Updated a number of functions to work better with ICEPack Output

Author: nholschuh

Untitled.ipynb

@@ -0,0 +1,138 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "14148bd2-6f71-4fe3-8fb1-c16533bf9190",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import sys\n",
+    "sys.path.append('/mnt/data01/Code/')\n",
+    "import NDH_Tools as ndh\n",
+    "\n",
+    "import mat73"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "07d07ffd-d284-4fd7-8fe0-3c41487eda3f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fn = '/home/nholschuh/Drive/Research_Projects/74_Multipass/PetermannWork/Picking_iPad/Picked/Data_20110429_01_010_fs_25_crop_1065.pdf'\n",
+    "\n",
+    "\n",
+    "local_fn_whole = fn.split('/')[-1]\n",
+    "fileparts = local_fn_whole.split('.')[0].split('_')\n",
+    "\n",
+    "fs = int(fileparts[5])\n",
+    "crop = int(fileparts[7])\n",
+    "day_seg = '_'.join(fileparts[1:3])\n",
+    "local_fn = '_'.join(fileparts[0:4])\n",
+    "data_dir = '/mnt/data01/Data/RadarData/CReSIS_Filestructure/ct_data/rds/2011_Greenland_P3/'\n",
+    "surf_load = 'CSARP_surf_ndh'\n",
+    "fn = data_dir+surf_load+'/'+day_seg+'/'+local_fn+'.mat'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "ce6643b2-1acf-4cea-b666-a5c8febe7fdd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "surf_data = mat73.loadmat(fn)\n",
+    "ndh.savemat(surf_data,'test.mat')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "862a104c-a9aa-44e3-bd88-2b08c9e3c6d0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!ls /mnt/data01/Data/RadarData/CReSIS_Filestructure/ct_data/rds/2011_Greenland_P3/CSARP_surf_ndh/20110429_01/"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ee60fdb1-1aae-41e1-a135-bccefa835e3e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "scipy.io.loadmat(fn)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d94cf1f1-6b82-41a7-926b-537bacffc72c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data = read_h5(fn)\n",
+    "data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bd7251ce-c037-485c-88ab-48c08ec9f8a1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data = mat73.loadmat(fn)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "77250c20-1682-4d7e-9f8f-42bb259511c9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "27e3dd33-6962-4482-bdf2-2befd813a4ad",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.10"
+  },
+  "widgets": {
+   "application/vnd.jupyter.widget-state+json": {
+    "state": {},
+    "version_major": 2,
+    "version_minor": 0
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

calculate_flowlines.py

@@ -0,0 +1,53 @@
+import numpy as np
+import matplotlib.pyplot as plt
+
+def calculate_flowlines(x,y,u,v,seed_points,max_error=0.00001):
+    """
+    % (C) Nick Holschuh - Amherst College -- 2022 (Nick.Holschuh@gmail.com)
+    %
+    % This function prints out the minimum and maximum values of an array
+    %
+    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+    % The inputs are:
+    %
+    %     input_array -- array of data to analyze
+    %
+    %%%%%%%%%%%%%%%
+    % The outputs are:
+    %
+    %      output -- the min and max in a 1x2 array
+    %
+    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+    """ 
+
+    ################# This uses a modified plt.streamline to pass through a user-editable keyword
+    ################# argument "max_error", which goes into the interpolater to guarantee
+    ################# accurate streammline calculation. Copy this version of streamplot
+    ################# into your matplotlib directory to enable the use of streamline
+    ################# calculation from NDH_Tools
+
+    
+    sls = []
+    
+    if isinstance(seed_points,list):
+        seed_points = np.array(seed_points)
+    
+    if len(seed_points.shape) == 1:
+        seed_points = np.expand_dims(seed_points,axis=0)
+    
+    fig = plt.figure()
+    
+    for ind0, sp in enumerate(seed_points[:,0]):
+        streamlines = plt.streamplot(x,y,u,v,start_points=[seed_points[ind0,:]], max_error=max_error)
+
+
+        ########### Here we extract the coordinate information along the streamline
+        sl = [streamlines.lines.get_paths()[0].vertices[0]]
+        for i in streamlines.lines.get_paths():
+            sl.append(i.vertices[1])
+
+        sls.append(np.array(sl))
+    
+    plt.close(fig)
+    
+    return sls