diff --git a/examples/WPTO_hindcast_example.ipynb b/examples/WPTO_hindcast_example.ipynb index 75b5c914f..99d6fa33e 100644 --- a/examples/WPTO_hindcast_example.ipynb +++ b/examples/WPTO_hindcast_example.ipynb @@ -6,7 +6,9 @@ "source": [ "# MHKiT WPTO Hindcast Example\n", "\n", - "This example loads data from the [WPTO hindcast data set](https://registry.opendata.aws/wpto-pds-us-wave/), hosted on AWS. \n", + "This example loads data from the [WPTO hindcast data set](https://registry.opendata.aws/wpto-pds-us-wave/), hosted on AWS. \n", + "\n", + "Note: Some of the plotting functionality shown in this notebook will only work in Jupyter-notebook. Jupyter-Lab and VSCode may not work. \n", "\n", "## Dataset Description\n", "\n", @@ -15,7 +17,7 @@ "The 'virtual buoy dataset' (hereafter the *'1-hour' dataset*) is also available at specific locations within the large spatial domain. These virtual buoys span the same 32-years of the spatial dataset however the time resolution is 1-hour.\n", "\n", "### Included 3-hour Variables: \n", - "- Dataset variables included are indexed by **'coordinates'** (latitude and longitude), and a **'time_index'**\n", + "- Dataset variables included are indexed by **'coordinates'** (latitude and longitude), and a **'time_index'**. These variables can be accessed through the `request_wpto_point_data` function. \n", "\n", "| Variable Name | Units |\n", "| :------------ | :---: |\n", @@ -40,6 +42,11 @@ "| mean_wave_direction | degrees_true |\n", "| frequency_bin_edges | Hz |\n", "\n", + "These variables can be accessed through the `request_wpto_point_data` function.\n", + "\n", + "### Directional Wave Spectra\n", + "- The 1-hour data also contains directional wave spectra which can be accessed one year at time throught the `request_wpto_directional_spectrum` function. \n", + "\n", "\n", "\n", "### Setting up Access to WPTO Hindcast Data\n", @@ -58,7 +65,7 @@ " hs_api_key = {your key}\n", "\n", " \n", - "## Using the WPTO Hindcast MHKiT Function\n", + "## Using the WPTO Hindcast MHKiT Functions\n", "\n", "In this section we will walk through an example to request hindcast data at a point using MHKiT. To start we will import the MHKiT wave module." ] @@ -76,14 +83,41 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### 1. Download WPTO Hindcast Data from a Single Location\n", + "### 1. Check if Lat/Lon pair is in WPTO Hindcast Dataset\n", + "You can check to see if your desired data location is included in the WPTO Hindcast dataset using the `region_selection` function. If a valid lat/lon pair is passed, the name of the hindcast region is passed back, otherwise a message indicating that the pair is out or range is printed to the screen. " + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "West_Coast\n" + ] + } + ], + "source": [ + "lat_lon = [44.624076,-124.280097]\n", + "region = wave.io.hindcast.region_selection(lat_lon)\n", + "print(region)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 2. Download WPTO Hindcast Data from a Single Location\n", "\n", "In this example we will request 3-hour significant wave height for 1995 at the point (44.624076,-124.280097, near the PacWave site). We will speficy each of these as a variable and pass them to the wave IO hindacast function `request_wpto_dataset`. The data type will be a high-spatial-resolution dataset, year(s) will be 1995, latitude/longitude pairs will be for a point near PacWave, and the parameter will be significant wave height." ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -105,7 +139,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "metadata": {}, "outputs": [ { @@ -159,7 +193,7 @@ "0 Federal " ] }, - "execution_count": 3, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -174,12 +208,12 @@ "source": [ "#### Hindacast Data Returned \n", "\n", - "We can also take a look at the first 5 rows of the returned data by call the `head()` method on the returned data. By calling this below we can see that the returned data has a time index and a single column of significant wave height. The siginifcant wave height column has a 0 integer on the end of it reffering to the index in the metadata. In out next example the importance of this integer will become more clear as we begin to request multiple locations." + "We can also take a look at the first 5 rows of the returned data by call the `head()` method on the returned data. By calling this below we can see that the returned data has a time index and a single column of significant wave height. The siginifcant wave height column has a 0 integer on the end of it refering to the index in the metadata. In out next example the importance of this integer will become more clear as we begin to request multiple locations." ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "metadata": {}, "outputs": [ { @@ -245,7 +279,7 @@ "1995-01-01 12:00:00+00:00 2.66992" ] }, - "execution_count": 4, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } @@ -258,14 +292,14 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## 2. Download WPTO Hindcast Data from Multiple Locations\n", + "### 3. Download WPTO Hindcast Data from Multiple Locations\n", "\n", "Multiple locations can be requested by passing a list or tuple of lat/lon pairs. This time we will request the 3-hour energy period at two points. The data type and years requested remanin the same as before. By looking at the `head` of the returned DataFrame we can see that this time two energy periods are returned. The integers on each of the energy periods refer to the index in the metadata. This allows the user to connect the quantities of interest and the metadata fro each point." ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -338,7 +372,7 @@ "1995-01-01 12:00:00+00:00 10.6579 10.5877" ] }, - "execution_count": 5, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -356,7 +390,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "metadata": {}, "outputs": [ { @@ -421,7 +455,7 @@ "1 Federal " ] }, - "execution_count": 6, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -434,15 +468,17 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## 3. Download WPTO Hindcast Data from Multiple Years\n", + "### 4. Download WPTO Hindcast Data from Multiple Years\n", "\n", "Multiple years can be requested simply by adding years to the passed list. Recall the hindcast data spans 01/01/1979 - 12/31/2010. A demonstration of requesting multiple years of 3-hour data for a single point is shown below. By looking at the the returned data we can see that the data is returned in the order of the years passed to the function. " ] }, { "cell_type": "code", - "execution_count": 7, - "metadata": {}, + "execution_count": 8, + "metadata": { + "scrolled": true + }, "outputs": [ { "data": { @@ -540,7 +576,7 @@ "[5848 rows x 1 columns]" ] }, - "execution_count": 7, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -557,7 +593,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "metadata": {}, "outputs": [ { @@ -611,7 +647,7 @@ "0 Federal " ] }, - "execution_count": 8, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -624,22 +660,22 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## 4. Download 1-hour data\n", - "1-hour temporal resolutions data can be requested by passing '1-hour' as the data_type. An example for requesting this higer temporal data is below. " + "### 5. Download 1-hour data\n", + "1-hour temporal resolutions data can be requested by passing '1-hour' as the data_type. An example for requesting this higher temporal data is below. " ] }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "data_type = '1-hour' # Setting the data_type to 1 hour data\n", "years = [1995] \n", - "parameter = 'omni-directional_wave_power'\n", + "parameter = ['significant_wave_height','peak_period','mean_wave_direction']\n", "lat_lon = (44.624076,-124.280097) \n", "\n", - "J, metadata= wave.io.hindcast.request_wpto_point_data(data_type,parameter,lat_lon,years) " + "data, metadata= wave.io.hindcast.request_wpto_point_data(data_type,parameter,lat_lon,years) " ] }, { @@ -651,7 +687,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 11, "metadata": {}, "outputs": [ { @@ -675,66 +711,1243 @@ " \n", " \n", " \n", - " omni-directional_wave_power_0\n", + " significant_wave_height_0\n", + " peak_period_0\n", + " mean_wave_direction_0\n", " \n", " \n", " time_index\n", " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " 1995-01-01 00:00:00+00:00\n", - " 33531.0\n", - " \n", - " \n", " 1995-01-01 01:00:00+00:00\n", - " 33828.0\n", + " 2.484366\n", + " 14.662757\n", + " 15.084534\n", " \n", " \n", " 1995-01-01 02:00:00+00:00\n", - " 34563.0\n", + " 2.630712\n", + " 14.662757\n", + " 25.247620\n", " \n", " \n", " 1995-01-01 03:00:00+00:00\n", - " 35494.0\n", + " 2.593185\n", + " 14.662757\n", + " 26.125366\n", " \n", " \n", " 1995-01-01 04:00:00+00:00\n", - " 36117.0\n", + " 2.563252\n", + " 14.662757\n", + " 26.771942\n", + " \n", + " \n", + " 1995-01-01 05:00:00+00:00\n", + " 2.534683\n", + " 14.662757\n", + " 27.553558\n", " \n", " \n", "\n", "" ], "text/plain": [ - " omni-directional_wave_power_0\n", - "time_index \n", - "1995-01-01 00:00:00+00:00 33531.0\n", - "1995-01-01 01:00:00+00:00 33828.0\n", - "1995-01-01 02:00:00+00:00 34563.0\n", - "1995-01-01 03:00:00+00:00 35494.0\n", - "1995-01-01 04:00:00+00:00 36117.0" + " significant_wave_height_0 peak_period_0 \\\n", + "time_index \n", + "1995-01-01 01:00:00+00:00 2.484366 14.662757 \n", + "1995-01-01 02:00:00+00:00 2.630712 14.662757 \n", + "1995-01-01 03:00:00+00:00 2.593185 14.662757 \n", + "1995-01-01 04:00:00+00:00 2.563252 14.662757 \n", + "1995-01-01 05:00:00+00:00 2.534683 14.662757 \n", + "\n", + " mean_wave_direction_0 \n", + "time_index \n", + "1995-01-01 01:00:00+00:00 15.084534 \n", + "1995-01-01 02:00:00+00:00 25.247620 \n", + "1995-01-01 03:00:00+00:00 26.125366 \n", + "1995-01-01 04:00:00+00:00 26.771942 \n", + "1995-01-01 05:00:00+00:00 27.553558 " ] }, - "execution_count": 10, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "J.head()" + "data.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 6. Calculate a Directional JPD\n", + "Using numpy, we can calculate a directional JPD using the 1-hour data requested above. " ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "metadata": {}, "outputs": [], + "source": [ + "from numpy import histogramdd, array, arange, mean\n", + "\n", + "# Generate bins for Hm0, Te and Direction\n", + "Hm0_bins = arange(0, data.significant_wave_height_0.values.max() + 0.5, 0.5) \n", + "Te_bins = arange(0, data.peak_period_0.values.max() + 1, 1)\n", + "Dir_bins = arange(0, data.mean_wave_direction_0.values.max() + 10, 10)\n", + "\n", + "# Combine data for better handling\n", + "jpd_3d = array([\n", + " data.significant_wave_height_0.values.flatten(),\n", + " data.peak_period_0.values.flatten(),\n", + " data.mean_wave_direction_0.values.flatten()\n", + " ]).T\n", + "\n", + "# Calculate the bin centers of the data\n", + "Hm0_center = array([\n", + " mean([Hm0_bins[i+1],Hm0_bins[i]]) \n", + " for i in range(Hm0_bins.shape[0]-1)\n", + " ])\n", + "Te_center = array([\n", + " mean([Te_bins[i+1],Te_bins[i]]) \n", + " for i in range(Te_bins.shape[0]-1)\n", + " ])\n", + "Dir_center = array([\n", + " mean([Dir_bins[i+1],Dir_bins[i]]) \n", + " for i in range(Dir_bins.shape[0]-1)\n", + " ])\n", + "\n", + "\n", + "# Calculate the JPD for Hm0, Te, and Dir \n", + "probability, edges = histogramdd(jpd_3d,bins=[Hm0_bins,Te_bins,Dir_bins],density=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can then plot the directional JPD using matplotlib. Click along the slider below the \n", + "plot to view the JPD for each incoming wave direction. " + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "application/javascript": [ + "/* Put everything inside the global mpl namespace */\n", + "/* global mpl */\n", + "window.mpl = {};\n", + "\n", + "mpl.get_websocket_type = function () {\n", + " if (typeof WebSocket !== 'undefined') {\n", + " return WebSocket;\n", + " } else if (typeof MozWebSocket !== 'undefined') {\n", + " return MozWebSocket;\n", + " } else {\n", + " alert(\n", + " 'Your browser does not have WebSocket support. ' +\n", + " 'Please try Chrome, Safari or Firefox ≥ 6. 