'Decidecade SPL')"
+       "[[<matplotlib.axis.XTick at 0x1c002c72b50>,\n",
+       "  <matplotlib.axis.XTick at 0x1c00012a410>,\n",
+       "  <matplotlib.axis.XTick at 0x1c0254651d0>,\n",
+       "  <matplotlib.axis.XTick at 0x1c000130110>,\n",
+       "  <matplotlib.axis.XTick at 0x1c025647690>,\n",
+       "  <matplotlib.axis.XTick at 0x1c025655950>],\n",
+       " [Text(0.0, 0, '0'),\n",
+       "  Text(1.0, 0, '1'),\n",
+       "  Text(2.0, 0, '2'),\n",
+       "  Text(3.0, 0, '3'),\n",
+       "  Text(4.0, 0, '4'),\n",
+       "  Text(5.0, 0, '5')],\n",
+       " (1.68, 4.75),\n",
+       " (40.0, 120.0),\n",
+       " Text(0.5, 0, 'log(Frequency) [Hz]'),\n",
+       " Text(0, 0.5, 'Decidecade SPL [dB re 1 uPa]')]"
       ]
      },
-     "execution_count": 18,
+     "execution_count": 20,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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77jvk5OT4tJSjluqrh+9ID4s+3S26zczMRN++ffHll1/6qoluR+/F3pNal6aV0xmXs2DY3d9s1KhRaNmyJUaNGqX6Z00PgS2R3jAoICJdUvqiLacja7FYkJGRgTNnziAjI8OnpRy15K4evl5mT8RYLBZMmjQJhYWFSE1N9XVzROkhuLJarRg4cCCaNGmCgQMHunTG5ez3oPVnTc65Qg+vPZHeMCggIl2SumjL6QTITXdISkoCACQlJekyRUUNUmkejrMIN998s9Pj9DL6Gh0djdmzZwMAxo4d69O2SNF6Q7f6WCwWZGdno6amBtnZ2S6dcbEZAam/tRqpRXLKlcpto17ex0RaY1BApHOBeoGSUydfipycfLPZjClTpgAApkyZottSjkqTSvNwnEXYuHGj0+P0MvpqNpsxfPhwAEC/fv2c7vvyyy/Rt29fZGZm+jwdTGqDOK04BlCzZ8/2uDMu9beW+1mTSrUSW9sAiJ8r5LZR6rnUEKjneNIfBgVEGuI0t+ekLtpyRiJ54VWG44iubUEscHUGoWPHjggODkbHjh193uEWk5qaisLCQkyaNMnn6WB6SMNyDKCGDx/ukuefnJyML774AvPnz3d6nB7a7o7c2YDKykrU1taisrLSq8fJFajneNIfliQl0pCcMn5al6LUepMsOaQ21lKyhCK5chzRtS2IBf7ICQeuvtajRo1SffMvOcaOHYvCwsJ6R8W1JvU+1gPbTtQA0Lt3b6f7zpw5g6NHj2L37t3o2bOnUzCh9DnEarUiMTHR6V/H5xP7bEu9vlLng9DQUDRq1AihoaFePU4ubsxGesGggEhDck7+WnccjN55VnKXWPKcLQ1l7ty5uuhwi7GlE9UdFdea1WrFrl27cOjQIQwdOhRt27b1WVvEOO5EPWTIEKf7bDMuhYWF6Nevn1MAqPQ5xLZwHEC9zyf22ZYKTsQe4y4AUeM8ovfgkAIHgwIiDRnh5G/0zrNY+43w2huZLQ1l7ty5Pu9wG4HjRl5r1qzB6NGjfdwiV2KzQoD0jEt8fDy2b9+u2AJqx+DEm70bkpOTkZ+fj4qKCuTl5TndJ3Y+cBeA8DxC/oxrCojIidabZCnN6O2nwCC2NsMoxGZcrFYrsrOz8fvvvyM7O1uRtSXuFiF7m5PvuI9F3QXnDamCRGR0DAqINCTngsKLELnD94jxSI3CG5ltHUJNTQ22bNmiyWJusQXFYnssOO5jUXfBeUOqIClN7uea5wOSi0EBkYbkVJnQujwe6ZOcOu1EWnM30q40qX0zbr755np35XZXhlXquSorKyEIAiorK1WvsCV17lfjfMBgghgUEGlI6TJ+apzElT6mEdqoBi13ZDZCeUgKDO5G2pUmtW/Gxo0b692VW6oMq7vnKikpgSAIKCkpUWwWRM65Qs6+DQCQmZmJyMhIZGZmutzHwQViUECkITn57mJT4IA6J3Glj6nGqJWcY2odnCj9Okpd6LmOggKV1NoM2/dKzVg0ZBZEzrkiMTERYWFhSExMbFjDHaSlpaGsrAxpaWku93FwgRgUEOmc2BQ4oM5JXO4ok5zjSZE7EiZGjQBK6TZKYcefyJXU2gzb90rNWLibBZHq+Ms5V0jteC01WCT1XCkpKYiIiEBKSor0L1uHnHM/GQ9LkhLpnG0KHACKiopU3xBKquSe4yjTxIkTG3w8MfXl7jpegOUcc9y4cTh69Cji4+NdjqcGli4kCixi+zNYrVYcP34ctbW1OH78uMfnM6ny0GKPkTp32gaVbrjhBvv3nmwCB8g795PxcKaASOekpsC1XoQsd5TJW1K5u1LlBKWcOXOm3mojDSE1Wic1asgqVET+Jz4+Hq1bt3bZn8FisWD//v0AgP3794uez7788kunx8mZHZQ6d0pVXQKkZze1OveTbzEoINI5pafAG2LixIk4fvy46iNFUrm77i5sYp1nqeBKbodb6qItla4kJ5WJiwCJ9C07OxsnTpxAdna20+1S1Y4cz2epqalOj/v999/x4YcfoqCgwOPBD6lzp7uqS1LnM7FzPwcr/AuDAiKDslqtSExMRK9evZCYmKhYeTw9nOSlcnfdXdjEZk+kgis1FkNLjbqJjSiKsVqtiI+PR/fu3e3pT0RkDFLVjhzPZ2PHjnV6nFj1JED83CN17nRXdUnOuZ+DFf6FQQGRQbkbMZeil5r3ci5CcssJSpGzKNhqtSI5ORlffPEFkpOTveqoi40oimnI35qItCGVTijG8Xxm2yXaRmx2syHnHjFyj8mKRf6FQQGRQTWkPJ5eat6rEYDIuTDLzd0V27lV6Yu21htCEZF3HDdRc/y+IcRmN9XYNVruMaXOnXqYdSbvMCgg0pCSJ8mGbBIklr6ixoVNitIBiNTupkpzt+5BKmCwpX09++yzHj1XQ0ohEpH6HDdRqy/dR0lqDBKocUypQR+es/SJQQGRhvSSfylW/1qNC5vUyV/p2vtSu5sqzd26B08WSp85c0aRtujlfUUUqLSczVNj12ipY0pVSJIiNejDc5Y+cZ8CIg1J1Z3WQztsF7YxY8YoPloEuNa+Vppj++vubqolTwIGJduol/cVUaBSo6OuF7aBDABITU3Ffffd1+Bj8pylT5wpINKQHnaltVqt2L17N44ePYrdu3c7pQipcWHzttJOQ0jtbipFy6lsuW2Uoof3FRH5J6kKSVKkZgN4ztInBgVEGrFarSgoKPC67rTS1KpaJEYsVUlPjD6VzfxcIlKLVIUkuWWZSZ88Sh+qqqry+sAtWrTw+jFE/syW725TVFSEXr16ad4O26jP3Llz663zL0VOKpDUNHFmZibS0tKQkpKi+oZoUow8lW2rdLRt2zZUVFTgq6++8qvUBSLSr+TkZOTn56OiogJ5eXlO98XFxXEmwGA8milo2bIlWrVq5fFX69atceDAAbfH3bJlCx544AFERkbCZDJh/fr1TvcLgoDU1FRERkYiODgYgwYNwk8//eT0M9XV1ZgyZQratm2L5s2b48EHH8SxY8c8fwWINKKXspJy6/w7bqA1btw4j59PbJrYarUiJSUFZWVlSElJ8emGXEaeylajPCERkSdqamogCAIqKysVO4dnZmYiMjISmZmZihyPPOdx+tDHH3+Mb7/91u3Xv//9bzRt2tSjY54/fx49evTA0qVL671/wYIFWLRoEZYuXYodO3YgPDwc8fHxOHv2rP1npk2bhpycHGRnZyM/Px/nzp3D/fffjytXrnj6qxFpwugL0ZSummOxWFBRUQEAqKio8Fln1rGyRmZmpuF2C9ZLsElEgSc+Ph6CIKCkpMSl9LLc82paWhrKysqQlpbmVVuYRtlwHqUPtWvXDgMGDECbNm08OmjHjh3RpEkTtz9377334t577633PkEQsHjxYsyaNQsjR44EAKxevRphYWHIysrChAkTUFlZiZUrV+KDDz7A4MGDAVy9KEZFReGbb77B0KFDPWovEbmndNUcNSodyeFYWaOwsBD9+vXzSVqXXEYPNonIuIYMGYK5c+eKll4G6j+vSqWOpqSk2O/zhpaV7vyVRzMFBw8e9DggAIAff/wRUVFRshtle87y8nIMGTLEfltQUBAGDhyIrVu3Ariak11TU+P0M5GRkejWrZv9Z+pTXV2Nqqoqpy8ikianao7U4mq9dGYdK2t4u8aCiCiQie26LHVedZc6OnHiRBw/frzedWZc2Kwu3VYfKi8vBwCEhYU53R4WFma/r7y8HE2bNkWrVq1Ef6Y+8+fPR2hoqP2roQEMEdVPy10+5ZK7xoKIiOondV5tSOqonDKnTCvynKyg4Pz589iwYQPefPNNvPHGG05fSjOZTE7fC4Lgcltd7n5m5syZqKystH8dPXpUkbYSkTPmuxMRkSN31wWlZwOkAgkGDM683tF4165dGDZsGKxWK86fP4/WrVvj999/h9lsxvXXX4+pU6cq0rDw8HAAV2cDIiIi7LefPHnSPnsQHh6OS5cu4fTp006zBSdPnkT//v1Fjx0UFISgoCBF2klE4vSSIkRERPogdV1wV2JZqsxpQUEBMjIyMGPGDKefkSo5zXUIzryeKXjqqafwwAMP4NSpUwgODsb27dtx+PBh9O7dGwsXLlSsYR06dEB4eLjThkeXLl1CXl6evcPfu3dvNGnSxOlnysrK8OOPP0oGBURERESkL+5KLEuN7MvZhDI+Ph6tW7dGfHx8g9vuD7yeKSguLsaKFSvQuHFjNG7cGNXV1ejYsSMWLFiAxx57zF4pyBPnzp3D/v377d8fPHgQxcXFaN26NW666SZMmzYN6enp6Ny5Mzp37oz09HSYzWaMGjUKABAaGopx48ZhxowZaNOmDVq3bo2nn34a3bt3t1cjIiIiIiL9k6pKZ7VaMXnyZOzevRsHDhzA1q1bnWYRxGYEnnnmGWzfvr3ex+Tm5uLUqVPIzc316QaaeuH1TEGTJk3s+fphYWE4cuQIgKsddNv/PVVYWIiePXuiZ8+eAIDp06ejZ8+e9hXrzz77LKZNm4ZJkyahT58++PXXX7Fp0yaEhITYj/Haa69hxIgReOSRRxAXFwez2YzPP/8cjRs39vZXIyIiIiIfkUotslgsKCkpqXdfBCmnT58WfQxnCpx5HRT07NkThYWFAIC77roLs2fPxocffohp06ahe/fuXh1r0KBBEATB5WvVqlUAri4yTk1NRVlZGS5evIi8vDx069bN6RjNmjXDkiVLUFFRAavVis8//5zVhIiIiIj8iLsyp8nJyfjiiy8wf/58p8fZ1rrWV3LacaagrkDcWdnroCA9Pd2+8DctLQ1t2rTBxIkTcfLkSbz11luKN5CI5GFVBSIi8hfuypza1iL07t3b6XH9+vWr9zGAdDUjuTsrG5lXQYEgCAgNDUVYWBguX76M6667Dhs2bEBVVRV27tyJHj16qNVOIvKSnEVXRERERuNY5tRxQ1sptk3THnroIafvbVJSUhAREVHvzsr+OujmcVBw6NAhxMbGIjo6Gt27d0enTp2wc+dONdtGpLqnn34azZo1w9NPP+3rpih+kuHujkREFAgc1yLYdll2x93mmlI7K/vroJvHQcFzzz2Hixcv4oMPPsC//vUvRERE4B//+IeabSNS3dKlS1FdXY2lS5f6uimKnmSsVitycnLw3XffIScnx2UEhIiIKJBJbaJmtVqRmZmJvn37IjMz0+Ua2rFjR6d//YXHQcH333+Pt956C6NGjcLIkSPxr3/9C0VFRbhw4YKa7SNS1RNPPIGgoCA88cQTvm6KolUQLBYLMjIycObMGWRkZHi1jTwREZG/c1fpaNKkSSgsLMSkSZNcrqFZWVmorq5GVlaWpm1Wm8dBQXl5uVMUdeONNyI4OBgnTpxQpWFEWli4cCEuXryo6MZ7cmVnZ+PEiRPIzs5u8LGio6ORlJQEAEhKSnKpuEBERET1c1fpaNSoUWjZsiVGjRrlMotg5PUGHgcFJpMJjRo5/3ijRo0gCILijSLSgtVqRUFBAT788EMUFBT4VYqN2WzGlClTAABTpkxxqbhAZASlpaXYu3cvAGDv3r0oLS31cYuIKBC4q3QkNROfnJyMTz/9FMnJyZq2WQke72gsCAK6dOli37gMuLojcc+ePZ2ChVOnTinbQiKV2BYZ2RQVFaFXr14+a096ejoyMjK4MJgIVwOCLl262L8fM2YMAGDfvn3o3Lmzr5pFRAFOatdlo/M4KHjvvffUbAeR5vT2wY6Li0NcXJxP20CkF2fPngUArFy5EkFBQaiursa4cePstxMR+YLUWgTA2AN8HgcFjz32mJrtINKcuw+2lqxWK3bt2oVDhw5h6NChaNu2rc/aQqQnsbGx6NWrF0tgExGpzOsdjYk8ZeTFNlpzrJe8ceNGXzeHiIiIvGS1WpGcnIwvvvgCycnJhlur6HVQ0KhRIzRu3Fj0i8jGXzf3UINjveT27dv7tjFERETkNYvFgi1btqCmpgZbtmwxXDlwj9OHbHJycpy+r6mpwa5du7B69WrMmTNHsYaR8dny6YyYV6c1ObsxEhERkX7oba2it7wOCmwlmhw9/PDDuPXWW/HRRx9h3LhxijSMjM/oC2cLCgrsi4WM/HsQERGR+vS0VlEOxdYU9OvXD998841ShyM/YPQ1BUx/IiIiokDh9UxBfS5cuIAlS5bgxhtvVOJw5CeSk5ORn5+PiooK5OXl+bo5XmP6ExEREQUKr4OCVq1aOW1gJggCzp49C7PZbF8oSeQPjJ7+RERERPqh97Rkr4OCxYsXO33fqFEjXHfddejXrx9atWqlVLvI4KxWKxITE53+NVpuHREREZFSJk+ejJKSEhw4cADFxcW+bo4Lr4MCbmJGnrBYLJg0aRIAoLCwEP369UOvXr183CptZGZmIi0tDSkpKZg4caKvm0NEREQ+ZrVacejQIQDA0aNHfdsYEdy8jFThWHffiGW5GiIlJQVlZWVISUnxdVOIiIhIBywWCyorKwEADz74oI9bUz8GBaQKo5flagjbgnsuvCciIiLAebB0/PjxPm5N/RgUECnIarViwoQJ6NOnDyZMmGC4Lc6JiIhIeUbYpFSRkqREdFUgr6UgIiIi4+JMAZGXSktLsXfvXgDA3r17UVpaar8vkNdSEMkh9XkiIiLtKBYU7N27Fx07dlTqcKSSp59+Gs2aNcPTTz/t66YYUmlpKbp06YIxY8YAAMaMGYMuXbrYOzKBvJaCyFvuPk9ERKQdxdKHLl26hMOHDyt1OFLJ0qVLUV1djaVLl2LhwoW+bo7hnD17FgCwcuVKBAUFobq6GuPGjbPfTkSe4+eJiEg/PA4Kpk+fLnn/b7/91uDGkLqsVisSEhLwySefICEhgRuKNUBsbCx69eqFnTt3+ropunDkyBEAV2cMQ0JC0LlzZx+3iIyEnyciIt/zOCh4/fXXERsbixYtWtR7/7lz5xRrFKnDYrEgOzsbAJCdnY1nnnmGi2CpwUpLS5GQkAAA9jSQffv2MTAgIiIyEI+Dgs6dO+Opp56yX/TrKi4uRu/evRVrGCnPtgh2zJgxXARLirGleqSlpSEyMpLpH0RERAbk8ULj3r17o6ioSPR+k8kEQRAUaRSpg4tgSU3Dhg1DbGysr5tBREREMngcFGRkZGDatGmi9/fo0QO1tbVKtImIiEg3WDaViNRUUFCAkSNHoqCgwKft8Dh9KDw8XM12EBER6Y6tbKoN180QkdIyMjKwYcMGAEBcXJzP2sHNy4iIyHAcR+9t1a8ayrGKlm02wLFs6po1a7By5Uqn24mIGio+Ph6tW7dGfHy8T9uh2D4FRERkHHVTYoxUSrbu6H1CQkKDR+7FqmjZsGwqEaklOzsbJ06cQHZ2NiZOnOizdnCmgEiEXnL8KHDUN1KtBqPvJOw4ep+WluZ0W0OPmZaWxtkAD2j1XiUKBDU1NRAEAZWVlbBarT5rB4MConpYrVZMnjwZ69evx+TJk336IaXAUHekWs1Our+kxMTGxmLYsGEutzcktYhVtNyT+17lgm2i+sXHx0MQBJSUlMBisfisHbKDgkuXLuHnn3/G5cuXlWwPkS5YLBaUlJTo4kNKgcEXI9WxsbEYPXq0X3WC686CJCQkBHznU25nXCy4kvNeNfrsFJGahgwZAgA+30PK66DAarVi3LhxMJvNuPXWW+0niqlTp+Lll19WvIFnz57FtGnT0K5dOwQHB6N///7YsWOH/X5BEJCamorIyEgEBwdj0KBB+OmnnxRvBwWW6OhozJ49GwAwe/ZsbvRGmuFIdcOokVokRarDrcZiaDntk9MZ9yS4EnuvcsE2kXeCg4MB+H4PKa+DgpkzZ6KkpASbN29Gs2bN7LcPHjwYH330kaKNA4Dx48cjNzcXH3zwAfbs2YMhQ4Zg8ODB+PXXXwEACxYswKJFi7B06VLs2LED4eHhiI+P54mGGsRsNmP48OEAgOHDh3OjNyKDEUstUpJUh7shMxZK5uu764y7mw3wNrhyl1rkj7NTRP7C66Bg/fr1WLp0Ke68806YTCb77bfccgt++eUXRRt34cIFfPLJJ1iwYAEGDBiATp06ITU1FR06dEBmZiYEQcDixYsxa9YsjBw5Et26dcPq1athtVqRlZWlaFuIiMj4tOpwq9WplnqcVIpQfZ1xTwIXb4MrLtgmMi6vg4LffvsN119/vcvt58+fdwoSlHD58mVcuXLFaUYCuDrNkp+fj4MHD6K8vNyeiwUAQUFBGDhwILZu3Sp63OrqalRVVTl9ERGROvSywFStxdxSo99adKrlpgipmWrFNDgi4/E6KOjbty++/PJL+/e2QODtt9/GHXfcoVzLAISEhOCOO+5AWloajh8/jitXrmDNmjX44YcfUFZWhvLycgBAWFiY0+PCwsLs99Vn/vz5CA0NtX9FRUUp2m4iIrpKTwtMjTSKrWW+vhapVkSkf15vXjZ//nz8+c9/xn//+19cvnwZr7/+On766Sds27YNeXl5ijfwgw8+wNixY3HDDTegcePG6NWrF0aNGuW0gUzdGQpBECRnLWbOnInp06fbv6+qqmJgQESkAscOa1BQEKqrqzFu3DifdsaN2gH25w3WjLyZHpG/8HqmoH///ti6dSusViv+9Kc/YdOmTQgLC8O2bdvQu3dvxRv4pz/9CXl5eTh37hyOHj2K//znP6ipqUGHDh0QHh4OAC6zAidPnnSZPXAUFBSEFi1aOH0REZF6uMC04Yw00+ENPc0mEQUyr2YKampq8Pe//x0pKSlYvXq1Wm2qV/PmzdG8eXOcPn0aGzduxIIFC+yBQW5uLnr27Ang6v4JeXl5eOWVVzRtHxERkRaMOtMhxt1sEmcRiLTh1UxBkyZNkJOTo1Zb6rVx40Z8/fXXOHjwIHJzc3HXXXfh5ptvxuOPPw6TyYRp06YhPT0dOTk5+PHHH5GUlASz2YxRo0Zp2k4iIiJP6WEPA73xpEJS3VkEvo5EyvF6TUFCQgLWr1/vlJOvpsrKSsycORPHjh1D69at8dBDD+Gll15CkyZNAADPPvssLly4gEmTJuH06dPo168fNm3ahJCQEE3a56igoAAZGRmYMWMG4uLiNH9+IiLSP1tH1yYhIQH79u3j6Hc9pGYRGvI6Oi7Y5swD0VVeBwWdOnVCWloatm7dit69e6N58+ZO90+dOlWxxgHAI488gkceeUT0fpPJhNTUVKSmpir6vHJkZGRgw4YNAMCggIiI6uXY0T1+/DhSUlL8Ym2AmupbRC33dRRbsM3AgAKd10HBO++8g5YtW6KoqAhFRUVO95lMJsWDAiOZMWOG079ERERiYmNjERsbi5SUFF83xdC8fR0dF2xHRkZy/QLR//E6KDh48KAa7fALcXFxnCEg8iNG6CAYoY1EvuAuRajugu266UicRaBA43VQQOK4poDIfxihg2CENhL5gpwUIT3uqUGkJQYFCuKaAiL/YYQOghHaSOQLUilC7hh5EziihmBQoCCuKSDyP0boIGjZxrolIHv16qX6cxLJ5W97OhCpyesdjYmMpqCgACNHjkRBQYGvm0JkCGK13+vWjE9ISOCusxQw6q7f4Xuf/A1nChTE9CF94t+FyHNStd/dlYBk7XfyV1y/Q4GgQTMF58+fx7vvvotly5YxYsbVtKFhw4YxfUhn4uPj0bp1a8THx/u6KUS659jxT0tLc7rNJjY2tt7KLY4LOx13nSUyOsfPxZo1a7By5Uqn24nUkpmZicjISGRmZqr+XB4HBUeOHMHAgQMREhKC+Ph4ey7p+PHjMWXKFMTGxmLLli1qtlX34uLisG7dOo5Gq0hOKlB2djZOnDiB7OxsFVtGeuc4ih0ondWGpDvU1/GX4riwkx0m8lexsbEYPXo0YmNjfd0UChBpaWkoKyuzD9KoyeOg4Omnn8alS5eQmZkJs9mMoUOHonPnzigrK8OJEycwbNgwXewq7CtWqxUFBQX48MMPUVBQAKvV6usm+SVbKlBGRoavm0IGEoij2HXz/7X6vYcNG8YOExGRQlJSUhAREaHJJocerynYsmULPvvsM9x2220YNmwY2rZti3fffRdhYWEAgBdeeAH33HOPag3VC7G9CCwWC+68807790VFRazKoQI5FZ7S09PtfzOS5q+VZRpSntCoWK6UiMj4YmJicPvttyMmJkb15/I4KPjtt9/Qrl07AEDr1q1hNpvtAQEAhIeH4/Tp08q3UGfEFq1GR0djzZo1GDNmDNasWYPo6GhfNdGvydk1mjtNe0Zqgam/CMTyhEYoqUpkdNxZnNRgtVqRnJyMbdu2oaKiAl999RXMZrNqz+dxUCAIAkwmk/17x/8HErGRarPZjK5duwIAunbtquofjQKLWEUXpS9C7irLEBGRK1YmIrVYLBb7et0tW7bAYrGoOoPvVUnS2bNn2zu7ly5dwksvvYTQ0FAACJgceo46G8/vv/+OjRs3on379ujZs6ehAra6ufDA1QsNANUuQrGxsYiNjdUkf9Ff+WsaFhG5YqoeqUXrLBSPg4IBAwbg559/tn/fv39/HDhwwOVniPRm48aN9k6z0dZ6uMuF99eLkJGn4tVKw+IeAET6xlQ9UprWWSgeBwWbN29WsRlEDSe2CLx9+/YA4PO1Hg0ZPRbLhTfCRcjbzqy7qXi9j8KrkYYlNWNERESkhAZtXhaI5NTJ92davx5SzydWrjQ4OBiAb9d61C0PmZCQ4PclMQF5pUClNgky0uvobZ1/KdwDgMi46g5kEOmVRzMF06dP9/iAixYtkt0YI0hOTkZ+fj4qKiqQl5fn6+b4nFg1Jl88n5xypVoJ1EW8DSkFWt8siLvXUe4sgpapOWrMGBGRPgVCVTfyHx4FBbt27XL6vqioCFeuXMHNN98M4Oo0duPGjdG7d2/lW6gjVqsVlZWVEAQBlZWVsFqthlq0qgatO+JSz2eEReBGXsSrp85sfa+j3Iuvlqk57CAQBRa1BjKI1OBR+tB3331n/3rggQcwaNAgHDt2DDt37sTOnTtx9OhR3HXXXbjvvvvUbq9PWSwWlJSUQBAElJSUwGKx+LpJPhcXF4d169bpojPO1C71GCFtx/Hia9sO3pNZCS1Tc+S2kYiMrb50QiOcVymweL2mICMjA/Pnz0erVq3st7Vq1Qrz5s1zyeX2N7bSUIDvF61KyczMRGRkJDIzM33dFMWJrRtwdx81jJE6s3Jz+YcNG4bY2FjlG1QPJdcbEJExGem8SoHB66CgqqoKJ06ccLn95MmTfv9mNsoGZWlpaSgrK7OfZPyF1WpFfHw8unfvjvj4eJe9MWbMmIFhw4bpck2Bv2BnlohIWTyvkl54HRQkJCTg8ccfx8cff4xjx47h2LFj+PjjjzFu3DiMHDlSjTaSl1JSUhAREWHIvHUpFosFkyZNQmFhISZNmsT0LYOruxcBp82JiP7gWACB50fSgtdBwZtvvon77rsPY8aMQbt27dCuXTuMHj0a9957L5YvX65GG8lLMTExuP322xETE6P6c2mZx+8ufUtO+hBPur5RN5fW03KlRESBQE45Z6KG8njzMhuz2Yzly5fj1VdfxS+//AJBENCpUyc0b95cjfaRDFqWCdXyuaTSt2ypRUePHsW4ceM8Op5Y1Rl/rwSjh92CHXNp/XFHZiKihmhIOWciubwOCmyaN2+uyUg0ecexc2zLu1dz7UN8fDy2b9+O+Ph4rx4ntvuwXLbUIgA4c+aMR48JxJOu1G7BvmCEHZmJiHyFaw1ISx6lD40cORJVVVUeH3T06NE4efKk7EaRfFrn3efm5uLUqVPIzc316nFKVwpyTC1q3769V4/VsuqMr0ntFkze4ZoIIvIFnntILR7NFHz66af47bffPDqgIAj4/PPPkZaWhuuvv75BjSPv2TrHY8aM0aRsqtzNy+TOMIhxTC0KDg5W5Jj+jCP0DaO3GRciCgxS5x5/T30l9XkUFAiC4PQmJP3Sumyq3F2Es7OzceLECWRnZ2PixIkqtIxIPVwTQUS+wHMPqcmjoOC7777z+sA33HCD148JVErn1+ud1WpFZWUlBEFAZWWl6useiNTCGRci8gWxc48eCkmQcXkUFAwcOFDtdgQ0LSv4KO3333/Hxo0b0b59e/Ts2dOjzr3FYkFJSQkAoKSkBBaLBb169VK7qURERH6LqUXUULKrD5Fy5Obl68HGjRvtJ56ioiKPOvdar3sgIiLyd+5SiziLQO54vXkZaUfLjcHkslX68aZz727dgxF+byIiIj2KjY3F6NGjnarqccNI8gRnCjQitW5ALH3ICGlFtko/Si5qnjx5MkpKSnDgwAEUFxcrckwiIqJAxQXK5AkGBRqR6uCLpQ/pKa1Iy8XQx44dc/qXiIiIGo7FEUiKYkFBSUkJevXqhStXrih1SL8i1cGXW9ZTS3JmLY4cOQLAu9xFq9WKpKQkrFy5EklJSaxMROTnwq81IfjMPuB4IwSf2Yfwa00e3UdEynFcb3DkyBEW/whQis4UCIKg5OH8ipyOv1RHXMuRe6vViqCgINTW1iIiIsKjx5SWliIhIQGAdxUQLBaLfZfjjIwMjBo1iicnIj82oXdTdN0yAdgCdP2/7z25j4iUUbdqUUJCAisWBShFFxqbTBzFUdKMGTMwbNiwemcXbAGDrQOtJovFguzsbNTU1CArK8ujx9jyFNPS0rBy5Uqn26TYKhMB3i1eJiJjWlF0CXsHrAD+noe9A1ZgRdElj+4jImU4rjdIS0tzuo0Ci66rD12+fBkvvPACOnTogODgYHTs2BFz585FbW2t/WcEQUBqaioiIyMRHByMQYMG4aeffvJhq7URHx+P1q1bIz4+XvXnio6ORlJSEgBg3LhxXj122LBhThUQ3NF6R2Yi8q3ycwIutOwCRMbiQssuKD8neHQfESkrNjYWw4YN83UzyIc8Dgqqqqokv9SIKl955RW8+eabWLp0Kfbu3YsFCxbg1VdfxZIlS+w/s2DBAixatAhLly7Fjh07EB4ejvj4eL+IcqVmA3Jzc3Hq1Cnk5uYq9nxipUDNZjOmTJkCABg1apRiz0dEZAR/rG0o5toGIvJbHq8paNmypWR6kCAIiqcPbdu2DcOHD8d9990H4GpN/LVr16KwsND+nIsXL8asWbMwcuRIAMDq1asRFhaGrKwsTJgwod7jVldXo7q62v59VVWVou1Wyrhx43D06FHEx8e7LLhVujKRbYHv/v37sWfPHpSUlHCU3sC4SQ2Rcri2gYgCgcdBwXfffadmO+p155134s0338S+ffvQpUsXlJSUID8/H4sXLwYAHDx4EOXl5RgyZIj9MUFBQRg4cCC2bt0qGhTMnz8fc+bM0eJXaJAzZ86gsLAQhYWF6Nevn9OCW6UrFlksFuzfvx8AsH//flgsFi7wFaH3iihSW90TkfdWFF3C/85eha7R0dhrsWBFxig86OtGEREpzOOgYODAgWq2o17PPfccKisrER0djcaNG+PKlSt46aWX8Ne//hUAUF5eDgAICwtzelxYWBgOHz4setyZM2di+vTp9u+rqqoQFRWlwm/QMHJ2C5bLtm5g1apVSEpK4gJfCXofNeQmNUTKclrbUF7LtQ1E5Jc8XlMgCAJeffVVxMXF4bbbbkNycjIuXryoZtvw0UcfYc2aNcjKysLOnTuxevVqLFy4EKtXr3b6ubppS+5SmYKCgtCiRQunLz1SY7dgMY7rBqZMmcLUIQlGqYhS31b3RCTONguoxxlAIl+pu4cB+S+Pg4KXX34Zzz//PJo3b46IiAgsWrQIU6dOVbNteOaZZ/D8888jMTER3bt3x6OPPoqnnnoK8+fPBwCEh4cD+GPGwObkyZMuswd6ZbVakZmZib59++LLL7/0+HFii4JJfayIQv7AnxfPyu3c22YBu26ZoLsZQH/gz+85f2VLR7WloSYkJKC0tNTHrSK1eJw+tGrVKixZsgSTJk0CAHz99dcYMWIEVqxYodr+BFarFY0aOcctjRs3tpck7dChA8LDw5Gbm4uePXsCAC5duoS8vDy88sorqrRJaRaLxf6apqam2hdVS7FarUhOTsa2bdtQUVGBr776iiP7ROQVvafBuWPvYP7f/x3Zfze4/l5Sj7OtHQDg8boBva8x0hOjv+cCkWM66vHjx5GSksJUVD/m8UzB4cOHcf/999u/Hzp0KARBwPHjx1VpGAA88MADeOmll/Dll1/i0KFDyMnJwaJFi+w75ZpMJkybNg3p6enIycnBjz/+iKSkJJjNZsOUzoyOjsbs2bMBAGPHjvXoMRaLBVu2bEFNTQ22bNkCi8WiZhNJA5yeJa0ZJQ1OjNSovu13q+/3knqcbRbQmxlAe0f3rYGcYXDD6O+5QMY9DAKDx0HBpUuX7DnuwNUOedOmTZ1KeyptyZIlePjhhzFp0iR07doVTz/9NCZMmGDfcQ8Ann32WUybNg2TJk1Cnz598Ouvv2LTpk0ICQmR/bxapuaYzWYMHz4cANCvXz+PHsNdf/0Lp2fJF4yeBifV8Zfq3Es9riHtqK+jyzUKzoz+niPydx6nDwFASkqKU5rKpUuX8NJLLyE0NNR+26JFixRrXEhICBYvXmwvQVofk8mE1NRUpKamKva8tk3DACha9lMp3PXXv3B6lsh79g7m//1f7ce5PV49lYmk0pi0xBQnIvKEx0HBgAED8PPPPzvd1r9/fxw4cMD+vVprC7Sm9MZgRJ6IjY1FbGwsUlJSfN0UIlKAnDUK7kitiRDDXH5Siy3dlZtk+gePg4LNmzer2Ax9UXpjMOBqSlJGRgZmzJjhs9kH7nJLRKQdpWclAHmzD9x8jdRQWlpqX+PpuEkm+xXG5VX6UH0uX76Mixcv4tprr1WiPX4rOTkZ+fn5qKioQF5enubPL7XLLT/ARETGIGf2gZuvkRpsaa5paWmIjIzkJpl+wOOgYMOGDaioqMCjjz5qv+2ll15CWloaLl++jLvvvhsfffQRWrVqpUpDqWG4y602OBtD5Io57cpRY/ZBDqk0JjkpTnyPGBerEvkPj4OChQsX4qGHHrJ/v3XrVsyePRtz585F165dMWvWLKSlpSm60NifpKen29OHfCk2Nha9evXCzp07fdoOfyQ1G0MUyJjTrj65nWo5HXhAOo1JTooT3yP+h+sNjMfjkqQ//vgj+vfvb//+448/Rnx8PGbNmoWRI0ciIyMDn3/+uSqN1FpmZiYiIyORmZmpyPGsVisA2IMq2/fkXxxnY9asWYOVK1c63U4UqFifXn1y90uQ2rdBqqSqVGlXOWVf+R7xL3XXG3Tp0oWltg3A45mCs2fPok2bNvbv8/Pz8fDDD9u/v/XWW1XdyEwrVqsVKSkpqKioQEpKCh577LEGl/y0WCy488477d8XFRWhV69eDW0qeUjr0QrOxhA5Y067K7kj9GLkLiaWWqMgNeIvlcYkJ8WJ7xH/wvUGxuTxTEFkZKQ9V/rcuXMoKSlxqqJTUVHhF/XyLRYLKioqAFz9nZTYLZibjfkORyuISI/kjtCLkbsxmJYbvcn1R2pUMdcbGMywYcMQGxvrdFvdtXe8JuuHxzMFDz/8MKZNm4bk5GRs2LAB4eHhuP322+33FxYW4uabb1alkVqydeDHjBmjWAeem435DkcriEiP5I7Qa0kvi5q53sB/sBKivnkcFLz44os4fvw4pk6divDwcKxZswaNGze237927Vo88MADqjRSS+zA+ydWRyAiPZHqcKux6ZmRcZ8F/+GuEiIr+PmWx0GB2WzGBx98IHr/d999p0iDiIiIApleRuj1gusN/E99a+84i+B7Dd68jIiIiIioIbifku8xKCAiIiIiXWAFP99hUEB+T+nSf0REpH889xN5h0EB+T29VPIgIiLtSJ37GTAYj+Mi5CNHjnC/JxU0KCi4ePEimjVrplRbiFTBSh5ERP5JqnNvhLKv5Jm6i5ATEhK4AFkFHm9eZlNbW4u0tDTccMMNuPbaa3HgwAEAQEpKClauXKl4A4kaSmpzHjHcXIXIe3I23SJqCKlN4IywMRt5xnERclpamtNtgOssAsnjdVAwb948rFq1CgsWLEDTpn98ALt374533nlH0cYRNZTVagUA5OTkoLi42KPH2EYkbOXQuBMykWekOmhEapDbuRcLGLh7sr7Fxsa67DtU95qdkJDA67VMXqcPvf/++3jrrbdwzz334B//+If99piYGFgsFkUbR9RQtvfkvHnz7LeFhIRIPoZl0YjkYaoeaU3pPR24e7LxOF6zjx8/jpSUFKfrtW3mgJuhuef1TMGvv/6KTp06udxeW1uLmpoaRRpFpJQRI0bghRdeAACsWbPGqxzE2NhYjB49GrGxsSq2kMh/yEnVI9IT28wD/p7H1CKDEZtFSEhIAMBZf094HRTceuut+P77711u/9e//oWePXsq0igipbRt29Z+QujatStHCIgaiOsGyJ857Z7M1CLDs80YpKWl2de9is0iMFiQkT704osv4tFHH8Wvv/6K2tparFu3Dj///DPef/99fPHFF2q0kYiIdIJVWyhQMbXIuOrOIACuswgAAr6ikdczBQ888AA++ugjbNiwASaTCbNnz8bevXvx+eefIz4+Xo02BixGsMq4cOECgKuvo23hMZEnODLoilVbKFAxtci/uJtFCESy9ikYOnQohg4dqnRbyAEjWOUcOnQIwNXXsaioiBuekMe0Hhk0woZKSi/sJDIKp9Si8lq+//1EfbMIgcrrmYJAJlW7Xum69oxglXP8+HG0bNkSM2bMQHR0tK+bQwai9cggS3oSEfleoO5V5NFMQatWrWAyeTZqderUqQY1SK/q7qbnOHoPQPS+ho7sM4JtuNdeew1nzpxBVlYWFi5c6OvmkIFoPTLIkp5ERL4l1d/z92wNj4KCxYsX2/9fUVGBefPmYejQobjjjjsAANu2bcPGjRuRkpKiSiP1wJPa9Xqoa183uvWnmrxyf7eUlBSkpaX59fuT/ANTc4j8jxHSAukP7vp7/tzP8igoeOyxx+z/f+ihhzB37lw88cQT9tumTp2KpUuX4ptvvsFTTz2lfCt1JDY2Fr169cLOnTu9uk8L7mYz9ELOB6ohkXtMTAxuv/12xMTENLDlJIYXPSIKZH8UJWjkUpSAFbuMqb4+nb/PIni90Hjjxo145ZVXXG4fOnQonn/+eUUa5WtG2P2uvjYaYSdeuR+ohvxuGRkZ2LBhAwAgLi6uIc0nEbzo+RcGeUTekSpKIJUWyM+asRihn9UQXgcFbdq0QU5ODp555hmn29evX482bdoo1jBfEav6