(self)
| 3080 | self.h5file.close() |
| 3081 | |
| 3082 | def populateFile(self): |
| 3083 | group = self.rootgroup |
| 3084 | for j in range(3): |
| 3085 | # Create a table |
| 3086 | filterprops = tb.Filters( |
| 3087 | complevel=self.compress, shuffle=self.shuffle |
| 3088 | ) |
| 3089 | table = self.h5file.create_table( |
| 3090 | group, |
| 3091 | "table" + str(j), |
| 3092 | self.record, |
| 3093 | title=self.title, |
| 3094 | filters=filterprops, |
| 3095 | expectedrows=self.expectedrows, |
| 3096 | ) |
| 3097 | |
| 3098 | # Get the row object associated with the new table |
| 3099 | row = table.row |
| 3100 | |
| 3101 | # Fill the table |
| 3102 | for i in range(self.expectedrows): |
| 3103 | row["var1"] = "%04d" % (self.expectedrows - i) |
| 3104 | row["var7"] = row["var1"][-1] |
| 3105 | row["var2"] = i |
| 3106 | row["var3"] = i % self.maxshort |
| 3107 | if isinstance(row["var4"], np.ndarray): |
| 3108 | row["var4"] = [float(i), float(i * i)] |
| 3109 | else: |
| 3110 | row["var4"] = float(i) |
| 3111 | if isinstance(row["var5"], np.ndarray): |
| 3112 | row["var5"] = np.array((float(i),) * 4) |
| 3113 | else: |
| 3114 | row["var5"] = float(i) |
| 3115 | |
| 3116 | # var6 will be like var3 but byteswaped |
| 3117 | row["var6"] = ((row["var3"] >> 8) & 0xFF) + ( |
| 3118 | (row["var3"] << 8) & 0xFF00 |
| 3119 | ) |
| 3120 | row.append() |
| 3121 | |
| 3122 | # Flush the buffer for this table |
| 3123 | table.flush() |
| 3124 | # Create a new group (descendant of group) |
| 3125 | group2 = self.h5file.create_group(group, "group" + str(j)) |
| 3126 | # Iterate over this new group (group2) |
| 3127 | group = group2 |
| 3128 | |
| 3129 | def check_range(self): |
| 3130 | # Create an instance of an HDF5 Table |
no test coverage detected