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rubberband_canvas.addEventListener(\n", + " 'mousemove',\n", + " on_mouse_event_closure('motion_notify')\n", + " );\n", + "\n", + " rubberband_canvas.addEventListener(\n", + " 'mouseenter',\n", + " on_mouse_event_closure('figure_enter')\n", + " );\n", + " rubberband_canvas.addEventListener(\n", + " 'mouseleave',\n", + " on_mouse_event_closure('figure_leave')\n", + " );\n", + "\n", + " canvas_div.addEventListener('wheel', function (event) {\n", + " if (event.deltaY < 0) {\n", + " event.step = 1;\n", + " } else {\n", + " event.step = -1;\n", + " }\n", + " on_mouse_event_closure('scroll')(event);\n", + " });\n", + "\n", + " canvas_div.appendChild(canvas);\n", + " canvas_div.appendChild(rubberband_canvas);\n", + "\n", + " this.rubberband_context = rubberband_canvas.getContext('2d');\n", + " this.rubberband_context.strokeStyle = '#000000';\n", + "\n", + " this._resize_canvas = function (width, height, forward) {\n", + " if (forward) {\n", + " canvas_div.style.width = width + 'px';\n", + " canvas_div.style.height = height + 'px';\n", + " }\n", + " };\n", + "\n", + " // Disable right mouse context menu.\n", + " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", + " event.preventDefault();\n", + " return false;\n", + " });\n", + "\n", + " function set_focus() {\n", + " canvas.focus();\n", + " canvas_div.focus();\n", + " }\n", + "\n", + " window.setTimeout(set_focus, 100);\n", + "};\n", + "\n", + "mpl.figure.prototype._init_toolbar = function () {\n", + " var fig = this;\n", + "\n", + " var toolbar = document.createElement('div');\n", + " toolbar.classList = 'mpl-toolbar';\n", + " this.root.appendChild(toolbar);\n", + "\n", + " function on_click_closure(name) {\n", + " return function (_event) {\n", + " return fig.toolbar_button_onclick(name);\n", + " };\n", + " }\n", + "\n", + " function on_mouseover_closure(tooltip) {\n", + " return function (event) {\n", + " if (!event.currentTarget.disabled) {\n", + " return fig.toolbar_button_onmouseover(tooltip);\n", + " }\n", + " };\n", + " }\n", + "\n", + " fig.buttons = {};\n", + " var buttonGroup = document.createElement('div');\n", + " buttonGroup.classList = 'mpl-button-group';\n", + " for (var toolbar_ind in mpl.toolbar_items) {\n", + " var name = mpl.toolbar_items[toolbar_ind][0];\n", + " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", + " var image = mpl.toolbar_items[toolbar_ind][2];\n", + " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", + "\n", + " if (!name) {\n", + " /* Instead of a spacer, we start a new button group. */\n", + " if (buttonGroup.hasChildNodes()) {\n", + " toolbar.appendChild(buttonGroup);\n", + " }\n", + " buttonGroup = document.createElement('div');\n", + " buttonGroup.classList = 'mpl-button-group';\n", + " continue;\n", + " }\n", + "\n", + " var button = (fig.buttons[name] = document.createElement('button'));\n", + " button.classList = 'mpl-widget';\n", + " button.setAttribute('role', 'button');\n", + " button.setAttribute('aria-disabled', 'false');\n", + " button.addEventListener('click', on_click_closure(method_name));\n", + " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", + "\n", + " var icon_img = document.createElement('img');\n", + " icon_img.src = '_images/' + image + '.png';\n", + " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", + " icon_img.alt = tooltip;\n", + " button.appendChild(icon_img);\n", + "\n", + " buttonGroup.appendChild(button);\n", + " }\n", + "\n", + " if (buttonGroup.hasChildNodes()) {\n", + " toolbar.appendChild(buttonGroup);\n", + " }\n", + "\n", + " var fmt_picker = document.createElement('select');\n", + " fmt_picker.classList = 'mpl-widget';\n", + " toolbar.appendChild(fmt_picker);\n", + " this.format_dropdown = fmt_picker;\n", + "\n", + " for (var ind in mpl.extensions) {\n", + " var fmt = mpl.extensions[ind];\n", + " var option = document.createElement('option');\n", + " option.selected = fmt === mpl.default_extension;\n", + " option.innerHTML = fmt;\n", + " fmt_picker.appendChild(option);\n", + " }\n", + "\n", + " var status_bar = document.createElement('span');\n", + " status_bar.classList = 'mpl-message';\n", + " toolbar.appendChild(status_bar);\n", + " this.message = status_bar;\n", + "};\n", + "\n", + "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", + " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", + " // which will in turn request a refresh of the image.\n", + " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", + "};\n", + "\n", + "mpl.figure.prototype.send_message = function (type, properties) {\n", + " properties['type'] = type;\n", + " properties['figure_id'] = this.id;\n", + " this.ws.send(JSON.stringify(properties));\n", + "};\n", + "\n", + "mpl.figure.prototype.send_draw_message = function () {\n", + " if (!this.waiting) {\n", + " this.waiting = true;\n", + " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", + " }\n", + "};\n", + "\n", + "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", + " var format_dropdown = fig.format_dropdown;\n", + " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", + " fig.ondownload(fig, format);\n", + "};\n", + "\n", + "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", + " var size = msg['size'];\n", + " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", + " fig._resize_canvas(size[0], size[1], msg['forward']);\n", + " fig.send_message('refresh', {});\n", + " }\n", + "};\n", + "\n", + "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", + " var x0 = msg['x0'] / fig.ratio;\n", + " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", + " var x1 = msg['x1'] / fig.ratio;\n", + " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", + " x0 = Math.floor(x0) + 0.5;\n", + " y0 = Math.floor(y0) + 0.5;\n", + " x1 = Math.floor(x1) + 0.5;\n", + " y1 = Math.floor(y1) + 0.5;\n", + " var min_x = Math.min(x0, x1);\n", + " var min_y = Math.min(y0, y1);\n", + " var width = Math.abs(x1 - x0);\n", + " var height = Math.abs(y1 - y0);\n", + "\n", + " fig.rubberband_context.clearRect(\n", + " 0,\n", + " 0,\n", + " fig.canvas.width / fig.ratio,\n", + " fig.canvas.height / fig.ratio\n", + " );\n", + "\n", + " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", + "};\n", + "\n", + "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", + " // Updates the figure title.