oyfu2ujrGQspDf1AyfndZsyY4fQvKY+58P6FQR6Rd2znwK7R0dhrsTidB6XSAvlZMyY997MawuugYM6cORg3bhw2b95sX1Owfft2fP3113jnnXcUb6DWHKv+REZG6jIC1FMb5c6qKP2BckxJOnLkiFPZ0bi4ONEZAo7SKIO58P6FQR6Rd+QWJeBnjfTE66AgKSkJXbt2xRtvvIF169ZBEATccsstKCgoQL9+/dRoo0/ooeqPuw6rVm0U63DrZS+FuilJCQkJHreDozRErhjkEWmDnzXSE1mbl/Xr1w8ffvih0m2hOvTQYZXqcKsxYyFnEbJjStLx48eRkpLicTs4SkNERHokZyZbasEzkTuyggKbCxcuoKamxum2Fi1aNKhB9Ac9dFg96XCLzVh4e0JraPWk2NhYxMbGelV6lKM05M/YQSAyLrGBQY8qHWm0Czs5k0plNgKvgwKr1Ypnn30W//znP1FRUeFy/5UrVxRpmB5JfRDVuPjqqcMqp8Pt7UyHv6/qJ9IaOwhExiU2MOhJpaP6FjyTuhqSyqwXjbx9wDPPPINvv/0Wy5cvR1BQEN555x3MmTMHkZGReP/999Voo+ZsHXzRCPytgei6ZYLTB1HqvkC1ougS9g5Ygb0DVmBF0SWPHxcbG4vRo0cjNjZWvcYRBQDbZxB/z/P6c0hEvmUbGLzQsovTwKDU59ppwXOdx5G6HAc209LSnG4zCq+Dgs8//xzLly/Hww8/jGuuuQb/8z//gxdeeAHp6el+s87A1sGv27mX+iDy4utK7IQWqMSCTaKG+GOWstjlvcUOApH/kfu5ljpXkHJiY2N1UaxGDq+DglOnTqFDhw4Arq4fOHXqFADgzjvvxJYtW5RtHYD27dvDZDK5fE2ePBkAIAgCUlNTERkZieDgYAwaNAg//fRTg55TbIRb6oOo9cVX6Q5m3Tw4Up5YsEnUEJylJCJPSJ0rOGhFgIygoGPHjjh06BAA4JZbbsE///lPAFdnEFq2bKlk2wAAO3bsQFlZmf0rNzcXAPCXv/wFALBgwQIsWrQIS5cuxY4dOxAeHo74+PgGTdkYYYRbyQ6mLQ/OtrA3ISEBpaWlSjSTHMhNpyKSwllKIvKE1LmCg1YEyAgKHn/8cZSUlAAAZs6caV9b8NRTT7nscqyE6667DuHh4favL774An/6058wcOBACIKAxYsXY9asWRg5ciS6deuG1atXw2q1IisrS/SY1dXVqKqqcvoyGiU7mP6QB2cERgg2yXiYIkREnpA6V3DQigAZQcFTTz2FqVOnAgDuuusuWCwWrF27Fjt37sSTTz6peAMdXbp0CWvWrMHYsWNhMplw8OBBlJeXY8iQIfafCQoKwsCBA7F161bR48yfPx+hoaH2r6ioKFXbrQY1OphGzoMjIiIieThoRUAD9ykAgJtuugk33XSTEm1xa/369Thz5gySkpIAAOXl5QCAsLAwp58LCwvD4cOHRY8zc+ZMTJ8+3f59VVWV7gIDq9UKAMjJybGv4aDAJGcDG3LF19FYbOfAbdu2Ye/evaiurvZxi4iI/JvXQcHUqVPRqVMn+2yBzdKlS7F//34sXrxYqba5WLlyJe69915ERkY63W4yOV/gBUFwuc1RUFAQgoKCVGmjUiwWCwBg3rx59ttCQkJ81RxR7GipTw87W/sDvo7GYjsHPvHEE063h4SEML2RiEgFXqcPffLJJ4iLi3O5vX///vj4448VaVR9Dh8+jG+++Qbjx4+33xYeHg7gjxkDm5MnT7rMHhjNiBEj8MILLwAA1qxZ49MNMKSqEnBxkvoCMddTjdJ5gfg6GtmIESPw9ttv45133gHg+/MgEZG/83qmoKKiAqGhoS63t2jRAr///rsijarPe++9h+uvvx733Xef/bYOHTogPDwcubm56NmzJ4Cr6w7y8vLwyiuvKPr8Wk9lt23bFgkJCZg3bx66du3q0wuh1Air2I6LpBw97WytFTV24g3E19HI2rZti/Hjx2Pnzp0A4PPzIFGgYkZA4PA6KOjUqRO+/vprlyndr776Ch07dlSsYY5qa2vx3nvv4bHHHsM11/zRZJPJhGnTpiE9PR2dO3dG586dkZ6eDrPZjFGjRsl6LrFcfqmp7BMnTgDQf+7rH6OvjbwafZXq+GvZ0ZLbfjIe23uua3Q09loshgs4pS6ici+w/nhhNsK6ASO00Qj4OhoXUy8Dh9dBwfTp0/HEE0/gt99+w9133w0A+Pe//42MjAzV1hN88803OHLkCMaOHety37PPPosLFy5g0qRJOH36NPr164dNmzbJzr8Xy+UfMWIEgKuByPjx47FmzRrcdttt6Ny5M/Ly8gDUHzC4U3fTsF69eslqtyfkjr7qZYRVjdHjQGSE4MqpdF55reFG9qUuonIvsP54YZYabNGaPw8I6QHXiBgXMwICh9dBwdixY1FdXY2XXnrJXtO+ffv2yMzMxN/+9jfFGwgAQ4YMgSDU3ykwmUxITU1FamqqIs81YsQIHD58GPPmzXPq+AMQncqWChik2DYNs0lISPAoZ1ZuZSItR1/VqJ5k9NFjvfDn4Eovo+lSF1G5F1h/vDDLPXeqQekBIXZ0nUm9jrbrKumTXgYG9ULuwJqWg8ByySpJOnHiREycOBG//fYbgoODce211yrdLp+Rk8svN/fVcdOw48ePIyUlxaMLidjFy91jtRx9lWqj3A+U0UeP9cKfgyu9jKZLXUTlXmD98cKsp3UDSg8IsaPrTE9/a3/lixQtvQzEaEnOwJrcQWCtyQoKLl++jM2bN+OXX36x5+4fP34cLVq08KsAQSnuosPY2FjExsYiJSXFo+OJXbz0dBGSaqM/j1RrKVCDK6mLkD+OppMrx87P6dOnFTmmlgNC/kzOLLFUZ1aNjq5YG7Vuh9J8kaKll4EYrVitVqwouoSuI6YjJCQENTWXsKJojttrjdxBYK15HRQcPnwYf/7zn3HkyBFUV1cjPj4eISEhWLBgAS5evIg333xTjXYalhrRodTFSy/54lJt9OeRai0FanAldRHiwnfPGKGDI6W+zo/e9nFRI3BpaDu0+FvL2WNHqjNrC7iU7OiKtVHqudRohxQ5gYvUzFV+fr7o4xrCXwdixM7vFosF5ecEJD413+nnPX0feDsIrDWvg4Inn3wSffr0QUlJCdq0aWO/PSEhwWkPAbpK6+jQCB1FqZFqI3e0tBaowZUaFyE5U+BG+KyJMfqiz7qdn5ycHPvAg1RnXMud4vUSuKjxt5Z6HaXSsMRIdWZbtWolep/c2XGxNko9lxrtkCIncJGauVLrM++PaY2A+Pnd31MGvQ4K8vPzUVBQgKZNnS+A7dq1w6+//qpYw/yNVtGh3I6iXvIC9d7R0tMIq9+kAclNf4JyFyE5U+BGDsqMfmGr2/m56aab7PdJdca13CleKnBRmtzRY7l/a6nXUek0LLkpWlKBi1gb1WyHtzNGcgIXd8cTe5xan3m99CvkEDu/+3vKoNdBQW1tLa5cueJy+7Fjx3Q3fRuI5HYU9ZIXqPeOltFHWPVETwGgnNkHIwdl/nxhk+qMyxnFlksqcJFLTtlUqb+1J7Mq9d2n5esoRaqNWgaAUqSCVKn2ywlcpMh9HzSEWL9CakBID9kCVqsV5ecEfLu3AjvLfkJ1dbXT+d1qteLTTz8FAHz66aeIjo6G2WzWvJ1q8DooiI+Px+LFi/HWW28BuHriPXfuHF588UUMGzZM8QaSNsQ6RVrnxWrZ0ZKTSmD0EVY90VMA6K9T4IFIqjOup53i5ZBTNtWT40nNqtR3n15eR6k2ahm4eDNT4xik6jnFTIl2iPUrpAaEtB4sqm82w93+KRaLBXPnzgUAzJ07F8OHD9dleVE5vA4KXnvtNdx111245ZZbcPHiRYwaNQqlpaVo27Yt1q5dq0YbSQNinSK9nLTUSNuRU9rVn0dYtWbkkXYiX5BTNtXd8QDxWRWx+/RCqo1aBi7ezNQ4Bql6eY3VaodYv0JqQEjqPjV2iq9vNsNdkB0dHY1OnTph//796NSpE6Kjoz1+Pr3zOiiIjIxEcXEx1q5di507d6K2thbjxo3D6NGjERwcrEYb/Zrec+48WdDnq0V7QMPSdoxQ2lVren8/EgUypTu67mZVlE5/Uppe2ih3pkYv7de6HVIDQlL3qbFTfH2zGW3btsWoUaOQk5Nj/7kbbrjB/n+z2YzIyEgcOHAAkZGRfpM6BMjcpyA4OBhjx47F2LFjlW5PwNFLLr8YTxb0+WLRnhKdeDVGkvSQD9kQUu9HuQEDAw0i8mf+PIOsl9K6gDo7xUtlSYwZMwYAMGbMGBQVFTmlCKWnpyMjIwMzZsyQ++vokkdBwWeffebxAR98UE/LQvXBXzdbkpOzKTcNyCgnXT0tnpVD6v0oN4DVe+BLpDU9dbSIpOglhRiQv1O8WB9MKtvBXYpQXFwc4uLiFPit9MWjoMA2SmtjMpkgCILLbQDqrUwU6PSw2ZIaOflyRtr9vXqPXkrCqlHuU24Aa+TAlxpOT2V89cKTijRapGWS/7Fardi7dy8AYO/evQ2ujKOXdQ8NIdYHk8p2MJvN9oD99OnTfpUiJMWjoKC2ttb+/2+++QbPPfcc0tPTcccdd8BkMmHr1q144YUXkJ6erlpDjUwPnSK9dMb9vXqPXkrCqjFjITeAZWWfwOaukkcg8qQija9LaQYqqXKTSne43blw4UK9z2W1WrFkyRIAwJIlS7Bs2TL7fe7SXryll3UPDSHWB3OX7ZCWloa0tDSv9pcyerpsI28fMG3aNLz++usYOnQoWrRogZCQEAwdOhSLFi3C1KlT1Wij4dk6RRdadvFZp2jEiBF4++238c477wAA1qxZg3379mke8dtOMD179gSg3zQgra0ouoS9A1Zg74AVWFF0SbHj4e95Tsd0HLX98MMPUVxc3ODnIpKil3OPntQ9D9atSPPCCy8A4GvlC3XLTdqCNNt9jh1ux/vUYPvM1H0ui8WCVatWAQBWrVrldF90dDTatGkDAGjTpo1T2kvdgMd2PZDLcVbLl9cSx+vahg0bXO4X64OZzWY0anS1G7xv3z6nxcQAMHHiRBw/fhwTJ070uC22AbmuWyZ4NRh35MgRAFcDwNLSUo8fpzSvFxr/8ssvCA0Ndbk9NDQUhw4dUqJNpAIj5OQHcpqB0qPpYjMWepkxosBhhHOPnuhlD4BAFR0djRkzZmDlypUYN26cU6c6OjoaiYmJ+OSTT/DQQw+pXoryq6++AuDauZdqh9lsRlJSEpYuXYqkpCSnmQyl6+tLzWrJSYOT6gN4slGdt+se1NhvQE5mSGlpKRISEgDAHnT6ajDA66Cgb9++mDZtGtasWYOIiAgAQHl5OWbMmIHbbrtN8QaS+vSy6I1pBurz9/QtIiJ3pFKEzGYzDhw4gAsXLuDAgQNOnWqz2YycnBzU1NQgJydHkb2ZHNvyww8/OHVKX3zxRXv6St12VFdXo1GjRqiurnZJYTpw4IDTvzbR0dFYvnw53n33XYwdO7bBQY1U+o2cfYCk+gC265PYRnWA9+sepAJAORx3Qj59+rTHA3y21yQtLQ2RkZEYN26czwbpvA4K3n33XSQkJKBdu3b2Kc8jR46gS5cuWL9+vdLtIw3opbqA3FrPajB6aVExHLUlokDnboQ4Pj4e27dvR3x8vMtjn3jiCSxdutSl4ypFKghxbMsbb7zhlKoyceJE0dQVWynM+kpiit1nNpsRExODqKgoxMTENHg9hNSslljAkJ+fD8Cz3Z8dH9eqVSun++puVCe27kFqxsJsNmPHjh2oqqrCjh07Gvx6NLQvNWzYsAY9vxK8Dgo6deqE3bt3Izc3FxaLBYIg4JZbbsHgwYPtFYjIN+Sm3+iluoCeOqxGLy1KDRfI6WxipGYVWTWHjCI6OhqhoaGorKxEaGioywhxbm4uTp06hdzcXJdO+cKFC7Fw4UKXY3ra8a8bhERHR6NHjx7YvXu3vePrCamSmFL3ZWRk2PPu1SypKRYweLP7s+Pj5C549uV+Skas1CRr8zKTyYQhQ4ZgyJAhSrcnoCidtiM3/cYfqgsoveJfbmlR8h9cf+FKaiSMVXPIHa2r94gxm82YP39+vak5gPQovBh3HX+xIMRsNmPZsmX1boRVUFBgv12pDrzULIgW1MoIcHxv2ao22Z5PqsKQkpuQ2XZCfuWVVwAAu3btwpAhQwxVztSjoOCNN97A3//+dzRr1gxvvPGG5M/6cwUipU9oSqft6Cn9RmtKl/SUW1qU/AfXX7iSGgmTs5khBRapcpnuSoGK3SeXVGqOnI2p3HX8pYIQsedTY1RfbBZEjde4PmplBDi+t9555x376+Vu4b7Sm5CpsXhZSx6VJH3ttddw/vx5+//FvhYvXqxmW31O6XJkdUv1NXSqKZDLfSpd0pMokD9PYqRKadouvgBfK6qfVLlMd6VAxe7TC1vHPyIiAvPnz3fpUEuVtywoKMDIkSNRUFDgdPuMGTMwbNgwRUax3R3TCK+xFFtQBgCfffaZ032O+z00tAyrJ+3o0aMHTCYTevTooXqFKqV5FBQcPHjQ/kE+ePCg6Ffdle7+Rs4fW6p+rtQFlryjh70giPyBu5rfRFLqzqg7dsJs5TKDgoJcymXaKsG0bNkSM2bMcCnBKXbtrVu9x5HteyVq8ntCTl174I8ZgYyMDKfb4+LisG7dOkVHssWOGR0djU6dOgG4unZUj53Zupu21X1vtW/fHgAQFRXl9Dix/R7UYDabMWHCBISHh2PChAmGSh0CZGxeFsjMZjNCQ0NhMpkQGhrq0R/bMUXItiuepylCWp/QiPTACBusqdFGvWwE1JBzFpG7GXWxcpnuSoGKdbQcR7hff/11p2Pa0p31PvKtxoyAt8xmMyIjI9GoUSNERkY6vcZi+fpqkOr4S23aBgDLli1DQkICli1b5nS7beagvkXlanBM0TIarxcaP/zww+jTpw+ef/55p9tfffVV/Oc//8G//vUvxRqnR2KLUsTWGzRkNfq7774LwJh5aRQ4lK46Y4QFvmq0US8Ldf2hggb5jmM1nZiYGJdOmJxSmoB4Lrzj87Vu3drpMa1atYLJZKq3HXqidF67XGL9G8dAb9OmTaq2tW7Hf8qUKU4LtqU2jxN7HaOionDq1Cm0b99ek5F7OQvV9cLroCAvLw8vvviiy+1//vOf6y3T5W/E3nRiC6gaUtnnkUcewf79+xXZVINILUp3Zo2wwFeNNiq9UFduSVV/qEZGvuNuRl1uB1iq9r5Y9Z5HH30Uhw4dMmQahy+I/W0cA6/c3FzMmTPHfp9jvr4Si5Pd7dYstWmbGLH3h1r0EuTJ4XVQcO7cOTRt6lrdpUmTJqiqqlKkUUYUHR2N/Px8HDp0CO3bt1ekE79t27Z6p1KJpGhdX19OZ1aqjXrar0KMGm10VyXDW9whnNQk1RmUW+ZRqtqOnLr8UvsNkOccA70mTZo43bdp0yYA9VeTklOt0V3HX84ovJE76VrzOijo1q0bPvroI8yePdvp9uzsbNxyyy2KNUyvxOoGm81mxd94Rp6C0ks96kCkdWdQTmc2UDusSu9NIiWQSxQrTep8plUpR70R6ww2hNLXPCNfQ/UmMTERpaWlSExMdLo9Nze33hQtueVnAem/Gzv46vI6KEhJScFDDz2EX375BXfffTcA4N///jfWrl3rF+sJ3HVmtdoN0HZ8o775pU4IpC4jdAa1bqNedttVem8So8+46InUuV/qfCZVl9zogyN1K/s4nsPFOoOA/Ouk3Gue2GCdka+heiM269KkSZN6U8Vs5WcrKirclp+tu2aSfzff8TooePDBB7F+/Xqkp6fj448/RnBwMGJiYvDNN99g4MCBarRRU+46sxx58Iwa6VTkGSN0BrVuo78u4g3UGRc1SJ37o6OjsXz5crz77rsYO3asS7nMFi1aoKqqCi1atPB4tFRL7mY6pIIhW+ftjTfe8KgzCGh/ndRysC5Qif1NxWYQzGYz0tLS6t2wzd1idHJ25MgRAFc/nyEhIapeK2WVJL3vvvtQUFCA8+fP4/fff8e3337rFwEB8McilyZNmiAxMbHe1e1idYPFNiCRS+njacmWTjV69GjExcWpOjrGuurK8OfXccSIEXjhhRcAAGvWrMG+fft8EigpvTdJ3Q0Qffm7GZ1UnXyz2Yzs7Gzs3LkT2dnZLuUyX375ZURERODll1926fzYNlRSuxyi1P4AUmVCpe5zrF3fuHFjp+dLT0/H8OHDkZ6e7tIWNerrS9FDSU9/J/Y3lSq/KbZvg21x+IgRI7Bs2TJDzZ5prbS01L4p5JgxY9ClSxeUlpaq9nyygoIzZ87gnXfeQXJyMk6dOgUA2LlzJ3799VdFG+cLZrMZOTk5qKmpQU5OjldvVrENSOQSO17dfDy19zCQ2hxGD4xQV90IHW4jvI5y+etuu/6+67KW5zqz2YysrCycOXMGWVlZXp37pTo/tg2V1C6H6K5zbysQ0rRpU5eZDrFNqxxr19s2MNUjrYMQ+oNUQGbkgU01hF9rQvCZfQg+sw/h15o8eoytxHVaWhpWrlzpdJsavE4f2r17NwYPHozQ0FAcOnQI48ePR+vWrZGTk4PDhw/j/fffV6OdmnriiSewdOlSlyl5d7RaJOUuH09pdTeH0VsVByPUVdcyl9yTxyq9p4ZWtFyoS76nxrkuKysLwNWNkeqOUqakpNjTHeqSW1FHq3KIUmlMZrMZU6ZMsV/X6s502D5Lp0+fdglcxH5vpuwQIJ3/L/UeCcT3z4TeTdF1ywT7/70xbNgwNZrkwuugYPr06UhKSsKCBQucOjX33nsvRo0apWjjfGXhwoWy9lxQenGMVM1gqQ08lCa1OYzSNYqliHVmla6rrkZJTz3lksvZU0MvnXGlgyuj0MtCaTVIVSKRyuWXyzbaVndjJACIiYnB7bffjpiYmAY/j42S1wWp18psNqNDhw4oKSlBhw4dXM7FUtc1x9xvT9vP9XXkjtyN6vzViqJL+N/Zq67+P2MUHvRtc+rldVCwY8cOrFixwuX2G264AeXl5Yo0yqjEKiAozWw2Iy8vDzU1NcjLy1M9H09qc5hDhw4B0GYRnVaL9tRYvCk3cBHrDDakeo9UVQgxeumMG2E2Qw16WSitBqnZALPZjJiYGERFRSEmJkaRc11ycjLS09Pr3RRS7yOb7mZO5M5KTJw40esZYFaIIXfk7C3hz8rPCbjQsov9/45sqUW2//uK10FBs2bN6t2k7Oeff8Z1112nSKOMSsuLhtQ0txrEPsBDhw7FmjVrFKswJFUJIzo6GgMGDMC2bdtwxx13qDZDIrfDrcYMg1hnsCHVe6SqQoiR2xlXeoTbCLMZalB6t2M9cTcbkJycjPz8fFRUVCAvL89+u6d7B9QtpfnMM8/gmWeeqbcteh/ZdFe1JRA7WkRG4O761JDUIiV5HRQMHz4cc+fOxT//+U8AVzsJR44cwfPPP4+HHnpI8QYaSXx8PLZv3474+HjVn0vOyI4a2rZti9GjR9d7n5yZE6nZALPZ7FT+TK0ZErkdbjVmGNTqDHr7/pE706HlCLdeZjPUCE6U3u1YT8xms6zzmad7B7z77rseH1vvI5tmsxkTJkxAWloaJkyYwKotRAbh7vqkl9Qir6sPLVy4EL/99huuv/56XLhwAQMHDkSnTp0QEhKCl156SY02GoZUaS5/JVVdQE71JNuoYZ8+fbB8+XKXkTAlX2OpEn5yqFEeUq2qOVpVhZBbClTO36bu6y9nNqO4uNjtz7tjlCpOSr//G0Lq/ShW+tI2am4ymdCjRw+Xijq280hqaqrHz6Ulx9fftjbLE4F4nSEyOqnrk9VqRfk5AVnf/YRth6wuqUVa8nqmoEWLFsjPz8e3336LnTt3ora2Fr169cLgwYPVaB9+/fVXPPfcc/jqq69w4cIFdOnSBStXrkTv3r0BAIIgYM6cOXjrrbdw+vRp9OvXD8uWLcOtt96qSnuk6GF6WYoau2uKTe0D8qonmc1m5ObmYs+ePS47J0odUw6l1yjInWHwRdqLVqlucke45fxttJ7NMHIVJ0A/G2sB0u9HsRF6s9mM0NDQejfQkpp90MPaAMD59d+0aZNTW6QKOOj9OkNErtq2bYtRo0Zh8uTJAID8/Hz7tUJPa8a8Dgps7r77btx9991KtsXF6dOnERcXh7vuugtfffUVrr/+evzyyy9o2bKl/WcWLFiARYsWYdWqVejSpQvmzZuH+Ph4/Pzzz5q/qHqYXpYi1QmQGzBUVlaitrYWlZWVLvdJVU8SK50HSF/0lHyN9bKroi/SXvTesVCj6owYuSlacqo46YlWa3Q8Iff9KFUmVCx9US/vfcfXv6ioyOm+TZs2Aag/WNP7dYaI6mexWLBq1SoAwIoVK+zVwEaMGIHNmzfjww8/xPjx4zFlyhSfDSR5FRTU1tZi1apVWLduHQ4dOgSTyYQOHTrg4YcfxqOPPgqTSdkV06+88gqioqLw3nvv2W+zbQQDXJ0lWLx4MWbNmoWRI0cCAFavXo2wsDBkZWVhwoQJ9R63urraaRFofQun/VF0dDTy8/Nx6NAhl4XBckcNQ0ND0ahRI/uunZ6w7QAqttBVq4ue7XkFQXD6Xmu+GFnWe8fCcQdZ26ivWuTOZth2wF25cmW9lWz0zmw2O3Wq1S4nLFZKE1Dn/Sg2I6CX977ZbEbfvn3xww8/1JsmaTKZfDpYQUTKsm0UuH//frRr185+e9u2bfH9998DAN555x2frhf1eE2BIAh48MEHMX78ePz666/o3r07br31Vhw+fBhJSUn2vGclffbZZ+jTpw/+8pe/4Prrr0fPnj3x9ttv2+8/ePAgysvLMWTIEPttQUFBGDhwILZu3Sp63Pnz5yM0NNT+FRUVpXjb9ch2Ef7kk0+cvgfc5/KLkdrqXorYDqCAtjm/coIapdXdlVavI8vkrCE74AaauimDjrvtAvI/81K7yEvttKoXWVlZqK6utm+oZtOkSZN606KIyLjMZjNWrVqFhIQEl9L+586dA3C1T1K3/yVnJ2S5PA4KVq1ahS1btuDf//43du3ahbVr1yI7OxslJSX45ptv8O233yq+m/GBAweQmZmJzp07Y+PGjfjHP/6BqVOn2p/Hti9CWFiY0+PCwsIk90yYOXMmKisr7V9Hjx5VtN16lpycjE8//RTJyclOt9fN5ff0QqTG9vJSF3qlyQ1qqOHcLXQ1wt8mJSUFERERmpUGVppWnzV3gw5y22GEjr8UsfdPYmIiwsLCkJiY6KOWEZEaxPpM8+bNQ0REBObPn+/U/7JarfZypV23TFC9XKnH6UNr165FcnIy7rrrLpf77r77bjz//PP48MMP8be//U2xxtXW1qJPnz72TkHPnj3x008/ITMz0+l56qYtCYIgmcoUFBSEoKAgxdrZEFL1tLWml1xbLduhl1SCQKSnha5y6aU0sFxafdbcbUImtx1Sn1+9LCiWIvb+cawwZOT3FxF5RuxcYLFYsKLoEj77uQYAUHZOwGgV1xx6PFOwe/du/PnPfxa9/95770VJSYkijbKJiIjALbfc4nRb165dceTIEQBAeHg4ALjMCpw8edJl9kCvHKfVX3/9ddWfT2r0VelRfzXSgPRQTlBPpRyNzJaT37JlS8yYMUOx0WMluftb6+H92BBKfualSg0D4rOUSrfDxsizCEZuOxEpZ8SIERg/bRZ2lddixsL3sWXnz6quOfQ4KDh16pRkRzssLEzxcopxcXH4+eefnW7bt2+ffYFGhw4dEB4e7lSv+dKlS8jLy0P//v0VbYtaHGttt27d2qdtUbqDI7dTJ/U4PXQU645w182P1gMjBC62/MozZ85g1apV9Y4e+7pj5O5vrYf3Y0PI+cyL1dd3t25Aa2oEGloxctuJSDlms9lpwOyGG25Q9fk8Th+6cuUKrrlG/McbN26My5cvK9Iom6eeegr9+/dHeno6HnnkEfznP//BW2+9hbfeegvA1bShadOmIT09HZ07d0bnzp2Rnp4Os9mMUaNGKdoWtZjNZixbtky0rJ7SpKbUpfYckENuSoDU4/SQ4qSXUqZStE7NkaqrLuXGG29ERUUFbrzxRpf79JDa5a5spx7ejw0hJ8VGrL5+dHQ0QkNDUVlZWe9iOanyoURE5Erra7nHQYEgCEhKShLNxXcs8amUvn37IicnBzNnzsTcuXPRoUMHLF68GKNHj7b/zLPPPosLFy5g0qRJ9s3LNm3apMsdRPXACPn6Uo/TQ0dRatMkvdA6cJGqqy5Fy4BYDrPZjMTERJSWliIxMdFn5XPVIud84Pjeys3NxZw5cwBcfa3mz5/v81LDRET+Ijo6Gk2bNsWlS5fQtGlT1a/lHgcFjz32mNufUXKRsc3999+P+++/X/R+k8mE1NRUl63sjUTJBXFWqxVLliwBACxZsgTLli3zuB640iN5YpsH+QO9j3pqvQfDunXrAACdOnXy6qRlhI6iPy/6lPP6OwbFTZo0cbrP6AuviYj0xGw2Y8qUKVi6dCmeeOIJ1a/lHgcFjhuIkbKUHL133DFv1apVmDJlisejtkp30IxQ/UMuI3RmtdyDoaysDMDVXcj1OHPSEPHx8di+fTvi4+MVOZ5YTr4Sx6ubviV3p3J3j3OcPSEiIvUsXLjQvvux2jxeaEzqUXJRWXR0NBITE9GkSRMkJib6NN9dDwtF/cEPP/wAwLWii9Z1/uuWz3WUlpaGiIgIpKWlKfJceuI4U6AExxzRd955R9Hj1V0MLXdRvLvHKf2aEBGR7zEo0IC7Un1KMpvNqK6uRqNGjVBdXe3TUVstK2goPfqqJ++++y4A14ou7jpucl5/qUDDsbrMG2+84fQ4qR2qjU7p4DY6Ohpt2rQBAHz11VeKHq9NmzZOAwFydyq3LRoG6t9hkwE/EZH/YVCgAa1L9QXiBbtuRRSjkRqFT01NrbdTFx0djfz8fKxZswb5+fmKzApJBRrR0dHo1KkTgKvVxgKF0sGt2Wy2z6y8+OKLTvc5VnHydPDA8XhpaWlOAwFmsxnZ2dnYuXMnsrOzPR4kMJvNaN++PQCgffv29S4aZslMIiL/wqBAA3JH6+QKxAu2rXRkkyZNUFRU1ODjaV3nX2oTu5YtW9a7E6zZbMbu3bvxzDPPYPfu3YrMCkmNOpvNZkRGRqJRo0b2n3FHy1kyd8TSsHxBbGbl0KFDALzf/0JqpqayshK1tbWorKz0qo3Lli1DQkICli1b5tXjiIjImBgUaMBsNiMmJqbejh0pw2w2o2/fvmjUqJHqI+ZqkNrETmon2LS0NJSVlSmWy282m+2lh5OSklzeq96uU9DThlZiaVi+ILZpWMuWLRUfPJC74DwQBxeIiAIZgwKNGH3nUyPIyspCdXU1srKyGnwsubM7cmcYzGYzJkyYgPDwcDz66KMetzMlJQURERFISUnx+DHuHDhwwOlfR952FB1TjrwtV6q0Rx55BC1btsSMGTN8vuGc2Plg1qxZKCwsxIoVK5wCMnfvK6mdiZVecE5ERP6JQYFGAjHPX2tKdpDNZjNyc3OxZ88e5Obmejy705AZBrGKLlKdOjUW+Cr5XnVMOYqMjFRklkxu4LVt2zZcuHABBw4c8PlsndhrfOzYMad/bdy9r6QGHTjiT0REHhFIqKysFAAIlZWVvm6KbuXn5wsJCQlCfn6+r5uiGTm/8/nz54Xly5cLffr0EZYvXy6cP3/e6f6ioiIBgFBUVKTI8xmB0r+X7TW0fdV9LcVeY6l2SP1dGtpOb465fPlyISIiQli+fLnT7efPnxfatGkjABDatGnj8r7y1/cOERE1jDd9XI83L6PA5s8bkYmRu9ur4wyD4wh+3UW3dTeEMsKGaHIo/XvZUrveffddjB071uNUILF2yN3gSw1iOwLb1nosXbq03rUe/vreISIi7TB9iDwSiOlPUnnaUsReKzUW3cpto5FJpXZJlXYVe620XlQul9RaDyIiogbTYOZC97RIH+L0vvEkJCQIQUFBQkJCgiLHc5daJIfSbTQKsc+TY2rRzTff7HSf2Gt1/vx5oUePHoLJZBJ69OihyN/FsS1KpSTxHEJERN5i+pAOBWL6jdHZRvqVmh0xm82i6SFyKd1Go9i9eze2b9+O3bt3O32ebKVdd+/e7VLaVey1MpvNCA0NhclkQmhoqM8XIYthihAREalKgyBF9zhTQN6S+nvyb62+iIgIAYAQERHhcp+c11/pv9n58+eFpKQkAYCQlJSk2OwDERGRNzhToEMc5fMvUjM/nBVSX0pKCtLS0uotP6uHz5rFYsGqVasAAKtWrcKUKVPQq1cvn7aJiIhICoMCIhmk0nYCNaVHS0qnYSkdyEVHRyMxMRGffPIJHnroIZ9vlkZEROQOgwIiGaRGo6XuKygoQEZGBmbMmOHz0Wz6gxrrR6qrq9GoUSNUV1frdp0CERGRDYMCIg0xtUh9cgIvNVKOOGNERERGwqCASEPsKKpPL4GXHtY2EBEReYpBAZGG2FFUHwMvIiIi73FHYyIRauwWHIg7EGstLi4O69atY/BFRETkBQYFRCJsaSgZGRlePU6q4y/3mERERERqYvoQkQi5aShSOe1MbSEiIiI9MgmCIPi6Eb5WVVWF0NBQVFZWokWLFr5uDhkcy44SERGRHnjTx2VQAAYFREREROR/vOnjck0BEREREVGAY1BARERERBTgGBQQEREREQU4BgVERERERAGOQQERERERUYBjUEBEREREFOAYFBARERERBTgGBUREREREAY5BARERERFRgGNQQEREREQU4BgUEBEREREFOAYFREREREQBTtdBQWpqKkwmk9NXeHi4/X5BEJCamorIyEgEBwdj0KBB+Omnn3zYYiIiIiIi49F1UAAAt956K8rKyuxfe/bssd+3YMECLFq0CEuXLsWOHTsQHh6O+Ph4nD171octJiIiIiIyFt0HBddccw3Cw8PtX9dddx2Aq7MEixcvxqxZszBy5Eh069YNq1evhtVqRVZWlo9bTURERERkHLoPCkpLSxEZGYkOHTogMTERBw4cAAAcPHgQ5eXlGDJkiP1ng4KCMHDgQGzdulXymNXV1aiqqnL6IiIiIiIKVLoOCvr164f3338fGzduxNtvv43y8nL0798fFRUVKC8vBwCEhYU5PSYsLMx+n5j58+cjNDTU/hUVFaXa70BEREREpHe6DgruvfdePPTQQ+jevTsGDx6ML7/8EgCwevVq+8+YTCanxwiC4HJbXTNnzkRlZaX96+jRo8o3noiIiIjIIHQdFNTVvHlzdO/eHaWlpfYqRHVnBU6ePOkye1BXUFAQWrRo4fRFRERERBSoDBUUVFdXY+/evYiIiECHDh0QHh6O3Nxc+/2XLl1CXl4e+vfv78NWEhEREREZyzW+boCUp59+Gg888ABuuukmnDx5EvPmzUNVVRUee+wxmEwmTJs2Denp6ejcuTM6d+6M9PR0mM1mjBo1ytdNJyIiIiIyDF0HBceOHcNf//pX/P7777juuutw++23Y/v27WjXrh0A4Nlnn8WFCxcwadIknD59Gv369cOmTZsQEhLi45YTERERERmHSRAEwdeN8LWqqiqEhoaisrKS6wuIiIiIyC9408c11JoCIiIiIiJSHoMCIiIiIqIAx6CAiIiIiCjAMSggIiIiIgpwDAqIiIiIiAIcgwIiIiIiogDHoICIiIiIKMAxKCAiIiIiCnAMCoiIiIiIAhyDAiIiIiKiAMeggIiIiIgowDEoICIiIiIKcAwKiIiIiIgCHIMCIiIiIqIAx6CAiIiIiCjAMSggIiIiIgpwDAqIiIiIiAIcgwIiIiIiogDHoICIiIiIKMAxKCAiIiIiCnAMCoiIiIiIAhyDAiIiIiKiAMeggIiIiIgowDEoICIiIiIKcAwKiIiIiIgCHIMCIiIiIqIAx6CAiIiIiCjAMSggIiIiIgpwDAqIiIiIiAIcgwIiIiIiogDHoICIiIiIKMAxKCAiIiIiCnAMCoiIiIiIAhyDAiIiIiKiAMeggIiIiIgowDEoICIiIiIKcAwKiIiIiIgCnKGCgvnz58NkMmHatGn22wRBQGpqKiIjIxEcHIxBgwbhp59+8l0jiYiIiIgMxjBBwY4dO/DWW28hJibG6fYFCxZg0aJFWLp0KXbs2IHw8HDEx8fj7NmzPmopEREREZGxGCIoOHfuHEaPHo23334brVq1st8uCAIWL16MWbNmYeTIkejWrRtWr14Nq9WKrKwsH7aYiIiIiMg4rvF1AzwxefJk3HfffRg8eDDmzZtnv/3gwYMoLy/HkCFD7LcFBQVh4MCB2Lp1KyZMmFDv8aqrq1FdXW3/vrKyEgBQVVWl0m9ARERERKQtW99WEAS3P6v7oCA7Oxs7d+7Ejh07XO4rLy8HAISFhTndHhYWhsOHD4sec/78+ZgzZ47L7VFRUQ1sLRERERGRvpw9exahoaGSP6ProODo0aN48sknsWnTJjRr1kz050wmk9P3giC43OZo5syZmD59uv372tpanDp1Cm3atJF8XCCrqqpCVFQUjh49ihYtWvi6OUQBi59FIn3gZ5GMQBAEnD17FpGRkW5/VtdBQVFREU6ePInevXvbb7ty5Qq2bNmCpUuX4ueffwZwdcYgIiLC/jMnT550mT1wFBQUhKCgIKfbWrZsqWzj/VSLFi148iPSAX4WifSBn0XSO3czBDa6Xmh8zz33YM+ePSguLrZ/9enTB6NHj0ZxcTE6duyI8PBw5Obm2h9z6dIl5OXloX///j5sORERERGRceh6piAkJATdunVzuq158+Zo06aN/fZp06YhPT0dnTt3RufOnZGeng6z2YxRo0b5oslERERERIaj66DAE88++ywuXLiASZMm4fTp0+jXrx82bdqEkJAQXzfNrwQFBeHFF190SbsiIm3xs0ikD/wskr8xCZ7UKCIiIiIiIr+l6zUFRERERESkPgYFREREREQBjkEBEREREVGAY1BARERERBTgGBSQqPnz56Nv374ICQnB9ddfjxEjRtg3jCMi7WRmZiImJsa+SdIdd9yBr776ytfNIgp48+fPh8lkwrRp03zdFKIGY1BAovLy8jB58mRs374dubm5uHz5MoYMGYLz58/7umlEAeXGG2/Eyy+/jMLCQhQWFuLuu+/G8OHD8dNPP/m6aUQBa8eOHXjrrbcQExPj66YQKYIlScljv/32G66//nrk5eVhwIABvm4OUUBr3bo1Xn31VYwbN87XTSEKOOfOnUOvXr2wfPlyzJs3D7GxsVi8eLGvm0XUIJwpII9VVlYCuNoZISLfuHLlCrKzs3H+/Hnccccdvm4OUUCaPHky7rvvPgwePNjXTSFSjOF3NCZtCIKA6dOn484770S3bt183RyigLNnzx7ccccduHjxIq699lrk5OTglltu8XWziAJOdnY2du7ciR07dvi6KUSKYlBAHnniiSewe/du5Ofn+7opRAHp5ptvRnFxMc6cOYNPPvkEjz32GPLy8hgYEGno6NGjePLJJ7Fp0yY0a9bM180hUhTXFJBbU6ZMwfr167FlyxZ06NDB180hIgCDBw/Gn/70J6xYscLXTSEKGOvXr0dCQgIaN25sv+3KlSswmUxo1KgRqqurne4jMhLOFJAoQRAwZcoU5OTkYPPmzQwIiHREEARUV1f7uhlEAeWee+7Bnj17nG57/PHHER0djeeee44BARkagwISNXnyZGRlZeHTTz9FSEgIysvLAQChoaEIDg72ceuIAkdycjLuvfdeREVF4ezZs8jOzsbmzZvx9ddf+7ppRAElJCTEZV1d8+bN0aZNG663I8NjUECiMjMzAQCDBg1yuv29995DUlKS9g0iClAnTpzAo48+irKyMoSGhiImJgZff/014uPjfd00IiLyE1xTQEREREQU4LhPARERERFRgGNQQEREREQU4BgUEBEREREFOAYFREREREQBjkEBEREREVGAY1BARERERBTgGBQQEREREQU4BgVERERERAGOQQERkQYGDRqEadOmqXLsAQMGICsrS5Vj+5s9e/bgxhtvxPnz5yV/LjU1FSaTCSaTCYsXL1a0DYcOHbIfOzY2VtFjExHJxaCAiMjAvvjiC5SXlyMxMdF+W/v27e2dTtvXjTfe6MNW6kf37t1x22234