\n", + " fig.header.textContent = msg['label'];\n", + "};\n", + "\n", + "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", + " var cursor = msg['cursor'];\n", + " switch (cursor) {\n", + " case 0:\n", + " cursor = 'pointer';\n", + " break;\n", + " case 1:\n", + " cursor = 'default';\n", + " break;\n", + " case 2:\n", + " cursor = 'crosshair';\n", + " break;\n", + " case 3:\n", + " cursor = 'move';\n", + " break;\n", + " }\n", + " fig.rubberband_canvas.style.cursor = cursor;\n", + "};\n", + "\n", + "mpl.figure.prototype.handle_message = function (fig, msg) {\n", + " fig.message.textContent = msg['message'];\n", + "};\n", + "\n", + "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", + " // Request the server to send over a new figure.\n", + " fig.send_draw_message();\n", + "};\n", + "\n", + "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", + " fig.image_mode = msg['mode'];\n", + "};\n", + "\n", + "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", + " for (var key in msg) {\n", + " if (!(key in fig.buttons)) {\n", + " continue;\n", + " }\n", + " fig.buttons[key].disabled = !msg[key];\n", + " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", + " }\n", + "};\n", + "\n", + "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", + " if (msg['mode'] === 'PAN') {\n", + " fig.buttons['Pan'].classList.add('active');\n", + " fig.buttons['Zoom'].classList.remove('active');\n", + " } else if (msg['mode'] === 'ZOOM') {\n", + " fig.buttons['Pan'].classList.remove('active');\n", + " fig.buttons['Zoom'].classList.add('active');\n", + " } else {\n", + " fig.buttons['Pan'].classList.remove('active');\n", + " fig.buttons['Zoom'].classList.remove('active');\n", + " }\n", + "};\n", + "\n", + "mpl.figure.prototype.updated_canvas_event = function () {\n", + " // Called whenever the canvas gets updated.\n", + " this.send_message('ack', {});\n", + "};\n", + "\n", + "// A function to construct a web socket function for onmessage handling.\n", + "// Called in the figure constructor.\n", + "mpl.figure.prototype._make_on_message_function = function (fig) {\n", + " return function socket_on_message(evt) {\n", + " if (evt.data instanceof Blob) {\n", + " var img = evt.data;\n", + " if (img.type !== 'image/png') {\n", + " /* FIXME: We get \"Resource interpreted as Image but\n", + " * transferred with MIME type text/plain:\" errors on\n", + " * Chrome. But how to set the MIME type? It doesn't seem\n", + " * to be part of the websocket stream */\n", + " img.type = 'image/png';\n", + " }\n", + "\n", + " /* Free the memory for the previous frames */\n", + " if (fig.imageObj.src) {\n", + " (window.URL || window.webkitURL).revokeObjectURL(\n", + " fig.imageObj.src\n", + " );\n", + " }\n", + "\n", + " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", + " img\n", + " );\n", + " fig.updated_canvas_event();\n", + " fig.waiting = false;\n", + " return;\n", + " } else if (\n", + " typeof evt.data === 'string' &&\n", + " evt.data.slice(0, 21) === 'data:image/png;base64'\n", + " ) {\n", + " fig.imageObj.src = evt.data;\n", + " fig.updated_canvas_event();\n", + " fig.waiting = false;\n", + " return;\n", + " }\n", + "\n", + " var msg = JSON.parse(evt.data);\n", + " var msg_type = msg['type'];\n", + "\n", + " // Call the \"handle_{type}\" callback, which takes\n", + " // the figure and JSON message as its only arguments.\n", + " try {\n", + " var callback = fig['handle_' + msg_type];\n", + " } catch (e) {\n", + " console.log(\n", + " \"No handler for the '\" + msg_type + \"' message type: \",\n", + " msg\n", + " );\n", + " return;\n", + " }\n", + "\n", + " if (callback) {\n", + " try {\n", + " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", + " callback(fig, msg);\n", + " } catch (e) {\n", + " console.log(\n", + " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", + " e,\n", + " e.stack,\n", + " msg\n", + " );\n", + " }\n", + " }\n", + " };\n", + "};\n", + "\n", + "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", + "mpl.findpos = function (e) {\n", + " //this section is from http://www.quirksmode.org/js/events_properties.html\n", + " var targ;\n", + " if (!e) {\n", + " e = window.event;\n", + " }\n", + " if (e.target) {\n", + " targ = e.target;\n", + " } else if (e.srcElement) {\n", + " targ = e.srcElement;\n", + " }\n", + " if (targ.nodeType === 3) {\n", + " // defeat Safari bug\n", + " targ = targ.parentNode;\n", + " }\n", + "\n", + " // pageX,Y are the mouse positions relative to the document\n", + " var boundingRect = targ.getBoundingClientRect();\n", + " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", + " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", + "\n", + " return { x: x, y: y };\n", + "};\n", + "\n", + "/*\n", + " * return a copy of an object with only non-object keys\n", + " * we need this to avoid circular references\n", + " * http://stackoverflow.com/a/24161582/3208463\n", + " */\n", + "function simpleKeys(original) {\n", + " return Object.keys(original).reduce(function (obj, key) {\n", + " if (typeof original[key] !== 'object') {\n", + " obj[key] = original[key];\n", + " }\n", + " return obj;\n", + " }, {});\n", + "}\n", + "\n", + "mpl.figure.prototype.mouse_event = function (event, name) {\n", + " var canvas_pos = mpl.findpos(event);\n", + "\n", + " if (name === 'button_press') {\n", + " this.canvas.focus();\n", + " this.canvas_div.focus();\n", + " }\n", + "\n", + " var x = canvas_pos.x * this.ratio;\n", + " var y = canvas_pos.y * this.ratio;\n", + "\n", + " this.send_message(name, {\n", + " x: x,\n", + " y: y,\n", + " button: event.button,\n", + " step: event.step,\n", + " guiEvent: simpleKeys(event),\n", + " });\n", + "\n", + " /* This prevents the web browser from automatically changing to\n", + " * the text insertion cursor when the button is pressed. We want\n", + " * to control all of the cursor setting manually through the\n", + " * 'cursor' event from matplotlib */\n", + " event.preventDefault();\n", + " return false;\n", + "};\n", + "\n", + "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", + " // Handle any extra behaviour associated with a key event\n", + "};\n", + "\n", + "mpl.figure.prototype.key_event = function (event, name) {\n", + " // Prevent repeat events\n", + " if (name === 'key_press') {\n", + " if (event.key === this._key) {\n", + " return;\n", + " } else {\n", + " this._key = event.key;\n", + " }\n", + " }\n", + " if (name === 'key_release') {\n", + " this._key = null;\n", + " }\n", + "\n", + " var value = '';\n", + " if (event.ctrlKey && event.key !