bXXXnP7s7feeivKysrw97//3X5b+/bt6w0SUlNTPe7gR0VFoaysDDNmzPC02UREqmNQQERkYG+88QYef/xxNGrkfDqfO3cuysrK7F+7du2q9/E1NTVaNFNXHn/8cWRmZuLKlSuSP3fNNdcgPDwcZrNZ0edv3LgxwsPDce211yp6XCKihmBQQETkA6dPn8bf/vY3tGrVCmazGffeey9KS0udfubtt99GVFQUzGYzEhISsGjRIrRs2dJ+/++//45vvvkGDz74oMvxQ0JCEB4ebv+67rrrAAAmkwlvvvkmhg8fjubNm2PevHkAgM8//xy9e/dGs2bN0LFjR8yZMweXL1+2H6+0tBQDBgxAs2bNcMsttyA3Nxcmkwnr168HAGzevBkmkwlnzpyxP6a4uBgmkwmHDh2y37Z161YMGDAAwcHBiIqKwtSpU51Sedq3b4/09HSMHTsWISEhuOmmm/DWW285/W7Hjh1DYmIiWrdujebNm6NPnz744YcfcOjQITRq1AiFhYVOP79kyRK0a9cOgiAAAIYOHYqKigrk5eW5+SvJV3emxmQyoX379qo9HxFRQzEoICLygaSkJBQWFuKzzz7Dtm3bIAgChg0bZh+5LygowD/+8Q88+eSTKC4uRnx8PF566SWnY+Tn58NsNqNr165ePfeLL76I4cOHY8+ePRg7diw2btyIMWPGYOrUqfjvf/+LFStWYNWqVfbnq62txciRI9G4cWNs374db775Jp577jmvf+c9e/Zg6NChGDlyJHbv3o2PPvoI+fn5eOKJJ5x+LiMjA3369MGuXbswadIkTJw4ERaLBQBw7tw5DBw4EMePH8dnn32GkpISPPvss6itrUX79u0xePBgvPfee07He++995CUlASTyQQAaNq0KXr06IHvv//e69/BU46zNPv370enTp0wYMAA1Z6PiKjBBCIiUt3AgQOFJ598UhAEQdi3b58AQCgoKLDf//vvvwvBwcHCP//5T0EQBOF///d/hfvuu8/pGKNHjxZCQ0Pt37/22mtCx44dXZ6rXbt2QtOmTYXmzZvbv15//XVBEAQBgDBt2jSnn/+f//kfIT093em2Dz74QIiIiBAEQRA2btwoNG7cWDh69Kj9/q+++koAIOTk5AiCIAjfffedAEA4ffq0/Wd27dolABAOHjwoCIIgPProo8Lf//53p+f5/vvvhUaNGgkXLlywt33MmDH2+2tra4Xrr79eyMzMFARBEFasWCGEhIQIFRUVLr+3IAjCRx99JLRq1Uq4ePGiIAiCUFxcLJhMJnsbbBISEoSkpKR6jyEIgvDiiy8KPXr0cLm9vte2efPmQpMmTer9+draWiEhIUHo3bu3YLVaPXoOIiJfuManEQkRUQDau3cvrrnmGvTr189+W5s2bXDzzTdj7969AICff/4ZCQkJTo+77bbb8MUXX9i/v3DhApo1a1bvczzzzDNISkqyf9+2bVv7//v06eP0s0VFRdixY4fTTMSVK1dw8eJFWK1W7N27FzfddJPTYuU77rjDi9/4j+fZv38/PvzwQ/ttgiCgtrYWBw8etM94xMTE2O83mUwIDw/HyZMnAVxNSerZsydat25d73OMGDECTzzxBHJycpCYmIh3330Xd911l0vqTnBwMKxWq9e/A+D62gJX13Zs2bLF5WeTk5Oxbds27NixA8HBwbKej4hICwwKiIg0Jvxfbnt9t9tSXBz/L/a4tm3b4vTp0/Ueq23btujUqVO99zVv3tzp+9raWsyZMwcjR450+dlmzZrV2966bbMtdHb82bqLmGtrazFhwgRMnTrV5Xg33XST/f9NmjRxea7a2loAcNuxbtq0KR599FG89957GDlyJLKysuqtFnTq1Cn86U9/kjyWmPpe2/qClDVr1uC1117D5s2bWf2JiHSPQQERkcZuueUWXL58GT/88AP69+8PAKioqMC+ffvso+XR0dH4z3/+4/S4ugtoe/bsifLycpw+fRqtWrWS3Z5evXrh559/Fg0ibrnlFhw5cgTHjx9HZGQkAGDbtm1OP2NbyFxWVmZvS3Fxscvz/PTTT6LP44mYmBi88847OHXqlOhswfjx49GtWzcsX74cNTU19QY7P/74Ix5++GHZ7XBn27ZtGD9+PFasWIHbb79dtechIlIKFxoTEWmsc+fOGD58OP7f//t/yM/PR0lJCcaMGYMbbrgBw4cPBwBMmTIFGzZswKJFi1BaWooVK1bgq6++chqh79mzJ6677joUFBQ0qD2zZ8/G+++/j9TUVPz000/Yu3cvPvroI7zwwgsAgMGDB+Pmm2/G3/72N5SUlOD777/HrFmznI7RqVMnREVFITU1Ffv27cOXX36JjIwMp5957rnnsG3bNkyePBnFxcUoLS3FZ599hilTpnjc1r/+9a8IDw/HiBEjUFBQgAMHDuCTTz5xClK6du2K22+/Hc899xz++te/uswuHDp0CL/++isGDx7s7UvlkfLyciQkJCAxMRFDhw5FeXk5ysvL8dtvv6nyfERESmBQQETkA++99x569+6N+++/H3fccQcEQcCGDRvsqTNxcXF48803sWjRIvTo0QNff/01nnrqKac1BI0bN8bYsWOdcvTlGDp0KL744gvk5uaib9++uP3227Fo0SK0a9cOwNXUoJycHFRXV+O2227D+PHjXSohNWnSBGvXroXFYkGPHj3wyiuv2Mud2sTExCAvLw+lpaX4n//5H/Ts2RMpKSmIiIjwuK1NmzbFpk2bcP3112PYsGHo3r07Xn75ZTRu3Njp58aNG4dLly5h7NixLsdYu3YthgwZYv/9lGaxWHDixAmsXr0aERER9q++ffuq8nxEREowCWLJrUREpCv/7//9P1gsFqdSmidOnMCtt96KoqIi1Tq5YkwmE3JycjBixAhNn9cTL730ErKzs7Fnzx6n26urq9G5c2esXbsWcXFxoo9PTU3F+vXrXVKglKTFcxAReYozBUREOrVw4UKUlJRg//79WLJkCVavXo3HHnvM6WfCwsKwcuVKHDlyxEet1Jdz585hx44dWLJkSb0Lmg8fPoxZs2ZJBgQ2e/bswbXXXovly5cr2sYjR47g2muvRXp6uqLHJSJqCM4UEBHp1COPPILNmzfj7Nmz6NixI6ZMmYJ//OMfvm6WnR5nCpKSkrB27VqMGDECWVlZLmlFnjp16hROnToF4Ooi6tDQUMXaePnyZfsuz0FBQYiKilLs2EREcjEoICIiIiIKcEwfIiIiIiIKcAwKiIiIiIgCHIMCIiIiIqIAx6CAiIiIiCjAMSggIiIiIgpwDAqIiIiIiAIcgwIiIiIiogDHoICIiIiIKMD9f54ypQgUvNyvAAAAAElFTkSuQmCC",
       "text/plain": [
-       "<Figure size 600x500 with 1 Axes>"
+       "<Figure size 900x500 with 1 Axes>"
       ]
      },
      "metadata": {},
@@ -931,23 +1169,25 @@
     "# Decidecade octave sound pressure level (also interquartile)\n",
     "spl10 = acoustics.decidecade_sound_pressure_level(spsd, fmin, fmax)\n",
     "\n",
-    "# Time average into 30 s windows\n",
-    "window = 30\n",
-    "spl10_q50 = acoustics.time_aggregate(spl10, window, method=\"median\")\n",
-    "spl10_q25 = acoustics.time_aggregate(spl10, window, method={\"quantile\":0.25})\n",
-    "spl10_q75 = acoustics.time_aggregate(spl10, window, method={\"quantile\":0.75})\n",
-    "\n",
-    "# Plot medians and quantiles\n",
-    "fig, ax = acoustics.graphics.plot_spectra(spl10_q50[0], fmin, fmax)\n",
-    "ax.fill_between(\n",
-    "    spl10_q50[\"freq_bins\"],\n",
-    "    spl10_q25[0],\n",
-    "    spl10_q75[0],\n",
-    "    alpha=0.5,\n",
-    "    facecolor=\"C0\",\n",
-    "    edgecolor=None\n",
+    "# Plot the decidecade sound pressure level\n",
+    "fig, ax = plt.subplots(figsize=(9, 5))\n",
+    "ax.boxplot(\n",
+    "    spl10.values,\n",
+    "    whis=(1, 99),\n",
+    "    showfliers=True,\n",
+    "    positions=np.log10(spl10[\"freq_bins\"].values),\n",
+    "    widths=0.015,\n",
+    "    flierprops={\"marker\": \".\", \"markersize\": 1.5},\n",
     ")\n",
-    "ax.set_title(\"Decidecade SPL\")"
+    "xticks = np.linspace(0, 5, 6)\n",
+    "ax.set(\n",
+    "    xticks=xticks,\n",
+    "    xticklabels=xticks.astype(int),\n",
+    "    xlim=(1.68, 4.75),\n",
+    "    ylim=(40, 120),\n",
+    "    xlabel=\"log(Frequency) [Hz]\",\n",
+    "    ylabel=\"Decidecade SPL [dB re 1 uPa]\",\n",
+    ")"
    ]
   },
   {
@@ -956,29 +1196,44 @@
    "source": [
     "### Third Octave Sound Pressure Level\n",
     "\n",
-    "Since you're now curious, you can also calculate the 1/3 octave SPLs using `third_octave_sound_pressure_level`. Third octaves are often measured because the human ear appears to have evolved to filter sound at this bandwidth. "
+    "Since you're now curious, you can also calculate the 1/3 octave SPLs using `third_octave_sound_pressure_level`. Third octaves are often measured because the human ear appears to have evolved to filter sound at this bandwidth, and these plots may also be used to reduce the \"busy-ness\" of a figure. "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "Text(0.5, 1.0, 'Third Octave SPL')"
+       "[[<matplotlib.axis.XTick at 0x1c025724590>,\n",
+       "  <matplotlib.axis.XTick at 0x1c000165250>,\n",
+       "  <matplotlib.axis.XTick at 0x1c034138990>,\n",
+       "  <matplotlib.axis.XTick at 0x1c025730110>,\n",
+       "  <matplotlib.axis.XTick at 0x1c0341c1390>,\n",
+       "  <matplotlib.axis.XTick at 0x1c0341c3350>],\n",
+       " [Text(0.0, 0, '0'),\n",
+       "  Text(1.0, 0, '1'),\n",
+       "  Text(2.0, 0, '2'),\n",
+       "  Text(3.0, 0, '3'),\n",
+       "  Text(4.0, 0, '4'),\n",
+       "  Text(5.0, 0, '5')],\n",
+       " (1.68, 4.75),\n",
+       " (50.0, 130.0),\n",
+       " Text(0.5, 0, 'log(Frequency) [Hz]'),\n",
+       " Text(0, 0.5, 'Decidecade SPL [dB re 1 uPa]')]"
       ]
      },
-     "execution_count": 19,
+     "execution_count": 21,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
+      "image/png": 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",
       "text/plain": [
-       "<Figure size 600x500 with 1 Axes>"
+       "<Figure size 800x400 with 1 Axes>"
       ]
      },
      "metadata": {},
@@ -989,23 +1244,24 @@
     "# Median third octave sound pressure level\n",
     "spl3 = acoustics.third_octave_sound_pressure_level(spsd, fmin, fmax)\n",
     "\n",
-    "# Time average into 30 s windows\n",
-    "window = 30\n",
-    "spl3_q50 = acoustics.time_aggregate(spl3, window, method=\"median\")\n",
-    "spl3_q25 = acoustics.time_aggregate(spl3, window,  method={\"quantile\":0.25})\n",
-    "spl3_q75 = acoustics.time_aggregate(spl3, window,  method={\"quantile\":0.25})\n",
-    "\n",
-    "# Plot medians and quantiles\n",
-    "fig, ax = acoustics.graphics.plot_spectra(spl3_q50[0], fmin, fmax)\n",
-    "ax.fill_between(\n",
-    "    spl3_q50[\"freq_bins\"],\n",
-    "    spl3_q25[0],\n",
-    "    spl3_q75[0],\n",
-    "    alpha=0.5,\n",
-    "    facecolor=\"C0\",\n",
-    "    edgecolor=None\n",
+    "fig, ax = plt.subplots(figsize=(8, 4))\n",
+    "ax.boxplot(\n",
+    "    spl3.values,\n",
+    "    whis=(1, 99),\n",
+    "    showfliers=True,\n",
+    "    positions=np.log10(spl3[\"freq_bins\"].values),\n",
+    "    widths=0.04,\n",
+    "    flierprops={\"marker\": \".\", \"markersize\": 1.5},\n",
     ")\n",
-    "ax.set_title(\"Third Octave SPL\")"
+    "xticks = np.linspace(0, 5, 6)\n",
+    "ax.set(\n",
+    "    xticks=xticks,\n",
+    "    xticklabels=xticks.astype(int),\n",
+    "    xlim=(1.68, 4.75),\n",
+    "    ylim=(50, 130),\n",
+    "    xlabel=\"log(Frequency) [Hz]\",\n",
+    "    ylabel=\"Decidecade SPL [dB re 1 uPa]\",\n",
+    ")"
    ]
   },
   {
diff --git a/mhkit/acoustics/analysis.py b/mhkit/acoustics/analysis.py
index 89d93b5b..bea1058a 100644
--- a/mhkit/acoustics/analysis.py
+++ b/mhkit/acoustics/analysis.py
@@ -2,13 +2,13 @@
 This module contains key functions for passive acoustics analysis, designed to process
 and analyze sound pressure data from .wav files in the frequency and time domains.
 The functions herein build on each other, with a structured flow that facilitates the
-calculation of sound pressure levels, spectral densities, and banded averages, based on 
+calculation of sound pressure levels, spectral densities, and banded averages, based on
 input audio data.
 
 The following functionality is provided:
 
 1. **Frequency Validation and Warning**:
-   - `_fmax_warning`: Ensures specified maximum frequency does not exceed the Nyquist frequency, 
+   - `_fmax_warning`: Ensures specified maximum frequency does not exceed the Nyquist frequency,
      adjusting if necessary to avoid aliasing.
 
 2. **Shallow Water Cutoff Frequency**:
@@ -20,11 +20,11 @@
      using FFT binning with Hanning windowing and 50% overlap.
 
 4. **Calibration**:
-   - `apply_calibration`: Applies calibration adjustments to the spectral density data using 
+   - `apply_calibration`: Applies calibration adjustments to the spectral density data using
      a sensitivity curve, filling missing values as specified.
 
 5. **Spectral Density Level Calculation**:
-   - `sound_pressure_spectral_density_level`: Converts mean square spectral density values to 
+   - `sound_pressure_spectral_density_level`: Converts mean square spectral density values to
      sound pressure spectral density levels in dB.
 
 6. **Spectral Density Aggregation**:
@@ -41,10 +41,9 @@
 8. **Frequency-Banded Sound Pressure Level**:
    - `_band_sound_pressure_level`: Helper function for calculating sound pressure levels
      over specified frequency bandwidths.
-     
-   - `third_octave_sound_pressure_level` and `decidecade_sound_pressure_level`: 
-     Compute sound pressure levels across third-octave and decidecade bands, respectively.
 
+   - `third_octave_sound_pressure_level` and `decidecade_sound_pressure_level`:
+     Compute sound pressure levels across third-octave and decidecade bands, respectively.
 """
 
 from typing import Union, Dict, Tuple, Optional
@@ -333,7 +332,8 @@ def _validate_method(
     method: Union[str, Dict[str, Union[float, int]]]
 ) -> Tuple[str, Optional[Union[float, int]]]:
     """
-    Validates the 'method' parameter and returns the method name and its argument (if any).
+    Validates the 'method' parameter and returns the method name and its argument (if any)
+    for an xarray.core.groupby.DataArrayGroupBy method.
 
     Parameters
     ----------
@@ -345,15 +345,26 @@ def _validate_method(
             the value is its argument, e.g., {'quantile': 0.25}.
 