== 'Control') {\n", + " value += 'ctrl+';\n", + " }\n", + " else if (event.altKey && event.key !== 'Alt') {\n", + " value += 'alt+';\n", + " }\n", + " else if (event.shiftKey && event.key !== 'Shift') {\n", + " value += 'shift+';\n", + " }\n", + "\n", + " value += 'k' + event.key;\n", + "\n", + " this._key_event_extra(event, name);\n", + "\n", + " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", + " return false;\n", + "};\n", + "\n", + "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", + " if (name === 'download') {\n", + " this.handle_save(this, null);\n", + " } else {\n", + " this.send_message('toolbar_button', { name: name });\n", + " }\n", + "};\n", + "\n", + "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", + " this.message.textContent = tooltip;\n", + "};\n", + "\n", + "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", + "// prettier-ignore\n", + "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", + "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", + "\n", + "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", + "\n", + "mpl.default_extension = \"png\";/* global mpl */\n", + "\n", + "var comm_websocket_adapter = function (comm) {\n", + " // Create a \"websocket\"-like object which calls the given IPython comm\n", + " // object with the appropriate methods. Currently this is a non binary\n", + " // socket, so there is still some room for performance tuning.\n", + " var ws = {};\n", + "\n", + " ws.binaryType = comm.kernel.ws.binaryType;\n", + " ws.readyState = comm.kernel.ws.readyState;\n", + " function updateReadyState(_event) {\n", + " if (comm.kernel.ws) {\n", + " ws.readyState = comm.kernel.ws.readyState;\n", + " } else {\n", + " ws.readyState = 3; // Closed state.\n", + " }\n", + " }\n", + " comm.kernel.ws.addEventListener('open', updateReadyState);\n", + " comm.kernel.ws.addEventListener('close', updateReadyState);\n", + " comm.kernel.ws.addEventListener('error', updateReadyState);\n", + "\n", + " ws.close = function () {\n", + " comm.close();\n", + " };\n", + " ws.send = function (m) {\n", + " //console.log('sending', m);\n", + " comm.send(m);\n", + " };\n", + " // Register the callback with on_msg.\n", + " comm.on_msg(function (msg) {\n", + " //console.log('receiving', msg['content']['data'], msg);\n", + " var data = msg['content']['data'];\n", + " if (data['blob'] !== undefined) {\n", + " data = {\n", + " data: new Blob(msg['buffers'], { type: data['blob'] }),\n", + " };\n", + " }\n", + " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", + " ws.onmessage(data);\n", + " });\n", + " return ws;\n", + "};\n", + "\n", + "mpl.mpl_figure_comm = function (comm, msg) {\n", + " // This is the function which gets called when the mpl process\n", + " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", + "\n", + " var id = msg.content.data.id;\n", + " // Get hold of the div created by the display call when the Comm\n", + " // socket was opened in Python.\n", + " var element = document.getElementById(id);\n", + " var ws_proxy = comm_websocket_adapter(comm);\n", + "\n", + " function ondownload(figure, _format) {\n", + " window.open(figure.canvas.toDataURL());\n", + " }\n", + "\n", + " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", + "\n", + " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", + " // web socket which is closed, not our websocket->open comm proxy.\n", + " ws_proxy.onopen();\n", + "\n", + " fig.parent_element = element;\n", + " fig.cell_info = mpl.find_output_cell(\"
\");\n", + " if (!fig.cell_info) {\n", + " console.error('Failed to find cell for figure', id, fig);\n", + " return;\n", + " }\n", + " fig.cell_info[0].output_area.element.on(\n", + " 'cleared',\n", + " { fig: fig },\n", + " fig._remove_fig_handler\n", + " );\n", + "};\n", + "\n", + "mpl.figure.prototype.handle_close = function (fig, msg) {\n", + " var width = fig.canvas.width / fig.ratio;\n", + " fig.cell_info[0].output_area.element.off(\n", + " 'cleared',\n", + " fig._remove_fig_handler\n", + " );\n", + " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", + "\n", + " // Update the output cell to use the data from the current canvas.\n", + " fig.push_to_output();\n", + " var dataURL = fig.canvas.toDataURL();\n", + " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", + " // the notebook keyboard shortcuts fail.\n", + " IPython.keyboard_manager.enable();\n", + " fig.parent_element.innerHTML =\n", + " '';\n", + " fig.close_ws(fig, msg);\n", + "};\n", + "\n", + "mpl.figure.prototype.close_ws = function (fig, msg) {\n", + " fig.send_message('closing', msg);\n", + " // fig.ws.close()\n", + "};\n", + "\n", + "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", + " // Turn the data on the canvas into data in the output cell.\n", + " var width = this.canvas.width / this.ratio;\n", + " var dataURL = this.canvas.toDataURL();\n", + " this.cell_info[1]['text/html'] =\n", + " '';\n", + "};\n", + "\n", + "mpl.figure.prototype.updated_canvas_event = function () {\n", + " // Tell IPython that the notebook contents must change.\n", + " IPython.notebook.set_dirty(true);\n", + " this.send_message('ack', {});\n", + " var fig = this;\n", + " // Wait a second, then push the new image to the DOM so\n", + " // that it is saved nicely (might be nice to debounce this).\n", + " setTimeout(function () {\n", + " fig.push_to_output();\n", + " }, 1000);\n", + "};\n", + "\n", + "mpl.figure.prototype._init_toolbar = function () {\n", + " var fig = this;\n", + "\n", + " var toolbar = document.createElement('div');\n", + " toolbar.classList = 'btn-toolbar';\n", + " this.root.appendChild(toolbar);\n", + "\n", + " function on_click_closure(name) {\n", + " return function (_event) {\n", + " return fig.toolbar_button_onclick(name);\n", + " };\n", + " }\n", + "\n", + " function on_mouseover_closure(tooltip) {\n", + " return function (event) {\n", + " if (!event.currentTarget.disabled) {\n", + " return fig.toolbar_button_onmouseover(tooltip);\n", + " }\n", + " };\n", + " }\n", + "\n", + " fig.buttons = {};\n", + " var buttonGroup = document.createElement('div');\n", + " buttonGroup.classList = 'btn-group';\n", + " var button;\n", + " for (var toolbar_ind in mpl.toolbar_items) {\n", + " var name = mpl.toolbar_items[toolbar_ind][0];\n", + " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", + " var image = mpl.toolbar_items[toolbar_ind][2];\n", + " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", + "\n", + " if (!name) {\n", + " /* Instead of a spacer, we start a new button group. */\n", + " if (buttonGroup.hasChildNodes()) {\n", + " toolbar.appendChild(buttonGroup);\n", + " }\n", + " buttonGroup = document.createElement('div');\n", + " buttonGroup.classList = 'btn-group';\n", + " continue;\n", + " }\n", + "\n", + " button = fig.buttons[name] = document.createElement('button');\n", + " button.classList = 'btn btn-default';\n", + " button.href = '#';\n", + " button.title = name;\n", + " button.innerHTML = '';\n", + " button.addEventListener('click', on_click_closure(method_name));\n", + " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", + " buttonGroup.appendChild(button);\n", + " }\n", + "\n", + " if (buttonGroup.hasChildNodes()) {\n", + " toolbar.appendChild(buttonGroup);\n", + " }\n", + "\n", + " // Add the status bar.\n", + " var status_bar = document.createElement('span');\n", + " status_bar.classList = 'mpl-message pull-right';\n", + " toolbar.appendChild(status_bar);\n", + " this.message = status_bar;\n", + "\n", + " // Add the close button to the window.\n", + " var buttongrp = document.createElement('div');\n", + " buttongrp.classList = 'btn-group inline pull-right';\n", + " button = document.createElement('button');\n", + " button.classList = 'btn btn-mini btn-primary';\n", + " button.href = '#';\n", + " button.title = 'Stop Interaction';\n", + " button.innerHTML = '';\n", + " button.addEventListener('click', function (_evt) {\n", + " fig.handle_close(fig, {});\n", + " });\n", + " button.addEventListener(\n", + " 'mouseover',\n", + " on_mouseover_closure('Stop Interaction')\n", + " );\n", + " buttongrp.appendChild(button);\n", + " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", + " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", + "};\n", + "\n", + "mpl.figure.prototype._remove_fig_handler = function (event) {\n", + " var fig = event.data.fig;\n", + " if (event.target !== this) {\n", + " // Ignore bubbled events from children.\n", + " return;\n", + " }\n", + " fig.close_ws(fig, {});\n", + "};\n", + "\n", + "mpl.figure.prototype._root_extra_style = function (el) {\n", + " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", + "};\n", + "\n", + "mpl.figure.prototype._canvas_extra_style = function (el) {\n", + " // this is important to make the div 'focusable\n", + " el.setAttribute('tabindex', 0);\n", + " // reach out to IPython and tell the keyboard manager to turn it's self\n", + " // off when our div gets focus\n", + "\n", + " // location in version 3\n", + " if (IPython.notebook.keyboard_manager) {\n", + " IPython.notebook.keyboard_manager.register_events(el);\n", + " } else {\n", + " // location in version 2\n", + " IPython.keyboard_manager.register_events(el);\n", + " }\n", + "};\n", + "\n", + "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", + " var manager = IPython.notebook.keyboard_manager;\n", + " if (!manager) {\n", + " manager = IPython.keyboard_manager;\n", + " }\n", + "\n", + " // Check for shift+enter\n", + " if (event.shiftKey && event.which === 13) {\n", + " this.canvas_div.blur();\n", + " // select the cell after this one\n", + " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", + " IPython.notebook.select(index + 1);\n", + " }\n", + "};\n", + "\n", + "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", + " fig.ondownload(fig, null);\n", + "};\n", + "\n", + "mpl.find_output_cell = function (html_output) {\n", + " // Return the cell and output element which can be found *uniquely* in the notebook.\n", + " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", + " // IPython event is triggered only after the cells have been serialised, which for\n", + " // our purposes (turning an active figure into a static one), is too late.\n", + " var cells = IPython.notebook.get_cells();\n", + " var ncells = cells.length;\n", + " for (var i = 0; i < ncells; i++) {\n", + " var cell = cells[i];\n", + " if (cell.cell_type === 'code') {\n", + " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", + " var data = cell.output_area.outputs[j];\n", + " if (data.data) {\n", + " // IPython >= 3 moved mimebundle to data attribute of output\n", + " data = data.data;\n", + " }\n", + " if (data['text/html'] === html_output) {\n", + " return [cell, data, j];\n", + " }\n", + " }\n", + " }\n", + " }\n", + "};\n", + "\n", + "// Register the function which deals with the matplotlib target/channel.\n", + "// The kernel may be null if the page has been refreshed.\n", + "if (IPython.notebook.kernel !== null) {\n", + " IPython.notebook.kernel.comm_manager.register_target(\n", + " 'matplotlib',\n", + " mpl.mpl_figure_comm\n", + " );\n", + "}\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "Text(0.5, 0.98, 'Joint Probability Density\\n of Hm0 and Te per Direction')" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "%matplotlib notebook\n", + "\n", + "import matplotlib.pyplot as plt\n", + "from numpy import arange\n", + "from matplotlib.widgets import Slider\n", + "\n", + "\n", + "fig, ax = plt.subplots()\n", + "fig.subplots_adjust(right=0.8, bottom=0.25)\n", + "\n", + "d = 0\n", + "plot_jpd = probability[:,:,d]\n", + "\n", + "im = ax.imshow(plot_jpd, origin='lower', aspect='auto')\n", + "\n", + "axcolor = 'lightgoldenrodyellow'\n", + "axDir = plt.axes([0.3, 0.075, 0.45, 0.03], facecolor=axcolor)\n", + "\n", + "newD = Slider(axDir, 'Income Wave\\n Direction', 5, 355, valinit=d, valstep=10)\n", + "\n", + "def update(val):\n", + " d = int(newD.val/10)\n", + " im.set_data(probability[:,:,d])\n", + " fig.canvas.draw()\n", + "\n", + "newD.on_changed(update)\n", + "\n", + "cax = fig.add_axes([0.82, 0.3, 0.03, 0.5])\n", + "cbar = fig.colorbar(im, cax=cax, orientation='vertical')\n", + "\n", + "cbar.set_label('Probability Density (1/(sec*m*deg)', rotation=270, labelpad=15)\n", + "\n", + "ax.set_xlabel('Te (seconds)')\n", + "ax.set_ylabel('Hm0 (meters)')\n", + "\n", + "ax.set_xticks(arange(len(Te_center)))\n", + "ax.set_yticks(arange(len(Hm0_center)))\n", + "ax.set_xticklabels(Te_center,rotation=45)\n", + "ax.set_yticklabels(Hm0_center)\n", + "\n", + "fig.suptitle('Joint Probability Density\\n of Hm0 and Te per Direction')\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 7. Download Directional Spectra Data\n", + "1-hour directional wave spectra data can be downloaded using `request_wpto_directional_spectrum`. The spectra data will be returned as an xarray while the metadata will be returned as a Pandas DataFrame. \n" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Dimensions: (direction: 24, frequency: 29, time_index: 8748)\n", + "Coordinates:\n", + " * time_index (time_index) object 725850000000000000 ... 