         Supported methods are:
-          - 'median'
+          - 'all'
+          - 'any'
+          - 'assign_coords' (requires coordinate argument)
+          - 'count'
+          - 'cumprod'
+          - 'fillna'
+          - 'first'
+          - 'last'
+          - 'map' (requires custom function argument)
+          - 'max'
           - 'mean'
+          - 'median'
           - 'min'
-          - 'max'
-          - 'sum'
-          - 'quantile' (requires an argument between 0 and 1)
+          - 'prod'
+          - 'quantile' (requires a quantile between 0 and 1)
+          - 'reduce' (requires custom function argument)
           - 'std'
+          - 'sum'
           - 'var'
-          - 'count'
+          - 'where' (requires condition argument)
 
     Returns
     -------
@@ -394,15 +405,27 @@ def _validate_method(
     """
 
     allowed_methods = [
-        "median",
+        "all",
+        "any",
+        "assign_coords",
+        "count",
+        "cumsum",
+        "fillna",
+        "first",
+        "last",
+        "map",
+        "max",
         "mean",
+        "median",
         "min",
-        "max",
-        "sum",
+        "prod",
         "quantile",
+        "reduce",
+        "sum",
         "std",
+        "sum",
         "var",
-        "count",
+        "where",
     ]
 
     if isinstance(method, str):
@@ -527,16 +550,22 @@ def band_aggregate(
     elif isinstance(method, dict):
         method_name, method_arg = list(method.items())[0]
         func = getattr(spsdl_group, method_name.lower())
-        out = func(method_arg)
+        if isinstance(method_arg, list) or isinstance(method_arg, tuple):
+            out = func(*method_arg)
+        else:
+            out = func(method_arg)
     else:
         raise ValueError(
             f"Unsupported method type: {type(method)}. "
             "Must be a string or dictionary."
         )
 
-    out.attrs.update(
-        {"units": spsdl.units, "comment": f"Third octave frequency band {method}"}
-    )
+    # Update attributes
+    out.attrs["units"] = spsdl.units
+
+    # Remove 'quantile' coordinate if present
+    if method == "quantile":
+        out = out.drop_vars("quantile")
 
     return out
 
@@ -605,16 +634,25 @@ def time_aggregate(
     # Use xarray binning methods
     spsdl_group = spsdl.groupby_bins("time", time_bins, labels=center_time)
 
-    # Apply the aggregation method
-    func = getattr(spsdl_group, method_name)
-    if method_arg is not None:
-        out = func(method_arg)
-    else:
+    # Handle method being a string or a dict
+    if isinstance(method, str):
+        func = getattr(spsdl_group, method.lower())
         out = func()
+    elif isinstance(method, dict):
+        method_name, method_arg = list(method.items())[0]
+        func = getattr(spsdl_group, method_name.lower())
+        if isinstance(method_arg, list) or isinstance(method_arg, tuple):
+            out = func(*method_arg)
+        else:
+            out = func(method_arg)
+    else:
+        raise ValueError(
+            f"Unsupported method type: {type(method)}. "
+            "Must be a string or dictionary."
+        )
 
     # Update attributes
     out.attrs["units"] = spsdl.units
-    out.attrs["comment"] = f"Time average {method}"
 
     # Remove 'quantile' coordinate if present
     if method == "quantile":
diff --git a/mhkit/acoustics/graphics.py b/mhkit/acoustics/graphics.py
index 1f9aa052..cb30f972 100644
--- a/mhkit/acoustics/graphics.py
+++ b/mhkit/acoustics/graphics.py
@@ -86,7 +86,7 @@ def plot_spectrogram(
         shading="nearest",
         **kwargs
     )
-    fig.colorbar(h, ax=ax, label=spsdl.units)
+    fig.colorbar(h, ax=ax, label=getattr(spsdl, "units", None))
     ax.set(xlabel="Time", ylabel="Frequency [Hz]")
 
     return fig, ax
@@ -147,6 +147,8 @@ def plot_spectra(
             left=0.1, right=0.95, top=0.85, bottom=0.2, hspace=0.3, wspace=0.15
         )
     ax.plot(spsdl[freq], spsdl.T, **kwargs)
-    ax.set(xlim=(fmin, fmax), xlabel="Frequency [Hz]", ylabel=spsdl.units)
+    ax.set(
+        xlim=(fmin, fmax), xlabel="Frequency [Hz]", ylabel=getattr(spsdl, "units", None)
+    )
 
     return fig, ax

From 86646022ee5f8aada1ab5f583780534fad08f5ac Mon Sep 17 00:00:00 2001
From: jmcvey3 <53623232+jmcvey3@users.noreply.github.com>
Date: Thu, 14 Nov 2024 13:03:18 -0800
Subject: [PATCH 2/4] Clarify jupyter notebook text

---
 examples/acoustics_example.ipynb | 562 +++++--------------------------
 1 file changed, 79 insertions(+), 483 deletions(-)

diff --git a/examples/acoustics_example.ipynb b/examples/acoustics_example.ipynb
index 09837f09..fe73e44c 100644
--- a/examples/acoustics_example.ipynb
+++ b/examples/acoustics_example.ipynb
@@ -42,7 +42,7 @@
     "\n",
     "The `read_hydrophone` function scales and transforms raw measurements given a few input parameters. Most parameters needed to convert the raw data are stored in the native .wav format header blocks, but two, the peak voltage (\"peak_voltage\") of the sensor's analog-to-digital converter (ADC) and file \"start_time\" (usually stored in the filename) are required. \n",
     "\n",
-    "Two other inputs, the hydrophone \"sensitivity\" and an amplifier \"gain\" (typically for custom hydrophone builds) can also be input. If a sensitivity value is provided, the function will convert voltage to pressure; otherwise the sensitivity(ies) can be provided later using a calibration curve. Gain should be provided if the instrument utilizes an amplifier gain, which is then added to the sensitivity."
+    "Two other inputs, the hydrophone sensitivity (\"sensitivity\") and an amplifier gain (\"gain\") can also be input. If a sensitivity value is provided, the function will convert voltage to pressure; otherwise the sensitivity(ies) can be provided later using a calibration curve. Gain should be provided if the instrument utilizes an amplifier gain (typically for custom hydrophone builds), which is then added to the sensitivity."
    ]
   },
   {
@@ -89,7 +89,7 @@
    "source": [
     "\"Smart\" hydrophones are those where the hydrophone element, pre-amplifier board, ADC, motherboard and memory card are sold in a single package. Companies that sell these often store metadata in the .wav file header, and MHKiT has a couple of wrapper functions for these hydrophones.\n",
     "\n",
-    "OceanSonics icListens and OceanInstruments Soundtraps are two common smart hydrophones datafiles with examples as follows.\n",
+    "OceanSonics icListen and OceanInstruments Soundtrap are two common smart hydrophone models, with examples as follows.\n",
     "\n",
     "For icListen datafiles, only the filename is necessary to provide to return file contents in units of pressure. The stored sensitivity calibration value can be overridden by setting the \"sensitivity\" input, and to return measurements in units of voltage, set `sensitivity` to None and `use_metadata` to False."
    ]
@@ -131,7 +131,7 @@
    "source": [
     "### Mean Square Sound Pressure Spectral Density\n",
     "\n",
-    "After the .wav file is read in, either in units of pressure or voltage, we calculate the mean square sound pressure spectral density (SPSD) of the timeseries using `sound_pressure_spectral_density`. This splits the timeseries into windows and uses fast Fourier transforms to convert the raw measurements into the frequency domain, with units of $Pa^2/Hz$ or $V^2/Hz$, depending on the input. The function takes the original datafile, the hydrophone's sampling rate, which is stored as an attribute of the measurement timeseries, and a window size in seconds as input.\n",
+    "After the .wav file is read in, either in units of pressure or voltage, we calculate the mean square sound pressure spectral density (SPSD) of the timeseries using `sound_pressure_spectral_density`. This splits the timeseries into windows and uses fast Fourier transforms to convert the raw measurements into the frequency domain, with units of $Pa^2/Hz$ or $V^2/Hz$, depending on the input. The function takes the original datafile, the hydrophone's sampling rate (\"fs\"), which is stored as an attribute of the measurement timeseries, and a window size (\"bin_length\") in seconds as input.\n",
     "\n",
     "The IEC-40 considers an acoustic sample to have a length of 1 second, so we'll set the bin length as such here."
    ]
@@ -154,7 +154,7 @@
     "\n",
     "For conducting scientific-grade analysis, it is critical to use calibration curves to correct the SPSD calculations. Hydrophones should be calibrated (i.e., a sensitivity calibration curve should be generated for a hydrophone) every few years. The IEC-40 asks that a hydrophone be calibrated both before and after the test deployment.\n",
     "\n",
-    "A calibration curve consists of the hydrophone's sensitivity (in units of $dB$ rel $1 V^2/uPa^2$) vs frequency and should be applied to the spectral density we just calculated.\n",
+    "A calibration curve consists of the hydrophone's sensitivity (in units of $dB$ rel $1$ $V^2/uPa^2$) vs frequency and should be applied to the spectral density we just calculated.\n",
     "\n",
     "The easiest way to apply a sensitivity calibration curve in MHKiT is to first copy the calibration data into a CSV file, where the left column contains the calibrated frequencies and the right column contains the sensitivity values. Here we use the function in the following codeblock to read in a CSV file created with the column headers \"Frequency\" and \"Analog Sensitivity\"."
    ]
@@ -204,426 +204,10 @@
    "cell_type": "code",
    "execution_count": 7,
    "metadata": {},
-   "outputs": [
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-       "  white-space: pre-wrap;\n",
-       "  word-break: break-all;\n",
-       "}\n",
-       "\n",
-       ".xr-icon-database,\n",
-       ".xr-icon-file-text2,\n",
-       ".xr-no-icon {\n",
-       "  display: inline-block;\n",
-       "  vertical-align: middle;\n",
-       "  width: 1em;\n",
-       "  height: 1.5em !important;\n",
-       "  stroke-width: 0;\n",
-       "  stroke: currentColor;\n",
-       "  fill: currentColor;\n",
-       "}\n",
-       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;Analog Sensitivity&#x27; (Frequency: 40)&gt; Size: 320B\n",
-       "array([-223.49, -220.8 , -218.13, -215.41, -212.68, -209.91, -207.12,\n",
-       "       -204.29, -201.45, -198.58, -195.69, -192.79, -189.85, -186.9 ,\n",
-       "       -183.93, -180.93, -177.92, -174.97, -172.16, -169.61, -167.69,\n",
-       "       -166.52, -165.96, -165.81, -165.85, -165.95, -166.05, -166.13,\n",
-       "       -166.2 , -166.25, -166.28, -166.29, -166.29, -166.27, -166.24,\n",
-       "       -166.17, -166.03, -165.79, -165.47, -164.87])\n",
-       "Coordinates:\n",
-       "  * Frequency  (Frequency) float64 320B 1.0 1.183 1.399 ... 500.3 591.8 700.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'Analog Sensitivity'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>Frequency</span>: 40</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-b5c0b57b-42cf-4d90-b7a2-c79988062e0d' class='xr-array-in' type='checkbox' checked><label for='section-b5c0b57b-42cf-4d90-b7a2-c79988062e0d' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>-223.5 -220.8 -218.1 -215.4 -212.7 ... -166.0 -165.8 -165.5 -164.9</span></div><div class='xr-array-data'><pre>array([-223.49, -220.8 , -218.13, -215.41, -212.68, -209.91, -207.12,\n",
-       "       -204.29, -201.45, -198.58, -195.69, -192.79, -189.85, -186.9 ,\n",
-       "       -183.93, -180.93, -177.92, -174.97, -172.16, -169.61, -167.69,\n",
-       "       -166.52, -165.96, -165.81, -165.85, -165.95, -166.05, -166.13,\n",
-       "       -166.2 , -166.25, -166.28, -166.29, -166.29, -166.27, -166.24,\n",
-       "       -166.17, -166.03, -165.79, -165.47, -164.87])</pre></div></div></li><li class='xr-section-item'><input id='section-17ea6d17-3d8b-4cdb-a2c2-06e1ad0cd939' class='xr-section-summary-in' type='checkbox'  checked><label for='section-17ea6d17-3d8b-4cdb-a2c2-06e1ad0cd939' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>Frequency</span></div><div class='xr-var-dims'>(Frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 1.183 1.399 ... 591.8 700.0</div><input id='attrs-366aa3af-24f9-4345-b6b3-b2ce1ee17056' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-366aa3af-24f9-4345-b6b3-b2ce1ee17056' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6e703b10-4c32-4f9a-b708-b60496744b10' class='xr-var-data-in' type='checkbox'><label for='data-6e703b10-4c32-4f9a-b708-b60496744b10' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  1.   ,   1.183,   1.399,   1.655,   1.958,   2.316,   2.74 ,   3.241,\n",
-       "         3.834,   4.535,   5.364,   6.345,   7.506,   8.879,  10.5  ,  12.42 ,\n",
-       "        14.7  ,  17.38 ,  20.56 ,  24.33 ,  28.78 ,  34.04 ,  40.26 ,  47.63 ,\n",
-       "        56.34 ,  66.65 ,  78.84 ,  93.26 , 110.3  , 130.5  , 154.4  , 182.6  ,\n",
-       "       216.   , 255.5  , 302.2  , 357.5  , 422.9  , 500.3  , 591.8  , 700.   ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8138cb9e-803b-49d8-b786-c7b1fb18ee70' class='xr-section-summary-in' type='checkbox'  ><label for='section-8138cb9e-803b-49d8-b786-c7b1fb18ee70' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>Frequency</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-52ca0b16-c3a3-49d1-b7a6-57eea7100c0c' class='xr-index-data-in' type='checkbox'/><label for='index-52ca0b16-c3a3-49d1-b7a6-57eea7100c0c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  1.0, 1.183, 1.399, 1.655, 1.958, 2.316,  2.74, 3.241, 3.834, 4.535,\n",
-       "       5.364, 6.345, 7.506, 8.879,  10.5, 12.42,  14.7, 17.38, 20.56, 24.33,\n",
-       "       28.78, 34.04, 40.26, 47.63, 56.34, 66.65, 78.84, 93.26, 110.3, 130.5,\n",
-       "       154.4, 182.6, 216.0, 255.5, 302.2, 357.5, 422.9, 500.3, 591.8, 700.0],\n",
-       "      dtype=&#x27;float64&#x27;, name=&#x27;Frequency&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6b900d85-7ed8-4da5-ae94-23f1cfa281f9' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6b900d85-7ed8-4da5-ae94-23f1cfa281f9' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
-      ],
-      "text/plain": [
-       "<xarray.DataArray 'Analog Sensitivity' (Frequency: 40)> Size: 320B\n",
-       "array([-223.49, -220.8 , -218.13, -215.41, -212.68, -209.91, -207.12,\n",
-       "       -204.29, -201.45, -198.58, -195.69, -192.79, -189.85, -186.9 ,\n",
-       "       -183.93, -180.93, -177.92, -174.97, -172.16, -169.61, -167.69,\n",
-       "       -166.52, -165.96, -165.81, -165.85, -165.95, -166.05, -166.13,\n",
-       "       -166.2 , -166.25, -166.28, -166.29, -166.29, -166.27, -166.24,\n",
-       "       -166.17, -166.03, -165.79, -165.47, -164.87])\n",
-       "Coordinates:\n",
-       "  * Frequency  (Frequency) float64 320B 1.0 1.183 1.399 ... 500.3 591.8 700.0"
-      ]
-     },
-     "execution_count": 7,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "sensitivity_curve"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
    "outputs": [],
    "source": [
     "# Use last value in calibration curve for higher frequencies\n",
-    "fill_Sf = sensitivity_curve[-1].values.item()\n",
+    "fill_Sf = sensitivity_curve[-1].values\n",
     "spsd = acoustics.apply_calibration(spsd, sensitivity_curve, fill_value=fill_Sf)"
    ]
   },
@@ -633,14 +217,14 @@
    "source": [
     "### Mean Square Sound Pressure Spectral Density Level\n",
     "\n",
-    "We can use the function `sound_pressure_spectral_density_level` to calculate the mean square sound pressure spectral density levels (SPSDLs) from the calibrated SPSD. This function converts absolute pressure into relative pressure in log-space, the traditional means with which we measure sound, in units of decibels relative to 1 uPa ($dB$ rel $1 uPa$), the standard for underwater sound. \n",
+    "We can use the function `sound_pressure_spectral_density_level` to calculate the mean square sound pressure spectral density levels (SPSDLs) from the calibrated SPSD. This function converts absolute pressure into relative pressure in log-space, the traditional means with which we measure sound, in units of decibels relative to 1 uPa ($dB$ rel $1$ $uPa$), the standard for underwater sound. \n",
     "    \n",
-    "Sidenote: Sound in air is measured in decibels relative to 20 uPa, the minimum pressure level humans can hear. To convert between dB rel 1 uPa and dB rel 20 uPa, one simply needs to subtract 26 dB from the dB rel 1 uPa value."
+    "Sidenote: Sound in air is measured in decibels relative to 20 uPa, the minimum sound pressure humans can hear. To convert between \"$dB$ rel $1$ $uPa$\" and \"$dB$ rel $20$ $uPa$\", one simply needs to subtract 26 dB from the \"$dB$ rel $1$ $uPa$\" value."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -653,35 +237,33 @@
    "source": [
     "Now that the SPSDL is calculated, we can create spectrograms, or waterfall plots, using the `plot_spectrogram` function in the graphics submodule. While spectrograms aren't required by the IEC-40, they are useful to do quality control so we can avoid using contaminated soundbytes in further analysis (like the boat noise shown in this one).\n",
     "\n",
-    "To do this, we'll give the function the minimum and maximum frequencies to plot, as well as keyword arguments supplied to the matplotlib pcolormesh function. For these measurements, we're setting fmin = 10 Hz, the minimum specified by the IEC-40, and fmax = 48,000 Hz, the Nyquist frequency for these data. \n",
+    "To do this, we'll give the function the minimum and maximum frequencies to plot, as well as keyword arguments supplied to the matplotlib `pcolormesh` function. For these measurements, we're setting fmin = 10 Hz, the minimum specified by the IEC-40, and fmax = 48,000 Hz, the Nyquist frequency for these data. \n",
     "\n",
     "Note, the IEC-40 requires a maximum frequency of 100,000 Hz, so a hydrophone capable of sampling faster than 200,000 Hz should be used for IEC testing."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
-     "data": {
-      "text/plain": [
-       "48000.0"
-      ]
-     },
-     "execution_count": 10,
-     "metadata": {},
-     "output_type": "execute_result"
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<xarray.DataArray 'freq' ()> Size: 8B\n",
+      "array(48000.)\n"
+     ]
     }
    ],
    "source": [
     "# Show Nyquist frequency (maximum in frequency vector)\n",
-    "spsdl[\"freq\"].max().item()"
+    "print(spsdl[\"freq\"].max())"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -720,7 +302,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -742,7 +324,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
@@ -751,13 +333,13 @@
        "Text(0.5, 1.0, 'Median and Quantile Sound Pressure Spectral Density Level')"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 600x500 with 1 Axes>"
       ]
@@ -800,7 +382,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -820,7 +402,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -829,7 +411,7 @@
        "Text(0.5, 1.0, 'Median and Quantile Sound Pressure Spectral Density Level')"
       ]
      },
-     "execution_count": 15,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -865,14 +447,14 @@
    "source": [
     "### Band Averaging\n",
     "\n",
-    "Analysis can also be completed by grouping the data into specific frequency bands, called \"band aggregating here. In other words, instead of aggregating by the time dimension, we do this in the frequency dimension. The band_aggregate function operates by taking the SPSDL and grouping it based on a specified octave.\n",
+    "Analysis can also be completed by grouping the data into specific frequency bands, called \"band aggregating\" here. In other words, instead of aggregating by the time dimension, we aggregate by the frequency dimension. The `band_aggregate` function operates by taking the SPSDL and grouping it based on a specified octave.\n",
     "\n",
-    "If one wants to do more analysis on the grouped frequency bands than the simple statistical methods that xarray offers, it is possible to use the \"map\" function to apply a custom function to a file. Ih the following block of code, we find the empirical quantile function (the empirical version of the cumulative distribution function, CDF) to each decidecade (10th octave) frequency band and plot the 160 Hz band. "
+    "If one wants to do more analysis on the grouped frequency bands than the simple statistical methods that xarray offers, it is possible to use the \"map\" function to apply a custom function to a file. In the following block of code, we find the empirical quantile function (the empirical version of the cumulative distribution function, CDF) to each decidecade (10th octave) frequency band and plot the 160 Hz band. "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
@@ -891,7 +473,7 @@
        " Text(0.5, 0, 'Decidecade SPSDL [dB re 1 uPa^2/Hz]')]"
       ]
      },
-     "execution_count": 16,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -907,7 +489,7 @@
     }
    ],
    "source": [
-    "def cdf(x):\n",
+    "def quantile_function(x):\n",
     "    # Empirical CDF/Quantile Function/Exceedance Probability\n",
     "    # Use the median of the coordinate we're grouped in\n",
     "    x = x.median(\"freq\")\n",
@@ -922,7 +504,7 @@
     "    return x\n",
     "\n",
     "\n",
-    "cdfs = acoustics.band_aggregate(spsdl, octave=10, method={\"map\": cdf})\n",
+    "cdfs = acoustics.band_aggregate(spsdl, octave=10, method={\"map\": quantile_function})\n",
     "# Plot\n",
     "fig, ax = plt.subplots(figsize=(4, 4))\n",
     "ax.plot(cdfs[40].values, cdfs[\"probability\"].values)\n",
@@ -944,7 +526,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
@@ -958,12 +540,12 @@
     {
      "data": {
       "text/plain": [
-       "[[<matplotlib.axis.XTick at 0x1c000041f90>,\n",
-       "  <matplotlib.axis.XTick at 0x1c00007d410>,\n",
-       "  <matplotlib.axis.XTick at 0x1c033af9a10>,\n",
-       "  <matplotlib.axis.XTick at 0x1c002c2b290>,\n",
-       "  <matplotlib.axis.XTick at 0x1c000be4e50>,\n",
-       "  <matplotlib.axis.XTick at 0x1c002b19350>],\n",
+       "[[<matplotlib.axis.XTick at 0x20703772990>,\n",
+       "  <matplotlib.axis.XTick at 0x207037a05d0>,\n",
+       "  <matplotlib.axis.XTick at 0x2070694f490>,\n",
+       "  <matplotlib.axis.XTick at 0x20704e02690>,\n",
+       "  <matplotlib.axis.XTick at 0x20704de5750>,\n",
+       "  <matplotlib.axis.XTick at 0x20704e1db90>],\n",
        " [Text(0.0, 0, '0'),\n",
        "  Text(1.0, 0, '1'),\n",
        "  Text(2.0, 0, '2'),\n",
@@ -976,7 +558,7 @@
        " Text(0, 0.5, 'Decidecade SPSDL [dB re 1 uPa^2/Hz]')]"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -1038,7 +620,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
@@ -1078,20 +660,35 @@
     "#### Flow Noise\n",
     "Flow noise, or psuedo-sound, is the other reason to increase the minimum frequency of our SPL measurements. Flow noise is caused by one of three things: turbulence advected past the hydrophone element, turbulence caused by the hydrophone element, and the sensitivity of the hydrophone element to temperature inhomogeneities in the advected flow. Flow noise is most noticeably apparent when flow speeds increase above 0.5 m/s, seen in spectrograms as a logarithmic increase in pressure with decreasing frequency.\n",
     "\n",
+    "#### Cumulative SPL\n",
+    "\n",
     "The particular data shown here was measured in around 8-10 m of water, and a mix of mild flow noise below 20 Hz and low frequency attenutation below ~50 Hz can be seen in the spectrogram. We'll again use the Nyquist frequency of 48,000 Hz."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "spl_median: 86.02\n"
-     ]
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x20706250fd0>]"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     }
    ],
    "source": [
@@ -1100,15 +697,14 @@
     "fmax = 48000\n",
     "\n",
     "spl = acoustics.sound_pressure_level(spsd, fmin, fmax)\n",
-    "spl_q50 = acoustics.time_aggregate(spl, window, method=\"median\")\n",
-    "print(f\"spl_median: {spl_q50[0].values:0.2f}\")"
+    "spl.plot()"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "So our median SPL for this overall frequency band is 98.5 dB rel 1 uPa."
+    "So we can see our cumulative SPL start out at 86 dB and then peak at 120 dB as the boat drives by. If you haven't listened to the audio track, this peak SPL of 125 dB rel 1 uPa (underwater) is equivalent to 99 dB rel 20 uPa (air). For reference, the OSHA time limit for workers experiencing 100 dB rel 20 uPa of sound is 2 hours. Vessel traffic quite loud and is the largest contributor to noise in the marine environment."
    ]
   },
   {
@@ -1126,18 +722,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "[[<matplotlib.axis.XTick at 0x1c002c72b50>,\n",
-       "  <matplotlib.axis.XTick at 0x1c00012a410>,\n",
-       "  <matplotlib.axis.XTick at 0x1c0254651d0>,\n",
-       "  <matplotlib.axis.XTick at 0x1c000130110>,\n",
-       "  <matplotlib.axis.XTick at 0x1c025647690>,\n",
-       "  <matplotlib.axis.XTick at 0x1c025655950>],\n",
+       "[[<matplotlib.axis.XTick at 0x20709d51dd0>,\n",
+       "  <matplotlib.axis.XTick at 0x20709da66d0>,\n",
+       "  <matplotlib.axis.XTick at 0x2070aef2b90>,\n",
+       "  <matplotlib.axis.XTick at 0x2070af30b50>,\n",
+       "  <matplotlib.axis.XTick at 0x20704d97690>,\n",
+       "  <matplotlib.axis.XTick at 0x20709e04a10>],\n",
        " [Text(0.0, 0, '0'),\n",
        "  Text(1.0, 0, '1'),\n",
        "  Text(2.0, 0, '2'),\n",
@@ -1150,7 +746,7 @@
        " Text(0, 0.5, 'Decidecade SPL [dB re 1 uPa]')]"
       ]
      },
-     "execution_count": 20,
+     "execution_count": 19,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -1201,18 +797,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "[[<matplotlib.axis.XTick at 0x1c025724590>,\n",
-       "  <matplotlib.axis.XTick at 0x1c000165250>,\n",
-       "  <matplotlib.axis.XTick at 0x1c034138990>,\n",
-       "  <matplotlib.axis.XTick at 0x1c025730110>,\n",
-       "  <matplotlib.axis.XTick at 0x1c0341c1390>,\n",
-       "  <matplotlib.axis.XTick at 0x1c0341c3350>],\n",
+       "[[<matplotlib.axis.XTick at 0x2070b2aa190>,\n",
+       "  <matplotlib.axis.XTick at 0x2070b04c650>,\n",
+       "  <matplotlib.axis.XTick at 0x2070bb42e10>,\n",
+       "  <matplotlib.axis.XTick at 0x20709a48150>,\n",
+       "  <matplotlib.axis.XTick at 0x2070bb4e350>,\n",
+       "  <matplotlib.axis.XTick at 0x2070b1743d0>],\n",
        " [Text(0.0, 0, '0'),\n",
        "  Text(1.0, 0, '1'),\n",
        "  Text(2.0, 0, '2'),\n",
@@ -1225,7 +821,7 @@
        " Text(0, 0.5, 'Decidecade SPL [dB re 1 uPa]')]"
       ]
      },
-     "execution_count": 21,
+     "execution_count": 20,
      "metadata": {},
      "output_type": "execute_result"
     },