757378800000000000\n", + " * frequency (frequency) float64 0.035 0.0385 0.0424 ... 0.4173 0.4591 0.505\n", + " * direction (direction) float64 7.5 22.5 37.5 52.5 ... 322.5 337.5 352.5\n", + "Data variables:\n", + " 87 (time_index, frequency, direction) float32 0.0 0.0 ... 4.535e-05\n" + ] + } + ], + "source": [ + "year = '1993' # only one year can be passed at a time as a string\n", + "dir_spectra,meta = wave.io.hindcast.request_wpto_directional_spectrum(lat_lon,year)\n", + "\n", + "print(dir_spectra)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "\n" + ] } ], "metadata": { + "interpreter": { + "hash": "29d4f3f9417e26053c15fead58122d92d3e4d33b81eac28eefb5cabca755f3aa" + }, "kernelspec": { "display_name": "Python 3", "language": "python", diff --git a/examples/data/wave/hindcast/multi_year_dir.csv b/examples/data/wave/hindcast/multi_year_dir.csv new file mode 100644 index 000000000..3083bbc48 --- /dev/null +++ b/examples/data/wave/hindcast/multi_year_dir.csv @@ -0,0 +1,69601 @@ +time_index,frequency,direction,87,58 +1995-01-01 01:00:00+00:00,0.035,7.5,0.0,0.0 +1995-01-01 01:00:00+00:00,0.035,22.5,0.0,0.0 +1995-01-01 01:00:00+00:00,0.035,37.5,0.0,0.0 +1995-01-01 01:00:00+00:00,0.035,52.5,0.0,0.0 +1995-01-01 01:00:00+00:00,0.035,67.5,0.0,0.0 +1995-01-01 01:00:00+00:00,0.035,82.5,0.0,0.0 +1995-01-01 01:00:00+00:00,0.035,97.5,0.0,0.0 +1995-01-01 01:00:00+00:00,0.035,112.5,0.0,0.0 +1995-01-01 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000000000..8bf8cbd27 --- /dev/null +++ b/examples/data/wave/hindcast/multi_year_dir_meta.csv @@ -0,0 +1,3 @@ +water_depth,latitude,longitude,distance_to_shore,timezone,jurisdiction +67.7445,44.567,-124.229,12353.165,-8,Federal +191.8491,43.08,-124.72,22735.91,-8,Federal diff --git a/mhkit/tests/test_wave.py b/mhkit/tests/test_wave.py index 294fe6c34..40e50ffe8 100644 --- a/mhkit/tests/test_wave.py +++ b/mhkit/tests/test_wave.py @@ -923,6 +923,17 @@ def setUpClass(self): names = [None,'water_depth','latitude','longitude','distance_to_shore','timezone' ,'jurisdiction'],header = 0, dtype = {'water_depth':'float32','latitude':'float32' ,'longitude':'float32','distance_to_shore':'float32','timezone':'int16'}) + + my_dir = pd.read_csv(join(datadir,'hindcast/multi_year_dir.csv'),header = 0, + dtype={'87':'float32','58':'float32'}) + my_dir['time_index'] = pd.to_datetime(my_dir['time_index']) + my_dir = my_dir.set_index(['time_index','frequency','direction']) + self.my_dir = my_dir.to_xarray() + + self.my_dir_meta = pd.read_csv(join(datadir,'hindcast/multi_year_dir_meta.csv'), + names = ['water_depth','latitude','longitude','distance_to_shore','timezone' + ,'jurisdiction'],header = 0, dtype = {'water_depth':'float32','latitude':'float32' + ,'longitude':'float32','distance_to_shore':'float32','timezone':'int16'}) @classmethod def tearDownClass(self): @@ -932,8 +943,7 @@ def tearDownClass(self): # only run test for one version of python per to not spam the server # yet keep coverage high on each test if float(sys.version[0:3]) == 3.7: - def test_multi_year_sig_wave_height(self): - + def test_multi_year(self): data_type = '3-hour' years = [1990,1992] lat_lon = (44.624076,-124.280097) @@ -944,7 +954,7 @@ def test_multi_year_sig_wave_height(self): elif float(sys.version[0:3]) == 3.8: # wait five minute to ensure python 3.7 call is complete - time.sleep(300) + #time.sleep(300) def test_multi_loc(self): data_type = '3-hour' years = [1995] @@ -952,8 +962,14 @@ def test_multi_loc(self): parameters = 'mean_absolute_period' wave_multiloc, meta= wave.io.hindcast.request_wpto_point_data(data_type, parameters,lat_lon,years) + dir_multiyear, meta_dir = wave.io.hindcast.request_wpto_directional_spectrum(lat_lon,year='1995') + dir_multiyear = dir_multiyear.sel(time_index=slice(dir_multiyear.time_index[0],dir_multiyear.time_index[99])) + dir_multiyear = dir_multiyear.rename_vars({87:'87',58:'58'}) + assert_frame_equal(self.ml,wave_multiloc) assert_frame_equal(self.ml_meta,meta) + xrt.assert_allclose(self.my_dir,dir_multiyear) + assert_frame_equal(self.my_dir_meta,meta_dir) elif float(sys.version[0:3]) == 3.9: # wait ten minutes to ensure python 3.7 and 3.8 call is complete diff --git a/mhkit/wave/io/hindcast.py b/mhkit/wave/io/hindcast.py index 5ea14dfe6..ac834def3 100644 --- a/mhkit/wave/io/hindcast.py +++ b/mhkit/wave/io/hindcast.py @@ -1,6 +1,44 @@ import pandas as pd import numpy as np -from rex import MultiYearWaveX +from rex import MultiYearWaveX, WaveX +import sys + + +def region_selection(lat_lon): + ''' + Returns the name of the predefined region in which the given coordinates reside. + Can be used to check if the passed lat/lon pair is within the WPTO hindcast dataset. + + Parameters + ---------- + lat_lon : list or tuple + Latitude and longitude coordinates as flaots or intigers + + Returns + ------- + region : string + Name of predefined region for given coordinates + ''' + assert isinstance(lat_lon, (list,tuple)), 'lat_lon must be of type list or tuple' + assert isinstance(lat_lon[0], (float,int)), 'lat_lon values must be of type float or int' + assert isinstance(lat_lon[1], (float,int)), 'lat_lon values must be of type float or int' + + rDict = { + 'Hawaii':{ 'lat':[15.0,27.000002], 'lon':[-164.0,-151.0] }, + 'West_Coast':{ 'lat':[30.0906, 48.8641], 'lon':[-130.072, -116.899] }, + 'Atlantic':{ 'lat':[24.382, 44.8247], 'lon':[-81.552, -65.721] }, + } + + region_search = lambda x: all( ( True if rDict[x][dk][0] <= d <= rDict[x][dk][1] else False + for dk, d in {'lat':lat_lon[0],'lon':lat_lon[1]}.items() ) ) + region = [key for key in rDict if region_search(key)] + + if len(region)==0: + print('ERROR: coordinates out of bounds') + else: + return region[0] + + def request_wpto_point_data(data_type, parameter, lat_lon, years, tree=None, unscale=True, str_decode=True,hsds=True): @@ -17,10 +55,10 @@ def request_wpto_point_data(data_type, parameter, lat_lon, years, tree=None, Parameters ---------- data_type : string - data set type of interst + Data set type of interest Options: '3-hour' '1-hour' parameter: string or list of strings - dataset parameter to be downloaded + Dataset parameter to be downloaded 3-hour dataset options: 'directionality_coefficient', 'energy_period', 'maximum_energy_direction' 'mean_absolute_period', 'mean_zero-crossing_period', 'omni-directional_wave_power', 'peak_period' 'significant_wave_height', 'spectral_width', 'water_depth' @@ -29,7 +67,7 @@ def request_wpto_point_data(data_type, parameter, lat_lon, years, tree=None, 'significant_wave_height', 'spectral_width', 'water_depth', 'maximim_energy_direction', 'mean_wave_direction', 'frequency_bin_edges' lat_lon: tuple or list of tuples - latitude longitude pairs at which to extract data + Latitude longitude pairs at which to extract data years : list Year(s) to be accessed. The years 1979-2010 available. Examples: [1996] or [2004,2006,2007] tree : str | cKDTree (optional) @@ -43,16 +81,16 @@ def request_wpto_point_data(data_type, parameter, lat_lon, years, tree=None, strings. Setting this to False will speed up the meta data read. Default = True hsds : bool (optional) - Boolean flag to use h5pyd to handle .h5 'files' hosted on AWS - behind HSDS. Setting to False will indicate to look for files on - local machine, not AWS. Default = True + Boolean flag to use h5pyd to handle .h5 'files' hosted on AWS + behind HSDS. Setting to False will indicate to look for files on + local machine, not AWS. Default = True Returns --------- data: DataFrame Data indexed by datetime with columns named for parameter and cooresponding metadata index meta: DataFrame - location metadata for the requested data location + Location metadata for the requested data location """ assert isinstance(parameter, (str, list)), 'parameter must be of type string or list' @@ -64,10 +102,25 @@ def request_wpto_point_data(data_type, parameter, lat_lon, years, tree=None, assert isinstance(str_decode,bool), 'str_decode must be bool type' assert isinstance(hsds,bool), 'hsds must be bool type' + if 'directional_wave_spectrum' in parameter: + sys.exit('This function does not support directional_wave_spectrum output') + + # check for multiple region selection + if isinstance(lat_lon[0], float): + region = region_selection(lat_lon) + else: + reglist = [] + for loc in lat_lon: + reglist.append(region_selection(loc)) + if reglist.count(reglist[0]) == len(lat_lon): + region = reglist[0] + else: + sys.exit('Coordinates must be within the same region!') + if data_type == '3-hour': - wave_path = f'/nrel/US_wave/West_Coast/West_Coast_wave_*.h5' + wave_path = f'/nrel/US_wave/'+region+'/'+region+'_wave_*.h5' elif data_type == '1-hour': - wave_path = f'/nrel/US_wave/virtual_buoy/West_Coast/West_Coast_virtual_buoy_*.h5' + wave_path = f'/nrel/US_wave/virtual_buoy/'+region+'/'+region+'_virtual_buoy_*.h5' else: print(f'ERROR: invalid data_type') pass @@ -97,4 +150,79 @@ def request_wpto_point_data(data_type, parameter, lat_lon, years, tree=None, meta = rex_waves.meta.loc[col,:] meta = meta.reset_index(drop=True) - return data, meta \ No newline at end of file + return data, meta + +def request_wpto_directional_spectrum(lat_lon, year, tree=None, + unscale=True, str_decode=True,hsds=True): + + """ + Returns directional spectra data from the WPTO wave hindcast hosted on AWS at the specified latitude and longitude point(s), + or the closest available pont(s). + Visit https://registry.opendata.aws/wpto-pds-us-wave/ for more information about the dataset and available + locations and years. + + Note: To access the WPTO hindcast data, you will need to configure h5pyd for data access on HSDS. + Please see the WPTO_hindcast_example notebook for more information. + + Parameters + ---------- + lat_lon: tuple or list of tuples + Latitude longitude pairs at which to extract data + year : string + Year to be accessed. The years 1979-2010 available. Only one year can be requested at a time. + tree : str | cKDTree (optional) + cKDTree or path to .pkl file containing pre-computed tree + of lat, lon coordinates, default = None + unscale : bool (optional) + Boolean flag to automatically unscale variables on extraction + Default = True + str_decode : bool (optional) + Boolean flag to decode the bytestring meta data into normal + strings. Setting this to False will speed up the meta data read. + Default = True + hsds : bool (optional) + Boolean flag to use h5pyd to handle .h5 'files' hosted on AWS + behind HSDS. Setting to False will indicate to look for files on + local machine, not AWS. Default = True + + Returns + --------- + data: xarray + Coordinates as datetime, frequency, and direction for data at specified location(s) + meta: DataFrame + Location metadata for the requested data location + """ + assert isinstance(lat_lon, (list,tuple)), 'lat_lon must be of type list or tuple' + assert isinstance(year,str), 'years must be a string' + assert isinstance(tree,(str,type(None))), 'tree must be a sring' + assert isinstance(unscale,bool), 'unscale must be bool type' + assert isinstance(str_decode,bool), 'str_decode must be bool type' + assert isinstance(hsds,bool), 'hsds must be bool type' + + # check for multiple region selection + if isinstance(lat_lon[0], float): + region = region_selection(lat_lon) + else: + reglist = [] + for loc in lat_lon: + reglist.append(region_selection(loc)) + if reglist.count(reglist[0]) == len(lat_lon): + region = reglist[0] + else: + sys.exit('Coordinates must be within the same region!') + + wave_path = f'/nrel/US_wave/virtual_buoy/'+region+'/'+region+'_virtual_buoy_'+year+'.h5' + parameter = 'directional_wave_spectrum' + waveKwargs = {'tree':tree,'unscale':unscale,'str_decode':str_decode, 'hsds':hsds} + + with WaveX(wave_path, **waveKwargs) as rex_waves: + # get data + data_raw = rex_waves.get_lat_lon_df(parameter,lat_lon) + # get metadata + col = data_raw.columns[:] + meta = rex_waves.meta.loc[col,:] + meta = meta.reset_index(drop=True) + + data = data_raw.to_xarray() + + return data, meta \ No newline at end of file