From ba7617e3ad1e8b4f5018024ef04a8180ea581659 Mon Sep 17 00:00:00 2001
From: jmcvey3 <53623232+jmcvey3@users.noreply.github.com>
Date: Thu, 14 Nov 2024 13:34:46 -0800
Subject: [PATCH 3/4] Pylint complaints

---
 mhkit/acoustics/analysis.py | 38 ++++++++++++-------------------------
 1 file changed, 12 insertions(+), 26 deletions(-)

diff --git a/mhkit/acoustics/analysis.py b/mhkit/acoustics/analysis.py
index bea1058a..fc1d613f 100644
--- a/mhkit/acoustics/analysis.py
+++ b/mhkit/acoustics/analysis.py
@@ -501,24 +501,20 @@ def band_aggregate(
     # Type checks
     if not isinstance(spsdl, xr.DataArray):
         raise TypeError("'spsdl' must be an xarray.DataArray.")
-    if not isinstance(octave, int):
-        raise TypeError("'octave' must be an integer.")
-    if not isinstance(fmin, int):
-        raise TypeError("'fmin' must be an integer.")
-    if not isinstance(fmax, int):
-        raise TypeError("'fmax' must be an integer.")
+    if not isinstance(octave, int) or (octave <= 0):
+        raise TypeError("'octave' must be a positive integer.")
+    if not isinstance(fmin, int) or (fmin <= 0):
+        raise TypeError("'fmin' must be a positive integer.")
+    if not isinstance(fmax, int) or (fmin <= 0):
+        raise TypeError("'fmax' must be a positive integer.")
+    if fmax <= fmin:
+        raise ValueError("'fmax' must be greater than 'fmin'.")
     if not isinstance(method, (str, dict)):
         raise TypeError("'method' must be a string or a dictionary.")
 
     # Value checks
-    if "freq" not in spsdl.dims or "time" not in spsdl.dims:
+    if ("freq" not in spsdl.dims) or ("time" not in spsdl.dims):
         raise ValueError("'spsdl' must have 'time' and 'freq' as dimensions.")
-    if octave <= 0:
-        raise ValueError("'octave' must be a positive integer.")
-    if fmin <= 0:
-        raise ValueError("'fmin' must be a positive integer.")
-    if fmax <= fmin:
-        raise ValueError("'fmax' must be greater than 'fmin'.")
 
     # Validate method and get method_name and method_arg
     method_name, method_arg = _validate_method(method)
@@ -550,15 +546,10 @@ def band_aggregate(
     elif isinstance(method, dict):
         method_name, method_arg = list(method.items())[0]
         func = getattr(spsdl_group, method_name.lower())
-        if isinstance(method_arg, list) or isinstance(method_arg, tuple):
+        if isinstance(method_arg, (list, tuple)):
             out = func(*method_arg)
         else:
             out = func(method_arg)
-    else:
-        raise ValueError(
-            f"Unsupported method type: {type(method)}. "
-            "Must be a string or dictionary."
-        )
 
     # Update attributes
     out.attrs["units"] = spsdl.units
@@ -641,15 +632,10 @@ def time_aggregate(
     elif isinstance(method, dict):
         method_name, method_arg = list(method.items())[0]
         func = getattr(spsdl_group, method_name.lower())
-        if isinstance(method_arg, list) or isinstance(method_arg, tuple):
+        if isinstance(method_arg, (list, tuple)):
             out = func(*method_arg)
         else:
             out = func(method_arg)
-    else:
-        raise ValueError(
-            f"Unsupported method type: {type(method)}. "
-            "Must be a string or dictionary."
-        )
 
     # Update attributes
     out.attrs["units"] = spsdl.units
@@ -692,7 +678,7 @@ def sound_pressure_level(
         raise TypeError("'fmax' must be an integer.")
 
     # Ensure 'freq' and 'time' dimensions are present
-    if "freq" not in spsd.dims or "time" not in spsd.dims:
+    if ("freq" not in spsd.dims) or ("time" not in spsd.dims):
         raise ValueError("'spsd' must have 'time' and 'freq' as dimensions.")
 
     # Check that 'fs' (sampling frequency) is available in attributes

From bda330a8a332317d1579ec433155de59b122bda4 Mon Sep 17 00:00:00 2001
From: jmcvey3 <53623232+jmcvey3@users.noreply.github.com>
Date: Thu, 14 Nov 2024 14:05:30 -0800
Subject: [PATCH 4/4] Will fail anyway if not a dict

---
 mhkit/acoustics/analysis.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/mhkit/acoustics/analysis.py b/mhkit/acoustics/analysis.py
index fc1d613f..66099b32 100644
--- a/mhkit/acoustics/analysis.py
+++ b/mhkit/acoustics/analysis.py
@@ -543,7 +543,7 @@ def band_aggregate(
     if isinstance(method, str):
         func = getattr(spsdl_group, method.lower())
         out = func()
-    elif isinstance(method, dict):
+    else:
         method_name, method_arg = list(method.items())[0]
         func = getattr(spsdl_group, method_name.lower())
         if isinstance(method_arg, (list, tuple)):
@@ -629,7 +629,7 @@ def time_aggregate(
     if isinstance(method, str):
         func = getattr(spsdl_group, method.lower())
         out = func()
-    elif isinstance(method, dict):
+    else:
         method_name, method_arg = list(method.items())[0]
         func = getattr(spsdl_group, method_name.lower())
         if isinstance(method_arg, (list, tuple)):